OTTER Paper Plots

In this (rather long) tutorial we go through creating most of the figures in the OTTER paper using the OTTER python API.

Note: This tutorial was created with the OTTER dataset as of August, 2025. Rerunning this tutorial with future datasets may produce different results than the plots shown in the paper. To exactly reproduce those plots please use a backup copy of the dataset from that time.

Some Setup

# imports we will use throughout
# if you get an ImportError you may need to install something

import os
import io
import warnings
from copy import deepcopy

import otter # of course!
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
import scipy

from astropy import units as u, constants as c
from astropy.coordinates import SkyCoord
from astropy.time import Time

import astropy.cosmology.units as cu
from astropy.cosmology import Planck18 as cosmo

import matplotlib as mpl
import cmasher as cmr

from matplotlib.colors import ListedColormap
from matplotlib.lines import Line2D
from matplotlib.ticker import AutoMinorLocator

# connect to the OTTER server
db = otter.Otter()

Attempting to login to https://otter.idies.jhu.edu/api with the following credentials:
username: user-guest
password: test

# create a directory to save the figures to, if it doesn't exist
plotdir = os.path.join(os.getcwd(), "otter_paper_plots") # change this if you want the figures to go somewhere else
if not os.path.exists(plotdir):
    os.makedirs(plotdir)

# and define some keyword arguments for saving so the figures look nice :)
plot_save_kwargs = dict(
    bbox_inches="tight",
    dpi = 200
)

# and a function to save the figures to a consistent place
def savefig(fig, figname, plotdir=plotdir, plot_save_kwargs=plot_save_kwargs):
    fig.savefig(
        os.path.join(plotdir, figname),
        **plot_save_kwargs
    )

Sections 3 and 4: Summary Plots of the Current Dataset

Figure 3: Maximum Confidence Flag

This plot is created by pulling the maximum classification flag associated with each transient in otter. This requires pulling it out of the default classification stored in a transient object. Luckily, there’s a method built into the Transient class for this!

# get all the metadata associated with each transient
meta = db.get_meta()

# meta is a list of Transient objects so we need to loop over them to get the class
class_flag = []
for transient in meta:
    class_, conf_flag, ref_list = transient.get_classification()

    # the only thing we really need is the conf_flag for this plot
    class_flag.append(conf_flag)

# now we can create the plot!
fig, ax = plt.subplots()
ax.hist(
    class_flag,
    facecolor = "cornflowerblue",
    edgecolor = "k",
    bins = 4,
    range = (0,4),
    align = "left"
)
ax.set_xticks([0, 1, 2, 3], [0, 1, 2, 3])
ax.set_ylabel("Number of Transient Events")
ax.set_xlabel("Maximum Confidence Flag")
savefig(fig, "max-conf-flag-hist.png")

Figure 7 (And Figure 16 in Appendix C)

These are histograms showing the discovery regime of different TDEs. This information is stored in the classification dictionary in the metadata.

# get all the metadata associated with each transient
meta = db.get_meta()

# similarly, iterate over the metadata and pull out the "discovery_method"
discovery_types = []
discovery_date = []
names = []
for transient in meta:
    class_info = transient["classification"]
    if "discovery_method" in class_info:
        disc_method = class_info["discovery_method"]
    else:
        # Since the discovery_method is not a *required* key, some transient don't have it
        # for these, we use some other logic
        if "VAST" in transient.default_name or "VT" in transient.default_name:
            # these are radio discovered
            disc_method = "radio"
        elif transient.default_name in {"2019azh", "2020vdq", "2018cqh"}:
            disc_method = "optical"
        else:
            # a catch-all in case the dataset has changed
            warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
            continue

    # then, we also need to pull out a discovery year
    # for archival searches we use the date of publication
    this_dd = transient.get_discovery_date()

    if this_dd is None and any(["WTP" in n['value'] for n in transient['name/alias']]):
        this_dd = Time("2024-02-01", format="iso")

    if this_dd is None and any(["VT" in n['value'] for n in transient['name/alias']]):
        this_dd = Time("2025-04-01", format="iso")

    if this_dd is None and any(["VAST" in n['value'] for n in transient['name/alias']]):
        this_dd = Time("2024-10-01", format="iso")

    discovery_date.append(this_dd)
    discovery_types.append(disc_method)
    names.append(transient.default_name)

/tmp/ipykernel_489627/1340418342.py:22: UserWarning: 2022csn does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
/tmp/ipykernel_489627/1340418342.py:22: UserWarning: 2021qth does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
/tmp/ipykernel_489627/1340418342.py:22: UserWarning: 2023ugy does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
/tmp/ipykernel_489627/1340418342.py:22: UserWarning: 2022fpx does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
/tmp/ipykernel_489627/1340418342.py:22: UserWarning: 2023kvy does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
/tmp/ipykernel_489627/1340418342.py:22: UserWarning: 2024tvd does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")
/tmp/ipykernel_489627/1340418342.py:22: UserWarning: ASASSN-15lh does not have a known discovery method! Skipping!
  warnings.warn(f"{transient.default_name} does not have a known discovery method! Skipping!")

# now that we have the discovery year and wavelength regime we can create the plot!

cumulative = True # toggle this depending on if you want a cumulative version of the histogram

fig, ax = plt.subplots(figsize=(10,6))

rawdf = pd.DataFrame({'tde': names, 'discovery_method': discovery_types, 'discovery_date': discovery_date})
df = deepcopy(rawdf)
df = df[~pd.isna(df.discovery_date)]
df.discovery_method = df.discovery_method.replace('radio', 'Radio')
df.discovery_method = df.discovery_method.replace('xray', 'X-Ray')
df.discovery_method = df.discovery_method.replace('uv', 'UV')
df.discovery_method = df.discovery_method.replace('optical', 'Optical')
df.discovery_method = df.discovery_method.replace('ir', 'IR')

df['discovery_year'] = [int(np.floor(d.decimalyear)) for d in df.discovery_date]

n = df.discovery_year.max()-df.discovery_year.min()
bottom = np.zeros(n)

all_colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
cs = {
    "Radio":"#AE2012",
    "X-Ray":"#005F73",
    "Optical":"#EE9B00",
    "IR":"k",
    "UV":"grey"
} #[all_colors[1], all_colors[5], all_colors[8]]
# labels, years
labels, years = np.array([(y,g.discovery_year.values) for y,g in df.groupby('discovery_method')], dtype="object").T
label_order = ["Radio", "IR", "Optical", "UV", "X-Ray"]
yrs = [years[np.where(labels == ll)[0][0]] for ll in label_order]
colors = [cs[ll] for ll in label_order]
ax.hist(yrs, label=label_order, bins=n, stacked=True, color=colors, cumulative=cumulative)
n, bins, _ = ax.hist(df.discovery_year, bins=n, stacked=True, histtype='step', edgecolor='k', cumulative=cumulative)

if cumulative:
    ax.set_ylabel('Cumulative Number of TDEs Discovered', fontsize=16, fontweight="semibold")
else:
    ax.set_ylabel('Number of TDEs Discovered', fontsize=16, fontweight="semibold")
ax.set_xlabel('Discovery Year', fontsize=16, fontweight="semibold")

lsst_years = list(range(2026, 2035))
lsst_n = n[-1] + np.linspace(1000, 10000, len(lsst_years))

lsst_years_plot = [2025,2026] + lsst_years
lsst_n_plot = [n[-1], 2*n[-1]] + list(lsst_n)

lsst_hist_kwargs = dict(color='k', linestyle='--', where="pre", label='LSST Projection\n(van Velzen+2011)')
if cumulative:
    ax.step(lsst_years_plot, lsst_n_plot, **lsst_hist_kwargs)
else:
    ax.step(lsst_years_plot, [0]+[1e3]*(len(lsst_years_plot)-1), **lsst_hist_kwargs)

if cumulative:
    # 10 tdes/yr
    years = list(range(2000, 2020))
    ten_per_year = 60 + np.array(list(range(0, 10*len(years), 10)))
    print(years, ten_per_year)
    ax.plot(years, ten_per_year, color='k', alpha=0.5)
    ax.text(2002, 100, "~10 TDEs/yr", alpha=0.5, rotation=15, fontsize=16)

    # 1000 tdes/yr
    years = list(range(2020, 2035))
    thsnd_per_year = 2000 + np.array(list(range(0, 1000*len(years), 1000)))
    ax.plot(years, thsnd_per_year, color='k', alpha=0.5)
    ax.text(2022, 7000, r"~10$^3$ TDEs/yr", alpha=0.5, rotation=15, fontsize=16)

# add some vertical lines were different surveys started
surveys = ["ZTF", "ASASSN", "ROSAT", "PTF", "Swift", "XMM", "GALEX"]
start_dates = [2017+(10/12), 2014+(11/12), 1991+(7/12), 2009+(6/12), 2004+(10/12), 1999+(11/12), 2003+(4/12)]
ymin = 0.95
ymin_coord = 17*(1-ymin)*ax.get_ylim()[1]
for x, lab in zip(start_dates, surveys):
    ax.axvline(x, ymin=ymin, ymax=1, color='k', alpha=1)
    ax.text(x-0.25, ymin_coord, lab, rotation=-90, alpha=1, verticalalignment="top", horizontalalignment="center", fontsize=16)

ax.set_xlim(1989, 2030)


ax.set_yscale('log')

ax.tick_params(axis='x', labelsize=16)      # x-axis tick labels
ax.tick_params(axis='y', labelsize=16)      # y-axis tick labels

ax.legend(frameon=False, bbox_to_anchor=(-0.05,1), loc="lower left", ncols=4, fontsize=16);

if cumulative:
    savefig(fig, "tde-discovery-histogram-cumulative.png");
else:
    savefig(fig, "tde-discovery-histogram.png");

[2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019] [ 60  70  80  90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
 240 250]

# then this cell generates a GIF where the y axis is in linear space

import pandas as pd
from copy import deepcopy
from matplotlib import animation
from matplotlib import ticker as mticker

plt.rcParams["animation.html"] = "jshtml"

fig, ax = plt.subplots(figsize=(10,6))

ax.xaxis.set_major_locator(mticker.MaxNLocator(integer=True))
ax.yaxis.set_major_locator(mticker.MaxNLocator(integer=True))


rawdf = pd.DataFrame({'tde': names, 'discovery_method': discovery_types, 'discovery_date': discovery_date})
df = deepcopy(rawdf)
df = df[~pd.isna(df.discovery_date)]
df.discovery_method = df.discovery_method.replace('radio', 'Radio')
df.discovery_method = df.discovery_method.replace('xray', 'X-Ray')
df.discovery_method = df.discovery_method.replace('uv', 'UV')
df.discovery_method = df.discovery_method.replace('optical', 'Optical')
df.discovery_method = df.discovery_method.replace('ir', 'IR')

df['discovery_year'] = [int(np.floor(d.decimalyear)) for d in df.discovery_date]

n = df.discovery_year.max()-df.discovery_year.min()
bottom = np.zeros(n)

all_colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
cs = {
    "Radio":"#AE2012",
    "X-Ray":"#005F73",
    "Optical":"#EE9B00",
    "IR":"k",
    "UV":"grey"
} #[all_colors[1], all_colors[5], all_colors[8]]
# labels, years
labels, years = np.array([(y,g.discovery_year.values) for y,g in df.groupby('discovery_method')], dtype="object").T
label_order = ["Radio", "IR", "Optical", "UV", "X-Ray"]
yrs = [years[np.where(labels == ll)[0][0]] for ll in label_order]
colors = [cs[ll] for ll in label_order]
ax.hist(yrs, label=label_order, bins=n, stacked=True, color=colors, cumulative=cumulative)
n, bins, _ = ax.hist(df.discovery_year, bins=n, stacked=True, histtype='step', edgecolor='k', cumulative=cumulative)

ax.set_ylabel('Cumulative Number of TDEs Discovered', fontsize=16, fontweight="semibold")
ax.set_xlabel('Discovery Year', fontsize=16, fontweight="semibold")

lsst_years = list(range(2026, 2035))
lsst_n = n[-1] + np.linspace(1000, 10000, len(lsst_years))

lsst_years_plot = [2025,2026] + lsst_years
lsst_n_plot = [n[-1], 2*n[-1]] + list(lsst_n)

lsst_hist_kwargs = dict(color='k', linestyle='--', where="pre", label='LSST Projection\n(van Velzen+2011)')
ax.step(lsst_years_plot, lsst_n_plot, **lsst_hist_kwargs)

# set the initial x and y lims
ax.set_xlim(1989, 1994)
ax.set_ylim(0, 10)

ax.tick_params(axis='x', labelsize=16)      # x-axis tick labels
ax.tick_params(axis='y', labelsize=16)      # y-axis tick labels

# add some vertical lines were different surveys started
surveys = ["ZTF", "ASASSN", "ROSAT", "PTF", "Swift", "XMM", "GALEX"]
start_dates = [2017+(10/12), 2014+(11/12), 1991+(7/12), 2009+(6/12), 2004+(10/12), 1999+(11/12), 2003+(4/12)]
ymin = 0.95
ymin_coord = 18*(1-ymin)*ax.get_ylim()[1]
vlines, txts = [], []
for x, lab in zip(start_dates, surveys):
    vline = ax.axvline(x, ymin=ymin, ymax=1, color='k', alpha=1, visible=False)
    txt = ax.text(x, ymin_coord, lab, rotation=-90, alpha=1, verticalalignment="top", horizontalalignment="center", fontsize=16, visible=False)
    vlines.append(vline)
    txts.append(txt)

ax.legend(frameon=False, bbox_to_anchor=(-0.05,1), loc="lower left", ncols=4, fontsize=16);

ylims = [10,10,10,10,20,20,20,20,30,30,40,40,40,60,80,80,80,80,80,150,150,150,200,200,200,200,200,200,300,500,2000,3000,4000,5000,6000]
def animate(i):
    ax.set_xlim(1989, 1996+i)
    ax.set_ylim(0, ylims[i])

    for date, vline, txt in zip(start_dates, vlines, txts):
        if date <= 1996+i:
            vline.set_visible(True)
            txt.set_visible(True)
            ymin_coord = 18*(1-ymin)*ax.get_ylim()[1]
            txt.set_y(ymin_coord)

    return ()

ani = animation.FuncAnimation(fig, animate, frames=35, interval=300, blit=False, repeat=False)

ani.save("tde-discovery-histogram-linear.gif", writer="pillow", fps=4)  # fps=frames per second

ani

/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/IPython/core/formatters.py:406: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all Axes decorations.
  return method()
/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/IPython/core/formatters.py:406: UserWarning: Tight layout not applied. The bottom and top margins cannot be made large enough to accommodate all Axes decorations.
  return method()

Once Loop Reflect

/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/IPython/core/pylabtools.py:170: UserWarning: Tight layout not applied. The left and right margins cannot be made large enough to accommodate all Axes decorations.
  fig.canvas.print_figure(bytes_io, **kw)

Figure 8: Redshift Histogram

# get the transient meta
all_transients = db.get_meta()

# now gather the redshifts
z  = []
n_z = 0
n = len(all_transients)
for t in all_transients:
    try:
        z.append(t.get_redshift())
        n_z += 1
    except KeyError:
        continue

z = np.array(z).astype(float)

print(n_z/n * 100, "% of the transients in OTTER have a redshift")

# and create the figure

fig, ax1 = plt.subplots()

ax1.hist(z, lw=4, histtype="stepfilled", color="cornflowerblue", bins=30, edgecolor="k")
ax1.set_yscale("log")

ax = ax1.inset_axes([0.4, 0.4, 0.57, 0.57])
med = np.median(z)
ax.axvline(np.log10(med), color="r", linestyle = "--")
ax.text(np.log10(med)+0.05, 0, f"Med.={med}", rotation=90, horizontalalignment="left", fontsize=14)

quantiles =  np.quantile(z, [0.5-0.34, 0.5+.34])
ax.axvspan(*np.log10(quantiles), alpha=0.2, color='red')

logbins = np.logspace(np.log10(z.min()),np.log10(z.max()),25)
counts, edges = np.histogram(z,bins=logbins)

ax.step(np.log10(edges[1:]), counts, color='k')

ax.set_xlabel(r"$\log_{10}$(z)", fontsize=14)
ax1.set_xlabel("Redshift", fontsize=16)
ax1.set_ylabel("Number of TDEs", fontsize=16)

savefig(fig, "redshift-hist.png")

94.58333333333333 % of the transients in OTTER have a redshift

Figure 9: Lightcurves

# get all of the photometry in otter
with warnings.catch_warnings(action="ignore"):
    allphot = db.get_phot(flux_unit="erg/s/cm^2/Hz", return_type="pandas")

J121116 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021nwa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14li has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aaldjb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...883..111H'
AT2019ahk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aatsnw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023arXiv231003791S'
2020vdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ack has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CNSS J0019+00 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF16axa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2018jbv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
SDSSJ1323 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J141036 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021utq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Dougie has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J215418.2+002442 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021lo has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019eve has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2022mim has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019teq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
RX J1624+75 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbjsh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J030257 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020pj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J142401 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J093634.7-054755 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dbl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019pqt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024qab has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J113527 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021qxv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021jjm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15oi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022czy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021sdu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020acka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018bsi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adeqka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022A&A...666A...6W'
2020zso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020riz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J145851 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019ehz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14acnjbu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.197....1W'
2023mhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1342 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019vcb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1350 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Swift J2058.4+0516 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020mot has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021crk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022pna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018cqh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ehb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022wtn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2020yue has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021axu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.4816W', '2020SSRv..216...81A']"
2018fyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020wey has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2002RvMA...15...27K', '2020SSRv..216...81A']"
NGC 5905 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09ge has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022cmc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
eRASSt J234403-352640 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019meg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J104315.9+005059 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
DES14C1kia has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
RX J1242-11A has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.250....1C'
2023mfm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021gje has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2006ApJ...653L..25G'
D1-9 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J144848.2+030235 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ocn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022ApJ...925...67L'
2019cmw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbgpn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1185375 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J17361-4441 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP18aajkmk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15abymdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yzv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018lna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamoxe has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1112-82 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J100933 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
PTF10iya has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2020MNRAS.499..482N'
2019qiz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022exr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...887..218L'
AT2018dyb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF10nuj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020qhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamzew has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.102....1Y'
2023cvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dyt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16aax has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.326....1H'
2023rvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J155223 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J213437.8-620433 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ddv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbuuv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aaqrcr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09djl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14ae has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020nov has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1644+57 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133837 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019gte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021zlg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
PS1-10jh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J230053.0-020732 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RX J1420+53 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2017bcc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RBS 1032 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022arb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021blz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbwvs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0159 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2016fnl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
NGC 3599 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0952 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J221936.0+004724 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2020abri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...780...44C', '2020SSRv..216...81A']"
PS1-11af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ksf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ARP 299-B AT1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN.106....1F'
2022hvp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2011ApJ...732L..12B', '2020SSRv..216...81A']"
D3-13 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because 'arXiv:2405.11343'
2022lri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PS1-12yp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019bhf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022agi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018hyz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019lwu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN..99....1Y'
2022gri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019mha has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020opy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
XMMSL1 J0740-85 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
SDSSJ1311 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aalzpx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018dyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022adm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
TDE1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019A&A...630A..98S', '2020SSRv..216...81A']"
XMMSL2 J144605.0+685735 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2011MNRAS.417L..51V', '2020SSRv..216...81A']"
TDE2 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
D23H-1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
FIRST J153350.8+272729 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019dsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J091225 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133737 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1190358 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J12580+0134 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J234449.6+015434 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.1878N', '2020SSRv..216...81A']"
2017eqx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2017ApJ...843..106B', '2020SSRv..216...81A']"
AT2016ezh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021uvz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
LEDA 095953 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WINGS J1348 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018lni has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16ajq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022rz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2MASX J0249 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J210626.2-020055 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J123715 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...793...38A', '2020SSRv..216...81A']"
PTF09axc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021uqv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dsb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021MNRAS.500.1673H'
2019azh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019cho has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021mhg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018iih has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J011148.1-025539 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF-15af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J130819 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018hco has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022bdw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021jsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
3XMM J152130.7+074916 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aanbso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020neh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2018ASPC..517..737V', '2020SSRv..216...81A']"
2018zr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018gn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0748 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020ysg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020mbq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
OGLE16aaa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF11glr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2012A&A...541A.106S', '2020SSRv..216...81A']"
SDSSJ1201 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2020vwl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024tvd has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2024arXiv240111773C'
2023clx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15lh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CSS100217 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022upj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2023lli has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.

Now, we need to calculate all of the luminosities from these fluxes

dfs = []

for name,grp in allphot.groupby("name"):
    t = db.get_meta(names=name)[0]

    try:
        z = t.get_redshift() * cu.redshift
    except (KeyError, otter.exceptions.FailedQueryError):
        print("No redshift! SKipping", t.default_name)
        continue
    lum_dist = z.to(u.Mpc, equivalencies=cu.redshift_distance(cosmo, kind="luminosity"))

    lum_nu = [(4*np.pi*lum_dist**2 * (val * u.erg/u.s/u.cm**2/u.Hz)).to(u.erg/u.s/u.Hz) for val in grp.converted_flux]
    grp["nu_lum_nu"] = [(val*eff*u.GHz).to(u.erg/u.s).value for val, eff in zip(lum_nu, grp.converted_freq)]
    dfs.append(grp)

convphot = pd.concat(dfs)

convphot

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WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1089' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.051' to a unit explicitly. [warnings]
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WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.088' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0457266' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.212' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.091' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.071' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.022' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1206' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0512' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.074' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.117' to a unit explicitly. [warnings]

No redshift! SKipping 2019pqt

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WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0942' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.07' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.062' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.084' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0705' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.159' to a unit explicitly. [warnings]
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WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.184' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.064' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.22405' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.132' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.207' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.026' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.05' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.147' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0636' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.31167' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0615' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0789' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.146' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.18' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.08754' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0366' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0777' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.89' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.354' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '1.1853' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.136' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.2515' to a unit explicitly. [warnings]

No redshift! SKipping VAST J011148.1-025539
No redshift! SKipping VAST J093634.7-054755
No redshift! SKipping VAST J104315.9+005059
No redshift! SKipping VAST J144848.2+030235
No redshift! SKipping VAST J210626.2-020055
No redshift! SKipping VAST J213437.8-620433
No redshift! SKipping VAST J215418.2+002442
No redshift! SKipping VAST J221936.0+004724
No redshift! SKipping VAST J230053.0-020732
No redshift! SKipping VAST J234449.6+015434

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.062' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0173' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.029' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.108' to a unit explicitly. [warnings]

	name	converted_flux	converted_flux_err	converted_date	converted_wave	converted_freq	converted_flux_unit	converted_date_unit	converted_wave_unit	converted_freq_unit	filter_name	obs_type	upperlimit	reference	human_readable_refs	telescope	nu_lum_nu
0	2016fnl	9.600000e-28	0.000000e+00	57631.680	1.934145e+07	1.550000e+01	erg/s/cm^2/Hz	MJD	nm	GHz	Ku	radio	True	2021ApJ...920L...5H	Horesh, Assaf et al. (2021)	AMI-LA	9.518954e+36
1	2016fnl	1.260000e-27	0.000000e+00	57635.690	1.934145e+07	1.550000e+01	erg/s/cm^2/Hz	MJD	nm	GHz	Ku	radio	True	2021ApJ...920L...5H	Horesh, Assaf et al. (2021)	AMI-LA	1.249363e+37
2	2016fnl	1.080000e-27	0.000000e+00	57648.600	1.934145e+07	1.550000e+01	erg/s/cm^2/Hz	MJD	nm	GHz	Ku	radio	True	2021ApJ...920L...5H	Horesh, Assaf et al. (2021)	AMI-LA	1.070882e+37
3	2016fnl	6.600000e-28	0.000000e+00	57683.500	1.934145e+07	1.550000e+01	erg/s/cm^2/Hz	MJD	nm	GHz	Ku	radio	True	2021ApJ...920L...5H	Horesh, Assaf et al. (2021)	AMI-LA	6.544281e+36
4	2016fnl	1.200000e-27	2.400000e-28	58010.000	1.934145e+07	1.550000e+01	erg/s/cm^2/Hz	MJD	nm	GHz	Ku	radio	False	2021ApJ...920L...5H	Horesh, Assaf et al. (2021)	AMI-LA	1.189869e+37
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
351	iPTF16axa	2.187762e-28	1.277525e-30	57613.248	2.600000e+02	1.153048e+06	erg/s/cm^2/Hz	MJD	nm	GHz	UVM2	uvoir	False	[2017ApJ...842...29H]	Hung et al. (2017)	Swift	8.055109e+42
352	iPTF16axa	1.836538e-28	1.682460e-30	57620.538	2.246000e+02	1.334784e+06	erg/s/cm^2/Hz	MJD	nm	GHz	UVW1	uvoir	False	[2017ApJ...842...29H]	Hung et al. (2017)	Swift	7.827716e+42
353	iPTF16axa	3.191538e-28	3.169352e-30	57620.540	3.650000e+02	8.213492e+05	erg/s/cm^2/Hz	MJD	nm	GHz	U	uvoir	False	[2017ApJ...842...29H]	Hung et al. (2017)	Swift	8.370510e+42
354	iPTF16axa	2.355049e-28	1.035439e-30	57620.542	1.928000e+02	1.554940e+06	erg/s/cm^2/Hz	MJD	nm	GHz	UVW2	uvoir	False	[2017ApJ...842...29H]	Hung et al. (2017)	Swift	1.169332e+43
355	iPTF16axa	1.836538e-28	1.328258e-30	57620.546	2.600000e+02	1.153048e+06	erg/s/cm^2/Hz	MJD	nm	GHz	UVM2	uvoir	False	[2017ApJ...842...29H]	Hung et al. (2017)	Swift	6.761942e+42

118317 rows × 17 columns

And now we need to find the discovery date of each object so that we can plot everything normalized to the discovery date

disc_date_dict = {}
for name, phot in convphot.groupby("name"):
    t = db.get_meta(names=name)[0]

    try:
        disc_date = t.get_discovery_date().mjd
    except (KeyError, TypeError, otter.exceptions.FailedQueryError, AttributeError):
        #  print("No Discovery Date! Skipping", t.default_name)
        #  continue
        disc_date = phot.converted_date.min()

    disc_date_dict[t.default_name] = disc_date

Now that we have all the information, we can create the plot!

