zebra/pyzebra
3
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Update ccl_findpeaks.py

Browse Source
This commit is contained in:
JakHolzer 2020-09-14 09:42:14 +02:00 committed by GitHub
parent 90c0256595
commit d30b348425
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 14 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

33
pyzebra/ccl_findpeaks.py
View File

@ -15,54 +15,49 @@ def ccl_findpeaks(
i.e. will only detect peaks above 75% of max intensity
prominence - defines a drop of values that must be between two peaks, must be positive number
i.e. if promimence is 20, it will detect two neigbouring peaks of 300 and 310 intesities,
i.e. if promimence is 20, it will detect two neigbouring peaks of 300 and 310 intesities,
if none of the itermediate values are lower that 290
smooth - if true, smooths data by savitzky golay filter, if false - no smoothing
window_size - window size for savgol filter, must be odd positive integer
poly_order = order of the polynomial used in savgol filter, must be positive integer smaller than
poly_order = order of the polynomial used in savgol filter, must be positive integer smaller than
window_size returns: dictionary with following structure:
D{M34{ 'num_of_peaks': 1, #num of peaks
'peak_indexes': [20], # index of peaks in omega array
'peak_heights': [90.], # height of the peaks (if data vere smoothed
'peak_heights': [90.], # height of the peaks (if data vere smoothed
its the heigh of the peaks in smoothed data)
"""
if type(data) is not dict and data["file_type"] != "ccl":
print("Data is not a dictionary or was not made from ccl file")
if 0 <= int_threshold <= 1:
pass
else:
int_threshold = 0.75
if not 0 <= int_threshold <= 1:
int_threshold = 0.8
print(
"Invalid value for int_threshold, select value between 0 and 1, new value set to:",
int_threshold,
)
if isinstance(window_size, int) is True and (window_size % 2) != 0 and window_size >= 1:
pass
else:
if isinstance(window_size, int) is False or (window_size % 2) == 0 or window_size <= 1:
window_size = 7
print(
"Invalid value for window_size, select positive odd integer, new value set to:",
window_size,
)
if isinstance(poly_order, int) is True and window_size > poly_order >= 1:
pass
else:
"Invalid value for window_size, select positive odd integer, new value set to!:",
window_size)
if isinstance(poly_order, int) is False or window_size < poly_order:
poly_order = 3
print(
"Invalid value for poly_order, select positive integer smaller than window_size, new value set to:",
poly_order,
)
if isinstance(prominence, (int, float)) is True and prominence > 0:
pass
else:
if isinstance(prominence, (int, float)) is False and prominence < 0:
prominence = 50
print("Invalid value for prominence, select positive number, new value set to:", prominence)
omega = data["Measurements"][str(keys)]["omega"]
counts = np.array(data["Measurements"][str(keys)]["counts"])
if smooth is True: