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diagnostics.py
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diagnostics.py
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""" DIAGNOSTICS - diagnostic routines for photometry pipeline
v1.0: 2016-02-25, mommermiscience@gmail.com
"""
# Photometry Pipeline
# Copyright (C) 2016-2018 Michael Mommert, mommermiscience@gmail.com
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see
# <http://www.gnu.org/licenses/>.
import os
import sys
import numpy as np
import logging
import subprocess
from astropy.io import fits
from astropy.visualization import (ZScaleInterval, ImageNormalize,
LogStretch, LinearStretch)
from astropy.time import Time
from astropy import wcs
try:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pylab as plt
matplotlib.rcdefaults() # restore default parameters
except ImportError:
print('Module matplotlib not found. Please install with: pip install '
'matplotlib')
sys.exit()
try:
from skimage.transform import resize
except ImportError:
print('Module skimage not found. Please install with: pip install '
'scikit-image')
sys.exit()
# pipeline-specific modules
import _pp_conf
import toolbox
from catalog import *
# setup logging
logging.basicConfig(filename=_pp_conf.log_filename,
level=_pp_conf.log_level,
format=_pp_conf.log_formatline,
datefmt=_pp_conf.log_datefmt)
class Diagnostics_Html():
"""basis class for building pp html diagnostic output"""
from pp_setup import confdiagnostics as conf
def create_website(self, filename, content=''):
"""
create empty website for diagnostics output
"""
html = ("<!DOCTYPE html PUBLIC '-//W3C//DTD HTML 4.01//EN'>\n"
"<HTML>\n"
"<HEAD>\n"
"<TITLE>Photometry Pipeline - Diagnostics</TITLE>\n"
"<LINK rel=\"stylesheet\" href=\"{:s}"
"diagnostics_stylesheet.css\">\n"
"</HEAD>\n"
"<BODY>\n"
"<script>\n"
"function toggledisplay(elementID)\n"
"{{\n"
"(function(style) {{\n"
"style.display = style.display === 'none' ? '' :"
"'none';\n"
"}})(document.getElementById(elementID).style);\n"
"}}\n"
"</script>\n\n"
"{:s}\n"
"</BODY>\n"
"</HTML>\n").format(os.getenv('PHOTPIPEDIR'), content)
outf = open(filename, 'w')
outf.writelines(html)
outf.close()
def append_website(self, filename, content,
replace_from='X?!do not replace anything!?X',
keep_at='</BODY>',):
"""append content to an existing website: replace content starting
at line containing `replace_from` until line containin `keep_at`;
by default, all content following `replace_from` is
replaced
"""
# read existing code
existing_html = open(filename, 'r').readlines()
# insert content into existing html
outf = open(filename, 'w')
delete = False
for line in existing_html:
if replace_from in line:
delete = True
continue
if keep_at in line:
outf.writelines(content)
delete = False
if delete:
continue
outf.writelines(line)
outf.close()
def abort(self, where):
"""
use this function to add information to index.html that the
pipeline crashed and where
"""
logging.info('adding pipeline crash to diagnostics')
html = ("<P><FONT COLOR=\"RED\">Pipeline crashed "
"unexpectedly in module {:s}; refer to <A "
"HREF=\"{:s}\">log</A> "
"for additional information</FONT>\n").format(
_pp_conf.log_filename, where)
self.append_website(os.path.join(self.conf.diagnostics_path,
self.conf.main_html), html)
logging.info('pipeline crash added')
class Prepare_Diagnostics(Diagnostics_Html):
"""diagnostics run as part of pp_prepare"""
function_tag = "<!-- pp_prepare -->"
def frame_table(self, filenames, obsparam):
logging.info('create data summary table')
if self.conf.individual_frame_pages:
self.frame_pages(filenames, obsparam)
# create frame information table
html = "<P><TABLE CLASS=\"gridtable\">\n"
html += ("<TR><TH>Idx</TH>"
"<TH>Filename</TH>"
"<TH>Observation Midtime (UT)</TH>"
"<TH>Object Name</TH>"
"<TH>Airmass</TH>"
"<TH>Exptime (s)</TH>"
"<TH>Pixel Size (\")"
"<TH>Binning</TH>"
"<TH>FoV (')</TH></TR>\n")
for idx, filename in enumerate(filenames):
