# -*- coding: UTF-8 -*-
"""``figures`` contains functions for plotting alert and history data.
See the tutorials for usage help.
"""
import gzip
import io
from typing import Optional
import aplpy
import matplotlib as mpl
import numpy as np
import pandas as pd
from astropy.io import fits
from astropy.time import Time
from matplotlib import pyplot as plt
from . import utils as pgbu
# --- Plot object history
[docs]def plot_lightcurve(
dflc: pd.DataFrame,
objectId: Optional[str] = None,
ax: Optional[mpl.axes.Axes] = None,
days_ago: bool = True,
):
"""Plot the lighcurve (per band) of a single ZTF object.
Adapted from:
https://github.com/ZwickyTransientFacility/ztf-avro-alert/blob/master/notebooks/Filtering_alerts.ipynb
Args:
dflc: Lightcurve history of a unique objectId. Must contain columns
['jd','fid','magpsf','sigmapsf','diffmaglim']
objectId: objectId identifying dflc. Used for plot title.
ax: matplotlib axes for the figure. If None, a new figure will be created
days_ago: If True, x-axis will be number of days in the past.
Else x-axis will be Julian date.
"""
filter_code = pgbu.ztf_fid_names() # dict
filter_color = {1: "green", 2: "red", 3: "pink"}
# set the x-axis (time) details
if days_ago:
now = Time.now().jd
t = dflc.jd - now
xlabel = "Days Ago"
else:
t = dflc.jd
xlabel = "Time (JD)"
if ax is None:
plt.figure()
# plot lightcurves by band
for fid, color in filter_color.items():
# plot detections in this filter:
w = (dflc.fid == fid) & ~dflc.magpsf.isnull()
if np.sum(w):
label = f"{fid}: {filter_code[fid]}"
kwargs = {"fmt": ".", "color": color, "label": label}
plt.errorbar(t[w], dflc.loc[w, "magpsf"], dflc.loc[w, "sigmapsf"], **kwargs)
# plot nondetections in this filter
wnodet = (dflc.fid == fid) & dflc.magpsf.isnull()
if np.sum(wnodet):
plt.scatter(
t[wnodet],
dflc.loc[wnodet, "diffmaglim"],
marker="v",
color=color,
alpha=0.25,
)
plt.gca().invert_yaxis()
plt.xlabel(xlabel)
plt.ylabel("Magnitude")
plt.legend()
plt.title(f"objectId: {objectId}")
# --- Plot cutouts
[docs]def plot_stamp(stamp, fig=None, subplot=None, **kwargs):
"""Adapted from:
https://github.com/ZwickyTransientFacility/ztf-avro-alert/blob/master/notebooks/Filtering_alerts.ipynb
"""
with gzip.open(io.BytesIO(stamp), "rb") as f:
with fits.open(io.BytesIO(f.read())) as hdul:
if fig is None:
fig = plt.figure(figsize=(4, 4))
if subplot is None:
subplot = (1, 1, 1)
ffig = aplpy.FITSFigure(hdul[0], figure=fig, subplot=subplot, **kwargs)
# the following has been throwing: `ValueError: a must be > 0 and <= 1`
# this is fixed by requiring astropy==3.2.1
# Note: I see this related thing: https://github.com/aplpy/aplpy/issues/420
# but I am using the latest APLpy version (2.0.3).
# update (2023-06-26): this seems to be working now with astropy==5.2.2
ffig.show_grayscale(stretch="arcsinh")
return ffig
[docs]def plot_cutouts(alert_dict):
"""Adapted from:
https://github.com/ZwickyTransientFacility/ztf-avro-alert/blob/master/notebooks/Filtering_alerts.ipynb
"""
# fig, axes = plt.subplots(1,3, figsize=(12,4))
fig = plt.figure(figsize=(12, 4))
for i, cutout in enumerate(["Science", "Template", "Difference"]):
stamp = alert_dict["cutout{}".format(cutout)]["stampData"]
ffig = plot_stamp(stamp, fig=fig, subplot=(1, 3, i + 1))
ffig.set_title(cutout)
# --- Plot all
[docs]def plot_lightcurve_cutouts(alert_dict):
"""Adapted from:
https://github.com/ZwickyTransientFacility/ztf-avro-alert/blob/master/notebooks/Filtering_alerts.ipynb
"""
fig = plt.figure(figsize=(16, 4))
dflc = pgbu.Cast.alert_dict_to_dataframe(alert_dict)
plot_lightcurve(dflc, ax=plt.subplot(1, 4, 1))
for i, cutout in enumerate(["Science", "Template", "Difference"]):
stamp = alert_dict["cutout{}".format(cutout)]["stampData"]
ffig = plot_stamp(stamp, fig=fig, subplot=(1, 4, i + 2))
ffig.set_title(cutout)