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drop aplpy, matplotlib, numpy dependencies. add tutorial ztf-figures. update changelog.
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| Original file line number | Diff line number | Diff line change |
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| .. _ztf figures: | ||
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| ZTF Figures Tutorial | ||
| ============================== | ||
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| .. contents:: Table of Contents | ||
| :depth: 1 | ||
| :local: | ||
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| This tutorial demonstrates plotting ZTF cutouts and light curves. | ||
| It is based heavily on https://github.com/ZwickyTransientFacility/ztf-avro-alert/blob/master/notebooks/Filtering_alerts.ipynb. | ||
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| Prerequisites | ||
| ------------- | ||
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| 1. Load a ZTF alert to a dict or a pandas DataFrame. For examples, see: | ||
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| - :ref:`cloud storage` | ||
| - :ref:`bigquery` | ||
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| Imports | ||
| --------- | ||
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| .. code:: python | ||
| 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 | ||
| import pittgoogle | ||
| Plot a Light Curve | ||
| ------------------ | ||
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| .. code:: python | ||
| def plot_lightcurve(lightcurve_df: pd.DataFrame, days_ago: bool = True): | ||
| """Plot the per-band light curve of a single ZTF object. | ||
| Adapted from: | ||
| https://github.com/ZwickyTransientFacility/ztf-avro-alert/blob/master/notebooks/Filtering_alerts.ipynb | ||
| Parameters | ||
| ---------- | ||
| lightcurve_df | ||
| Lightcurve history of a ZTF object. Must contain columns | ||
| ['jd','fid','magpsf','sigmapsf','diffmaglim'] | ||
| days_ago | ||
| If True, x-axis will be number of days in the past. | ||
| Else x-axis will be Julian date. | ||
| """ | ||
| filter_code = pittgoogle.utils.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 = lightcurve_df.jd - now | ||
| xlabel = "Days Ago" | ||
| else: | ||
| t = lightcurve_df.jd | ||
| xlabel = "Time (JD)" | ||
| # plot lightcurves by band | ||
| for fid, color in filter_color.items(): | ||
| # plot detections in this filter: | ||
| w = (lightcurve_df.fid == fid) & ~lightcurve_df.magpsf.isnull() | ||
| if np.sum(w): | ||
| label = f"{fid}: {filter_code[fid]}" | ||
| kwargs = {"fmt": ".", "color": color, "label": label} | ||
| plt.errorbar(t[w], lightcurve_df.loc[w, "magpsf"], lightcurve_df.loc[w, "sigmapsf"], **kwargs) | ||
| # plot nondetections in this filter | ||
| wnodet = (lightcurve_df.fid == fid) & lightcurve_df.magpsf.isnull() | ||
| if np.sum(wnodet): | ||
| plt.scatter( | ||
| t[wnodet], | ||
| lightcurve_df.loc[wnodet, "diffmaglim"], | ||
| marker="v", | ||
| color=color, | ||
| alpha=0.25, | ||
| ) | ||
| plt.gca().invert_yaxis() | ||
| plt.xlabel(xlabel) | ||
| plt.ylabel("Magnitude") | ||
| plt.legend() | ||
| .. code:: python | ||
| plot_lightcurve(lightcurve_df) | ||
| Plot Cutouts | ||
| ------------ | ||
|
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| .. code:: python | ||
| 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) | ||
| ffig.show_grayscale(stretch="arcsinh") | ||
| return ffig | ||
| 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) | ||
| .. code:: python | ||
| plot_cutouts(alert_dict) | ||
| plt.show(block=False) |
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