hdulist = fits.open(filename, ignore_missing_end=True)
header = hdulist[0].header
binning = toolbox.get_binning(header, obsparam)
try:
objectname = header[obsparam['object']]
except KeyError:
objectname = 'Unknown Target'
if self.conf.individual_frame_pages:
framename = "<A HREF=\"{:s}\">{:s}</A>".format(
os.path.join(self.conf.diagnostics_path,
'.diagnostics', filename+'.html'),
filename)
if self.conf.show_quickview_image:
self.quickview_image(filename)
# update frame page
framehtml = ("<!-- Quickview -->\n"
"<A HREF=\"#quickview\" "
"ONCLICK=\"toggledisplay"
"('quickview');\"><H2>Quickview Image</H2>"
"</A>\n"
"<IMG ID=\"quickview\" SRC=\"{:s}\" "
"STYLE=\"display: none\"\>\n\n").format(
filename+'.' +
self.conf.image_file_format)
self.append_website(
os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'{:s}.html'.format(filename)),
framehtml, replace_from='<!-- Quickview -->')
else:
framename = filename
html += ("<TR><TD>{:d}</TD>"
"<TD>{:s}</TD>"
"<TD>{:s}</TD>"
"<TD>{:s}</TD>"
"<TD>{:4.2f}</TD>"
"<TD>{:.1f}</TD>"
"<TD>{:.2f} x {:.2f}</TD>"
"<TD>{:d} x {:d}</TD>"
"<TD>{:.1f} x {:.1f}</TD>\n"
"</TR>\n").format(
idx+1, framename,
Time(header["MIDTIMJD"], format='jd').to_value(
'iso', subfmt='date_hm'),
str(objectname),
float(header[obsparam['airmass']]),
float(header[obsparam['exptime']]),
obsparam['secpix'][0],
obsparam['secpix'][1],
int(binning[0]), int(binning[1]),
float(header[obsparam['extent'][0]]) *
obsparam['secpix'][0]*binning[0]/60.,
float(header[obsparam['extent'][1]]) *
obsparam['secpix'][1]*binning[1]/60.)
html += '</TABLE>\n'
logging.info('data summary table created')
return html
def quickview_image(self, filename):
"""create quickview image for one frame"""
logging.info('create image preview for file {:s}'.format(
filename))
hdulist = fits.open(filename, ignore_missing_end=True)
# create frame image
imgdat = hdulist[0].data.astype(np.float64)
# normalize imgdat to pixel values 0 < px < 1
imgdat[np.where(np.isnan(imgdat))[0]] = np.nanmedian(imgdat)
imgdat = np.clip(imgdat, np.percentile(imgdat, 1),
np.percentile(imgdat, 99))
imgdat = (imgdat-np.min(imgdat)) / np.max(imgdat-np.min(imgdat)+0.1)
# resize image larger than lg_image_size_px on one side
imgdat = resize(imgdat,
(min(imgdat.shape[0], self.conf.image_size_lg_px),
min(imgdat.shape[1], self.conf.image_size_lg_px)))
plt.figure(figsize=(self.conf.image_size_lg_in,
self.conf.image_size_lg_in))
norm = ImageNormalize(
imgdat, interval=ZScaleInterval(),
stretch={'linear': LinearStretch(),
'log': LogStretch()}[self.conf.image_stretch])
img = plt.imshow(imgdat, cmap='gray', norm=norm,
origin='lower')
# remove axes
plt.axis('off')
img.axes.get_xaxis().set_visible(False)
img.axes.get_yaxis().set_visible(False)
framefilename = os.path.join(self.conf.diagnostics_path,
'.diagnostics', filename + '.' +
self.conf.image_file_format)
plt.savefig(framefilename, format=self.conf.image_file_format,
bbox_inches='tight',
pad_inches=0, dpi=self.conf.image_dpi)
logging.info('image preview for file {:s} written to {:s}'.format(
filename, os.path.join(self.conf.diagnostics_path,
'.diagnostics', filename + '.' +
self.conf.image_file_format)))
plt.close()
hdulist.close()
def frame_pages(self, filenames, obsparam):
"""build information page for each individual frame"""
logging.info('setting up individual frame diagnostics report pages')
for idx, filename in enumerate(filenames):
header = fits.open(filename)[0].header
html = ("<H1>{:s} Diagnostics</H1>"
"<P><TABLE CLASS=\"gridtable\">\n"
"<TR><TH>Telescope/Instrument</TH><TD>{:s} ({:s})</TD>"
"</TR>\n"
"<TR><TH>Target/Field Identifier</TH><TD>{:s}</TD>"
"</TR>\n"
"<TR><TH>RA</TH><TD>{:s}</TD></TR>\n"
"<TR><TH>Dec</TH><TD>{:s}</TD></TR>\n"
"<TR><TH>Exposure Time (s)</TH><TD>{:s}</TD></TR>\n"
"<TR><TH>Observation Midtime</TH><TD>{:s}</TD></TR>\n"
"</TABLE><P>\n"
"<A HREF=\"{:s}\">"
"« previous frame «</A> | "
"<A HREF=\"../diagnostics.html\">run overview</A> | "
