Пример #1
0
o = optparse.OptionParser()
o.set_usage('combine_and_fit_uCal.py [.uCalResults.npz files] [options]')
o.add_option('--nofit', action='store_true',
    help='For speed, does not try to fit the bandpass.')
o.add_option('--combinedSuffix', type='string', default='combined',
    help='Saves the result as the first uCalResults.npz file, but with .npz replaced by .[suffix].npz. Default "combined"')
opts,args = o.parse_args(sys.argv[1:])

if len(args) == 0:
    print "WARNING!!! No arguments provided. Using testing parameters."
    resultsFiles = ["./Data/" + file for file in os.listdir("./Data") if file.startswith('zen.2456679.3') and file.endswith('xx.uCalResults.npz')]
else: resultsFiles = args

#%% Combine per-integration results
allSourceFiles, allBandpasses, meanBandpass, stdBandpass, unflaggedChans, channelRMSs, overallChannelRMS, bandpassFit = uc.from_npz(resultsFiles[0])
for file in resultsFiles[1:]:
    sourceFiles, allBP, _, _, unflagged, RMSs, _, _ = uc.from_npz(file)
    for source in sourceFiles: allSourceFiles = np.append(allSourceFiles,source)
    allBandpasses = np.concatenate((allBandpasses,allBP))
    unflaggedChans = np.concatenate((unflaggedChans,unflagged))
    channelRMSs = np.concatenate((channelRMSs,RMSs))

#%% Recompute Summary Results
meanBandpass = np.mean(np.ma.masked_equal(allBandpasses,0),axis=0).data
stdBandpass = np.std(np.abs(np.ma.masked_invalid(np.ma.masked_equal(allBandpasses,0))),axis=0).data
overallChannelRMS = np.mean(np.ma.masked_invalid(np.ma.masked_equal(channelRMSs,0))**2,axis=0).data ** .5

#%% Perform Fit
bandpassFit = None
if not opts.nofit:
Пример #2
0
    'Saves the result as the first uCalResults.npz file, but with .npz replaced by .[suffix].npz. Default "combined"'
)
opts, args = o.parse_args(sys.argv[1:])

if len(args) == 0:
    print "WARNING!!! No arguments provided. Using testing parameters."
    resultsFiles = [
        "./Data/" + file for file in os.listdir("./Data")
        if file.startswith('zen.2456679.3')
        and file.endswith('xx.uCalResults.npz')
    ]
else:
    resultsFiles = args

#%% Combine per-integration results
allSourceFiles, allBandpasses, meanBandpass, stdBandpass, unflaggedChans, channelRMSs, overallChannelRMS, bandpassFit = uc.from_npz(
    resultsFiles[0])
for file in resultsFiles[1:]:
    sourceFiles, allBP, _, _, unflagged, RMSs, _, _ = uc.from_npz(file)
    for source in sourceFiles:
        allSourceFiles = np.append(allSourceFiles, source)
    allBandpasses = np.concatenate((allBandpasses, allBP))
    unflaggedChans = np.concatenate((unflaggedChans, unflagged))
    channelRMSs = np.concatenate((channelRMSs, RMSs))

#%% Recompute Summary Results
meanBandpass = np.mean(np.ma.masked_equal(allBandpasses, 0), axis=0).data
stdBandpass = np.std(np.abs(
    np.ma.masked_invalid(np.ma.masked_equal(allBandpasses, 0))),
                     axis=0).data
overallChannelRMS = np.mean(np.ma.masked_invalid(
    np.ma.masked_equal(channelRMSs, 0))**2,
Пример #3
0
#! /usr/bin/env python

import numpy as np
import matplotlib.pyplot as plt
import optparse, sys, os
import capo.uCal as uc

o = optparse.OptionParser()
o.set_usage('plot_uCal_result.py [.uCalResults.npz file]')
opts,args = o.parse_args(sys.argv[1:])
if len(args) == 0:
    print "WARNING!!! No arguments provided. Using testing parameters."
    resultsFile = './Data/zen.2456679.49577.xx.uCalResults.npz'
else: resultsFile = args[0]

dataFiles, allBandpasses, meanBandpass, stdBandpass, unflaggedChans, channelRMSs, overallChannelRMS, bandpassFit = uc.from_npz(resultsFile)

allUnflaggedChans = sorted(np.unique([item for sublist in unflaggedChans for item in sublist]))

#%% Plot bandpass
plt.figure(1); plt.clf()
for chans, bandpass in zip(unflaggedChans, allBandpasses):
    plt.plot(chans, np.abs(bandpass)[chans],':')
plt.errorbar(allUnflaggedChans,np.abs(meanBandpass)[allUnflaggedChans],yerr=np.abs(stdBandpass)[allUnflaggedChans], fmt='k')
plt.xlabel('channel'); plt.ylabel('abs(Bandpass)')

#%% Plot phase
plt.figure(2); plt.clf()
for chans, bandpass in zip(unflaggedChans, allBandpasses):
    plt.plot(chans, np.angle(bandpass)[chans],':')
plt.plot(allUnflaggedChans, np.angle(meanBandpass)[allUnflaggedChans],'k')