Fix import * in agipdlib

Description

Going through a few CI logs, I noticed that cal_tools/cal_tools/agipdlib.py was flagged a few times due to its from agipdutils import *.
This fixes that, as well as a few other pep8 violations.

No logic changes were introduced.

How Has This Been Tested?

This was tested by running python agipdlib.py to ensure that the file can be loaded fine.

Types of changes

• Code cleanup

Checklist:

• My code follows the code style of this project.

Reviewers

@roscar @ahmedk @hammerd @schmidtp

cal_tools/cal_tools/agipdlib.py

@@ -5,12 +5,17 @@ from typing import Any, Dict, Optional, Tuple
 import h5py
 import numpy as np
 import sharedmem
-from cal_tools.agipdutils import *
+from iCalibrationDB import Conditions, Constants
+
+from cal_tools.agipdutils import (assemble_constant_dict,
+                                  baseline_correct_via_noise,
+                                  baseline_correct_via_stripe,
+                                  correct_baseline_via_hist,
+                                  correct_baseline_via_hist_asic,
+                                  make_noisy_adc_mask, match_asic_borders)
+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, Detectors
-
-from cal_tools.cython import agipdalgs as calgs
 
 
 def get_num_cells(fname, loc, module):
@@ -80,7 +85,8 @@ def get_acq_rate(fast_paths: Tuple[str, str, int],
 
 
 def get_gain_setting(fname: str, h5path_ctrl: str) -> int:
-    """
+    """Retrieve Gain setting.
+
     If the data is available from the middlelayer FPGA_COMP device, then it is
     retrieved from there.
     If not, the setting is calculated off `setupr` and `patternTypeIndex`
@@ -160,8 +166,8 @@ class AgipdCorrections:
             image/data section
         :param h5_index_path: path in HDF5 file which is prefixed to the
             index section
-        :param corr_bools: A dict with all of the correction booleans requested or
-                           available
+        :param corr_bools: A dict with all of the correction booleans requested
+                           or available
 
         The following example shows a typical use case:
         .. code-block:: python
@@ -203,7 +209,7 @@ class AgipdCorrections:
         self.rng_pulses = max_pulses
         # avoid list(range(*[0]]))
         self.pulses_lst = list(range(*max_pulses)) \
-            if not (len(max_pulses) == 1 and max_pulses[0] == 0) else max_pulses  #noqa
+            if not (len(max_pulses) == 1 and max_pulses[0] == 0) else max_pulses  # noqa
         self.max_cells = max_cells
 
         # Correction parameters
@@ -498,11 +504,11 @@ class AgipdCorrections:
         # force into high or medium gain if requested
         if self.corr_bools.get('force_mg_if_below'):
             gain[(gain == 2) & (
-                        (data - offsetb[1]) < self.mg_hard_threshold)] = 1
+                (data - offsetb[1]) < self.mg_hard_threshold)] = 1
 
         if self.corr_bools.get('force_hg_if_below'):
             gain[(gain > 0) & (
-                        (data - offsetb[0]) < self.hg_hard_threshold)] = 0
+                (data - offsetb[0]) < self.hg_hard_threshold)] = 0
 
         # choose constants according to gain setting
         off = calgs.gain_choose(gain, offsetb)
@@ -512,7 +518,7 @@ class AgipdCorrections:
         data -= off
         del off
 
-    def baseline_correction(self, i_proc:int, first:int, last:int):
+    def baseline_correction(self, i_proc: int, first: int, last: int):
         """
         Perform image-wise base-line shift correction for
         data in shared memory via histogram or stripe
@@ -536,14 +542,12 @@ class AgipdCorrections:
         # output is saved in sharedmem to pass for correct_agipd()
         # as this function takes about 3 seconds.
         self.shared_dict[i_proc]['msk'][first:last] = \
-                            calgs.gain_choose_int(gain,
-                                                  self.mask[module_idx][:, cellid])  # noqa
+            calgs.gain_choose_int(gain, self.mask[module_idx][:, cellid])
 
         if hasattr(self, "rel_gain"):
             # Get the correct rel_gain depending on cell-id
             self.shared_dict[i_proc]['rel_corr'][first:last] = \
-                                calgs.gain_choose(gain,
-                                                  self.rel_gain[module_idx][:, cellid])  # noqa
+                calgs.gain_choose(gain, self.rel_gain[module_idx][:, cellid])
 
         # do this image wise, as the shift is per image
         for i in range(data.shape[0]):
@@ -647,9 +651,9 @@ class AgipdCorrections:
         # after calculating it while offset correcting.
         if self.corr_bools.get('melt_snow'):
             _ = melt_snowy_pixels(self.shared_dict[i_proc]['raw_data'][first:last],  # noqa
-                                        data, gain,
-                                        self.shared_dict[i_proc]['t0_rgain'][first:last],  # noqa
-                                        self.snow_resolution)
+                                  data, gain,
+                                  self.shared_dict[i_proc]['t0_rgain'][first:last],  # noqa
+                                  self.snow_resolution)
 
         # Inner ASIC borders are matched to the same signal level
         if self.corr_bools.get("match_asics"):
@@ -712,7 +716,7 @@ class AgipdCorrections:
             valid_indices = np.concatenate([np.arange(validf[i],
                                                       validf[i]+validc[i])
                                             for i in range(validf.size)],
-                                            axis=0)
+                                           axis=0)
             valid_indices = np.squeeze(valid_indices).astype(np.int32)
 
         elif index_v == 1:
@@ -753,8 +757,8 @@ class AgipdCorrections:
         allpulses = data_dict['pulseId'][:n_img]
 