"<A HREF=\"{:s}\">"
"» next frame »</A></P>\n\n").format(
filename,
obsparam['telescope_instrument'],
obsparam['telescope_keyword'],
header[obsparam['object']],
str(header[obsparam['ra']]),
str(header[obsparam['dec']]),
str(header[obsparam['exptime']]),
str(Time(header['MIDTIMJD'], format='jd').to_value(
'iso', subfmt='date_hm')),
filenames[(idx-1) % len(filenames)]+'.html',
filenames[(idx+1) % len(filenames)]+'.html')
self.create_website(
os.path.join(self.conf.diagnostics_path,
'.diagnostics', '{:s}.html'.format(filename)),
html)
logging.info(('diagnostics report page for file {:s} '
'written to {:s}').format(
filename,
os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'{:s}.html'.format(filename))))
def add_index(self, filenames, datadirectory, obsparam):
"""
create index.html
diagnostic root website
"""
logging.info('create frame table')
os.mkdir(self.conf.diagnostics_path) if not os.path.exists(
self.conf.diagnostics_path) else None
os.mkdir(os.path.join(self.conf.diagnostics_path,
'.diagnostics')) if not os.path.exists(
os.path.join(self.conf.diagnostics_path,
'.diagnostics')) else None
# create header information
refheader = fits.open(filenames[0],
ignore_missing_end=True)[0].header
raw_filtername = refheader[obsparam['filter']]
translated_filtername = obsparam['filter_translations'][
refheader[obsparam['filter']]]
html = ("{:s}\n<H1>Photometry Pipeline Diagnostic Output</H1>\n"
"<TABLE CLASS=\"gridtable\">\n"
" <TR><TH>Data Directory</TH><TD>{:s}</TD></TR>\n"
" <TR><TH>Telescope/Instrument</TH><TD>{:s}</TD></TR>\n"
" <TR><TH>Number of Frames</TH><TD>{:d}</TD></TR>\n"
" <TR><TH>Raw Filter Identifier</TH><TD>{:s}</TD></TR>\n"
" <TR><TH>Translated Filter Identifier</TH>"
"<TD>{:s}</TD></TR>\n"
" <TR><TH>Log File</TH>"
" <TD><A HREF=\"{:s}\">available here</A></TD></TR>"
"</TABLE>\n").format(
self.function_tag,
datadirectory,
obsparam['telescope_instrument'],
len(filenames),
str(raw_filtername),
str(translated_filtername),
os.path.join(datadirectory, 'LOG'))
html += "<H3>Data Summary</H3>\n"
html += self.frame_table(filenames, obsparam)
self.create_website(os.path.join(self.conf.diagnostics_path,
self.conf.main_html), html)
logging.info('frame table created')
# registration results website
class Registration_Diagnostics(Diagnostics_Html):
function_tag = "<!-- pp_register -->"
def registration_table(self, data, extraction_data, obsparam):
"""build overview table with astrometric registration results"""
logging.info('creating image registration overview table')
html = ("<TABLE CLASS=\"gridtable\">\n<TR>\n"
"<TH>Filename</TH><TH>C<SUB>AS</SUB></TH>"
"<TH>C<SUB>XY</SUB></TH>"
"<TH>σ<SUB>RA</SUB> (arcsec)</TH>"
"<TH>σ<SUB>DEC</SUB> (arcsec)</TH>"
"<TH>χ<SUP>2</SUP><SUB>Reference</SUB></TH>"
"<TH>χ<SUP>2</SUP><SUB>Internal</SUB></TH>\n</TR>\n")
for dat in data['fitresults']:
framefilename = os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'{:s}.html'.format(dat[0]))
if self.conf.individual_frame_pages:
filename = '<A HREF=\"{:s}\">{:s}</A>'.format(
framefilename, dat[0])
else:
filename = dat[0]
html += ("<TR><TD>{:s}</TD>"
+ "<TD>{:4.1f}</TD><TD>{:4.1f}</TD>"
+ "<TD>{:5.3f}</TD><TD>{:5.3f}</TD>"
+ "<TD>{:e}</TD><TD>{:e}</TD>\n</TR>\n").format(
filename, dat[1], dat[2], dat[3],
dat[4], dat[5], dat[6])
html += "</TABLE>\n"
html += ("<P CLASS=\"caption\"><STRONG>Legend</STRONG>: "
"C<SUB>AS</SUB>: position "
"angle/scale contrast (values >{:.1f} are ok); ").format(
_pp_conf.scamp_as_contrast_limit)
html += ("C<SUB>XY</SUB>: xy-shift contrast "
"(values >{:.1f} are ok); ").format(
_pp_conf.scamp_xy_contrast_limit)
html += ("σ<SUB>RA</SUB> and σ<SUB>DEC</SUB> "
"refer to the internal astrometric uncertainties as "
"provided by SCAMP; χ<SUP>2</SUP><SUB>Reference</SUB> "
"and χ<SUP>2</SUP><SUB>Internal</SUB> refer to the "
"χ<SUP>2</SUP> statistics based on the reference "
"catalog and the respective frame as provided by SCAMP."
