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RyotaInagaki1RyotaInagaki1
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Reformatting
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‎.travis.yml‎

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@@ -17,8 +17,9 @@ addons:
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packages:
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- graphviz
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stages:
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script:
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- echo "skipping tests. This is a draft of code I want Professor Lu and Matt to take a look at.
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stages:
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# Do the style check and a single test job, don't proceed if it fails
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- name: Initial tests
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# Test docs, astropy dev, and without optional dependencies

‎IsochroneMakerReformatted.py‎

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import numpy as np
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import pandas as pd
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from astropy.io import fits
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from astropy.table import Table
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import os
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import hoki
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from hoki import load
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import glob
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import re
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"""Source: https://stackoverflow.com/questions/44369504/
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how-to-convert-entire-dataframe-values-to-float-in-pandas"""
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colsToElim = [x for x in range(96) if x not in [hoki.dummy_dict[y]
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for y in hoki.dummy_dict.keys()]]
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def merger_related(f):
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# Code that eventually returns whether
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# The given model (in form of dataframe)
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# has the conditions necessary
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# to be a merger model.
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return False
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def find_mergers(f):
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# returns when the merger occurs (first time)
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# assuming that f is a merger model.
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return False
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def reformatter(bevo_dir):
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"""I will expedite the process of writing and saving files by
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making the BPASS stellar input files binary fits tables This method
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creates a reformatted FITS version of
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all of the available BPASS data so that data can be loaded quickly
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and processed in the extractor method."""
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# The list of possible BPASS metallicities.
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# HMG stands for Qasi-Chemically Homogeneous Evolution Models.
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metallicities=["zem5", "zem4", "z001", "z002", "z003", "z004", "z006", "z008",
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"z010", "z014","z020","z030", "z040", "zem5_hmg",
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"zem4_hmg", "z001_hmg", "z002_hmg", "z003_hmg", "z004_hmg"]
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# I will use the Python HashSet since (assuming that strings
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# have a good HashCode, adding to the HashSet should be fast
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setofAll = set()
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for x in metallicity:
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a = set(glob.glob(hoki.MODELS_PATH + "/NEWSINMODS/" + x + "/*"))
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b = set(glob.glob(hoki.MODELS_PATH + "/NEWBINMODS/NEWBINMODS/" + x + "/*"))
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c = set(glob.glob(hoki.MODELS_PATH + "/NEWBINMODS/NEWSECMODS/" + x + "_2/*"))
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setofAll = setofAll.union(a, b, c)
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for x in setofAll:
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f = pd.read_csv(hoki.MODELS_PATH + x, sep = "\s+",
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header = None)
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f.apply(pd.to_numeric, errors = 'coerce')
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f.transpose()
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# Drop all of the columns that are not defined by the
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# HOKI package provided mapping of column name to
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# column number.
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f.drop(columns = [f.columns[x] for x in colsToElim],
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inplace = True)
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# Source: https://stackoverflow.com/questions/483666/
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# reverse-invert-a-dictionary-mapping
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# I create a mapping from column NUMBER to
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# column name
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invmap = {u: v for v, u in hoki.dummy_dict.items()}
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f.rename(columns = invmap, inplace = True)
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f["model_type"] = [typ] * len(f.index)
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astroTable = Table.from_pandas(f)
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# We will be recalculating the photometry related stuff
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# when we create the isochrone.
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# Will remove photometry related columns
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astroTable.remove_columns(['V-I', 'U',
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'B', 'V', 'R', 'I', 'J', 'H', 'K','u',
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'g', 'r', 'i', 'z', 'f300w', 'f336w',
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'f435w', 'f450w', 'f555w', 'f606w','f814w',
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'U2', 'B2', 'V2','R2', 'I2','J2','H2','K2',
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'u2','g2','r2','i2','z2','f300w2','f336w2',
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'f435w2','f450w2','f555w2','f606w2','f814w2',
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'Halpha','FUV','NUV'])
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# Merger Related indicates whether the star is
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# a model with a merger in it.
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astroTable['Merger_Related'] = [False] * len(astroTable)
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# Creates container directory for stellar models grouped by metallicity
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# and whether they are single or binary related
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# the latter included mergers, QHE Models
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if not os.path.isdir(bevo_dir + "iso/" + metallicity + '/' +
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"sin" +
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"/"):
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os.makedirs(bevo_dir +
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'iso/' + metallicity +
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"/" + SinOrBin + "/")
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if not os.path.isdir(bevo_dir + "iso/" + metallicity + '/' +
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"bin" +
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"/"):
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os.makedirs(bevo_dir +
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'iso/' + metallicity +
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"/" + "bin" + "/")
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# Single star models that are not the hmg models go into the <Metallicity>/sin
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# directory.
