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valid_table: PEP8 fixes and documentation (#13)
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@astrochun
astrochun committed Mar 26, 2020
1 parent c42be36 commit a564367
Showing 1 changed file with 78 additions and 74 deletions.
152 changes: 78 additions & 74 deletions Metallicity_Stack_Commons/valid_table.py
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Original file line number Diff line number Diff line change
@@ -1,41 +1,40 @@
from os.path import exists
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
from astropy.io import ascii as asc
from astropy.table import Table, Column

from Metallicity_Stack_Commons.column_names import filename_dict, bin_names0, remove_from_list
from Metallicity_Stack_Commons.column_names import filename_dict, valid_table_names0 # , bin_names0, remove_from_list


def make_validation_table(fitspath):
'''
Purpose:
"""
Purpose:
This function creates a validation table for a given binning set. The validation table
contains a OIII4363 detection column where 1.0 means detection, 0.5 means non-detection with
reliable OIII5007, and 0.0 means unreliable non-detection.
This function will be run every time the analysis is completed and will create a validation
table for every analysis.
This function will be run every time the analysis is completed and will create a validation
table for every analysis.
Usage:
valid_table.make_validation_table(fitspath, bin_type_str)
Params:
fitspath --> a string of the file path where the input file is and where the output file
will be placed.
not in use:
bin_type_str --> a string describing the binning type. (e.g. 'massLHbetabin' or 'massbin')
not in use:
bin_type_str --> a string describing the binning type. (e.g. 'massLHbetabin' or 'massbin')
--> This is dataset for Zcalbase_gal analysis
Returns:
Returns:
None
Outputs:
fitspath + 'bin_validation.tbl' --> a validation table containing bin IDs;
number of galaxies in each bin; and
number of galaxies in each bin; and
column indicating OIII4363 detection/non-detection
OIII4363_Flux_Observed
OIII4363_S/N
'''
"""

bin_table = asc.read(fitspath + filename_dict['bin_info'])
em_table = asc.read(fitspath + filename_dict['bin_fit'])
Expand All @@ -47,13 +46,12 @@ def make_validation_table(fitspath):
O_5007_SN = em_table['OIII_5007_S/N'].data

N_stack = bin_table['N_stack'].data
Hgamma_SN = em_table['HGAMMA_S/N'].data
Hgamma_SN = em_table['HGAMMA_S/N'].data
Hgamma = em_table['HGAMMA_Flux_Observed'].data

detection = np.zeros(len(bin_ID))
OIII4363 = np.zeros(len(bin_ID))
up_limit = (Hgamma/Hgamma_SN) *3

up_limit = (Hgamma/Hgamma_SN) * 3

valid_stacks_idx = np.where((O_4363_SN >= 3) & (O_5007_SN > 100) & (O_4363_sigma < 1.6))[0]
reliable_5007_stacks = np.where((O_4363_SN < 3) & (O_5007_SN > 100))[0]
Expand All @@ -64,17 +62,15 @@ def make_validation_table(fitspath):
print(detection)

for ii in range(len(OIII4363)):

if detection[ii] == 1:
OIII4363[ii]= raw_OIII4363[ii]
if detection[ii] == 0.5:
OIII4363[ii]= up_limit[ii]
if detection[ii] ==0:
OIII4363[ii]= up_limit[ii]

ver_tab = fitspath+ filename_dict['bin_valid']
n =('bin_ID','N_stack','Detection', 'OIII_4363_Flux_Observed', 'OIII_4363_S/N')
tab1 = Table([bin_ID, N_stack, detection, OIII4363, O_4363_SN], names = valid_table_names0) #names=n)
if detection[ii] == 1:
OIII4363[ii] = raw_OIII4363[ii]
if detection[ii] == 0.5:
OIII4363[ii] = up_limit[ii]
if detection[ii] == 0:
OIII4363[ii] = up_limit[ii]

ver_tab = fitspath + filename_dict['bin_valid']
tab1 = Table([bin_ID, N_stack, detection, OIII4363, O_4363_SN], names=valid_table_names0)
asc.write(tab1, ver_tab, format='fixed_width_two_line')

# Write revised file for human editing
Expand All @@ -91,83 +87,91 @@ def make_validation_table(fitspath):
print(" ")


def compare_to_by_eye(fitspath,dataset):
'''
Purpose -> This function takes the automated validation table and checks it against
inputted measurement that are determined by eye. These inputted measurements
are in the np.where statements. It outputs a revised validation table based
on the inputted measurements.
def compare_to_by_eye(fitspath, dataset):
"""
Purpose -> This function takes the automated validation table and checks it against
inputted measurement that are determined by eye. These inputted measurements
are in the np.where statements. It outputs a revised validation table based
on the inputted measurements.
Usage -> valid_table.make_validation_table(fitspath, dataset)
Params:
fitspath --> a string of the file path where the input file is and where the output file
will be placed
dataset --> a string that is used to determine which eye measurements to use
Returns:
Returns:
None
Outputs:
fitspath + 'bin_validation_revised.tbl' and '.csv' -->
fitspath + 'bin_validation_revised.tbl' and '.csv' -->
a validation table containing bin IDs;
number of galaxies in each bin; and
number of galaxies in each bin; and
column indicating OIII4363 detection/non-detection
OIII4363_Flux_Observed
OIII4363_S/N
Notes
'''
ver_table = fitspath+ filename_dict['bin_valid']
"""
ver_table = fitspath + filename_dict['bin_valid']
ver_tab = asc.read(ver_table)
indicate = ver_tab['Detection']
ID = ver_tab['bin_ID']

