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This update makes use of the original file names from the raw images for the count number for a direct way to relate the images together.
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@kjkoeller
kjkoeller committed Nov 11, 2022
1 parent b0ae2fb commit 68f4f34
Showing 1 changed file with 36 additions and 50 deletions.
86 changes: 36 additions & 50 deletions IRAF_Reduction.py
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Original file line number Diff line number Diff line change
@@ -1,26 +1,20 @@
"""
Author: Kyle Koeller
Created: 11/08/2022
Last Edited: 11/10/2022
Last Edited: 11/11/2022
This program is meant to automatically do the data reduction of the raw images from the
Ball State University Observatory (BSUO). The new calibrated images are placed into a new folder
"""

from pathlib import Path
# import os
import time

# from astropy.nddata import CCDData
from astropy.stats import mad_std
# from astropy.visualization import hist
from astropy import units as u
import ccdproc as ccdp
# import matplotlib.pyplot as plt
import numpy as np

from convenience_functions import show_image


def main():
"""
Expand All @@ -30,7 +24,8 @@ def main():
"""

# allows the user to input where the raw images are and where the calibrated images go to
path = input("Please enter a file path or folder name (if this code is in the same main folder) or type the word 'Close' to leave: ")
path = input(
"Please enter a file path or folder name (if this code is in the same main folder) or type the word 'Close' to leave: ")
if path.lower() == "close":
exit()
calibrated = input("Please enter a name for a new calibrated folder to not overwrite the original images: ")
Expand All @@ -49,13 +44,13 @@ def main():
break
else:
path = input("Please enter a file path or folder name (if this code is in the same main folder): ")
calibrated = input("Please enter a name for a new calibrated folder to not overwrite the original images: ")
calibrated = input("Please enter a name for a new calibrated folder to not overwrite the original images: ")

calibrated_data.mkdir(exist_ok=True)
rdnoise = 10.83 # gathered from fits headers manually
gain = 1.43 # gathered from fits headers manually
files = ccdp.ImageFileCollection(images_path)

zero = bias(files, calibrated_data)
master_dark = dark(files, zero, calibrated_data, rdnoise, gain)
flat(files, zero, master_dark, calibrated_data, rdnoise, gain)
Expand All @@ -69,23 +64,22 @@ def bias(files, calibrated_data):
:param calibrated_data: file location where the new images go
:return: the combined bias image
"""
count = 1
# raw_biases = files.files_filtered(include_path=True, imagetyp='BIAS')
for ccd, file_name in files.ccds(imagetyp='BIAS', ccd_kwargs={'unit': 'adu'}, return_fname=True):
# Just get the bias frames
# CCDData requires a unit for the image if
# it is not in the header # Provide the file name too.

# Subtract the overscan
ccd = ccdp.subtract_overscan(ccd, overscan=ccd[:, 13:2057], median=True)

# Trim the overscan
ccd = ccdp.trim_image(ccd[20:2065, 13:2057])

new_fname = "bias_osc_{}.fits".format(count)
list_of_words = file_name.split("-")

new_fname = "bias_osc_{}.fits".format(list_of_words[3])
# Save the result
ccd.write(calibrated_data / new_fname, overwrite=True)
count += 1

print("Finished overscan correcting bias frames.")
print()
Expand All @@ -98,7 +92,7 @@ def bias(files, calibrated_data):
minmax_clip=True, minmax_clip_min=0, minmax_clip_max=1,
sigma_clip=True, sigma_clip_low_thresh=3, sigma_clip_high_thresh=3,
sigma_clip_func=np.ma.median, signma_clip_dev_func=mad_std, mem_limit=450e6
)
)

combined_bias.meta['combined'] = True
combined_bias.write(calibrated_data / 'zero.fits', overwrite=True)
Expand All @@ -123,26 +117,25 @@ def dark(files, combined_bias, calibrated_path, rdnoise, gain):
print("Starting dark calibration.")
print()

# calibrating an combining the dark frames
count = 1
# calibrating a combining the dark frames
for ccd, file_name in files.ccds(imagetyp='DARK', ccd_kwargs={'unit': 'adu'}, return_fname=True):
# Just get the dark frames
# CCDData requires a unit for the image if
# it is not in the header # Provide the file name too.):

