''' reads a preprocessed catalog and computes tzav for it.
Writes a file with the numpy array
Written by: P. Gallardo.
'''
import numpy as np # noqa
from iskay import catalogTools # noqa
from iskay import pairwiser # noqa
#look in parent directory
df = catalogTools.preProcessedCat(directory='../ApPhotoResults').df
sigma_z = 0.01
dT = df.dT.values
z = df.z.values
tzav = pairwiser.get_tzav(dT, z, sigma_z)
np.savez('tzav_allCat', tzav)
from iskay import catalogTools
import matplotlib.pyplot as plt
from iskay import pairwiser
import numpy as np
import scipy.stats
fnames = [
"params_disjoint_bin_lum_gt_04p3_and_06p1_jk.ini",
"params_disjoint_bin_lum_gt_06p1_and_07p9_jk.ini",
"params_lum_gt_07p9_jk.ini"
]
for j in range(len(fnames)):
fname = fnames[j]
p = paramTools.params(fname)
df = catalogTools.preProcessedCat(howMany=None, query=p.CAT_QUERY).df
dT = df.dT.values
z = df.z.values
tzav = pairwiser.get_tzav_fast(dT, z, p.SIGMA_Z)
dT_ksz = dT - tzav
mean, std = np.mean(dT_ksz), np.std(dT_ksz)
plt.figure(figsize=[8, 4.5])
plt.hist(dT_ksz,
normed=True,
histtype='step',
color='black',
lw=2,
bins=200)
def test_preProcessedCat_howMany():
howMany = 14
directory = os.path.join(testPath, 'data_toTestAPI', 'ApPhotoResults')
pattern = 'testPreprocessedCat_*.csv'
df = catalogTools.preProcessedCat(pattern, directory, howMany=howMany).df
assert howMany == len(df.ra.values)
def test_preProcessedCat_sortBy():
sortby = 'ra'
directory = os.path.join(testPath, 'data_toTestAPI', 'ApPhotoResults')
pattern = 'testPreprocessedCat_*.csv'
df = catalogTools.preProcessedCat(pattern, directory, sortBy=sortby).df
assert (df.ra.values.max() == df.ra.values[0])
def test_preProcessedCat_query():
query = 'ra>20.0'
directory = os.path.join(testPath, 'data_toTestAPI', 'ApPhotoResults')
pattern = 'testPreprocessedCat_*.csv'
df = catalogTools.preProcessedCat(pattern, directory, query=query).df
assert np.all(df.ra.values > 20)
def test_preProcessedCat():
directory = os.path.join(testPath, 'data_toTestAPI', 'ApPhotoResults')
pattern = 'testPreprocessedCat_*.csv'
cat = catalogTools.preProcessedCat(pattern, directory)
assert len(cat.df) > 1