"</P>\n")
logging.info('image registration overview table created')
return html
def registration_maps(self, data, extraction_data, obsparam):
"""build overlays for image maps indicating astrometric reference
stars"""
logging.info('create registration overlays with reference stars')
# load reference catalog
refcat = catalog(data['catalog'])
for filename in os.listdir('.'):
if data['catalog'] in filename and '.cat' in filename:
refcat.read_ldac(filename)
break
# create overlays
for dat in extraction_data:
framefilename = os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'{:s}_astrometry.{:s}'.format(
dat['fits_filename'],
self.conf.image_file_format))
imgdat = fits.open(dat['fits_filename'],
ignore_missing_end=True)[0].data
resize_factor = min(
1.,
self.conf.image_size_lg_px/np.max(imgdat.shape))
header = fits.open(dat['fits_filename'],
ignore_missing_end=True)[0].header
# turn relevant header keys into floats
# astropy.io.fits bug
for key, val in list(header.items()):
if 'CD1_' in key or 'CD2_' in key or \
'CRVAL' in key or 'CRPIX' in key or \
'EQUINOX' in key:
header[key] = float(val)
plt.figure(figsize=(self.conf.image_size_lg_in,
self.conf.image_size_lg_in))
# create fake image to ensure image dimensions and margins
img = plt.imshow(np.ones((self.conf.image_size_lg_px,
self.conf.image_size_lg_px))*np.nan,
origin='lower')
# remove axes
plt.axis('off')
img.axes.get_xaxis().set_visible(False)
img.axes.get_yaxis().set_visible(False)
# plot reference sources
if refcat.shape[0] > 0:
try:
w = wcs.WCS(header)
world_coo = np.array(list(zip(refcat['ra_deg'],
refcat['dec_deg'])))
img_coo = w.wcs_world2pix(world_coo, True)
img_coo = [c for c in img_coo
if (c[0] > 0 and c[1] > 0 and
c[0] < header[obsparam['extent'][0]] and
c[1] < header[obsparam['extent'][1]])]
plt.scatter([c[0]*resize_factor for c in img_coo],
[c[1]*resize_factor for c in img_coo],
s=5, marker='o', edgecolors='red',
linewidth=self.conf.overlay_lg_linewidth,
facecolor='none')
except wcs._wcs.InvalidTransformError:
logging.error('could not plot reference sources due to '
'astropy.wcs._wcs.InvalidTransformError; '
'most likely unknown distortion '
'parameters.')
plt.savefig(framefilename, bbox_inches='tight',
pad_inches=0, dpi=self.conf.image_dpi,
transparent=True)
logging.info(('registration map image file for image {:s} '
'written to {:s}').format(
filename, os.path.abspath(framefilename)))
plt.close()
logging.info('create registration overlays with reference stars')
def add_registration(self, data, extraction_data):
"""
add registration results to website
"""
logging.info('adding registration information')
obsparam = extraction_data[0]['parameters']['obsparam']
html = self.function_tag+'\n'
html += ('<H2>Registration</H2>\n'
'<P>Registration based on {:s} catalog: \n').format(
data['catalog'])
if len(data['badfits']) == 0:
html += ('<STRONG><FONT COLOR="GREEN">All frames registered '
'successfully</FONT></STRONG></P>\n')
else:
html += ('<STRONG><FONT COLOR="RED">{:d} files could not be '
'registered</FONT></STRONG></P>\n').format(
len(data['badfits']))
if self.conf.show_registration_table:
html += self.registration_table(data, extraction_data, obsparam)
if (self.conf.individual_frame_pages and
self.conf.show_quickview_image and
self.conf.show_registration_star_map):
self.registration_maps(data, extraction_data, obsparam)
for framedata in data['fitresults']:
# update frame page
filename = framedata[0]
if filename in data['goodfits']:
resultstring = ('<P><FONT COLOR="GREEN">Registration '
'successful</FONT></P>')