# Create a colormap with only white
white_cmap = ListedColormap(['white'])

p = convphot[~convphot.upperlimit.astype(bool)]

fig, axs = plt.subplots(
    3,1,
    figsize=(7,9),
    sharex=True,
    gridspec_kw = {'wspace':0, 'hspace':0},
    # layout="tight"
)

ylims = [(1e36, 1e46), (1e37, 1e46), (1e39, 1e47)]
obs_types = ["radio", "uvoir", "xray"]
obs_type_labels = {
    "radio" : "Radio",
    "uvoir" : "UV/Optical/IR",
    "xray"  : "X-Ray"
}

yr = 365
xlim = (1e-2, 30*yr)
nbins = 40

all_dts = []

cmap = cmr.bubblegum

tick_color = "k" #cmr.dusk.colors[256 - (256//10)] #"peru"#"chocolate"

cmap.set_bad(color=cmap.colors[0])

plot_2dhist = False

levels = [
    [2,4,6,10],
    [2, 10, 30, 100],
    [2,4,6,10]
]

for ylim, obs_type, ax, levs in zip(ylims, obs_types, axs.flatten(), levels):

    ax.yaxis.set_minor_locator(mpl.ticker.AutoMinorLocator())
    ax.spines['bottom'].set_color(tick_color)
    ax.spines['top'].set_color(tick_color)
    ax.spines['right'].set_color(tick_color)
    ax.spines['left'].set_color(tick_color)
    ax.tick_params(axis='x', colors=tick_color, which="both", labelcolor="k")
    ax.tick_params(axis='y', colors=tick_color, which="both", labelcolor="k")

    grp = convphot[convphot.obs_type == obs_type]

    days, lum = [], []
    for (filt, targ), phot in grp.groupby(["filter_name", "name"]):
        if targ not in disc_date_dict: continue
        disc_date = disc_date_dict[targ]

        phot = phot.sort_values("converted_date")
        phot['mjd_norm'] = (phot.converted_date - disc_date)

        phot = phot[phot.mjd_norm > xlim[0]] # only plot photometry after discovery, otherwise the plot makes no sense

        # uncomment to plot each light curve as a black line:
        #ax.plot(phot.mjd_norm, phot.nu_lum_nu, color='k', alpha=0.05)

        days += phot.mjd_norm.to_list()
        lum += phot.nu_lum_nu.to_list()

        #x.set_ylabel(r"$\nu~L_\nu$ [erg s$^{-1}$]")

    ax.plot(days, lum, marker='o', markersize=3, alpha=1, color='silver', linestyle="none", zorder=0)

    xbins = np.logspace(np.log10(xlim[0]), np.log10(xlim[1]), nbins+1) # #np.linspace(xlim[0], xlim[1], nbins+1),
    ybins = np.logspace(np.log10(ylim[0]), np.log10(ylim[1]), nbins+1)

    heatmap, xedges, yedges = np.histogram2d(
        days,
        lum,
        bins=[xbins, ybins],
    )

    dx = np.diff(xedges)
    dy = np.diff(yedges)
    area = np.outer(dx, dy)

    ax.set_yscale("log")
    ax.set_xscale("log")
    # # heatmap[heatmap == 0] = 1e-20
    x,y = np.meshgrid(xedges[:-1], yedges[:-1])
    z = heatmap.T #(heatmap / dx[:, np.newaxis]).T #heatmap.T/np.diff(xedges) #heatmap.T,
    z[z==0] = np.min(z[z!=0])/10

    # do some smoothing of the contours
    z1 = scipy.ndimage.gaussian_filter(z, sigma=1.5, order=0)

    minlogz = np.log10(2.5) #0 # np.floor(np.min(np.log10(z)))
    maxlogz = np.ceil(np.max(np.log10(z))/2)
    #levs = [2, 4, 6, 10] #np.logspace(minlogz, maxlogz, 4)
    levs_wht = deepcopy(levs)
    levs_wht[-1] = 10**(maxlogz*2)

    cm = ax.contourf(
        x, y, z1,
        origin='lower',
        cmap=white_cmap,
        norm = mpl.colors.LogNorm(),
        extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]],
        levels = levs_wht,
        zorder=0.5
    )

    cm = ax.contour(
        x, y, z1,
        origin='lower',
        cmap=cmap,
        norm = mpl.colors.LogNorm(),
        extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]],
        levels = levs,
        zorder=100,
        linewidths= 3
    )

    if plot_2dhist:
        ax.pcolormesh(
            x,
            y,
            np.ma.masked_where(heatmap.T < (10**maxlogz)/3, heatmap.T),
            zorder = 20,
            cmap = "binary",
            # norm = mpl.colors.LogNorm()#mpl.colors.Normalize(4, 10**maxlogz),
            edgecolor="none",
            # alpha = 0.8
        )

    cbar = fig.colorbar(cm, ax=ax, shrink=0.8, pad=0.02)
    #cbar_labels = [v.get_text() for v in cbar.ax.get_yticklabels()]
    cbar_labels = [f"{int(v)}" for v in levs]
    #cbar_labels[0] = "$\\mathdefault{\\leq}$"+cbar_labels[0]#.replace("$\\mathdefault{", )
    # cbar.ax.set_yticklabels(cbar_labels)
    cbar_linecolors = cbar.lines[0].get_color()
    legend = ax.legend(
        [mpl.lines.Line2D([0],[0],color=c, lw=4) for c in cbar_linecolors],
        cbar_labels,
        loc="center",
        bbox_to_anchor=(1.15, 0.5),
        frameon=False,
        fontsize=16,
    )
    for text in legend.get_texts():
        text.set_rotation(30) # Rotate by 90 degrees
    cbar.remove()

    # print(heatmap.T)
    ax.text(
        0.01, 0.05,
        obs_type_labels[obs_type],
        horizontalalignment="left",
        transform=ax.transAxes,
        color="k",
        fontsize = 16,
        zorder = 1_000,
        weight = "semibold"
    )

    ax.set_ylim(*ylim)
    all_dts.append(days)

    ax2 = axs[0].secondary_xaxis("top", functions=(lambda x: x/yr, lambda x: x*yr))
    ax2.tick_params(axis='x', colors=tick_color, which="both", labelcolor="k", labelsize=16)

    ax.tick_params(axis='x', labelsize=16)      # x-axis tick labels
    ax.tick_params(axis='y', labelsize=16)      # y-axis tick labels


label_kwargs = dict(
    fontsize = 24,
    weight = "semibold",
)
fig.supxlabel("Days Since Discovery", **label_kwargs)
fig.supylabel(r"$\nu~L_\nu$ [erg s$^{-1}$]", **label_kwargs, x=-0.03)
fig.suptitle("Years Since Discovery", **label_kwargs)
fig.text(1.1, 0.5, "Number of Photometry Points", rotation=-90, va="center", **label_kwargs)

savefig(fig, "tde-lightcurves.png")

Figure 10: Photometry Point Wavelength Distribution

# get all of the photometry in otter
with warnings.catch_warnings(action="ignore"):
    allphot = db.get_phot(flux_unit="erg/s/cm^2/Hz", return_type="pandas")

J121116 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021nwa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14li has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aaldjb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...883..111H'
AT2019ahk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aatsnw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023arXiv231003791S'
2020vdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ack has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CNSS J0019+00 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF16axa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2018jbv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
SDSSJ1323 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J141036 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021utq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Dougie has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J215418.2+002442 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021lo has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019eve has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2022mim has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019teq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
RX J1624+75 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbjsh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J030257 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020pj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J142401 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J093634.7-054755 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dbl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019pqt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024qab has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J113527 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021qxv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021jjm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15oi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022czy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021sdu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020acka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018bsi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adeqka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022A&A...666A...6W'
2020zso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020riz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J145851 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019ehz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14acnjbu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.197....1W'
2023mhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1342 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019vcb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1350 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Swift J2058.4+0516 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020mot has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021crk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022pna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018cqh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ehb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022wtn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2020yue has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021axu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.4816W', '2020SSRv..216...81A']"
2018fyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020wey has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2002RvMA...15...27K', '2020SSRv..216...81A']"
NGC 5905 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09ge has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022cmc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
eRASSt J234403-352640 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019meg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J104315.9+005059 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
DES14C1kia has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
RX J1242-11A has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.250....1C'
2023mfm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021gje has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2006ApJ...653L..25G'
D1-9 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J144848.2+030235 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ocn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022ApJ...925...67L'
2019cmw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbgpn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1185375 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J17361-4441 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP18aajkmk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15abymdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yzv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018lna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamoxe has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1112-82 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J100933 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
PTF10iya has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2020MNRAS.499..482N'
2019qiz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022exr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...887..218L'
AT2018dyb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF10nuj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020qhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamzew has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.102....1Y'
2023cvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dyt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16aax has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.326....1H'
2023rvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J155223 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J213437.8-620433 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ddv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbuuv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aaqrcr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09djl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14ae has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020nov has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1644+57 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133837 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019gte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021zlg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
PS1-10jh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J230053.0-020732 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RX J1420+53 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2017bcc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RBS 1032 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022arb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021blz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbwvs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0159 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2016fnl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
NGC 3599 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0952 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J221936.0+004724 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2020abri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...780...44C', '2020SSRv..216...81A']"
PS1-11af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ksf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ARP 299-B AT1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN.106....1F'
2022hvp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2011ApJ...732L..12B', '2020SSRv..216...81A']"
D3-13 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because 'arXiv:2405.11343'
2022lri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PS1-12yp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019bhf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022agi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018hyz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019lwu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN..99....1Y'
2022gri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019mha has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020opy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
XMMSL1 J0740-85 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
SDSSJ1311 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aalzpx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018dyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022adm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
TDE1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019A&A...630A..98S', '2020SSRv..216...81A']"
XMMSL2 J144605.0+685735 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2011MNRAS.417L..51V', '2020SSRv..216...81A']"
TDE2 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
D23H-1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
FIRST J153350.8+272729 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019dsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J091225 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133737 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1190358 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J12580+0134 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J234449.6+015434 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.1878N', '2020SSRv..216...81A']"
2017eqx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2017ApJ...843..106B', '2020SSRv..216...81A']"
AT2016ezh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021uvz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
LEDA 095953 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WINGS J1348 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018lni has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16ajq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022rz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2MASX J0249 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J210626.2-020055 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J123715 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...793...38A', '2020SSRv..216...81A']"
PTF09axc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021uqv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dsb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021MNRAS.500.1673H'
2019azh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019cho has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021mhg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018iih has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J011148.1-025539 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF-15af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J130819 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018hco has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022bdw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021jsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
3XMM J152130.7+074916 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aanbso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020neh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2018ASPC..517..737V', '2020SSRv..216...81A']"
2018zr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018gn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0748 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020ysg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020mbq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
OGLE16aaa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF11glr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2012A&A...541A.106S', '2020SSRv..216...81A']"
SDSSJ1201 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2020vwl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024tvd has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2024arXiv240111773C'
2023clx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15lh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CSS100217 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022upj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2023lli has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.

fig, ax = plt.subplots()

f = allphot.converted_wave

logbins = np.logspace(np.log10(f.min()),np.log10(f.max()),40)
bins, edges = np.histogram(f, bins=logbins)

ax.stairs(bins, edges, color='cornflowerblue')

ax.set_xscale("log")
ax.set_yscale("log")

ax.tick_params(axis='x', top=False)

ax.set_xlabel("Wavelength [nm]", fontsize=14)
ax.set_ylabel("Number of Photometry Points", fontsize=14)