# Subtract the overscan
ccd = ccdp.subtract_overscan(ccd, overscan=ccd[:, 13:2057], median=True)

# Trim the overscan
ccd = ccdp.trim_image(ccd[20:2065, 13:2057])

# Subtract bias
ccd = ccdp.subtract_bias(ccd, combined_bias)

new_fname = "dark_osc_bs_{}.fits".format(count)
list_of_words = file_name.split("-")

new_fname = "dark_osc_bs_{}.fits".format(list_of_words[3])
# Save the result
ccd.write(calibrated_path / new_fname, overwrite=True)
count += 1

print("Finished overscan correcting and bias subtracting dark frames.")
print()
Expand All @@ -151,14 +144,14 @@ def dark(files, combined_bias, calibrated_path, rdnoise, gain):
time.sleep(10)
reduced_images = ccdp.ImageFileCollection(calibrated_path)
calibrated_darks = reduced_images.files_filtered(imagetyp='dark', include_path=True)

combined_darks = ccdp.combine(calibrated_darks,
method='average',
minmax_clip=True, minmax_clip_min=0, minmax_clip_max=1,
sigma_clip=True, sigma_clip_low_thresh=3, sigma_clip_high_thresh=3,
sigma_clip_func=np.ma.median, signma_clip_dev_func=mad_std,
rdnoise=rdnoise, gain=gain, mem_limit=450e6
)
method='average',
minmax_clip=True, minmax_clip_min=0, minmax_clip_max=1,
sigma_clip=True, sigma_clip_low_thresh=3, sigma_clip_high_thresh=3,
sigma_clip_func=np.ma.median, signma_clip_dev_func=mad_std,
rdnoise=rdnoise, gain=gain, mem_limit=450e6
)

combined_darks.meta['combined'] = True
combined_darks.write(calibrated_path / 'master_dark.fits', overwrite=True)
Expand All @@ -183,31 +176,25 @@ def flat(files, combined_bias, combined_darks, calibrated_path, rdnoise, gain):
print("Starting flat calibration.")
print()

skip = 0
count = 1
# calibrating and combining the flat frames
for ccd, file_name in files.ccds(imagetyp='FLAT', return_fname=True, ccd_kwargs={'unit': 'adu'}):
# Just get the bias frames
# Provide the file name too.

# Subtract the overscan
ccd = ccdp.subtract_overscan(ccd, overscan=ccd[:, 13:2057], median=True)

# Trim the overscan
ccd = ccdp.trim_image(ccd[20:2065, 13:2057])

# Subtract bias
ccd = ccdp.subtract_bias(ccd, combined_bias)

# Find the correct dark exposure
# closest_dark = find_nearest_dark_exposure(ccd, actual_exposure_times, tolerance=100)


# Subtract the dark current
ccd = ccdp.subtract_dark(ccd, combined_darks, exposure_time='exptime', exposure_unit=u.second, scale=True)
list_of_words = file_name.split("-")

new_fname = "flat_osc_bs_ds_{}_{}.fits".format(list_of_words[2], count)
count += 1

new_fname = "flat_osc_bs_ds_{}_{}.fits".format(list_of_words[2], list_of_words[4])
# Save the result
ccd.write(calibrated_path / new_fname, overwrite=True)

Expand All @@ -216,7 +203,7 @@ def flat(files, combined_bias, combined_darks, calibrated_path, rdnoise, gain):
print("Starting flat combination.")
print()
time.sleep(10)
count = 1

ifc = ccdp.ImageFileCollection(calibrated_path)
flat_filters = set(h['FILTER'] for h in ifc.headers(imagetyp="FLAT"))
for filt in flat_filters:
Expand All @@ -227,14 +214,13 @@ def flat(files, combined_bias, combined_darks, calibrated_path, rdnoise, gain):
sigma_clip=True, sigma_clip_low_thresh=3, sigma_clip_high_thresh=3,
sigma_clip_func=np.ma.median, signma_clip_dev_func=mad_std,
rdnoise=rdnoise, gain=gain, mem_limit=450e6
)
)

combined_flat.meta['combined'] = True
dark_file_name = 'master_flat_{}.fit'.format(filt.replace("Empty/", ""))

combined_flat.write(calibrated_path / dark_file_name, overwrite=True)
count += 1


print("Finished creating the master flats by filter.")
print()
print("Done")
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