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if (x[0:10] == 'NEWSINMODS' and
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not re.matches(r"NEWSINMODS/z[0-9]+_hmg/.*")):
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astroTable.write(bevo_dir + 'iso/' + met + '/' +
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"sin" + "/" + "FitsModels" +
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x[16:] + ".fits", format='fits',
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overwrite=True)
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print(x[16:] + ".fits")
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else:
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# Models that count as secondary star with compact remnants
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# go into the <metallicity>/bin subdirectory of iso.
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if (x[11:21] == 'NEWSECMODS'):
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astroTable.write(bevo_dir + 'iso/' + met + '/' +
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"bin" + "/" + "FitsModels" +
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x[29:] + "sec.fits", format='fits',
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overwrite = True)
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print(bevo_dir + 'iso/' + metallicity + '/' +
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SinOrBin + "/" + "FitsModels" +
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x[29:] +"sec.fits")
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else:
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# Check for merger related (models_type=0) models
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# and mark them.
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if (find_mergers(astroTable)):
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astroTable['Merger_Related'] = [True] * len(astroTable)
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# Models that count as secondary star with compact remnants
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# go into the <metallicity>/bin subdirectory of iso.
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astroTable.write(bevo_dir + 'iso/' + metallicity + '/' +
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"bin" + "/" + "FitsModels" +
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x[27:] + "bin.fits", format='fits',
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overwrite = True)
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print(x[27:] + ".fits")
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except FileNotFoundError:
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print("File not Readable/Found")
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notFound.append(x)
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#The following is commented out since I have yet to delete this version yet.
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""" still_to_do=set()
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if (x=="zem5" or x=="zem4" or x=="z001" or x=="z002" or x=="z003" or x=="z004"):
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c=set(c).union(set(glob.glob(hoki.MODELS_PATH+"/NEWSINMODS/"+x+"hmg"+"/*")))
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still_to_do=still_to_do.union(a, b, c)
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still_to_do=still_to_do.difference(included)
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lenModPath=len(HOKI.MODELS_PATH)
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for x in still_to_do:
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try:
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f = pd.read_csv(x, sep="\s+",
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header=None)
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f.apply(pd.to_numeric, errors='coerce')
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f.transpose()
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f.drop(columns=[f.columns[x] for x in colsToElim], inplace=True)
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included.add(hoki.MODELS_PATH+x)
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# Source: https://stackoverflow.com/questions/483666/
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# reverse-invert-a-dictionary-mapping
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invmap = {u: v for v, u in hoki.dummy_dict.items()}
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f.rename(columns=invmap, inplace=True)
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f["model_type"]=[typ]*len(f.index)
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astroTable = Table.from_pandas(f)
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astroTable.remove_columns(['?','modelimf','mixedimf', 'V-I', 'U',
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'B', 'V', 'R', 'I', 'J', 'H', 'K','u',
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'g', 'r', 'i', 'z', 'f300w', 'f336w',
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'f435w', 'f450w', 'f555w', 'f606w','f814w',
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'U2', 'B2', 'V2','R2', 'I2','J2','H2','K2',
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'u2','g2','r2','i2','z2','f300w2','f336w2',
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'f435w2','f450w2','f555w2','f606w2','f814w2',
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'Halpha','FUV','NUV'])
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if not os.path.isdir(bevo_dir + "iso/" + metallicity + '/' +
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SinOrBin + "/"):
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os.makedirs(bevo_dir + 'iso/' + metallicity +
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"/" + SinOrBin + "/")
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if (x[lenModPath+0:lenModPath+10]=='NEWSINMODS'):
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nameMatcher=re.match(re".*/NEWSINMODS/[a-z0-9]+hmg/.*")
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if (bool(nameMatcher)):
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astroTable["model_type"]=[4]*len(astroTable)
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else:
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astroTable["model_type"]=[-12]*len(astroTable)
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astroTable.write(bevo_dir + 'iso/' + met + '/' +
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SinOrBin + "/" + "FitsModels" +
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x[lenModPath+16:] + ".fits", format='fits',
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overwrite=True)
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print(x[lenModPath+16:]+".fits")
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else:
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print(x[lenModPath+11:lenModPath+21])
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if (x[lenModPath+11:lenModPath+21]=='NEWSECMODS'):
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astroTable.write(bevo_dir + 'iso/' + met + '/' +
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SinOrBin + "/" + "FitsModels" +
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x[lenModPath+29:] + "sec.fits", format='fits',
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overwrite=True)
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print(bevo_dir + 'iso/' + metallicity + '/' +
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SinOrBin + "/" + "FitsModels" +
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x[lenModPath+29:] +"sec.fits")
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# Added designation for secondary models that can be
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# either regular or single star
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astroTable["model_type"]=[-15]*len(astroTable)
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else:
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astroTable.write(bevo_dir + 'iso/' + metallicity + '/' + SinOrBin +
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"/" + "FitsModels" +
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x[lenModPath+27:] +"bin.fits", format='fits',
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overwrite=True)
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# Added designation for secondary models that can be
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# either regular or single star
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astroTable["model_type"]=[-10]*len(f.index)
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print(x[lenModPath+27:] + ".fits")
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"""
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except FileNotFoundError:
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print("File not Readable/Found")
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notFound.append(x)
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""" The follwing method takes in the reformatted stellar model files listed in
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the corresponding model-metallicity's cluster input files originally meant
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for color magnitude diagram makers. This is suppoesed to create the isochrone
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files out of which BPASS creates its isochrone objects. For each stellar model
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file, we try to find the row in the stellar model representing a model with the
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age closest to the inputted age and is within the specified margin error for
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log(age in years). Then that row is concattenated with other similar rows from
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different stellar model files to create the isochrone table. The age closest
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method may get rid of some data but is meant to improve accuracy of the age of the
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stellar model and improve computational efficiency to some extent."""