# create a dictionary of reference filters/bands to plot
filts = {
    "-":1e-2, # this is just to fix a bug in matplotlib
    #"0.5-1.2 keV" : ((c.h*c.c) / ((1.2-0.5)/2*u.keV)).to(u.m).value,
    #"1.2-2 keV" : ((c.h*c.c) / ((2-1.2)/2*u.keV)).to(u.m).value,
    # '2-7 keV' : ((c.c * c.h) / ((7-2)/2 * u.keV)).to(u.m).value,
    "7 keV" : ((c.h*c.c) / (7*u.keV)).to(u.nm).value,
    "0.5 keV" : ((c.h*c.c) / (0.5*u.keV)).to(u.nm).value,
    "FUV": 153.8620701901866,#*1e-9,
    "NUV": 231.56631043707714,#*1e-9,
    # "UVW2": 207.98754332676123*1e-9,
    "U": 353.10502283105023,#*1e-9,
    #"B": 443.0539845758355*1e-9,
    "V": 553.7155963302753,#*1e-9,
    # "G": 673.5412573108297*1e-9,
    #"R": 646.9439215118385*1e-9,
    "I": 788.558706467662,#*1e-9,
    "J": 1255.0918319447906,#*1e-9,
    "H": 1630.5155019191195,#*1e-9,
    # "K": 2157.3600605745955*1e-9,
    "WISE.1": (3.4*u.um).to(u.nm).value,
    "WISE.2": (4.6*u.um).to(u.nm).value,
    "WISE.3":(12*u.um).to(u.nm).value,
    "WISE.4": (22*u.um).to(u.nm).value,
} | {
    k:(
        (v[0] + ((v[1] - v[0]) / 2))*u.GHz
    ).to(
        u.nm,
        equivalencies=u.spectral()
    ).value
    for k, v in otter.util.RADIO_BAND_MAPPING.items()
    if k not in {"alma.1", "alma.9", "alma.5", "alma.8", "VHF", "HF"}
}

ytext = 1.5e5
for lab, xtext in filts.items():
    ax.text(xtext, ytext, lab, horizontalalignment="center", verticalalignment="bottom", rotation=90, fontsize=5)
    ax.vlines(xtext, ymin=ytext/1.5, ymax=ytext/1.1, lw=1, color="k")

ax.set_xlim(5e-2, 4e10)
ax.set_ylim(0.8, 8e5)

ax.secondary_xaxis(
    "top",
    functions=(
        lambda x: (x*u.nm).to(u.GHz, equivalencies=u.spectral()).value,
        lambda x: (x*u.GHz).to(u.nm, equivalencies=u.spectral()).value
    )
)
ax.set_title("Frequency [GHz]", fontsize=14)

savefig(fig, "photometry-histogram.png")

Figure 11: Number of Observations as a function of year

This is similar to Figure 7 but instead of discovery date it’s just the observation date of the photometry point stored in OTTER

# get all of the photometry in otter
with warnings.catch_warnings(action="ignore"):
    allphot = db.get_phot(flux_unit="erg/s/cm^2/Hz", return_type="pandas")

J121116 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021nwa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14li has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aaldjb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...883..111H'
AT2019ahk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aatsnw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023arXiv231003791S'
2020vdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ack has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CNSS J0019+00 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF16axa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2018jbv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
SDSSJ1323 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J141036 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021utq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Dougie has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J215418.2+002442 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021lo has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019eve has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2022mim has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019teq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
RX J1624+75 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbjsh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J030257 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020pj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J142401 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J093634.7-054755 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dbl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019pqt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024qab has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J113527 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021qxv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021jjm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15oi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022czy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2021sdu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020acka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018bsi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adeqka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022A&A...666A...6W'
2020zso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020riz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J145851 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019ehz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14acnjbu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.197....1W'
2023mhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1342 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019vcb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1350 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Swift J2058.4+0516 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020mot has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021crk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022pna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018cqh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ehb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022wtn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2020yue has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021axu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.4816W', '2020SSRv..216...81A']"
2018fyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020wey has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2002RvMA...15...27K', '2020SSRv..216...81A']"
NGC 5905 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09ge has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022cmc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
eRASSt J234403-352640 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019meg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J104315.9+005059 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
DES14C1kia has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
RX J1242-11A has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.250....1C'
2023mfm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021gje has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2006ApJ...653L..25G'
D1-9 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J144848.2+030235 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ocn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022ApJ...925...67L'
2019cmw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbgpn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1185375 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J17361-4441 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP18aajkmk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15abymdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yzv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018lna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamoxe has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1112-82 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J100933 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
PTF10iya has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2020MNRAS.499..482N'
2019qiz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022exr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...887..218L'
AT2018dyb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF10nuj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020qhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamzew has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.102....1Y'
2023cvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dyt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16aax has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.326....1H'
2023rvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J155223 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J213437.8-620433 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ddv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbuuv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aaqrcr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09djl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14ae has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020nov has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1644+57 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133837 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019gte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021zlg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
PS1-10jh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J230053.0-020732 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RX J1420+53 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2017bcc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RBS 1032 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022arb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021blz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbwvs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0159 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2016fnl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
NGC 3599 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0952 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J221936.0+004724 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
2020abri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...780...44C', '2020SSRv..216...81A']"
PS1-11af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ksf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ARP 299-B AT1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN.106....1F'
2022hvp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2011ApJ...732L..12B', '2020SSRv..216...81A']"
D3-13 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because 'arXiv:2405.11343'
2022lri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PS1-12yp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019bhf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022agi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018hyz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019lwu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN..99....1Y'
2022gri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019mha has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020opy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
XMMSL1 J0740-85 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
SDSSJ1311 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aalzpx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018dyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022adm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
TDE1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019A&A...630A..98S', '2020SSRv..216...81A']"
XMMSL2 J144605.0+685735 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2011MNRAS.417L..51V', '2020SSRv..216...81A']"
TDE2 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"
D23H-1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
FIRST J153350.8+272729 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019dsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J091225 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133737 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1190358 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J12580+0134 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J234449.6+015434 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.1878N', '2020SSRv..216...81A']"
2017eqx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2017ApJ...843..106B', '2020SSRv..216...81A']"
AT2016ezh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021uvz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
LEDA 095953 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WINGS J1348 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018lni has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16ajq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022rz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2MASX J0249 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J210626.2-020055 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J123715 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...793...38A', '2020SSRv..216...81A']"
PTF09axc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021uqv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022dsb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021MNRAS.500.1673H'
2019azh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019cho has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021mhg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018iih has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J011148.1-025539 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF-15af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J130819 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2018hco has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022bdw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021jsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
3XMM J152130.7+074916 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aanbso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020neh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2018ASPC..517..737V', '2020SSRv..216...81A']"
2018zr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018gn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0748 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020ysg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
2020mbq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
OGLE16aaa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF11glr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2012A&A...541A.106S', '2020SSRv..216...81A']"
SDSSJ1201 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2020vwl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024tvd has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2024arXiv240111773C'
2023clx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15lh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CSS100217 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022upj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2023lli has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.

allphot['obs_year'] = np.floor(Time(allphot.converted_date, format='mjd').decimalyear).astype(int)

cs = [ "#EE9B00", "#AE2012", "#005F73"]

allphot.obs_type = allphot.obs_type.replace('radio', 'Radio')
allphot.obs_type = allphot.obs_type.replace('xray', 'X-Ray')
allphot.obs_type = allphot.obs_type.replace('uvoir', 'UV/Optical/IR')

fig, ax = plt.subplots()

n = 40
bottom = np.zeros(n)

all_colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
grped_yrs = {y : g.obs_year.values for y,g in allphot.groupby('obs_type')}
labels = ["X-Ray", "Radio", "UV/Optical/IR"]
years = [grped_yrs[lb] for lb in labels]

ax.hist(years, label=labels, bins=n, stacked=True, color=cs)
ax.hist(allphot.obs_year, bins=n, stacked=True, histtype='step', edgecolor='k')

ax.set_yscale('log')

ax.set_ylabel('Number of Observations', fontsize=18, fontweight="semibold")
ax.set_xlabel('Year', fontsize=18, fontweight="semibold")

ax.set_xlim(1989, 2025)

ax.tick_params(axis='x', labelsize=14)      # x-axis tick labels
ax.tick_params(axis='y', labelsize=14)      # y-axis tick labels

ax.legend(fontsize=14, frameon=False)

savefig(fig, "tde-observations-vs-time.png")

Section 5: Example Analyses

Section 5.1: Time Delay Analysis

First, we need to import rpy2 which allows us to call R functions in python. This is necessary because the survival analysis statistical tools are well developed in R and not python (like Kaplan-Meier estimators and Greenwood Confidence).

To use rpy2

1. you need to install R: https://www.r-project.org/

2. And then install rpy2: https://rpy2.github.io/

import rpy2
import rpy2.robjects as ro
from rpy2.robjects.packages import importr
from rpy2.robjects import NA_Real, FloatVector, Formula, pandas2ri

/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/rpy2/rinterface/__init__.py:1211: UserWarning: Environment variable "LD_LIBRARY_PATH" redefined by R and overriding existing variable. Current: "/usr/lib/R/lib:/usr/lib/x86_64-linux-gnu:/usr/lib/jvm/default-java/lib/server", R: "/usr/lib/R/lib:/usr/lib/x86_64-linux-gnu:/usr/lib/jvm/default-java/lib/server:/usr/lib/R/lib:/usr/lib/x86_64-linux-gnu:/usr/lib/jvm/default-java/lib/server"
  warnings.warn(
/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/rpy2/rinterface/__init__.py:1211: UserWarning: Environment variable "R_LIBS_SITE" redefined by R and overriding existing variable. Current: "/usr/local/lib/R/site-library/:/usr/local/lib/R/site-library:/usr/lib/R/site-library:/usr/lib/R/library", R: "/usr/local/lib/R/site-library/:/usr/local/lib/R/site-library/:/usr/local/lib/R/site-library/:/usr/local/lib/R/site-library:/usr/lib/R/site-library:/usr/lib/R/library:/usr/lib/R/library:/usr/lib/R/library"
  warnings.warn(
/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/rpy2/rinterface/__init__.py:1211: UserWarning: Environment variable "R_PAPERSIZE_USER" redefined by R and overriding existing variable. Current: "a4", R: "letter"
  warnings.warn(
/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/rpy2/rinterface/__init__.py:1211: UserWarning: Environment variable "R_SESSION_TMPDIR" redefined by R and overriding existing variable. Current: "/tmp/RtmpvdmKMn", R: "/tmp/RtmpBVJoyi"
  warnings.warn(

Now we need to define a function to do the “survival analysis” (or the statistical analysis that takes the limits into account)

def surv_analysis(left_censored, right_censored, verbose=True):
    """
    This uses rpy2 to perform a survival analysis on differenced data that has both
    right and left censored values. It returns the results of a Kaplan-Meier fit
    and the corresponding quantiles
    """

    # lc = FloatVector([NA_Real if v else d for v, d in zip(left_censored, diff)])
    # rc = FloatVector([NA_Real if v else d for v, d in zip(right_censored, diff)])

    lc = FloatVector(left_censored)
    rc = FloatVector(right_censored)

    if verbose:
        print(tuple(lc), tuple(rc))

    rsurvival = importr("survival")
    r_surv_obj = rsurvival.Surv(lc, rc, type="interval2")

    ro.globalenv["r_surv_obj"] = r_surv_obj
    fit = ro.r("survfit(r_surv_obj ~ 1, conf.int=0.95, conf.type='plain')")

    ro.globalenv["fit"] = fit

    if verbose:
        print(ro.r("summary(fit)"))
    #ro.r("plot(fit)")
    # extract the results of the fit
    res = dict(fit.items())
    if verbose:
        print(str(res['call']))
    resdf = pd.read_csv(io.StringIO(str(res['call'])), skiprows=2, sep='\s+')

    # compute the quantiles
    ro.globalenv["fit"] = fit
    q = pd.read_csv(io.StringIO(str(ro.r("quantile(fit, prob=c(0.16, 0.25, 0.5, 0.75, 0.84))$quantile"))), sep="\s+")

    return resdf, q

<>:32: SyntaxWarning: invalid escape sequence '\s'
<>:36: SyntaxWarning: invalid escape sequence '\s'
<>:32: SyntaxWarning: invalid escape sequence '\s'
<>:36: SyntaxWarning: invalid escape sequence '\s'
/tmp/ipykernel_489627/2718474138.py:32: SyntaxWarning: invalid escape sequence '\s'
  resdf = pd.read_csv(io.StringIO(str(res['call'])), skiprows=2, sep='\s+')
/tmp/ipykernel_489627/2718474138.py:36: SyntaxWarning: invalid escape sequence '\s'
  q = pd.read_csv(io.StringIO(str(ro.r("quantile(fit, prob=c(0.16, 0.25, 0.5, 0.75, 0.84))$quantile"))), sep="\s+")

Now get the X-ray and UV/Optical/IR photometry

xrays = db.get_phot(obs_type="xray", flux_unit="erg s^-1 cm^-2", return_type="pandas")
uvoir = db.get_phot(obs_type="uvoir", flux_unit="Jy", return_type="pandas")
unambiguous = {t.default_name for t in db.query(unambiguous=True)}

