#! /usr/bin/env python3 # -*- coding: iso-8859-15 -*- import matplotlib as mpl mpl.use('Agg') # necessary to be able to generate the reports even without X server import matplotlib.pyplot as plt #import matplotlib.colors as colors import os import datetime try: import pyfits except: from astropy.io import fits as pyfits import numpy as np from . import gravi_visual_class #============================================================================== # Preparation of the report using reportlab #============================================================================== def produce_wave_report(wave,filename): # From gravi_visual_class from . import gravi_visual_class from .gravi_visual_class import myFirstPage, myLaterPages, styles from .gravi_visual_class import clipdata, transbarchartout, graphoutaxes, graphoutnoaxis from .gravi_visual_class import graphoutnoxaxes, graphscatteraxes, graphaxesplt from .gravi_visual_class import plotTitle, plotSubtitle from .gravi_visual_class import get_key_withdefault, create_array_from_list, baseline_phases from .gravi_visual_class import mean_angle, std_angle, clean_unwrap_phase, nanaverage from .gravi_visual_class import clean_gdelay_is, clean_gdelay_fft, clean_gdelay_full from .gravi_visual_class import base_list, tel_list, nbase, ntel from .gravi_visual_class import plotReductionSummary, plotSummary from .gravi_visual_class import stepbarchartout, get_reg_number, get_base_number from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, Image, PageBreak from reportlab.graphics.shapes import String from reportlab.lib.units import inch, cm, mm from reportlab.lib import colors import io from io import StringIO, BytesIO from svglib.svglib import svg2rlg #============================================================================== # Global parameters #============================================================================== #startx_mr = 53 #startx_hr = 38 delta_res = 0.005 if wave.nwave_sc > 50 else 0.05 #============================================================================== # Start Story #============================================================================== Story = [Spacer(1,1*mm)] plotSummary (Story, filename, wave, onTarget=False) Story.append(PageBreak()) #============================================================================== # Summary of reduction parameters #============================================================================== plotReductionSummary(Story, wave) Story.append(PageBreak()) #============================================================================== # FT wavelength NON-INTERPOLATED vector map (microns) - average #============================================================================== plotTitle(Story,"FT wavelength variation map") plotSubtitle(Story,"Average wavelength scale over outputs subtracted, deviation in percent of the pixel size.") Story.append(Spacer(1,2*mm)) meanchannel = np.mean(wave.wave_ft[:,3]-wave.wave_ft[:,2]) waveresidual = np.copy(wave.wave_ft) for channel in range(0,wave.wave_ft.shape[0]): waveresidual[channel,:] = 100.*(wave.wave_ft[channel,:] - np.mean(wave.wave_ft[:,:],axis=0))/meanchannel plt.close('all') fig=plt.figure(figsize=(6,9)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) maxdiff = np.max(np.abs(waveresidual)) plt.imshow(waveresidual,vmin=-maxdiff,vmax=maxdiff,cmap='cubehelix', interpolation='nearest', aspect='auto') plt.colorbar(fraction=0.15,aspect=15,orientation='horizontal',shrink=0.7,pad=0.05) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # Image display of the SC spectrum extraction mask #============================================================================== plotTitle(Story,"SC spectrum extraction mask") Story.append(Spacer(1,2*mm)) plt.close('all') fig=plt.figure(figsize=(6,9)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) plt.imshow(wave.test_wave[1,:,:],vmin=0,vmax=0.5,cmap='cubehelix', interpolation='nearest', aspect='auto') plt.colorbar(fraction=0.15,aspect=15,orientation='horizontal',shrink=0.7,pad=0.05) for i in range(0,6): text = plt.annotate("Base "+wave.base_list_sc[i],xy=(int(wave.test_wave.shape[0]/10), int(32+wave.test_wave.shape[1]*i/6)), xycoords='data', fontsize=6, color='white') fig.gca().add_artist(text) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # SC wavelength NON-INTERPOLATED vector map (microns) #============================================================================== plotTitle(Story,"SC wavelength NON-INTERPOLATED vector map (microns)") Story.append(Spacer(1,2*mm)) plt.close('all') fig=plt.figure(figsize=(6,9)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) plt.imshow(wave.test_wave[2,:,:],vmin=wave.minwave_sc,vmax=wave.maxwave_sc,cmap='flag', interpolation='none', aspect='auto') plt.colorbar(fraction=0.15,aspect=15,orientation='horizontal',shrink=0.7,pad=0.05) for i in range(0,6): text = plt.annotate("Base "+wave.base_list_sc[i],xy=(int(wave.test_wave.shape[0]/10), int(32+wave.test_wave.shape[1]*i/6)), xycoords='data', fontsize=6, color='white') fig.gca().add_artist(text) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # SC wavelength INTERPOLATED vector map (microns) #============================================================================== plotTitle(Story,"SC wavelength INTERPOLATED vector map (microns)") Story.append(Spacer(1,2*mm)) plt.close('all') fig=plt.figure(figsize=(6,9)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) plt.imshow(wave.test_wave[0,:,:],vmin=wave.minwave_sc,vmax=wave.maxwave_sc,cmap='flag', interpolation='none', aspect='auto') plt.colorbar(fraction=0.15,aspect=15,orientation='horizontal',shrink=0.7,pad=0.05) for i in range(0,6): text = plt.annotate("Base "+wave.base_list_sc[i],xy=(int(wave.test_wave.shape[0]/10), int(32+wave.test_wave.shape[1]*i/6)), xycoords='data', fontsize=6, color='white') fig.gca().add_artist(text) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # Offset of SC wavelength scale [INTERP. - NON-INTERP.] (nm) #============================================================================== plotTitle(Story,"Offset of SC wavelength scale [INTERP. - NON-INTERP.] (nm)") Story.append(Spacer(1,2*mm)) plt.close('all') fig=plt.figure(figsize=(6,9)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) offset_interp = (wave.test_wave[0,:,:]-wave.test_wave[2,:,:]) * 1000. # in nm valmax = np.percentile(np.abs(offset_interp),90) valmin = -valmax plt.imshow(offset_interp,vmin=valmin,vmax=valmax,cmap='seismic', interpolation='none', aspect='auto') plt.colorbar(fraction=0.15,aspect=15,orientation='horizontal',shrink=0.7,pad=0.05) for i in range(0,6): text = plt.annotate("Base "+wave.base_list_sc[i],xy=(int(wave.test_wave.shape[0]/10), int(32+wave.test_wave.shape[1]*i/6)), xycoords='data', fontsize=6, color='black') fig.gca().add_artist(text) plt.savefig(imgdata, format='PDF', dpi=250, bbox_inches='tight') imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # SC wavelengthvector map (microns) - average #============================================================================== y = np.mean(wave.wave_sc,axis=0) x = np.arange(len(y)) mean = np.poly1d(np.polyfit(x[3:-2], y[3:-2], 2))(x) plotTitle(Story,"SC wavelength (WAVE_FIBRE_SC) for each base and channel") plotSubtitle(Story,"region in horizontal, wavelenght in vertical [um], channel in color") plt.close('all') fig=plt.figure(figsize=(6,3)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) color = ['b','g','r','c','m','y'] for l in range(6): if wave.polarsplit == False: plt.plot (wave.wavefiber_c[l,:], c=color[l],ls='-') ids = get_reg_number(wave.regname_sc,l,"C") plt.plot (np.mean(wave.wave_sc[ids,:],axis=0), c=color[l],ls='--') else: plt.plot (wave.wavefiber_s[l,:]) ids = get_reg_number(wave.regname_sc,l,"S") plt.plot (np.mean(wave.wave_sc[ids,:],axis=0), c=color[l],ls='--') plt.ylim([1.8,2.6]) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(Spacer(1,1*cm)) plotSubtitle(Story,"the same, but a common mean 2sd order subtracted, region in color") plt.close('all') fig=plt.figure(figsize=(6,3)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) color = ['b','g','r','c','m','y'] for l in range(6): if wave.polarsplit == False: plt.plot (wave.wavefiber_c[l,:] - mean, c=color[l],ls='-') ids = get_reg_number(wave.regname_sc,l,"C") plt.plot (np.mean(wave.wave_sc[ids,:],axis=0) - mean, c=color[l],ls='--') else: plt.plot (wave.wavefiber_s[l,:] - mean, c=color[l],ls='-') ids = get_reg_number(wave.regname_sc,l,"S") plt.plot (np.mean(wave.wave_sc[ids,:],axis=0) - mean, c=color[l],ls='--') plt.ylim([-delta_res,delta_res]) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # SC wavelengthvector map (microns) - average #============================================================================== plotTitle(Story,"SC wavelength (WAVE_DATA_SC) for each region and channel") plotSubtitle(Story,"channel in horizontal, wavelenght in vertical [um], region in color") plt.close('all') fig=plt.figure(figsize=(6,3)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) for l in range(len(wave.wave_sc[:,0])): if 'P' in wave.regname_sc[l]: continue b = get_base_number (wave.regname_sc, l) plt.plot (wave.wave_sc[l,:], c=color[b]) plt.ylim([1.8,2.6]) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(Spacer(1,1*cm)) plotSubtitle(Story,"the same, but a common mean 2sd order subtracted, region in color") plt.close('all') fig=plt.figure(figsize=(6,3)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) for l in range(len(wave.wave_sc[:,0])): if 'P' in wave.regname_sc[l]: continue b = get_base_number (wave.regname_sc, l) plt.plot (wave.wave_sc[l,:] - mean, c=color[b]) plt.ylim([-delta_res,delta_res]) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # FT wavelengthvector map (microns) - average #============================================================================== if (wave.nwave_sc < 1000): plotTitle(Story,"SC wavelength (WAVE_DATA_SC) for each region and channel") plotSubtitle(Story,"region in horizontal, wavelenght in vertical [um], channel in color") plt.close('all') fig=plt.figure(figsize=(6,9)) plt.rc('xtick', labelsize=5) plt.rc('ytick', labelsize=5) for l in range(wave.nwave_sc): plt.plot (wave.wave_sc[:,l]) plt.ylim([1.8,2.6]) imgdata = BytesIO() fig.savefig(imgdata, format='svg', bbox_inches='tight') imgdata.seek(0) # rewind the data drawing = svg2rlg(imgdata) Story.append(drawing) Story.append(PageBreak()) #============================================================================== # Spectra step on detectors in pixels #============================================================================== plotTitle(Story,"Vertical step of SC extracted spectra (pixels)") Story.append(Spacer(1,2*mm)) hsize = 18*cm vsize = 4*cm step_sc = np.zeros(wave.nregion_sc-1) for i in range(1,wave.nregion_sc): step_sc[i-1] = wave.center_sc[i,1]-wave.center_sc[i-1,1] step_ft = np.zeros(wave.nregion_ft-1) for i in range(1,wave.nregion_ft): step_ft[i-1] = wave.center_ft[i,1]-wave.center_ft[i-1,1] data = [tuple(step_sc)] labelout = wave.regname_sc.astype('|S6').tolist() a = stepbarchartout(data, labelout, np.min(step_sc)-1, np.max(step_sc)+1, 0.5, hsize, vsize, colors.cornflower) Story.append(a) Story.append(Spacer(1,1*cm)) plotTitle(Story,"Vertical step of FT extracted spectra (pixels)") Story.append(Spacer(1,2*mm)) data = [tuple(step_ft)] #a = graphoutaxes( data, 1, wave.nregion_ft, 3, 6, 15*cm, 4*cm, '') labelout = wave.regname_ft.astype('|S6').tolist() a = stepbarchartout(data, labelout, np.min(step_ft)-1, np.max(step_ft)+1, 0.5, hsize, vsize, colors.cornflower) Story.append(a) Story.append(PageBreak()) #============================================================================== # Create report from Story #============================================================================== print("Create the PDF") gravi_visual_class.TITLE = "GRAVITY WAVE Quality Control Report" gravi_visual_class.PAGEINFO = "WAVE file: "+filename+".fits" reportname = filename+"-WAVE.pdf" doc = SimpleDocTemplate(reportname) doc.build(Story, onFirstPage=myFirstPage, onLaterPages=myLaterPages) print((" "+reportname)) #============================================================================== # MAIN PROGRAM #============================================================================== if __name__ == '__main__': import sys filename='' if len(sys.argv) == 2 : filename=sys.argv[1] if filename == '' : filename=input(" Enter WAVE file name (without .fits) : ") wave = gravi_visual_class.Wave(filename+'.fits') produce_wave_report(wave,filename)