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def extractor(SinOrBin, model, age, metallicity, input_dir, bpass_evo_dir,
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margin):
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entries = glob.glob(input_dir + "/*")
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print(len(entries))
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stopLen = 4
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bigOne = None;
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initlMass = np.nan
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initlMass2 = np.nan
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for x in entries:
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if x[0] != '.' and not os.path.isdir(x):
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# To Obtain initial mass I will use Regex
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# to extract the initial mass of a model.
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try:
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org = Table.read(x, format = 'fits')
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org = org.to_pandas()
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starIndex = "Not Applicable"
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if (x[-8:-5] == 'bin' and org['model_type'][0] == 0):
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starIndex = findLastRelMax(org)
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f = org[np.where(np.abs(np.log10(org['age'])-age) <= margin)[0]]
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if (len(f) != 0):
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f=f[np.where(np.abs(f['age'] - 10 ** age) ==
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np.min(np.abs(f['age'] - 10 ** age)))[0]]
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if len(f) != 0:
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index = f.index
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indexlen = len(index)
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if initial:
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initial = False
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bigOne = f
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# mass and mass2 stand for the initial masses
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# of the primary and secondary respectively.
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bigOne['mass'] = [initlMass] * indexlen
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bigOne['mass2'] = [initlMass2] * indexlen
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bigOne['single'] = [True] * indexlen
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bigOne['mergered?'] = [False] * indexlen
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if (x[-8:-5] == 'bin' or x[-8:-5] == 'sec'):
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bigOne['single'] = [False] * indexlen
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# I only need to check one row since
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# whether a model is a merger model
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# is the same for all rows of the model
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if bigOne['Merger_Related'][0]:
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# Find the row in which the model merges.
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# Note that I pass in the original grid.
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merge_pt = find_mergers(org)
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bigOne['mergered?'] = [x>merge for x in bigOne.index]
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print(bigOne.shape)
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else:
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f['mass'] = [initlMass] * indexlen
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f['mass2'] = [initlMass2] * indexlen
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f['single'] = [True] * indexlen
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f['Merger Related']=[False] * indexlen
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if (x[-8:-5] == 'bin'):
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f['single'] = [False] * indexlen
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if bigOne['Merger_Related'][0]:
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merge_pt = find_mergers(org)
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bigOne['mergered?'] = [x > merge for x
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in bigOne.index]
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bigOne = pd.concat([f, bigOne], axis = 0)
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print(bigOne.shape)
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except FileNotFoundError:
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print('File Not Found/Readable')
283+
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try:
285+
if not isinstance(bigOne, type(None)) and not (bigOne['age'].empty):
286+
bigOne = bigOne.apply(pd.to_numeric, errors = 'coerce')
287+
reduced = Table.from_pandas(bigOne)
288+
if not os.path.isdir(bpass_evo_dir +
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'iso/' + model + '/' + metallicity + '/'):
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os.makedirs(bpass_evo_dir +
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'iso/'+ model + '/' + metallicity + '/')
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print(reduced.columns)
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reduced.write(bpass_evo_dir + 'iso/' + model+"/" + metallicity +
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'/' + 'iso' + str(age) + SinOrBin +
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'.fits', format = 'fits', overwrite = True)
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print(bigOne.shape)
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except IndexError:
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print ('It looks like there are no stars in out input file' +
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' that have the specified age...')

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