else:
resultstring = ('<P><FONT COLOR="RED">Registration '
'failed</FONT></P>')
framehtml = (
"<!-- Registration -->\n"
"<A HREF=\"#registration\" "
"ONCLICK=\"toggledisplay('registration');\">"
"<H2>Astrometric Registration</H2></A>\n"
"<DIV ID=\"registration\" STYLE=\"display: none\">\n"
"<TABLE CLASS=\"gridtable\">\n<TR>\n"
"<TH>Filename</TH><TH>C<SUB>AS</SUB></TH>"
"<TH>C<SUB>XY</SUB></TH>"
"<TH>σ<SUB>RA</SUB> (arcsec)</TH>"
"<TH>σ<SUB>DEC</SUB> (arcsec)</TH>"
"<TH>χ<SUP>2</SUP><SUB>Reference</SUB></TH>"
"<TH>χ<SUP>2</SUP><SUB>Internal</SUB></TH>\n</TR>\n"
"<TR><TD>{:s}</TD>"
"<TD>{:4.1f}</TD><TD>{:4.1f}</TD>"
"<TD>{:5.3f}</TD><TD>{:5.3f}</TD>"
"<TD>{:e}</TD><TD>{:e}</TD>\n</TR>\n"
"</TABLE>\n"
"<STRONG>{:s}</STRONG>"
"<DIV CLASS=\"parent_image\">\n"
" <IMG CLASS=\"back_image\" SRC=\"{:s}\" />\n"
" <IMG CLASS=\"front_image\" SRC=\"{:s}\" />\n"
"</DIV>\n</DIV>\n\n").format(
filename, framedata[1], framedata[2], framedata[3],
framedata[4], framedata[5], framedata[6],
resultstring,
filename+'.'+self.conf.image_file_format,
filename+"_astrometry."+self.conf.image_file_format)
self.append_website(
os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'{:s}.html'.format(filename)),
framehtml, replace_from='<!-- Registration -->')
self.append_website(os.path.join(self.conf.diagnostics_path,
self.conf.main_html), html,
replace_from=self.function_tag)
logging.info('registration information added')
class Photometry_Diagnostics(Diagnostics_Html):
function_tag = "<!-- pp_photometry -->"
def curve_of_growth_plot(self, data):
""" create curve of growth plot"""
logging.info('create curve-of-growth plot')
parameters = data['parameters']
growth_filename = os.path.join(self.conf.diagnostics_path,
'.diagnostics', 'curve_of_growth.' +
self.conf.image_file_format)
f, (ax1, ax2) = plt.subplots(2, sharex=True)
ax1.set_xlim([min(parameters['aprad']), max(parameters['aprad'])])
ax1.set_ylabel('Fractional Combined Flux')
if not parameters['target_only']:
ax1.plot(parameters['aprad'], data['background_flux'][0],
color='black', linewidth=1,
label='background sources')
ax1.fill_between(parameters['aprad'],
(data['background_flux'][0] -
data['background_flux'][1]),
(data['background_flux'][0] +
data['background_flux'][1]),
color='black', alpha=0.2)
if not parameters['background_only']:
ax1.plot(parameters['aprad'], data['target_flux'][0],
color='red', linewidth=1,
label='target')
ax1.fill_between(parameters['aprad'],
(data['target_flux'][0] -
data['target_flux'][1]),
(data['target_flux'][0] +
data['target_flux'][1]),
color='red', alpha=0.2)
ax1.set_ylim([0, ax1.get_ylim()[1]])
ax1.plot([data['optimum_aprad'], data['optimum_aprad']],
[ax1.get_ylim()[0], ax1.get_ylim()[1]],
linewidth=2, color='blue')
ax1.plot([plt.xlim()[0], plt.xlim()[1]],
[data['fluxlimit_aprad'], data['fluxlimit_aprad']],
color='black', linestyle='--')
ax1.grid()
ax1.legend(loc=4)
ax2.set_ylim([-0.1, 1.1])
ax2.set_ylabel('SNR')
if not parameters['target_only']:
ax2.errorbar(parameters['aprad'], data['background_snr'],
color='black', linewidth=1)
if not parameters['background_only']:
ax2.errorbar(parameters['aprad'], data['target_snr'],
color='red', linewidth=1)
ax2.plot([data['optimum_aprad'], data['optimum_aprad']],
[plt.ylim()[0], plt.ylim()[1]],
linewidth=2, color='blue')
ax2.grid()
ax2.set_xlabel('Aperture Radius (px)')
plt.savefig(growth_filename, format=self.conf.image_file_format,
dpi=self.conf.plot_dpi)
plt.close()
data['growth_filename'] = growth_filename
logging.info('curve-of-growth plot created')
