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')
