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fixed typo, saved plots

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Sakimori 2025-08-05 11:21:15 -04:00
parent 54c128b45f
commit b09a1a9fbb
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1 changed files with 8 additions and 8 deletions
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testanalysis.py
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@ -99,7 +99,9 @@ detections = detections.reset_index(drop=True)
summary(3) summary(3)
postFilterCount = len(detections['dm']) postFilterCount = len(detections['dm'])
logger.info(f"Removed {preFilterCount-postFilterCount} detections by filtering.") logger.info(f"Removed {preFilterCount-postFilterCount} detections by filtering the following:")
for file in remFiles:
logger.info(file+"_injected.fil")
#Let's do detection matching! Yaaaay! #Let's do detection matching! Yaaaay!
#What detections line up to which injections? This will determine which ones got missed entirely. #What detections line up to which injections? This will determine which ones got missed entirely.
@ -149,6 +151,7 @@ logger.info(f"Successful detection ratio: {Counter(matchMaskInj)[True]/(len(inje
#Let's try to figure out if certain files are responsible for the weird amount of false #Let's try to figure out if certain files are responsible for the weird amount of false
#positives at around 10^2.7 pc/cc #positives at around 10^2.7 pc/cc
#IT WAS 5 FILES. Filtered out above.
fpFileCounts = Counter(detections[falsePositiveMask]['file']) fpFileCounts = Counter(detections[falsePositiveMask]['file'])
sortedFPCounts = [(k, v) for k,v in sorted(fpFileCounts.items(), key=lambda value: -value[1])] sortedFPCounts = [(k, v) for k,v in sorted(fpFileCounts.items(), key=lambda value: -value[1])]
@ -198,7 +201,7 @@ ax.hist([np.log10(injections['dm'][matchMaskInj]), np.log10(injections['dm'][mis
stacked=True, label=['Detected', 'Missed'], bins=15) stacked=True, label=['Detected', 'Missed'], bins=15)
ax.yaxis.get_major_locator().set_params(integer=True) ax.yaxis.get_major_locator().set_params(integer=True)
ax.legend(loc='upper center') ax.legend(loc='upper center')
ax.set_xlabel(r"DM (log pc cm$^3$)") ax.set_xlabel(r"DM (log pc cm$^{-3}$)")
ax.tick_params(labelbottom=True) ax.tick_params(labelbottom=True)
ax2 = plt.subplot(17,1,(9,16)) ax2 = plt.subplot(17,1,(9,16))
ax2.hist([np.log10(injections['pulseWidth'][matchMaskInj]), np.log10(injections['pulseWidth'][missedMask])], ax2.hist([np.log10(injections['pulseWidth'][matchMaskInj]), np.log10(injections['pulseWidth'][missedMask])],
@ -210,7 +213,7 @@ plt.title("Injected pulses")
wordAx = plt.subplot(17,1,17) wordAx = plt.subplot(17,1,17)
wordAx.text(.3,.5,f"Overall detection rate: {round(Counter(matchMaskInj)[True]/(len(injections['dm']))*100,1)}%", size=14) wordAx.text(.3,.5,f"Overall detection rate: {round(Counter(matchMaskInj)[True]/(len(injections['dm']))*100,1)}%", size=14)
wordAx.set_axis_off() wordAx.set_axis_off()
plt.draw() plt.savefig(os.path.join("out","injections.png"))
#Stacked histogram of detections #Stacked histogram of detections
plt.figure(figsize=(7,10)) plt.figure(figsize=(7,10))
@ -218,7 +221,7 @@ ax = plt.subplot(17,1,(1,8))
ax.hist([np.log10(detections['dm'][matchMaskDet]), np.log10(detections['dm'][falsePositiveMask])], ax.hist([np.log10(detections['dm'][matchMaskDet]), np.log10(detections['dm'][falsePositiveMask])],
stacked=True, label=['True detection', 'False positive'], bins=15) stacked=True, label=['True detection', 'False positive'], bins=15)
ax.yaxis.get_major_locator().set_params(integer=True) ax.yaxis.get_major_locator().set_params(integer=True)
ax.set_xlabel(r"DM (log pc cm$^3$)") ax.set_xlabel(r"DM (log pc cm$^{-3}$)")
ax.legend(loc='upper center') ax.legend(loc='upper center')
ax2 = plt.subplot(17,1,(9,16)) ax2 = plt.subplot(17,1,(9,16))
ax2.hist([np.log10(detections['pulseWidth'][matchMaskDet]), np.log10(detections['pulseWidth'][falsePositiveMask])], ax2.hist([np.log10(detections['pulseWidth'][matchMaskDet]), np.log10(detections['pulseWidth'][falsePositiveMask])],
@ -230,7 +233,4 @@ plt.title("Detections")
wordAx = plt.subplot(17,1,17) wordAx = plt.subplot(17,1,17)
wordAx.text(.3,.5,f"False positive rate: {round(Counter(falsePositiveMask)[True]/(len(detections['dm']))*100,1)}%", size=14) wordAx.text(.3,.5,f"False positive rate: {round(Counter(falsePositiveMask)[True]/(len(detections['dm']))*100,1)}%", size=14)
wordAx.set_axis_off() wordAx.set_axis_off()
plt.draw() plt.savefig(os.path.join("out","detections.png"))
#block end of script
plt.show()