#Detections By Eye
if dataset== 'Voronoi20': det_4363 = np.where((ID ==0)| (ID ==2)| (ID ==3) | (ID ==5) | (ID==6))[0]
if dataset== 'Voronoi14': det_4363 = np.where((ID ==0)| (ID ==7)| (ID ==10) | (ID ==11) | (ID==12))[0]
if dataset== 'Voronoi10': det_4363 = np.where((ID ==1)| (ID ==9)| (ID ==18) | (ID ==21))[0]
if dataset== 'Grid': det_4363 = np.where((ID ==11)| (ID ==13)| (ID ==19) | (ID ==20) | (ID == 21))[0]
if dataset== 'R23_Grid': det_4363 = np.where((ID ==0)| (ID ==4)| (ID ==5) | (ID ==6))[0]
if dataset== 'O32_Grid': det_4363 = np.where((ID ==6))[0]
if dataset== 'Double_Bin': det_4363 = np.where((ID ==0)| (ID ==1)| (ID ==2) | (ID ==7) | (ID ==9) | (ID ==10) | (ID ==11) | (ID ==13))[0]
if dataset== 'n_Bins':
det_4363= np.where( (ID ==10) | (ID ==11) |(ID==14) | (ID ==15) | (ID ==20) | (ID==23) | (ID ==26))[0]
rlimit = np.where( (ID ==5) | (ID ==7) |(ID==8) | (ID ==13) | (ID ==16) | (ID==17) | (ID ==19)| (ID ==22))[0]
# Detections By Eye
if dataset == 'Voronoi20':
det_4363 = np.where((ID == 0) | (ID == 2) | (ID == 3) | (ID == 5) | (ID == 6))[0]
if dataset == 'Voronoi14':
det_4363 = np.where((ID == 0) | (ID == 7) | (ID == 10) | (ID == 11) | (ID == 12))[0]
if dataset == 'Voronoi10':
det_4363 = np.where((ID == 1) | (ID == 9) | (ID == 18) | (ID == 21))[0]
if dataset == 'Grid':
det_4363 = np.where((ID == 11) | (ID == 13) | (ID == 19) | (ID == 20) | (ID == 21))[0]
if dataset == 'R23_Grid':
det_4363 = np.where((ID == 0) | (ID == 4) | (ID == 5) | (ID == 6))[0]
if dataset == 'O32_Grid':
det_4363 = np.where((ID == 6))[0]
if dataset == 'Double_Bin':
det_4363 = np.where((ID == 0) | (ID == 1) | (ID == 2) | (ID == 7) | (ID == 9) |
(ID == 10) | (ID == 11) | (ID == 13))[0]
if dataset == 'n_Bins':
det_4363 = np.where((ID == 10) | (ID == 11) | (ID == 14) | (ID == 15) | (ID == 20) |
(ID == 23) | (ID == 26))[0]
rlimit = np.where((ID == 5) | (ID == 7) | (ID == 8) | (ID == 13) | (ID == 16) |
(ID == 17) | (ID == 19) | (ID == 22))[0]

######Caroline: Add you conditions here#######
# Caroline: Add you conditions here

check_ID = np.zeros(len(ID))

check_ID[det_4363]=1
check_ID[rlimit] =0.5
check_ID[det_4363] = 1
if dataset == 'n_Bins':
check_ID[rlimit] = 0.5

for ii in range(len(ID)):
if check_ID[ii] == indicate[ii]:
print(ID[ii], 'matches with by eye validation')
else:
print('*****', ID[ii], 'does not match calculated values. Please check!')

###This is where I need to add the column for notes
# This is where I need to add the column for notes
if dataset == 'n_Bins':
notes = ['N/A','N/A','N/A','N/A','N/A',
'N/A','N/A','Broad features, but reliable OIII5007 and HGAMMA',
'Bad fit, but good OIII5007','N/A',
'N/A','N/A','N/A','N/A','N/A',
'High Temperature','not fit well, but reliable OIII5007 and HGAMMA',
'N/A','N/A','N/A','N/A','N/A','N/A','N/A','N/A','N/A','N/A']
note_add = Column(name='Notes', data = notes)
ver_tab.add_column(note_add,5)
notes = ['N/A', 'N/A', 'N/A', 'N/A', 'N/A',
'N/A', 'N/A', 'Broad features, but reliable OIII5007 and HGAMMA',
'Bad fit, but good OIII5007', 'N/A',
'N/A', 'N/A', 'N/A', 'N/A', 'N/A',
'High Temperature', 'not fit well, but reliable OIII5007 and HGAMMA',
'N/A', 'N/A', 'N/A', 'N/A', 'N/A', 'N/A', 'N/A', 'N/A', 'N/A', 'N/A']
note_add = Column(name='Notes', data=notes)
ver_tab.add_column(note_add, 5)

#######Caroline: Add your notes column here and copy the note_add and ver_tab.add_column lines to your if statement######
# Caroline: Add your notes column here and copy the note_add and ver_tab.add_column lines to your if statement


ver_tab.remove_column('Detection')

detect_add = Column(name='Detections', data =check_ID)
detect_add = Column(name='Detections', data=check_ID)
ver_tab.add_column(detect_add, 2)

asc.write(ver_tab, fitspath+ 'bin_validation_revised.tbl', format = 'fixed_width_two_line')
asc.write(ver_tab, fitspath+ 'bin_validation_revised.csv', format = 'csv')


asc.write(ver_tab, fitspath + 'bin_validation_revised.tbl', format='fixed_width_two_line')
asc.write(ver_tab, fitspath + 'bin_validation_revised.csv', format='csv')

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