diff --git a/cal_tools/cal_tools/agipdlib.py b/cal_tools/cal_tools/agipdlib.py
index c2c738e9a61429c2097e107ef99bbc019fa29666..e797a3bdea662b5ef7fa47c01dbf9f824f52073d 100644
--- a/cal_tools/cal_tools/agipdlib.py
+++ b/cal_tools/cal_tools/agipdlib.py
@@ -5,6 +5,8 @@ from typing import Any, Dict, Optional, Tuple
import h5py
import numpy as np
import sharedmem
+from iCalibrationDB import Conditions, Constants
+
from cal_tools.agipdutils import (assemble_constant_dict,
baseline_correct_via_noise,
baseline_correct_via_stripe,
@@ -12,11 +14,9 @@ from cal_tools.agipdutils import (assemble_constant_dict,
correct_baseline_via_hist_asic,
make_noisy_adc_mask, match_asic_borders,
melt_snowy_pixels)
+from cal_tools.cython import agipdalgs as calgs
from cal_tools.enums import BadPixels, SnowResolution
from cal_tools.tools import get_constant_from_db_and_time
-from iCalibrationDB import Conditions, Constants
-
-from cal_tools.cython import agipdalgs as calgs
def get_num_cells(fname, loc, module):
@@ -465,7 +465,7 @@ class AgipdCorrections:
for c in cells:
std = np.nanstd(data[cellid == c, ...], axis=0)
- mask_std[:, c, std == 0] |= BadPixels.DATA_STD_IS_ZERO.value
+ mask_std[:, c, std == 0] |= BadPixels.DATA_STD_IS_ZERO
def offset_correction(self, i_proc: int, first: int, last: int):
"""
@@ -664,7 +664,7 @@ class AgipdCorrections:
if self.corr_bools.get("zero_nans"):
bidx = ~np.isfinite(data)
data[bidx] = 0
- msk[bidx] |= BadPixels.VALUE_IS_NAN.value
+ msk[bidx] |= BadPixels.VALUE_IS_NAN
del bidx
# Add pixels with unrealistically high and low values to the mask.
@@ -672,7 +672,7 @@ class AgipdCorrections:
if self.corr_bools.get("zero_orange"):
bidx = (data < -1e7) | (data > 1e7)
data[bidx] = 0
- msk[bidx] |= BadPixels.VALUE_OUT_OF_RANGE.value
+ msk[bidx] |= BadPixels.VALUE_OUT_OF_RANGE
del bidx
# Mask entire ADC if they are noise above a threshold
diff --git a/cal_tools/cal_tools/agipdutils.py b/cal_tools/cal_tools/agipdutils.py
index 85bc81bb3d8e60e1104da6b9e792fd0aea464b3c..ae06e49bf9d661a6cc90265b445c93860bfee030 100644
--- a/cal_tools/cal_tools/agipdutils.py
+++ b/cal_tools/cal_tools/agipdutils.py
@@ -2,11 +2,12 @@ import copy
from typing import Tuple
import numpy as np
-from cal_tools.enums import BadPixels, SnowResolution
from scipy.signal import cwt, ricker
from sklearn.mixture import GaussianMixture
from sklearn.preprocessing import StandardScaler
+from cal_tools.enums import BadPixels, SnowResolution
+
def assemble_constant_dict(corr_bools, pc_bools, memory_cells, bias_voltage,
gain_setting, acquisition_rate,
@@ -429,8 +430,8 @@ def make_noisy_adc_mask(bmask, noise_threshold):
""" Mask entire ADC if they are noise above a relative threshold
"""
msk = np.count_nonzero(
- ((bmask & BadPixels.NOISE_OUT_OF_THRESHOLD.value != 0)
- | (bmask & BadPixels.OFFSET_NOISE_EVAL_ERROR.value != 0)).astype(
+ ((bmask & BadPixels.NOISE_OUT_OF_THRESHOLD != 0)
+ | (bmask & BadPixels.OFFSET_NOISE_EVAL_ERROR != 0)).astype(
np.int), axis=0)
fmask = np.zeros_like(msk).astype(np.uint32)
@@ -443,7 +444,7 @@ def make_noisy_adc_mask(bmask, noise_threshold):
bmask.shape[0] // 32)
if adc_cnt / (adc_i * adc_j) >= noise_threshold:
fmask[i * adc_i:(i + 1) * adc_i,
- j * adc_j:(j + 1) * adc_j] = BadPixels.NOISY_ADC.value
+ j * adc_j:(j + 1) * adc_j] = BadPixels.NOISY_ADC
return fmask
@@ -633,7 +634,7 @@ def melt_snowy_pixels(raw, im, gain, rgain, resolution=None):
mim[labels == implabel] = mimb[labels == implabel]
mimg[labels == implabel] = 0
# identify these pixels in a bad pixel mask
- mmsk[labels == implabel] = BadPixels.INTERPOLATED.value
+ mmsk[labels == implabel] = BadPixels.INTERPOLATED
# now set back to data
asic[fidx] = mim
diff --git a/cal_tools/cal_tools/agipdutils_ff.py b/cal_tools/cal_tools/agipdutils_ff.py
index 97d38ce87718cc5759ac807fd5a506decdffa02d..6774e5a0e85a619796e8d1c510e3a5a8b52852bf 100644
--- a/cal_tools/cal_tools/agipdutils_ff.py
+++ b/cal_tools/cal_tools/agipdutils_ff.py
@@ -1,9 +1,10 @@
from typing import Any, Dict, List, Optional, Tuple
import numpy as np
-from cal_tools.enums import BadPixelsFF
from iminuit import Minuit
+from cal_tools.enums import BadPixelsFF
+
def any_in(mask: np.ndarray, bits: int) -> bool:
return mask.astype(np.uint) & bits > 0
@@ -204,7 +205,7 @@ def get_mask(fit_summary: Dict[str, Any],
:return: Bad pixel mask
"""
if not fit_summary['is_valid']:
- return BadPixelsFF.FIT_FAILED.value
+ return BadPixelsFF.FIT_FAILED
m0 = fit_summary['g0mean']
s0 = fit_summary['g0sigma']
@@ -215,19 +216,19 @@ def get_mask(fit_summary: Dict[str, Any],
mask = 0
if not fit_summary['is_valid']:
- mask |= BadPixelsFF.FIT_FAILED.value
+ mask |= BadPixelsFF.FIT_FAILED
if not fit_summary['has_accurate_covar']:
- mask |= BadPixelsFF.ACCURATE_COVAR.value
+ mask |= BadPixelsFF.ACCURATE_COVAR
if not peak_lim[0] <= m0 <= peak_lim[1]:
- mask |= BadPixelsFF.NOISE_PEAK_THRESHOLD.value
+ mask |= BadPixelsFF.NOISE_PEAK_THRESHOLD
if not d0_lim[0] <= d01 <= d0_lim[1]:
- mask |= BadPixelsFF.GAIN_THRESHOLD.value
+ mask |= BadPixelsFF.GAIN_THRESHOLD
if not chi2_lim[0] <= chi2_ndof <= chi2_lim[1]:
- mask |= BadPixelsFF.CHI2_THRESHOLD.value
+ mask |= BadPixelsFF.CHI2_THRESHOLD
width_lim = peak_width_lim[0] * s0
inside_s1 = width_lim[0] <= s1 <= width_lim[1]
@@ -236,6 +237,6 @@ def get_mask(fit_summary: Dict[str, Any],
inside_s2 = width_lim[0] <= s2 <= width_lim[1]
if not inside_s1 and inside_s2:
- mask |= BadPixelsFF.PEAK_WIDTH_THRESHOLD.value
+ mask |= BadPixelsFF.PEAK_WIDTH_THRESHOLD
return mask
diff --git a/cal_tools/cal_tools/dssclib.py b/cal_tools/cal_tools/dssclib.py
index 7e17f2011471f185e39f38fedcfcfab0cb25523d..8eabb3f42e4b3ae7be67ea39941ee38c5c408186 100644
--- a/cal_tools/cal_tools/dssclib.py
+++ b/cal_tools/cal_tools/dssclib.py
@@ -1,12 +1,13 @@
import binascii
-import h5py
-from hashlib import blake2b
-import numpy as np
import os
import re
import struct
+from hashlib import blake2b
from typing import Dict, Tuple
+import h5py
+import numpy as np
+
def get_pulseid_checksum(fname, h5path, h5path_idx):
"""generates hash value from pulse pattern (veto defined)."""