def fwhm_vs_time_plot(self, extraction, data):
"""create fwhm plot"""
logging.info('create FWHM plot')
fwhm_filename = os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'fwhm.'+self.conf.image_file_format)
frame_midtimes = np.array([frame['time'] for frame in extraction])
fwhm = [np.median(frame['catalog_data']['FWHM_IMAGE'])
for frame in extraction]
fwhm_sig = [np.std(frame['catalog_data']['FWHM_IMAGE'])
for frame in extraction]
fig, ax = plt.subplots()
ax.set_title('Median PSF FWHM per Frame')
ax.set_xlabel('Minutes after {:s} UT'.format(
Time(frame_midtimes.min(), format='jd').to_value('iso', subfmt='date_hm')))
ax.set_ylabel('Point Source FWHM (px)')
ax.scatter((frame_midtimes-frame_midtimes.min())*1440,
fwhm, marker='o',
color='black')
xrange = [plt.xlim()[0], plt.xlim()[1]]
ax.plot(xrange, [data['optimum_aprad']*2, data['optimum_aprad']*2],
color='blue')
ax.set_xlim(xrange)
ax.set_ylim([0, max([data['optimum_aprad']*2+1, max(fwhm)])])
ax.grid()
fig.savefig(fwhm_filename, dpi=self.conf.plot_dpi,
format=self.conf.image_file_format)
data['fwhm_filename'] = fwhm_filename
# create html map
if self.conf.individual_frame_pages:
data['fwhm_map'] = ""
for i in range(len(extraction)):
x, y = ax.transData.transform_point(
[((frame_midtimes-frame_midtimes.min())*1440)[i],
fwhm[i]])
filename = extraction[i]['fits_filename']
data['fwhm_map'] += (
'<area shape="circle" coords="{:.1f},{:.1f},{:.1f}" '
'href="{:s}#{:s}" alt="{:s}" title="{:s}">\n').format(
x, fig.bbox.height - y, 5,
os.path.join(self.conf.diagnostics_path,
'.diagnostics', filename+'.html'),
'',
filename, filename)
logging.info('FWHM plot created')
def add_photometry(self, data, extraction):
"""
add photometry results to website
"""
logging.info('adding photometry information')
# create curve-of-growth plot
self.curve_of_growth_plot(data)
# create fwhm vs time plot
self.fwhm_vs_time_plot(extraction, data)
# update index.html
html = self.function_tag+'\n'
html += ("<H2>Instrumental Photometry</H2>\n"
"<TABLE CLASS=\"gridtable\">\n"
"<TR><TH>Photometry Method</TH><TD>{:s}</TD></TR>\n"
"<TR><TH>Source Extractor MINAREA (px)</TH>"
"<TD>{:.1f}</TD></TR>\n"
"<TR><TH>Source Extractor Detection Threshold (σ)"
"</TH><TD>{:.1f}</TD></TR>\n").format(
{'APER': 'Aperture Photometry'}[_pp_conf.photmode],
extraction[0]['parameters']['source_minarea'],
extraction[0]['parameters']['sex_snr'])
if _pp_conf.photmode == 'APER':
if data['n_target'] > 0 and data['n_bkg'] > 0:
apsrc = ("{:d} target detections and {:d} "
"background detections").format(
data['n_target'], data['n_bkg'])
elif data['n_target'] == 0 and data['n_bkg'] > 0:
apsrc = "{:d} frames with background detections".format(
data['n_bkg'])
elif data['n_bkg'] == 0 and data['n_target'] > 0:
apsrc = "{:d} frames with target detections".format(
data['n_target'])
else:
apsrc = "manually defined"
html += ("<TR><TH>Aperture Radius (px)</TH>"
"<TD>{:.2f}</TD></TR>\n"
"<TR><TH>Aperture Radius Basis</TH>"
"<TD>{:s}</TD></TR>\n"
"<TR><TH>Aperture Radius Strategy</TH>"
"<TD>{:s}</TD></TR>\n").format(
data['optimum_aprad'],
apsrc,
data['aprad_strategy']
)
html += "</TABLE>\n"
html += "<P><IMG SRC=\"{:s}\">\n".format(data['growth_filename'])
if self.conf.individual_frame_pages:
html += "<IMG SRC=\"{:s}\" USEMAP=\"#FWHM\">\n".format(
data['fwhm_filename'])
html += "<MAP NAME=\"#FWHM\">\n{:s}</MAP>\n".format(
data['fwhm_map'])
else:
html += "<IMG SRC=\"{:s}\">\n".format(
data['fwhm_filename'])
self.append_website(os.path.join(self.conf.diagnostics_path,
self.conf.main_html), html,
replace_from=self.function_tag)
logging.info('photometry information added')
class Calibration_Diagnostics(Diagnostics_Html):
function_tag = "<!-- pp_calibrate -->"
def zeropoint_overview_plot(self, data):
"""produce a plot of magnitude zeropoint as a function of time"""
logging.info('create zeropoint overview plot')
times = np.array([dat['obstime'][0] for dat in data['zeropoints']])
zp = [dat['zp'] for dat in data['zeropoints']]
zperr = [dat['zp_sig'] for dat in data['zeropoints']]
fig, ax = plt.subplots()
ax.errorbar((times-times.min())*1440, zp, yerr=zperr, linestyle='',
color='blue', marker='s', capsize=3)
ax.set_xlabel('Minutes after {:s} UT'.format(
Time(times.min(), format='jd').to_value('iso', subfmt='date_hm')))
ax.set_ylabel(
'{:s}-Band Magnitude Zeropoints (mag)'.format(
data['filtername']))
ax.set_ylim([ax.get_ylim()[1], ax.get_ylim()[0]])
ax.grid()
fig.savefig(os.path.join(self.conf.diagnostics_path, '.diagnostics',
'zeropoints.'+self.conf.image_file_format),
format=self.conf.image_file_format,
dpi=self.conf.plot_dpi)
logging.info('zeropoint overview plot written to {:s}'.format(
os.path.abspath(os.path.join(self.conf.diagnostics_path,
'.diagnostics', 'zeropoints.' +
self.conf.image_file_format))))
data['zpplot'] = 'zeropoints.' + self.conf.image_file_format
# create html map
if self.conf.individual_frame_pages:
data['zpplotmap'] = ""
for i in range(len(times)):
x, y = ax.transData.transform_point(
[((times-times.min())*1440)[i],
[dat['zp'] for dat in data['zeropoints']][i]])
filename = data['zeropoints'][i]['filename'][:-4]+'fits'
data['zpplotmap'] += (
'<area shape="circle" coords="{:.1f},{:.1f},{:.1f}" '
'href="{:s}#{:s}" alt="{:s}" title="{:s}">\n').format(
x, fig.bbox.height - y, 5,
os.path.join(self.conf.diagnostics_path,
'.diagnostics', filename+'.html'),
'calibration_overview',
filename, filename)
logging.info('zeropoint overview plot created')
def phot_calibration_plot(self, data, idx):
"""produce diagnostic plot for each frame"""
logging.info('create photometric calibration overview plot')
f, (ax1, ax3) = plt.subplots(2)
plt.subplots_adjust(hspace=0.3)
ax1.set_title('{:s}: {:s}-band from {:s}'.format(
data['catalogs'][idx].catalogname,
data['filtername'],
data['ref_cat'].catalogname))
ax1.set_xlabel('Number of Reference Stars')
ax1.set_ylabel('Magnitude Zeropoint', fontdict={'color': 'red'})
zp_idx = data['zeropoints'][idx]['zp_idx']
clipping_steps = data['zeropoints'][idx]['clipping_steps']
x = [len(clipping_steps[i][3]) for i
in range(len(clipping_steps))]
ax1.errorbar(x, [clipping_steps[i][0] for i
in range(len(clipping_steps))],
yerr=[clipping_steps[i][1] for i
in range(len(clipping_steps))], color='red')
ax1.set_ylim(ax1.get_ylim()[::-1]) # reverse y axis
ax1.plot([len(clipping_steps[zp_idx][3]),
len(clipping_steps[zp_idx][3])],
ax1.get_ylim(), color='black')
ax1.grid(linestyle='--')
ax2 = ax1.twinx()
ax2.plot(x, [clipping_steps[i][2] for i
in range(len(clipping_steps))],
color='blue')
ax2.set_ylabel(r'reduced $\chi^2$', fontdict={'color': 'blue'})
ax2.set_yscale('log')
ax2.plot([min(x), max(x)], [1, 1], linestyle='dotted', color='blue')
# residual plot
ax3.set_xlabel('Reference Star Magnitude')
ax3.set_ylabel('Calibration-Reference (mag)')
match = data['zeropoints'][idx]['match']
x = match[0][0][clipping_steps[zp_idx][3]]
residuals = (match[1][0][clipping_steps[zp_idx][3]]
+ clipping_steps[zp_idx][0]
- match[0][0][clipping_steps[zp_idx][3]])
residuals_sig = np.sqrt(match[1][1][clipping_steps[zp_idx][3]]**2
+ clipping_steps[zp_idx][1]**2)