Unable to apply the source mapping because Cannot set a DataFrame with multiple columns to the single column human_readable_refs
ASASSN-14li has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aaldjb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aatsnw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1323 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Dougie has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2022mim has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019teq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RX J1624+75 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbjsh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15oi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adeqka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019ehz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14acnjbu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1342 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019vcb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1350 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Swift J2058.4+0516 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021ehb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018fyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
NGC 5905 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09ge has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
DES14C1kia has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RX J1242-11A has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
D1-9 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ocn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbgpn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1185375 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
IGR J17361-4441 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP18aajkmk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15abymdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021yzv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamoxe has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1112-82 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF10iya has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF10nuj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aamzew has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16aax has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ddv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP15acbuuv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP16aaqrcr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09djl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-14ae has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Sw J1644+57 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PS1-10jh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
RX J1420+53 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Removing 28 photometry points from
                    2017bcc because we can't convert them from ct ->
                    erg s^-1 cm^-2
RBS 1032 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP14adbwvs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0159 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2016fnl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
NGC 3599 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0952 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PS1-11af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2020ksf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
D3-13 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PS1-12yp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018hyz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
XMMSL1 J0740-85 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1311 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aalzpx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018dyk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
TDE2 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
D23H-1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019dsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PGC 1190358 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
LEDA 095953 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WINGS J1348 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2MASX J0249 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF09axc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019azh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
3XMM J152130.7+074916 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WTP17aanbso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018zr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018gn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ0748 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
OGLE16aaa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
PTF11glr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSSJ1201 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
ASASSN-15lh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
CSS100217 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022upj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2023lli has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J121116 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021nwa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
Unable to apply the source mapping because '2019ApJ...883..111H'
AT2019ahk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023arXiv231003791S'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020vdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021ack has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
iPTF16axa has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...942....9H'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2018jbv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J141036 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023ApJ...955L...6Y'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021utq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021lo has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021ApJ...908....4V'
2019eve has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J030257 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020pj has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J142401 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022dbl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019pqt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2024qab has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J113527 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021qxv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021jjm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021sdu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020acka has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018bsi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021yte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022A&A...666A...6W'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020zso has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020riz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J145851 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
Unable to apply the source mapping because '2023TNSAN.197....1W'
2023mhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020mot has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021crk has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022pna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022wtn has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020yue has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021axu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020wey has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022cmc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2019meg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.250....1C'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2023mfm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021gje has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2006ApJ...653L..25G'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
Unable to apply the source mapping because '2022ApJ...925...67L'
2019cmw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2018lna has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J100933 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2020MNRAS.499..482N'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2019qiz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022exr has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2019ApJ...887..218L'
AT2018dyb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020qhs has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.102....1Y'
2023cvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022dyt has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2023TNSAN.326....1H'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2023rvb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J155223 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020nov has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133837 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021zlg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2017bcc has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020abri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
Unable to apply the source mapping because '2022TNSAN.106....1F'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022hvp has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because 'arXiv:2405.11343'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022lri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2019bhf has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022agi has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2019lwu has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2022TNSAN..99....1Y'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022gri has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2019mha has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020opy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
TDE1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J091225 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J133737 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2017eqx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2016ezh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021uvz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2018lni has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Gaia 16ajq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022rz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J123715 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021uqv has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022dsb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2021MNRAS.500.1673H'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2019cho has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021mhg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2018iih has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
iPTF-15af has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
J130819 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2018hco has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2022bdw has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2021jsg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020neh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020ysg has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2020mbq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2024tvd has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because '2024arXiv240111773C'
/home/nfranz/research/astro-otter/otter/src/otter/io/transient.py:835: RuntimeWarning: invalid value encountered in multiply
  flux_err = np.multiply(prefactor, np.divide(q_err.value, q.value))
2023clx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.

n_tdes = len(list(set(xrays.name.unique()) & set(uvoir.name.unique()) & unambiguous))
print(n_tdes)
cmap = mpl.colormaps['tab20']
colors_init = iter(cmap(np.linspace(0, 1, n_tdes)))
markers = list(Line2D.filled_markers)
markers.remove('.')
markers = iter(4*list(markers))

fs = 14

fig, ax = plt.subplots(figsize=(7,5))

max_xray_date = []
max_uvoir_date = []
labels = []
colors = []
markers_used = []
diff = []
left_censored = []
right_censored = []

exclude = {
    "Sw J1644+57", # we only want to do this for non-jetted events
    "Swift J2058.4+0516", # we only want to do this for non-jetted events
    "Gaia 16aax", # only one post-discovery X-ray observation
}

xray_flux_diffs = []
uvoir_flux_diffs = []

for name in list(set(xrays.name.unique()) & set(uvoir.name.unique()) & unambiguous):

    if name in exclude: continue

    t = db.get_meta(names=name)[0]
    try:
        disc_date = t.get_discovery_date().mjd
    except:
        print(f"Missing discovery date for {name}!")
        continue

    uvoir_data = uvoir[(uvoir.name == name) * (~uvoir.upperlimit) * (uvoir.converted_date > disc_date) * (uvoir.converted_wave < 1_000)].sort_values(by="converted_date")
    xray_data = xrays[(xrays.name == name) * (~xrays.upperlimit) * (xrays.converted_date > disc_date)].sort_values(by="converted_date")

    if len(uvoir_data) == 0 or len(xray_data) == 0:
        print(f"Insufficient data for {name}, skipping...")
        continue

    color = next(colors_init)
    mark = next(markers)

    try:
        z = t.get_redshift()
    except:
        print("Missing redshift for {name}!")
        continue

    lum_dist = cosmo.luminosity_distance(z)

    uvoir_lum = (4*np.pi*lum_dist**2 * (uvoir_data.converted_flux.values*u.Jy) * uvoir_data.converted_freq.values*u.GHz).to(u.erg/u.s).value
    xray_lum = (4*np.pi*lum_dist**2 * (xray_data.converted_flux.values*u.erg/u.s/u.cm**2)).to(u.erg/u.s).value

    max_uvoir_idx = np.argmax(uvoir_lum)
    max_xray_idx = np.argmax(xray_lum)

    max_uvoir_dt = uvoir_data.converted_date.values[max_uvoir_idx] - disc_date
    max_xray_dt = xray_data.converted_date.values[max_xray_idx] - disc_date

    # determine which are limits
    uvoir_uplim, uvoir_lolim, xray_uplim, xray_lolim = False, False, False, False
    if max_uvoir_idx == 0:
        ax.annotate("", xy=(max_xray_dt, max_uvoir_dt-max_uvoir_dt/3), xytext=(max_xray_dt, max_uvoir_dt), arrowprops=dict(arrowstyle="->", color=color, linewidth=2))

    if max_uvoir_idx == len(uvoir_data)-1:
        ax.annotate("", xy=(max_xray_dt, max_uvoir_dt+max_uvoir_dt/3), xytext=(max_xray_dt, max_uvoir_dt), arrowprops=dict(arrowstyle="->", color=color, linewidth=2))

    if max_xray_idx == 0:
        ax.annotate("", xy=(max_xray_dt-max_xray_dt/3, max_uvoir_dt), xytext=(max_xray_dt, max_uvoir_dt), arrowprops=dict(arrowstyle="->", color=color, linewidth=2))

    if max_xray_idx == len(xray_data)-1:
        ax.annotate("", xy=(max_xray_dt+max_xray_dt/3, max_uvoir_dt), xytext=(max_xray_dt, max_uvoir_dt), arrowprops=dict(arrowstyle="->", color=color, linewidth=2))

    has_lim = (max_uvoir_idx == 0 or max_uvoir_idx == len(uvoir_data)-1 or max_xray_idx == 0 or max_xray_idx == len(xray_data)-1)

    xray_is_uplim = max_xray_idx == 0
    xray_is_lolim = max_xray_idx == len(xray_data)-1
    uvoir_is_uplim = max_uvoir_idx == 0
    uvoir_is_lolim = max_uvoir_idx == len(uvoir_data)-1

    xray_min = xray_data.converted_date.values[max_xray_idx-1] - disc_date if not xray_is_uplim else -np.inf
    xray_max = xray_data.converted_date.values[max_xray_idx+1] - disc_date if not xray_is_lolim else np.inf
    uvoir_min = uvoir_data.converted_date.values[max_uvoir_idx-1] - disc_date if not uvoir_is_uplim else -np.inf
    uvoir_max = uvoir_data.converted_date.values[max_uvoir_idx+1] - disc_date if not uvoir_is_lolim else np.inf
    alldiffs = [xray_min-uvoir_min, xray_max-uvoir_min, xray_min-uvoir_max, xray_max-uvoir_max]

    loval,upval = min(alldiffs), max(alldiffs)

    if not xray_is_uplim:
        f1 = xray_data.converted_flux.values[max_xray_idx-1]
        f1_unc = xray_data.converted_flux_err.values[max_xray_idx-1]
        f2 = xray_data.converted_flux.values[max_xray_idx]
        f2_unc = xray_data.converted_flux_err.values[max_xray_idx]
        xray_sigma_sigma = (f2 - f1) / np.sqrt(f1_unc**2 + f2_unc**2)
        xray_flux_diffs.append(
            xray_sigma_sigma
        )
    else:
        f1 = xray_data.converted_flux.values[max_xray_idx+1]
        f1_unc = xray_data.converted_flux_err.values[max_xray_idx+1]
        f2 = xray_data.converted_flux.values[max_xray_idx]
        f2_unc = xray_data.converted_flux_err.values[max_xray_idx]
        xray_sigma_sigma = (f2 - f1) / np.sqrt(f1_unc**2 + f2_unc**2)
        xray_flux_diffs.append(
            xray_sigma_sigma
        )

    if not uvoir_is_uplim:
        f1 = uvoir_data.converted_flux.values[max_uvoir_idx-1]
        f1_unc = uvoir_data.converted_flux_err.values[max_uvoir_idx-1]
        f2 = uvoir_data.converted_flux.values[max_uvoir_idx]
        f2_unc = uvoir_data.converted_flux_err.values[max_uvoir_idx]
        uvoir_sigma_sigma = (f2 - f1) / np.sqrt(f1_unc**2 + f2_unc**2)
        uvoir_flux_diffs.append(
            uvoir_sigma_sigma
        )
    else:
        f1 = uvoir_data.converted_flux.values[max_uvoir_idx+1]
        f1_unc = uvoir_data.converted_flux_err.values[max_uvoir_idx+1]
        f2 = uvoir_data.converted_flux.values[max_uvoir_idx]
        f2_unc = uvoir_data.converted_flux_err.values[max_uvoir_idx]
        uvoir_sigma_sigma = (f2 - f1) / np.sqrt(f1_unc**2 + f2_unc**2)
        uvoir_flux_diffs.append(
            uvoir_sigma_sigma
        )

    max_uvoir_date.append(max_uvoir_dt)
    max_xray_date.append(max_xray_dt)

    diff.append(max_xray_dt-max_uvoir_dt)
    left_censored.append(NA_Real if xray_is_uplim or uvoir_is_lolim else loval)
    right_censored.append(NA_Real if xray_is_lolim or uvoir_is_uplim else upval)

    labels.append(name)
    colors.append(color)
    markers_used.append(mark)

    ax.errorbar(
        [max_xray_dt], [max_uvoir_dt],
        marker=mark,
        color=color,
        xerr=(
            [0] if xray_is_uplim else [max_xray_dt-xray_min],
            [0] if xray_is_lolim else [xray_max-max_xray_dt]
        ),
        yerr=(
            [0] if uvoir_is_uplim else [max_uvoir_dt-uvoir_min],
            [0] if uvoir_is_lolim else [uvoir_max-max_uvoir_dt]
        ),
        mec="k",
        linestyle="none",
        capsize=3
    )

diff = np.array(diff)
left_censored = np.array(left_censored)
right_censored = np.array(right_censored)

ax.legend(
    handles = [Line2D([0], [0], marker=m, color=c, label=name,
        markersize=6, linestyle="none", markeredgecolor="k") for c,name,m in zip(colors, labels, markers_used)] + [Line2D([0],[0], marker="none", color="k", label="1:1", linestyle="--", alpha=0.8)],
    loc = "lower left",
    bbox_to_anchor = (-0.03, 1.01),
    fontsize=10,
    ncols=4,
    fancybox=False,
    frameon=False,
    facecolor="w",
    framealpha=0.8
)

xy = np.linspace(0,2000)
ax.plot(xy,xy, linestyle="--", color="k", zorder=0, alpha=0.8)

ax.set_ylim(6e0, 8e2)

ax.set_yscale("log")
ax.set_xscale("log")

ax.set_ylabel(r"Time of Max. UV/Opt. $\nu L_\nu$ [days]", fontsize=fs)
ax.set_xlabel(r"Time of Max. X-ray Luminosity [days]", fontsize=fs)

savefig(fig, "max-uvoir-vs-max-xray.png")

resdf, quan = surv_analysis(list(left_censored), list(right_censored))
print()
print("###############################################################")
print("Median w/ Greenwood Confidence Levels:\n", resdf)
lo, lo25, med, up75, up = quan.T[0].values
print()
print("Quantiles of the Kaplan-Meier CDF:\n", quan)
print("###############################################################")

max_diff_df = pd.DataFrame({
    "name": labels,
    "diff": diff,
    "max_uvoir_dates": max_uvoir_date,
    "max_xray_dates":max_xray_date
}).sort_values(by="diff")

49
Insufficient data for PS1-11af, skipping...
Missing discovery date for AT2022mim!
Missing discovery date for WTP16aatsnw!
Missing discovery date for WTP15acbuuv!
Missing discovery date for WTP14adbwvs!
Insufficient data for D1-9, skipping...
Missing discovery date for WTP16aaqrcr!
Insufficient data for D23H-1, skipping...
Missing discovery date for WTP17aamoxe!
Insufficient data for ASASSN-14ae, skipping...
Insufficient data for PTF09ge, skipping...
Missing discovery date for WTP14acnjbu!
Insufficient data for SDSSJ1342, skipping...
Missing discovery date for WTP15abymdq!
Missing discovery date for WTP15acbgpn!
Missing discovery date for WTP17aalzpx!
Missing discovery date for WTP18aajkmk!
Insufficient data for 2016fnl, skipping...
Insufficient data for PTF09djl, skipping...
Missing discovery date for WTP14adeqka!
Missing discovery date for WTP14adbjsh!
Missing discovery date for WTP17aaldjb!
Missing discovery date for WTP17aamzew!
Missing discovery date for WTP17aanbso!
Insufficient data for TDE2, skipping...