diff --git a/cal_tools/cal_tools/enums.py b/cal_tools/cal_tools/enums.py
index 19420caeacf38580e808ee0da4a76c508e29e464..4abafdc10b646d7d81c92de9912f8b29f27f1e13 100644
--- a/cal_tools/cal_tools/enums.py
+++ b/cal_tools/cal_tools/enums.py
@@ -1,7 +1,7 @@
-from enum import Enum
+from enum import Enum, IntFlag
-class BadPixels(Enum):
+class BadPixels(IntFlag):
""" The European XFEL Bad Pixel Encoding
"""
@@ -28,7 +28,7 @@ class BadPixels(Enum):
NON_LIN_RESPONSE_REGION = 0b100000000000000000000 # bit 21
-class BadPixelsFF(Enum):
+class BadPixelsFF(IntFlag):
""" The SLopesFF Bad Pixel Encoding
"""
diff --git a/cal_tools/cal_tools/lpdlib.py b/cal_tools/cal_tools/lpdlib.py
index 716637a5261cbfddeb752758290644c0c1707c0c..217c769fcc6faef919697b2b671a1c9e3a65c488 100644
--- a/cal_tools/cal_tools/lpdlib.py
+++ b/cal_tools/cal_tools/lpdlib.py
@@ -3,11 +3,10 @@ from typing import Optional, Tuple
import h5py
import numpy as np
+from iCalibrationDB import Conditions, Constants, Detectors
from cal_tools.enums import BadPixels
-from cal_tools.tools import (get_constant_from_db,
- get_constant_from_db_and_time)
-from iCalibrationDB import Conditions, Constants, Detectors
+from cal_tools.tools import get_constant_from_db, get_constant_from_db_and_time
class LpdCorrections:
@@ -267,7 +266,7 @@ class LpdCorrections:
for gl, lr in enumerate(self.linear_between):
midx = (gain == gl) & ((im < lr[0]) | (im > lr[1]))
- msk[midx] = BadPixels.NON_LIN_RESPONSE_REGION.value
+ msk[midx] = BadPixels.NON_LIN_RESPONSE_REGION
numnonlin = np.count_nonzero(midx, axis=(1,2))
nlf += numnonlin
nlf = nlf/float(im.shape[0] * im.shape[1])
@@ -314,12 +313,12 @@ class LpdCorrections:
# create bad pixels masks, here non-finite values
bidx = ~np.isfinite(im)
im[bidx] = 0
- msk[bidx] = BadPixels.VALUE_IS_NAN.value
+ msk[bidx] = BadPixels.VALUE_IS_NAN
# values which are unphysically large or small
bidx = (im < -1e7) | (im > 1e7)
im[bidx] = 0
- msk[bidx] = BadPixels.VALUE_OUT_OF_RANGE.value
+ msk[bidx] = BadPixels.VALUE_OUT_OF_RANGE
# on first iteration we create histograms for the report
if cidx == 0:
diff --git a/cal_tools/cal_tools/pnccdlib.py b/cal_tools/cal_tools/pnccdlib.py
index ec8b92e7f65dfb21a09fa099df3a749d55833fc7..785d289c359ffe6d3e62aa15bb6e41de56d4145d 100644
--- a/cal_tools/cal_tools/pnccdlib.py
+++ b/cal_tools/cal_tools/pnccdlib.py
@@ -5,7 +5,6 @@ from typing import Tuple
import h5py
-
VALID_GAINS = {
"a" : 1.0,
"b" : 4.0,