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%matplotlib inline
import localgroup
import triangle
import sklearn
from sklearn import mixture
import numpy as np
import pickle
import matplotlib.patches as mpatches
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import localgroup.timingargument as tm
from __future__ import division
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q_path = '/afs/slac.stanford.edu/u/ki/mwillia1/Thesis/LocalGroupHaloProps/Tr_Q_samp.pickle'
p_path = '/afs/slac.stanford.edu/u/ki/mwillia1/Thesis/LocalGroupHaloProps/Tr_P_samp.pickle'
pe_path = '/afs/slac.stanford.edu/u/ki/mwillia1/Thesis/LocalGroupHaloProps/Tr_PE_samp.pickle'
with open(q_path, 'rb') as f:
qsamp = pickle.load(f)
with open(p_path, 'rb') as f:
psamp = pickle.load(f)
with open(pe_path, 'rb') as f:
pesamp = pickle.load(f)
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qM, a, x, e = tm.mass(qsamp[:,0], qsamp[:,1])
pM, a, x, e = tm.mass(psamp[:,0], psamp[:,1])
peM, a, x, e = tm.mass(pesamp[:,0], pesamp[:,1])
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qgmm_LG = np.power(10,qsamp[:,11])
pgmm_LG = np.power(10,psamp[:,5])
pegmm_LG = np.power(10,pesamp[:,5])
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qA = qgmm_LG/qM
pA = pgmm_LG/pM
peA = pegmm_LG/peM
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qnorm = qsamp.shape[0]
pnorm = psamp.shape[0]
penorm = pesamp.shape[0]
qnorm, pnorm, penorm
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fig, ax = subplots(ncols=1, figsize=(9,6))
y, xed = np.histogram(qA, np.logspace(-1, 1, 20), weights=None)
ax.semilogx(np.sqrt(xed[1:]*xed[:-1]), y/qnorm, label='Quads', color='b')
y, xed = np.histogram(pA, np.logspace(-1, 1, 20), weights=None)
ax.semilogx(np.sqrt(xed[1:]*xed[:-1]), y/pnorm, label='Pairs', color='r')
y, xed = np.histogram(peA, np.logspace(-1, 1, 20), weights=None)
ax.semilogx(np.sqrt(xed[1:]*xed[:-1]), y/penorm, label='Pairs Existence', color='k')
ax.set_xlabel('$A_{vir}$', fontsize=30)
ax.tick_params(axis='y', labelsize=20)
ax.tick_params(axis='x', labelsize=20)
#ax.set_ylabel('fraction of systems', fontsize=16)
ax.legend(fontsize=20)
fig.savefig('/afs/slac.stanford.edu/u/ki/mwillia1/Thesis/LocalGroupHaloProps/timing_plot.pdf', dpi=600)
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l=ax.get_xticklabels()
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l[0]
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