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Revert "multiprocessing for deccam" #28

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Dec 9, 2024
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Revert "multiprocessing for deccam" #28

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108 changes: 26 additions & 82 deletions astrosource/analyse.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
from tqdm import tqdm
#import traceback
import logging
from multiprocessing import Pool

#from astrosource.utils import photometry_files_to_array, AstrosourceException
from astrosource.utils import AstrosourceException
Expand Down Expand Up @@ -56,56 +55,6 @@ def get_total_counts(photFileArray, compFile, loopLength, photCoords):
#logger.debug(allCountsArray)
return allCountsArray

def process_varsearch_target(target, photFileArray, allCountsArray, matchRadius, minimumNoOfObs):
diffMagHolder = []

for allcountscount, photFile in enumerate(photFileArray):
# Efficiently calculate the closest match using numpy
idx = (np.abs(photFile[:, 0] - target[0]) + np.abs(photFile[:, 1] - target[1])).argmin()
d2d = np.sqrt((photFile[idx, 0] - target[0])**2 + (photFile[idx, 1] - target[1])**2) * 3600
multTemp = -2.5 * np.log10(photFile[idx, 11] / allCountsArray[allcountscount][0])

if d2d < matchRadius and not np.isinf(multTemp):
diffMagHolder.append(multTemp)

# Remove major outliers
diffMagHolder = np.array(diffMagHolder)
while True:
stdVar = np.std(diffMagHolder)
avgVar = np.mean(diffMagHolder)
sizeBefore = diffMagHolder.size

# Mask outliers
mask = (diffMagHolder <= avgVar + 4 * stdVar) & (diffMagHolder >= avgVar - 4 * stdVar)
diffMagHolder = diffMagHolder[mask]

if diffMagHolder.size == sizeBefore:
break

# Append to output if sufficient observations are available
if diffMagHolder.size > minimumNoOfObs:
return [target[0], target[1], np.median(diffMagHolder), np.std(diffMagHolder), diffMagHolder.size]
return None


def process_varsearch_targets_multiprocessing(targetFile, photFileArray, allCountsArray, matchRadius, minimumNoOfObs):
# Partial function to pass shared arguments
from functools import partial
worker = partial(
process_varsearch_target,
photFileArray=photFileArray,
allCountsArray=allCountsArray,
matchRadius=matchRadius,
minimumNoOfObs=minimumNoOfObs,
)

# Multiprocessing with Pool
with Pool() as pool:
results = pool.map(worker, targetFile)

# Filter out None results
return [res for res in results if res is not None]

def find_variable_stars(targets, matchRadius, errorReject=0.05, parentPath=None, varsearchglobalstdev=-99.9, varsearchthresh=10000, varsearchstdev=2.0, varsearchmagwidth=0.25, varsearchminimages=0.3, photCoords=None, photFileHolder=None, fileList=None):
'''
Find stable comparison stars for the target photometry and remove variables
Expand Down Expand Up @@ -175,44 +124,39 @@ def find_variable_stars(targets, matchRadius, errorReject=0.05, parentPath=None,
logger.info("Measuring variability of stars...... ")
taketime=time.time()

# for target in targetFile:
# diffMagHolder=[]
# allcountscount=0
for target in targetFile:
diffMagHolder=[]
allcountscount=0


# for photFile in photFileArray:
# # A bit rougher than using SkyCoord, but way faster
# # The amount of calculations is too slow for SkyCoord
# idx=(np.abs(photFile[:,0] - target[0]) + np.abs(photFile[:,1] - target[1])).argmin()
# d2d=pow(pow(photFile[idx,0] - target[0],2) + pow(photFile[idx,1] - target[1],2),0.5) * 3600
# multTemp=(multiply(-2.5,log10(divide(photFile[idx][11],allCountsArray[allcountscount][0]))))
# if less(d2d, matchRadius) and (multTemp != inf) :
# diffMagHolder=append(diffMagHolder,multTemp)
# allcountscount=add(allcountscount,1)
for photFile in photFileArray:
# A bit rougher than using SkyCoord, but way faster
# The amount of calculations is too slow for SkyCoord
idx=(np.abs(photFile[:,0] - target[0]) + np.abs(photFile[:,1] - target[1])).argmin()
d2d=pow(pow(photFile[idx,0] - target[0],2) + pow(photFile[idx,1] - target[1],2),0.5) * 3600
multTemp=(multiply(-2.5,log10(divide(photFile[idx][11],allCountsArray[allcountscount][0]))))
if less(d2d, matchRadius) and (multTemp != inf) :
diffMagHolder=append(diffMagHolder,multTemp)
allcountscount=add(allcountscount,1)

# ## REMOVE MAJOR OUTLIERS FROM CONSIDERATION
# diffMagHolder=np.array(diffMagHolder)
# while True:
# stdVar=std(diffMagHolder)
# avgVar=average(diffMagHolder)
## REMOVE MAJOR OUTLIERS FROM CONSIDERATION
diffMagHolder=np.array(diffMagHolder)
while True:
stdVar=std(diffMagHolder)
avgVar=average(diffMagHolder)

# sizeBefore=diffMagHolder.shape[0]
# #print (sizeBefore)
sizeBefore=diffMagHolder.shape[0]
#print (sizeBefore)

# diffMagHolder[diffMagHolder > avgVar+(4*stdVar) ] = np.nan
# diffMagHolder[diffMagHolder < avgVar-(4*stdVar) ] = np.nan
# diffMagHolder=diffMagHolder[~np.isnan(diffMagHolder)]
diffMagHolder[diffMagHolder > avgVar+(4*stdVar) ] = np.nan
diffMagHolder[diffMagHolder < avgVar-(4*stdVar) ] = np.nan
diffMagHolder=diffMagHolder[~np.isnan(diffMagHolder)]

# if diffMagHolder.shape[0] == sizeBefore:
# break

# if (diffMagHolder.shape[0] > minimumNoOfObs):
# outputVariableHolder.append( [target[0],target[1],median(diffMagHolder), std(diffMagHolder), diffMagHolder.shape[0]])
if diffMagHolder.shape[0] == sizeBefore:
break

# process_varsearch_target
outputVariableHolder = process_varsearch_targets_multiprocessing(
targetFile, photFileArray, allCountsArray, matchRadius, minimumNoOfObs
)
if (diffMagHolder.shape[0] > minimumNoOfObs):
outputVariableHolder.append( [target[0],target[1],median(diffMagHolder), std(diffMagHolder), diffMagHolder.shape[0]])

print ("Star Variability done in " + str(time.time()-taketime))

Expand Down
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