R callback write-console: In addition:
R callback write-console: Warning message:

R callback write-console: In (function (package, help, pos = 2, lib.loc = NULL, character.only = FALSE,  :
R callback write-console:

R callback write-console:  libraries ‘/usr/local/lib/R/site-library’, ‘/usr/lib/R/site-library’ contain no packages

(nan, -0.0036702939978567883, -11.994122355303261, nan, 132.00724400000036, 9.25480888189486, 19.367340796299686, nan, 145.71119999999792, 194.91548891320417, 2.637582697898324, nan, 14.278353847199469, 1698.0039039999974, 391.1165777720016, 277.4337409630025, 223.7857064560012, nan, 55.89299720599956, 199.75, 217.2471669548977) (421.39382399999886, 12.185895000002347, 7.038658547498926, 157.399936439484, 294.30390000000625, 74.06622221529688, 24.635232328699203, 1564.5708060000034, 154.05289999999513, 196.54873378130287, 37.944422834443685, 3.877359361096751, 28.257683756906772, nan, nan, 287.6586619873051, 231.4583406515958, 328.3842430000004, 65.65740801688662, nan, 223.16599999999744)
Call: survfit(formula = r_surv_obj ~ 1, conf.int = 0.95, conf.type = "plain")

   time n.risk  n.event survival std.err lower 95% CI upper 95% CI
   3.26  21.00 4.66e+00    0.778  0.1427       0.4188        1.000
  10.72  16.34 3.73e-05    0.778  0.1427       0.4188        1.000
  22.00  16.34 4.21e+00    0.578  0.1107       0.2025        0.953
  60.78  12.13 1.70e+00    0.497  0.0885       0.1476        0.846
 149.88  10.43 1.58e+00    0.422  0.0691       0.1006        0.743
 195.73   8.86 1.40e+00    0.355  0.0532       0.0616        0.649
 220.21   6.46 1.49e+00    0.274  0.0364       0.0126        0.534
 227.62   4.97 1.49e+00    0.192  0.0213       0.0000        0.409
 282.55   3.49 1.49e+00    0.110  0.0087       0.0000        0.265
 406.26   1.00 6.24e-17    0.110  0.0087       0.0000        0.265

Call: survfit(formula = r_surv_obj ~ 1, conf.int = 0.95, conf.type = "plain")

     records  n events median 0.95LCL 0.95UCL
[1,]      21 21     18   60.8    3.26     228


###############################################################
Median w/ Greenwood Confidence Levels:
       records   n  events  median  0.95LCL  0.95UCL
[1,]       21  21      18    60.8     3.26      228

Quantiles of the Kaplan-Meier CDF:
          16         25         50          75          84
0  3.257471  22.001287  60.775203  227.622024  282.546201
###############################################################

We now need to find the distribution of the first obesrvations

names = []
colors = []
first_uvoir_obs = []
first_xray_obs = []

for name, color, mark in zip(list(set(xrays.name.unique()) & set(uvoir.name.unique())), colors_init, markers):

    t = db.get_meta(names=name)[0]
    try:
        disc_date = t.get_discovery_date().mjd
    except:
        print(f"Missing discovery date for {name}!")
        continue

    uvoir_data = uvoir[(uvoir.name == name)* (uvoir.converted_date > disc_date)].sort_values(by="converted_date")
    xray_data = xrays[(xrays.name == name)* (xrays.converted_date > disc_date)].sort_values(by="converted_date")

    if len(uvoir_data) == 0 or len(xray_data) == 0:
        print(f"Insufficient data for {name}, skipping...")
        continue

    first_uvoir_obs.append(uvoir_data.iloc[0].converted_date - disc_date)
    first_xray_obs.append(xray_data.iloc[0].converted_date - disc_date)

    names.append(name)
    colors.append(color)

first_obs_df = pd.DataFrame({
    "name" : names,
    "first_uvoir_obs": first_uvoir_obs,
    "first_xray_obs": first_xray_obs
})

Insufficient data for PS1-11af, skipping...
Missing discovery date for AT2022mim!
Missing discovery date for WTP16aatsnw!
Missing discovery date for WTP15acbuuv!
Missing discovery date for WTP14adbwvs!
Missing discovery date for WTP16aaqrcr!
Missing discovery date for WTP17aamoxe!
Missing discovery date for WTP14acnjbu!
Missing discovery date for WTP15abymdq!

We can now merge these dataframes for creating the figure comparing the two distributions

alltimes = pd.merge(max_diff_df, first_obs_df, how="outer", on="name")

alltimes.sort_values("diff")

	name	diff	max_uvoir_dates	max_xray_dates	first_uvoir_obs	first_xray_obs
10	2020ksf	-0.001030	231.315771	231.314741	1.816906e+01	16.575000
5	2019dsg	0.001964	38.207431	38.209395	NaN	NaN
6	2019ehz	7.716357	18.531036	26.247392	1.018517e-02	18.531959
9	2020ddv	21.018945	60.875991	81.894936	NaN	NaN
17	ASASSN-14li	21.639733	8.459027	30.098760	8.454234e+00	8.481709
2	2018hyz	24.134167	27.238365	51.372532	4.804100e-01	29.876202
11	2020ocn	58.783199	71.684473	130.467672	NaN	NaN
7	2019teq	66.868941	62.367184	129.236125	1.131411e-08	45.412059
8	2019vcb	81.224087	25.999456	107.223543	1.152964e-05	107.223543
13	2021yzv	145.379454	66.119546	211.499000	NaN	NaN
23	OGLE16aaa	145.600500	41.999500	187.600000	3.346320e+01	63.300000
15	2023lli	149.075000	46.517000	195.592000	6.467000e+00	7.380700
1	2018fyk	195.876899	14.727311	210.604210	1.472379e+01	14.727585
14	2022upj	204.150000	77.372000	281.522000	NaN	NaN
18	ASASSN-15oi	222.665000	11.335000	234.000000	NaN	NaN
4	2019azh	226.669831	20.110000	246.779831	NaN	NaN
12	2021ehb	282.139892	31.885818	314.025709	NaN	NaN
24	PS1-10jh	386.830064	38.569936	425.400000	4.058880e-01	372.000000
22	D3-13	420.870806	116.429194	537.300000	6.400000e-01	537.300000
3	2018zr	628.164726	21.524000	649.688726	NaN	NaN
25	PTF09axc	2062.500138	33.299862	2095.800000	NaN	NaN
0	2018dyk	NaN	NaN	NaN	2.911163e+01	60.631462
16	ASASSN-14ae	NaN	NaN	NaN	2.904328e+00	7.900000
19	CSS100217	NaN	NaN	NaN	3.800000e-01	1035.100000
20	D1-9	NaN	NaN	NaN	5.465000e+01	873.200000
21	D23H-1	NaN	NaN	NaN	6.010500e-02	53.000000
26	PTF09ge	NaN	NaN	NaN	1.804800e-01	1767.100000
27	SDSSJ1342	NaN	NaN	NaN	2.427000e+02	0.700000
28	Sw J1644+57	NaN	NaN	NaN	1.066600e-01	1.060000

fig, ax = plt.subplots(figsize=(7,4))
xrange = (-300, 3000)

# Add minor ticks to the main axis
ax.xaxis.set_minor_locator(AutoMinorLocator(4))  # 2 minor ticks between each major


counts, bins, _ = ax.hist(diff, edgecolor="k", facecolor=(0,0,0,0), bins=12, label=r"$\Delta t_{\rm del}$", zorder=100, histtype="step", lw=3, range=xrange)
ax.set_xlabel("Days Between Maximum UV/Optical and Maximum X-ray", fontsize=fs)

resdf, quan = surv_analysis(list(left_censored), list(right_censored))
print()
print("###############################################################")
print("Median w/ Greenwood Confidence Levels:\n", resdf)
lo, lo25, med, up75, up = quan.T[0].values
print()
print("Quantiles of the Kaplan-Meier CDF:\n", quan)
print("###############################################################")
#ax.axvline(med, color="r", linestyle=":")
#ax.axvspan(lo, up, color="r", alpha=0.2)
ax.text(1400, 6, fr"Med. $\Delta t_{{\rm del}} \approx {med:.0f}^{{+{up-med:.0f}}}_{{-{med-lo:.0f}}}$ days", rotation=0, color="k", verticalalignment="bottom", ha="left", fontsize=fs)
ax.set_ylabel("Number of TDEs", fontsize=fs)
ax.set_xlim(*xrange)

# add the Kaplan-Meier Estimator fit to the distribution
surv_prob, time, upper, lower = ro.globalenv["fit"].rx2("surv"), ro.globalenv["fit"].rx2("time"), ro.globalenv["fit"].rx2("upper"), ro.globalenv["fit"].rx2("lower")
#ax.plot(time, surv_prob*max(counts), color="cornflowerblue", linestyle="-")
ax.fill_between(time, lower*max(counts), upper*max(counts), alpha=0.2, color="cornflowerblue", label="Kaplan-Meier\nEstimator")

twinax = ax.twiny()
twinax.hist(
    (alltimes["first_xray_obs"] - alltimes["first_uvoir_obs"]).dropna(),
    bins=25,
    edgecolor="red",
    color = "w",
    alpha=0.5,
    fc=(0, 0, 0, 0),
    label = r"$\Delta t_{\rm obs}$",
    zorder = 0,
    histtype="step",
    linestyle=":",
    lw = 3,
    range=xrange
)

lo, med, up = np.quantile((alltimes["first_xray_obs"] - alltimes["first_uvoir_obs"]).dropna(), [0.16, 0.5, 0.84])
ax.text(1400, 4, fr"Med. $\Delta t_{{\rm obs}} \approx {med:.0f}^{{+{up-med:.0f}}}_{{-{med-lo:.0f}}}$ days", rotation=0, color="red", verticalalignment="bottom", ha="left", fontsize=fs)

# twinax.set_xlim(ax.get_xlim())
# twinax.set_xticks(ax.get_xticks())
twinax.set_xlim(*xrange)
twinax.set_xlabel("Days Between First UV/Optical Obs. and First X-ray Obs.", fontsize=fs)
twinax.xaxis.set_minor_locator(AutoMinorLocator(4))  # 2 minor ticks between each major

fig.legend(loc="center", bbox_to_anchor=(0.75, 0.65), frameon=False, fontsize=14)

savefig(fig, "max-xray-vs-max-uvoir-delay-hist.png")

R callback write-console: In addition:
R callback write-console: Warning message:

R callback write-console: In (function (package, help, pos = 2, lib.loc = NULL, character.only = FALSE,  :
R callback write-console:

R callback write-console:  libraries ‘/usr/local/lib/R/site-library’, ‘/usr/lib/R/site-library’ contain no packages

(nan, -0.0036702939978567883, -11.994122355303261, nan, 132.00724400000036, 9.25480888189486, 19.367340796299686, nan, 145.71119999999792, 194.91548891320417, 2.637582697898324, nan, 14.278353847199469, 1698.0039039999974, 391.1165777720016, 277.4337409630025, 223.7857064560012, nan, 55.89299720599956, 199.75, 217.2471669548977) (421.39382399999886, 12.185895000002347, 7.038658547498926, 157.399936439484, 294.30390000000625, 74.06622221529688, 24.635232328699203, 1564.5708060000034, 154.05289999999513, 196.54873378130287, 37.944422834443685, 3.877359361096751, 28.257683756906772, nan, nan, 287.6586619873051, 231.4583406515958, 328.3842430000004, 65.65740801688662, nan, 223.16599999999744)
Call: survfit(formula = r_surv_obj ~ 1, conf.int = 0.95, conf.type = "plain")

   time n.risk  n.event survival std.err lower 95% CI upper 95% CI
   3.26  21.00 4.66e+00    0.778  0.1427       0.4188        1.000
  10.72  16.34 3.73e-05    0.778  0.1427       0.4188        1.000
  22.00  16.34 4.21e+00    0.578  0.1107       0.2025        0.953
  60.78  12.13 1.70e+00    0.497  0.0885       0.1476        0.846
 149.88  10.43 1.58e+00    0.422  0.0691       0.1006        0.743
 195.73   8.86 1.40e+00    0.355  0.0532       0.0616        0.649
 220.21   6.46 1.49e+00    0.274  0.0364       0.0126        0.534
 227.62   4.97 1.49e+00    0.192  0.0213       0.0000        0.409
 282.55   3.49 1.49e+00    0.110  0.0087       0.0000        0.265
 406.26   1.00 6.24e-17    0.110  0.0087       0.0000        0.265

Call: survfit(formula = r_surv_obj ~ 1, conf.int = 0.95, conf.type = "plain")

     records  n events median 0.95LCL 0.95UCL
[1,]      21 21     18   60.8    3.26     228


###############################################################
Median w/ Greenwood Confidence Levels:
       records   n  events  median  0.95LCL  0.95UCL
[1,]       21  21      18    60.8     3.26      228

Quantiles of the Kaplan-Meier CDF:
          16         25         50          75          84
0  3.257471  22.001287  60.775203  227.622024  282.546201
###############################################################

Example 2: ECLE Analysis

We’ve made a directory called ecle-data that has CSVs in the OTTER format (see the interfacing with private data tutorial). This dataset has the radio data in it.

