from SSINS import SS from SSINS import Catalog_Plot as cp import numpy as np inpath = '/Volumes/Faramir/uvfits' obslist = ['1061313128', '1061312640', '1066742016'] outpath = '/Users/mikewilensky/General/Hist_Compare_Big_Legend' read_kwargs = {'ant_str': 'cross'} for obs in obslist: ss = SS(inpath='%s/%s.uvfits' % (inpath, obs), obs=obs, outpath=outpath, read_kwargs=read_kwargs, bad_time_indices=[0, -1, -2, -3]) ss.VDH_prepare(fit_hist=True, bins='auto') ss.VDH.errors[0] *= 4 cp.VDH_plot(ss.VDH, leg_size='xx-large', xscale='linear', ylim=[0.1, 10 * np.amax(ss.VDH.counts[0])]) del ss
from SSINS import SS, INS import numpy as np import scipy.stats import matplotlib.pyplot as plt ss = SS(obs='1061312272', outpath='/Users/mike_e_dubs/576', inpath='/Users/mike_e_dubs/MWA/Data/uvfits/1061313128.uvfits', bad_time_indices=[0, -1, -2, -3], read_kwargs={'ant_str': 'cross'}) ss.VDH_prepare(bins='auto', fit_hist=True) N = ss.UV.data_array.size bins = ss.VDH.bins[0] centers = bins[:-1] + 0.5 * np.diff(bins) mu = np.mean(ss.UV.data_array) var = np.var(ss.UV.data_array) r_scale = np.sqrt(0.5 * np.mean(ss.UV.data_array**2)) norm = scipy.stats.norm rayleigh = scipy.stats.rayleigh gauss_fit = N * (norm.cdf(bins[1:], loc=mu, scale=np.sqrt(var)) - norm.cdf(bins[:-1], loc=mu, scale=np.sqrt(var))) rayleigh_fit = N * (rayleigh.cdf(bins[1:], scale=r_scale) - rayleigh.cdf(bins[:-1], scale=r_scale)) fig, ax = plt.subplots(figsize=(14, 8)) ax.plot(centers, ss.VDH.counts[0], drawstyle='steps-mid', label='Background') ax.errorbar(centers, ss.VDH.fits[0], yerr=3 * ss.VDH.errors[0], drawstyle='steps-mid', label='Rayleigh Mixture Fit')
UV6.phase(5.03706309897,.598912483314) for x in inpath5: UVtemp.read(x, ant_str = 'cross') UVtemp.object_name = 'same' if not UVtemp.phase_center_dec == .598912483314 or not UVtemp.phase_center_ra == 5.03706309897: UVtemp.unphase_to_drift() UVtemp.phase(5.03706309897,.598912483314) UV6 = UV6 + UVtemp UV = UV2 + UV3 + UV4 + UV5 + UV6 print UV.Nbls print UV.Ntimes print UV.Nblts print 'the buck stop here' ss = SS(obs=obs, outpath=outpath, UV = UV, diff= True) ss.INS_prepare() print 'Marker 1' ss.VDH_prepare() print 'Marker 2' ss.INS.save() ss.VDH.save() cp.INS_plot(ss.INS, ms_vmax=5, ms_vmin=-5) print 'Marker 3' cp.VDH_plot(ss.VDH, xscale = 'linear')