ax3.errorbar(x, residuals, yerr=residuals_sig, color='black',
marker='o', linestyle='')
x_range = ax3.get_xlim()
ax3.plot(x_range, [0, 0], color='black', linestyle='--')
ax3.set_xlim(x_range)
ax3.set_ylim(ax3.get_ylim()[::-1]) # reverse y axis
ax3.grid(linestyle='--')
plotfilename = os.path.join(self.conf.diagnostics_path,
'.diagnostics',
'{:s}_photcal.{:s}'.format(
data['catalogs'][idx].catalogname,
self.conf.image_file_format))
plt.savefig(plotfilename, dpi=self.conf.plot_dpi,
format=self.conf.image_file_format)
data['zeropoints'][idx]['plotfilename'] = plotfilename
logging.info('create photometric calibration overview plot')
def calibration_raw_data_tables(self, dat):
"""build table with photometric calibration raw data"""
logging.info('create calibration data table')
html = "<TD><TABLE CLASS=\"gridtable\">\n<TR>\n"
html += ("<TH>Idx</TH><TH>Source Name</TH><TH>RA</TH><TH>Dec</TH>"
"<TH>Catalog (mag)</TH>"
"<TH>Instrumental (mag)</TH><TH>Calibrated (mag)</TH>"
"<TH>Residual (mag</TH>\n</TR>\n")
for i, idx in enumerate(dat['zp_usedstars']):
name = str(dat['match'][0][2][idx])
if isinstance(name, bytes):
name = name.decode('utf8')
html += ("<TR><TD>{:d}</TD><TD>{:s}</TD><TD>{:12.8f}</TD>"
"<TD>{:12.8f}</TD><TD>{:.3f}+-{:.3f}</TD>"
"<TD>{:.3f}+-{:.3f}</TD>"
"<TD>{:.3f}+-{:.3f}</TD><TD>{:.3f}</TD>"
"</TR>").format(
i+1, name,
dat['match'][0][3][idx],
dat['match'][0][4][idx],
dat['match'][0][0][idx],
dat['match'][0][1][idx],
dat['match'][1][0][idx],
dat['match'][1][1][idx],
dat['zp']+dat['match'][1][0][idx],
np.sqrt(dat['zp_sig']**2 +
dat['match'][1][1][idx]**2),
(dat['zp']+dat['match'][1][0][idx]) -
dat['match'][0][0][idx])
html += "</TABLE>\n"
logging.info('calibration data table created')
return html
def calibration_star_maps(self, dat):
"""create thumbnail images with calibration stars marked"""
logging.info('create calibration reference star overlay')
fits_filename = (dat['filename'][:dat['filename'].find('.ldac')]
+ '.fits')
imgdat = fits.open(fits_filename,
ignore_missing_end=True)[0].data
resize_factor = min(
1.,
self.conf.image_size_lg_px/np.max(imgdat.shape))
header = fits.open(fits_filename,
ignore_missing_end=True)[0].header
# turn relevant header keys into floats
# astropy.io.fits bug
for key, val in list(header.items()):
if 'CD1_' in key or 'CD2_' in key or \
'CRVAL' in key or 'CRPIX' in key or \
'EQUINOX' in key:
header[key] = float(val)
plt.figure(figsize=(self.conf.image_size_lg_in,
self.conf.image_size_lg_in))
# create fake image to ensure image dimensions and margins
img = plt.imshow(np.ones((self.conf.image_size_lg_px,
self.conf.image_size_lg_px))*np.nan,
origin='lower')
# remove axes
plt.axis('off')
img.axes.get_xaxis().set_visible(False)
img.axes.get_yaxis().set_visible(False)
# plot reference sources
if len(dat['match'][0][3]) > 0 and len(dat['match'][0][4]) > 0:
try:
w = wcs.WCS(header)
world_coo = [[dat['match'][0][3][idx],
dat['match'][0][4][idx]]
for idx in dat['zp_usedstars']]
img_coo = w.all_world2pix(world_coo, True)
plt.scatter([c[0]*resize_factor for c in img_coo],
[c[1]*resize_factor for c in img_coo],
s=10, marker='o', edgecolors='red',
linewidth=0.3,
facecolor='none')
for i in range(len(dat['zp_usedstars'])):
plt.annotate(str(i+1),
xy=((img_coo[i][0]*resize_factor)+15,
img_coo[i][1]*resize_factor),
color='red',
horizontalalignment='left',
verticalalignment='center')
except wcs._wcs.InvalidTransformError:
logging.error('could not plot reference sources due to '
'astropy.wcs._wcs.InvalidTransformError; '
'most likely unknown distortion '
'parameters.')