The first thing we need to do is read that data into the Otter object using the Otter.from_csvs method.

db = otter.Otter.from_csvs(
    metafile="ecle-data/ecle-metadata.csv",
    photfile="ecle-data/all-photometry.csv",
    local_outpath="ecle-data/private-data"
)

/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:926: DtypeWarning: Columns (5,13,14,15,16,17) have mixed types. Specify dtype option on import or set low_memory=False.
  phot_unclean = pd.read_csv(photfile)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)
/home/nfranz/research/astro-otter/otter/src/otter/io/otter.py:1268: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.
The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.

For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.


  p[k].fillna("null", inplace=True)

Attempting to login to https://otter.idies.jhu.edu/api with the following credentials:
username: user-guest
password: test
2019qiz
Found this object in the database already, merging the data...
AT2017gge
Found this object in the database already, merging the data...
AT2018bcb
Found this object in the database already, merging the data...
AT2018dyk
Found this object in the database already, merging the data...
AT2020vdq
Found this object in the database already, merging the data...
AT2021acak
Found this object in the database already, merging the data...
AT2021dms
Found this object in the database already, merging the data...
AT2021qth
Found this object in the database already, merging the data...
AT2022fpx
Found this object in the database already, merging the data...
AT2022upj
Found this object in the database already, merging the data...
SDSS_J0748
Found this object in the database already, merging the data...
SDSS_J0807
Found this object in the database already, merging the data...
SDSS_J0938
Found this object in the database already, merging the data...
SDSS_J0952
Found this object in the database already, merging the data...
SDSS_J1055
Found this object in the database already, merging the data...
SDSS_J1207
Found this object in the database already, merging the data...
SDSS_J1241
Found this object in the database already, merging the data...
SDSS_J1247
Found this object in the database already, merging the data...
SDSS_J1342
Found this object in the database already, merging the data...
SDSS_J1350
Found this object in the database already, merging the data...
SDSS_J1402
Found this object in the database already, merging the data...
SDSS_J1459
Found this object in the database already, merging the data...
SDSS_J1715
Found this object in the database already, merging the data...
SDSS_J2220
Found this object in the database already, merging the data...

Now that we have the radio data we can query for all of the transients in OTTER (including the private ones). We also want to read in the metadata file so we know which events are ECLEs.

all_transients = db.query(query_private=True)
meta = pd.read_csv("ecle-data/ecle-metadata.csv")

Names have the same score! Just using the existing default_name

Finally, we can iterate through these transients, query WISE, and find both the maximum IR color and radio luminosity.

fig = plt.figure(figsize=(6,6))
gs = fig.add_gridspec(2, 2,  width_ratios=(4, 1), height_ratios=(1, 4),
                      left=0.1, right=0.9, bottom=0.1, top=0.9,
                      wspace=0.05, hspace=0.05)

ax = fig.add_subplot(gs[1, 0])
ax_histx = fig.add_subplot(gs[0, 0], sharex=ax)
ax_histy = fig.add_subplot(gs[1, 1], sharey=ax)

cmap = mpl.colormaps['plasma']

ecle_names = set(meta.name.unique())
n_ecle = len(meta)
colors = cmap(np.linspace(0, 1, n_ecle))
i = 0

radio_filts = ("L", "S", "C")
tdes_to_label = {"AT2019dsg", "AT2016ezh"}

radio_data, wise_data, class_ = [], [], []
cbar_labels = []

uplim_filter = []

for t in all_transients:
    try:
        phot = t.clean_photometry(flux_unit="mJy", obs_type="radio")
    except otter.exceptions.FailedQueryError:
        continue # this just means no radio photometry

    # query wise
    coord = t.get_skycoord()
    data_finder = otter.DataFinder(
        coord.ra.value,
        coord.dec.value,
        coord.ra.unit,
        coord.dec.unit,
        name = t.default_name
    )
    wise_phot = data_finder.query_wise(overwrite=False)

    if len(wise_phot) == 0:
        print(t.default_name, "has radio photometry but no good wise photometry!")
        continue

    keep_keys = ["filter", "flux", "flux_err", "date_mjd", "upperlimit"]
    w1 = wise_phot[wise_phot["filter"] == "w1"][keep_keys]
    w2 = wise_phot[wise_phot["filter"] == "w2"][keep_keys]

    w1_w2 = w1.merge(w2, on="date_mjd", suffixes=("_w1", "_w2")).dropna()

    wise_max = np.argmin(w1_w2.flux_w1) # choose peak W1
    wise_color = w1_w2.flux_w1.tolist()[wise_max] - w1_w2.flux_w2.tolist()[wise_max]
    wise_uplim = w1_w2.upperlimit_w1.values[wise_max] or w1_w2.upperlimit_w2.values[wise_max]

    # get the luminosity
    try:
        z = t.get_redshift() * cu.redshift
    except:
        print(f"Skipping {t.default_name} because no redshift!")
    lum_dist = z.to(u.Mpc, equivalencies=cu.redshift_distance(cosmo, kind="luminosity"))
    phot["lum_nu"] = [4*np.pi*lum_dist**2 * (val * u.mJy) for val in phot.converted_flux]
    phot["lum"] = [(val*eff*u.GHz).to(u.erg/u.s).value for val, eff in zip(phot.lum_nu, phot.converted_freq)]

    # get the discovery date
    try:
        disc_date = t.get_discovery_date().mjd
    except:
        continue

    aliases = [n["value"] for n in t["name"]["alias"]]
    isECLE = any(a in ecle_names for a in aliases)

    if isECLE:
        for a in aliases:
            if a in ecle_names:
                metadata = meta[a == meta.name]
                break
        classification = metadata.classification.values[0]

        color = colors[i]
        i += 1

        # All of the ECLEs have S-band data
        s = phot[phot.filter_name.isin(radio_filts)]
        cbar_labels.append(metadata.name.values[0].replace("_", ""))

        alpha = 1

        color = "cornflowerblue"

    else:
        s = phot[phot.filter_name.isin(radio_filts)]
        if len(s) == 0: continue
        classification = t.get_classification()[0]
        color = 'firebrick'
        alpha = 0.2

    if classification == "TDE":
        symb = "o"
    elif classification == "AGN":
        symb = "*"
    else:
        symb = "s"

    if np.all(s.upperlimit):
        max_idx = np.argmin(s.lum.values) # we want the MOST CONSTRAINING upperlimit
        toplot = s
        uplim_filter.append(True)
    else:
        toplot = s[~s.upperlimit]
        max_idx = np.argmax(toplot.lum.values)
        uplim_filter.append(False)

    y = toplot.lum.values[max_idx]
    x = wise_color

    radio_data.append(y)
    wise_data.append(x)
    class_.append(isECLE)

    ax.plot(x, y, color=color, marker=symb, alpha=alpha, markersize=8)

    if toplot.upperlimit.values[max_idx]:
        ax.annotate("", xy=(x, y/3), xytext=(x, y), arrowprops=dict(arrowstyle='->',color=color,alpha=alpha))

    if wise_uplim:
        ax.annotate("", xy=(y, x/3), xytext=(y, x), arrowprops=dict(arrowstyle='->',color=color,alpha=alpha))

radio_data, wise_data, ecle_filt, uplim_filt = np.array(radio_data), np.array(wise_data), np.array(class_), np.array(uplim_filter)
print(ecle_filt)

custom_legend_params = dict(
    lw = 4,
    markersize = 8,
    linestyle = "none"
)

custom_lines = [
    Line2D([0], [0], marker="*", color="k", **custom_legend_params),
    Line2D([0], [0], marker="o", color="k", **custom_legend_params),
    Line2D([0], [0], marker="s", color="k", **custom_legend_params),
    Line2D([0], [0], marker="o", alpha=0.2, **custom_legend_params, color="firebrick"),
    Line2D([0], [0], marker="o", alpha=1, **custom_legend_params, color="cornflowerblue")
]

custom_labels = ["Persistent ECLs", "Transient ECLs", "Ambiguous ECLs", "non-ECLE TDEs", "ECLE Sample"]

ax.set_yscale("log")

ax.legend(custom_lines, custom_labels, loc="upper left", ncols=1, fontsize=10, frameon=True, fancybox=False)

ax.set_ylabel(r"Peak Radio $\nu L_\nu$ [erg/s]", fontsize=18)
ax.set_xlabel("(W1 - W2) Color at W1 Peak", fontsize=18)

# plot the side histograms
nbins=15
wise_ecle_bins, wise_ecle_edges = np.histogram(wise_data[ecle_filt],bins=nbins)
wise_data_bins, wise_data_edges = np.histogram(wise_data[~ecle_filt],bins=nbins)
ax_histx.stairs(wise_data_bins, wise_data_edges, color='firebrick', linestyle='--', alpha=0.6, lw=3)
ax_histx.stairs(wise_ecle_bins, wise_ecle_edges, color='cornflowerblue', linestyle='-', alpha=1, lw=3)

nbins = 10
hist, bins = np.histogram(radio_data[~ecle_filt * ~uplim_filt],bins=nbins)
logbins = np.logspace(np.log10(bins[0]),np.log10(bins[-1]),len(bins))
radio_data_bins, radio_data_edges = np.histogram(radio_data[~ecle_filt * ~uplim_filt],bins=logbins)
ax_histy.stairs(radio_data_bins, radio_data_edges, orientation="horizontal", color='firebrick', linestyle='--', alpha=0.6, lw=3)

hist, bins = np.histogram(radio_data[ecle_filt * ~uplim_filt],bins=nbins)
logbins = np.logspace(np.log10(bins[0]),np.log10(bins[-1]),len(bins))
radio_ecle_bins, radio_ecle_edges = np.histogram(radio_data[ecle_filt * ~uplim_filt],bins=logbins)
ax_histy.stairs(radio_ecle_bins, radio_ecle_edges, orientation="horizontal", color='cornflowerblue', linestyle='-', alpha=1, lw=3)

ax_histx.tick_params(axis="x", labelbottom=False)
ax_histy.tick_params(axis="y", labelleft=False)

savefig(fig, "ecle-radio-vs-wise.png")

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0206' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0262' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.133' to a unit explicitly. [warnings]
CNSS J0019+00 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.018' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.108' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2013ApJ...763...84B', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.08754' to a unit explicitly. [warnings]
VAST J215418.2+002442 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.152' to a unit explicitly. [warnings]

Skipping VAST J215418.2+002442 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0874' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0636' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.068' to a unit explicitly. [warnings]
VAST J093634.7-054755 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.183' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.153' to a unit explicitly. [warnings]

Skipping VAST J093634.7-054755 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0484' to a unit explicitly. [warnings]
2022czy has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.338' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.053' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0565' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.074' to a unit explicitly. [warnings]
Unable to apply the source mapping because 'private'
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0365' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.088' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0777' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '1.1853' to a unit explicitly. [warnings]
2018cqh has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.017' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.19' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2019MNRAS.488.4816W', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.059' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2002RvMA...15...27K', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.01124' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '1.19325' to a unit explicitly. [warnings]
eRASSt J234403-352640 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
VAST J104315.9+005059 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.162' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.05' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.358' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2013A&A...552A...5V', '2020SSRv..216...81A']"

Skipping VAST J104315.9+005059 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.326' to a unit explicitly. [warnings]
VAST J144848.2+030235 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.286' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.091' to a unit explicitly. [warnings]

Skipping VAST J144848.2+030235 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.89' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.22405' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0151' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0955' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2020ApJ...898..161H', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.018' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.072' to a unit explicitly. [warnings]
VAST J213437.8-620433 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.043671' to a unit explicitly. [warnings]

Skipping VAST J213437.8-620433 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.354' to a unit explicitly. [warnings]
2019gte has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1696' to a unit explicitly. [warnings]
VAST J230053.0-020732 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.133' to a unit explicitly. [warnings]
2022arb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.

multiple cntr:
[1966001601351030620, 1966001601351030621]
Skipping VAST J230053.0-020732 because no redshift!