         # Initializing can_calibrate array
-        can_calibrate = self.choose_selected_pulses(allpulses,
-                                can_calibrate=[True]*len(allpulses))
+        can_calibrate = self.choose_selected_pulses(
+            allpulses, can_calibrate=[True]*len(allpulses))
 
         # Only select data corresponding to selected pulses
         # and overwrite data in shared-memory leaving
@@ -779,7 +783,7 @@ class AgipdCorrections:
         return n_img
 
     def validate_selected_pulses(self, allpulses: np.array
-                                ) -> Tuple[int, int, int]:
+                                 ) -> Tuple[int, int, int]:
         """Validate the selected pulses given from the notebook
 
         Validate that the given range of pulses to correct
@@ -816,7 +820,6 @@ class AgipdCorrections:
 
     def choose_selected_pulses(self, allpulses: np.array,
                                can_calibrate: np.array) -> np.array:
-
         """
         Choose given selected pulse from pulseId array of
         raw data. The selected pulses range is validated then
@@ -831,7 +834,7 @@ class AgipdCorrections:
         """
 
         (first_pulse, last_pulse,
-        pulse_step) = self.validate_selected_pulses(allpulses)
+         pulse_step) = self.validate_selected_pulses(allpulses)
 
         # collect the pulses to be calibrated
         cal_pulses = allpulses[first_pulse: last_pulse: pulse_step]
@@ -853,7 +856,8 @@ class AgipdCorrections:
         return can_calibrate
 
     def gen_valid_range(self, first_index: int, last_index: int,
-                        max_cells: int, allcells: np.array, allpulses: np.array,
+                        max_cells: int, allcells: np.array,
+                        allpulses: np.array,
                         valid_indices: Optional[np.array] = None,
                         apply_sel_pulses: Optional[bool] = True
                         ) -> np.array:
@@ -890,8 +894,8 @@ class AgipdCorrections:
             return
 
         if apply_sel_pulses:
-            can_calibrate = self.choose_selected_pulses(allpulses,
-                                            can_calibrate=can_calibrate)
+            can_calibrate = self.choose_selected_pulses(
+                allpulses, can_calibrate=can_calibrate)
         if valid_indices is None:
             firange = np.arange(first_index, last_index)
         else:
@@ -1075,7 +1079,7 @@ class AgipdCorrections:
 
         self.offset[module_idx][...] = cons_data["Offset"].transpose()[...]
         self.noise[module_idx][...] = cons_data["Noise"].transpose()[...]
-        self.thresholds[module_idx][...] = cons_data["ThresholdsDark"].transpose()[:3,...]  # noqa
+        self.thresholds[module_idx][...] = cons_data["ThresholdsDark"].transpose()[:3, ...]  # noqa
 
         if self.corr_bools.get("low_medium_gap"):
             t0 = self.thresholds[module_idx][0]
@@ -1090,7 +1094,7 @@ class AgipdCorrections:
                                                                       :bpixels.shape[2],  # noqa
                                                                       None]
 
-            if when["SlopesFF"]: # Checking if constant was retrieved
+            if when["SlopesFF"]:  # Checking if constant was retrieved
 
                 slopesFF = cons_data["SlopesFF"]
                 # This could be used for backward compatibility
@@ -1100,18 +1104,20 @@ class AgipdCorrections:
                 # This is for backward compatability for old FF constants
                 # (128, 512, mem_cells)
                 if slopesFF.shape[-1] == 2:
-                    xray_cor = np.squeeze(slopesFF[...,0])
+                    xray_cor = np.squeeze(slopesFF[..., 0])
                     xray_cor_med = np.nanmedian(xray_cor)
-                    xray_cor[np.isnan(xray_cor)]= xray_cor_med
-                    xray_cor[(xray_cor<0.8) | (xray_cor>1.2)] = xray_cor_med
+                    xray_cor[np.isnan(xray_cor)] = xray_cor_med
+                    xray_cor[(xray_cor < 0.8) | (
+                        xray_cor > 1.2)] = xray_cor_med
                     xray_cor = np.dstack([xray_cor]*self.max_cells)
                 else:
                     # Memory cell resolved xray_cor correction
                     xray_cor = slopesFF  # (128, 512, mem_cells)
                     if xray_cor.shape[-1] < self.max_cells:
-                        # In case of having new constant with less memory cells,
-                        # due to lack of enough FF data or during development.
-                        # xray_cor should be expanded by last memory cell.
+                        # When working with new constant with fewer memory
+                        # cells, eg. lacking enough FF data or during
+                        # development, xray_cor must be expand its last memory
+                        # cell to maintain a consistent shape.
                         xray_cor = np.dstack(xray_cor,
                                              np.dstack([xray_cor[..., -1]]
                                              * (self.max_cells - xray_cor.shape[-1])))  # noqa
@@ -1151,11 +1157,11 @@ class AgipdCorrections:
                 pc_med_l = slopesPC[..., :self.max_cells, 4]
 
                 # calculate median for slopes
-                pc_high_med = np.nanmedian(pc_high_m, axis=(0,1))
-                pc_med_med = np.nanmedian(pc_med_m, axis=(0,1))
+                pc_high_med = np.nanmedian(pc_high_m, axis=(0, 1))
+                pc_med_med = np.nanmedian(pc_med_m, axis=(0, 1))
                 # calculate median for intercepts:
-                pc_high_l_med = np.nanmedian(pc_high_l, axis=(0,1))
-                pc_med_l_med = np.nanmedian(pc_med_l, axis=(0,1))
+                pc_high_l_med = np.nanmedian(pc_high_l, axis=(0, 1))
+                pc_med_l_med = np.nanmedian(pc_med_l, axis=(0, 1))
 
                 # sanitize PC data
                 # (it should be done already on the level of constants)