2021blz has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0163' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0789' to a unit explicitly. [warnings]
VAST J221936.0+004724 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...780...44C', '2020SSRv..216...81A']"

multiple cntr:
[71133301351020297, 71133301351020298]
Skipping VAST J221936.0+004724 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.4046' to a unit explicitly. [warnings]
ARP 299-B AT1 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.010411' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2011ApJ...732L..12B', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.3698' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1206' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0457266' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.117' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.159' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0173' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.18' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.03672' to a unit explicitly. [warnings]
2022adm has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.136' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2019A&A...630A..98S', '2020SSRv..216...81A']"
XMMSL2 J144605.0+685735 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.029' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2011MNRAS.417L..51V', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.2515' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1855' to a unit explicitly. [warnings]
FIRST J153350.8+272729 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0512' to a unit explicitly. [warnings]
IGR J12580+0134 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.00411' to a unit explicitly. [warnings]
VAST J234449.6+015434 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2019MNRAS.488.1878N', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1089' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2017ApJ...843..106B', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0804' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.176' to a unit explicitly. [warnings]

Skipping VAST J234449.6+015434 because no redshift!

VAST J210626.2-020055 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
Unable to apply the source mapping because "['2014ApJ...793...38A', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.1146' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.106' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.023' to a unit explicitly. [warnings]

Skipping VAST J210626.2-020055 because no redshift!

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.022' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.073' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.212' to a unit explicitly. [warnings]
VAST J011148.1-025539 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.088' to a unit explicitly. [warnings]

Skipping VAST J011148.1-025539 because no redshift!
multiple cntr:
[1268118101351034424, 1268118101351034425]

WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0378' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.126' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.062' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2018ASPC..517..737V', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.071' to a unit explicitly. [warnings]
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.0615' to a unit explicitly. [warnings]
Unable to apply the source mapping because "['2012A&A...541A.106S', '2020SSRv..216...81A']"
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.146' to a unit explicitly. [warnings]
AT2020vwl has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2021qth has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
2022fpx has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
WARNING: AstropyDeprecationWarning: products involving a unit and a 'str' instance are deprecated since v7.1. Convert '0.054' to a unit explicitly. [warnings]

2021qth has radio photometry but no good wise photometry!

SDSS_J0807 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2017gge has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1715 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1247 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J2220 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1402 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1241 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1207 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2021acak has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2021dms has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2018bcb has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
AT2020vdq has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1055 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J1459 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
SDSS_J0938 has at least one photometry point where it is unclear if a host subtraction was performed. This can be especially detrimental for UV data. Please consider filtering out UV/Optical/IR or radio rows where the corr_host column is null/None/NaN.
/tmp/ipykernel_489627/2232853147.py:14: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
  fig.savefig(

[False False False False False False False False False False False False
 False False  True  True False False False False False False False False
 False False False False  True False False False False False False False
 False  True False False False False False False False False  True False
 False False False False False False False False False False False False
 False False False  True False False  True False  True  True  True  True
  True  True  True  True  True  True  True  True  True  True  True  True]

/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/IPython/core/events.py:82: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
  func(*args, **kwargs)
/home/nfranz/research/astro-otter/paper/rpy2-env/lib/python3.12/site-packages/IPython/core/pylabtools.py:170: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
  fig.canvas.print_figure(bytes_io, **kw)

Example 3: MOSFiT Model

This notebook will show you how to generate the plots in the paper from the outputs of MOSFiT. We recommend returning to the modeling notebook to see how to convert the dataset into the MOSFiT input format. This will assume that the MOSFiT inputs and outputs are stored in the mosfit directory.

For reference (and reproducability) the bash commands we used to run MOSFiT is

args=(
    -e $1 # input file directory
    -c # save the chains
    -o mosfit_output # the directory to save to
    -m tde # use the tde model
    --local-data-only # dont query OSC for more data
    -N 150 # use 150 walkers
    -i 20000 # run for 20,000 iterations
    -S 600 # use 600 synthetic photometry points between first and last observation
    -x radiusphot temperaturephot luminosities_out dense_times dense_luminosities dmdt times_out # extra outputs
    -E 200 1500
    -qs # quick saving
    -s $2 # the suffix for saving to prevent overwrite
)

mpirun -np 3 mosfit "${args[@]}"

First, we need to define a few variables (like the discovery dates).

# _t0 = discovery
# _p = peak date

zso_t0 = 59165.6500579
zso_p = 59184.2
sdu_t0 = 59400.9073264
sdu_p = 59419.36

Now we can plot AT2020zso.

lc = pd.read_csv('mosfit/AT2020zso.csv',sep='\t')
lc['m_ab'] = [-2.5*np.log10((f*1e-3)/3631) for f in lc.f_nu]
lc['m_ab_error'] = [2.5*(df*1e-3)/(f*1e-3*np.log(10)) for f,df in zip(lc.f_nu,lc.e_flux_density)]

df_walkers = pd.read_json('mosfit/AT2020zso_walkers_zso.json')
model = df_walkers.loc['models'][0][0]
photo = df_walkers.loc['photometry'][0]

p = pd.DataFrame(photo)
cols = ['time', 'e_magnitude', 'magnitude', 'band', 'realization']
ncols = ['time', 'e_magnitude', 'magnitude']
p = p[cols]
p[ncols] = p[ncols].apply(pd.to_numeric)
p = p.dropna(subset=['realization'])

/tmp/ipykernel_489627/2010292069.py:6: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
  model = df_walkers.loc['models'][0][0]
/tmp/ipykernel_489627/2010292069.py:7: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
  photo = df_walkers.loc['photometry'][0]

fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(10, 8),dpi=400)
rs = p['realization'].unique()
bs_all = ['r', 'g', 'B', 'U', 'UVW2', 'UVM2', 'UVW1']
c_lst_all = cmr.take_cmap_colors('nipy_spectral_r', 6, cmap_range=(0.03, 0.9), return_fmt='hex')+['hotpink','magenta']
o_lst = [-3, -2, -1, 0,1,2,3,4,5,6]
ol_lst = ['- 3', '-2', '- 1', '','+ 1','+ 2','+ 3','+ 4','+ 5', '+ 6']

bs = [b for b in bs_all if b in p['band'].unique()]
c_lst = [c for c,b in zip(c_lst_all,bs_all) if b in p['band'].unique()]

for i,(b,c,o,ol) in enumerate(zip(bs,c_lst,o_lst,ol_lst)):
    for r in rs[:50]:
        mjd = p[(p['realization']==r) & (p['band']==b)].time-zso_t0
        mag = p[(p['realization']==r) & (p['band']==b)].magnitude
        axes.plot(mjd,o+mag,'-',lw=1,alpha=0.5,color=c)
    axes.errorbar(lc[(lc['band']==b) & (lc['upperlimit']==False)].time-zso_t0,
                 o+lc[(lc['band']==b) & (lc['upperlimit']==False)].m_ab,
                  yerr = lc[(lc['band']==b) & (lc['upperlimit']==False)].m_ab_error,
              fmt='o',color=c,ms=12,label=f'{b} {ol}',mec='k',capsize=4)

axes.legend(loc=1,ncol = 2,fontsize = 15,markerscale=1)
axes.set_xlim(-3,100)
axes.set_ylim(24,14)
axes.tick_params(axis='both', labelsize=16)
axes.set_ylabel('Apparent Magnitude + Offset',fontsize=25)
axes.set_xlabel('Days Since Discovery',fontsize=25)
savefig(fig, "AT2020zso-mosfit-bestfit.png")

And now we can do the same with AT2021sdu.

lc = pd.read_csv('mosfit/AT2021sdu.csv',sep='\t')
lc['m_ab'] = [-2.5*np.log10((f*1e-3)/3631) for f in lc.f_nu]
lc['m_ab_error'] = [2.5*(df*1e-3)/(f*1e-3*np.log(10)) for f,df in zip(lc.f_nu,lc.e_flux_density)]

df_walkers = pd.read_json('mosfit/AT2021sdu_walkers_sdu.json')
model = df_walkers.loc['models'][0][0]
photo = df_walkers.loc['photometry'][0]

p = pd.DataFrame(photo)
cols = ['time', 'e_magnitude', 'magnitude', 'band', 'realization']
ncols = ['time', 'e_magnitude', 'magnitude']
p = p[cols]
p[ncols] = p[ncols].apply(pd.to_numeric)
p = p.dropna(subset=['realization'])

/tmp/ipykernel_489627/3281557049.py:6: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
  model = df_walkers.loc['models'][0][0]
/tmp/ipykernel_489627/3281557049.py:7: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`
  photo = df_walkers.loc['photometry'][0]

fig, axes = plt.subplots(nrows=1, ncols=1, figsize=(10, 8),dpi=400)
rs = p['realization'].unique()
bs_all = ['i', 'r', 'g', 'U', 'UVM2', 'UVW1', 'UVW2']
c_lst_all = cmr.take_cmap_colors('nipy_spectral_r', 6, cmap_range=(0.03, 0.9), return_fmt='hex')+['hotpink','magenta']
o_lst = [-3, -2, -1, 0,1,2,3,4,5]
ol_lst = ['- 3', '- 2', '- 1', '','+ 1','+ 2','+ 3','+ 4','+ 5', '+ 6']

bs = [b for b in bs_all if b in p['band'].unique()]
c_lst = [c for c,b in zip(c_lst_all,bs_all) if b in p['band'].unique()]


for i,(b,c,o,ol) in enumerate(zip(bs,c_lst,o_lst,ol_lst)):
    for r in rs[:50]:
        mjd = p[(p['realization']==r) & (p['band']==b)].time - sdu_t0
        mag = p[(p['realization']==r) & (p['band']==b)].magnitude
        axes.plot(mjd,o+mag,'-',lw=0.5,alpha=0.5,color=c)
    axes.errorbar(lc[(lc['band']==b) & (lc['upperlimit']==False)].time - sdu_t0,
                 o+lc[(lc['band']==b) & (lc['upperlimit']==False)].m_ab,
                  yerr = lc[(lc['band']==b) & (lc['upperlimit']==False)].m_ab_error,
              fmt='o',color=c,ms=12,label=f'{b} {ol}',mec='k',capsize=4)

axes.legend(loc=1,ncol = 2,fontsize = 15,markerscale=1)
axes.set_xlim(-3,100)
axes.set_ylim(25,15)
axes.tick_params(axis='both', labelsize=16)

axes.set_ylabel('Apparent Magnitude + Offset',fontsize=25)
axes.set_xlabel('Days Since Discovery',fontsize=25)

savefig(fig, "AT2021sdu-mosfit-bestfit.png")

Example 4: Testing a ML classifier

Similar to Example 3 above, running FLEET is complex and typically done outside a Jupyter notebook. See the FLEET code/documentation for running it yourself. Here, we show how we create the figure in section 5.4 from the FLEET output.

We assume you have run FLEET and saved the output to a file called OTTER_FLEET.txt

m0 = []
m1 = []
m2 = []

cols = [
    "AGN",
    "SLSNI",
    "SLSNII",
    "SNII",
    "SNIa",
    "SNIbc",
    "Star",
    "TDE"
]

df = pd.read_csv("OTTER_FLEET.txt", sep="\s+")

for _,row in df.iterrows():
    to_sort = row[["P_late_"+c for c in cols]]
    res = to_sort.sort_values(ascending=False)
    res_list = [v.split('_')[-1] for v in list(res.keys())]
    # print(res)

    m0.append(res_list[0])
    m1.append(res_list[1])
    m2.append(res_list[2])

fig,axs = plt.subplots(3,1,sharex=True, sharey=True, figsize=(10,6))

nbins = max(
    len(np.unique(m0)),
    len(np.unique(m1)),
    len(np.unique(m2)),

)
print(nbins)
for ax, m in zip(axs, [m0,m1,m2]):
    ax.hist(m, align="left", ec="k", range=(0,nbins), bins=nbins, fc="cornflowerblue")

    ax.tick_params(axis='both', labelsize=16)

fig.supylabel("Number of TDEs", fontsize=20, fontweight="semibold")
fig.supxlabel("Classification", fontsize=20, fontweight="semibold")

ax.tick_params(axis='both', labelsize=14)

fig.subplots_adjust(wspace=0, hspace=0)

savefig(fig, "fleet-classification-distributions.png")

<>:16: SyntaxWarning: invalid escape sequence '\s'
<>:16: SyntaxWarning: invalid escape sequence '\s'
/tmp/ipykernel_489627/2752914060.py:16: SyntaxWarning: invalid escape sequence '\s'
  df = pd.read_csv("OTTER_FLEET.txt", sep="\s+")

8