diff --git a/src/toolbox_scs/detectors/digitizers.py b/src/toolbox_scs/detectors/digitizers.py
index 067a75b22c345571346e2a91af8a751ecb84410b..506335db77819fffa2cd1259e6fc46039b2045bb 100644
--- a/src/toolbox_scs/detectors/digitizers.py
+++ b/src/toolbox_scs/detectors/digitizers.py
@@ -13,12 +13,9 @@ import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
from scipy.signal import find_peaks
-from scipy.signal import fftconvolve
from ..misc.bunch_pattern_external import is_pulse_at
-from ..util.exceptions import ToolBoxValueError
-from ..mnemonics_machinery import (mnemonics_to_process,
- mnemonics_for_run)
+from ..mnemonics_machinery import mnemonics_for_run
from extra_data import open_run
from extra_data.read_machinery import find_proposal
from extra.components import XrayPulses, OpticalLaserPulses
@@ -445,7 +442,6 @@ def find_peak_integration_parameters(run, mnemonic, raw_trace=None,
raise ValueError(add_text + 'All keys of integParams argument '
f'{required_keys} are required.')
params = integParams.copy()
-
# extract pulse ids from the parameters (starting at 0)
pulse_ids_params = None
if hasattr(params['pulseStart'], '__len__'):
@@ -458,9 +454,12 @@ def find_peak_integration_parameters(run, mnemonic, raw_trace=None,
pulse_ids_params = ((np.array(params['pulseStart']) -
params['pulseStart'][0]) / pulse_period).astype(int)
elif 'npulses' in params and 'period' in params:
+ if params['npulses'] == 1:
+ pulse_ids_params = np.array([0])
+ else:
pulse_ids_params = np.arange(0,
- params['npulses'] * params['period'] / pulse_period,
- params['period'] / pulse_period).astype(int)
+ params['npulses'] * params['period'] / pulse_period,
+ params['period'] / pulse_period).astype(int)
# Extract pulse_ids, period and npulses from bunch pattern
pulse_ids_bp, npulses_bp, period_bp = None, None, 0
@@ -512,7 +511,7 @@ def find_peak_integration_parameters(run, mnemonic, raw_trace=None,
params['npulses'] = npulses_bp
params['period'] = period_bp
- if regular == False:
+ if not regular:
# Irregular pattern
if hasattr(params['pulseStart'], '__len__'):
start = params['pulseStart'][0]
@@ -590,8 +589,8 @@ def check_peak_params(proposal, runNB, mnemonic, raw_trace=None,
if regular:
add_text = ''
if len(pulse_ids) > 1:
- add_text = f's, {(pulse_ids[1]-pulse_ids[0]) * pulse_period}' +\
- ' samples between two pulses'
+ add_text = f's, {(pulse_ids[1]-pulse_ids[0]) * pulse_period}'\
+ + ' samples between two pulses'
print(f'Bunch pattern {bunchPattern}: {len(pulse_ids)} pulse'
+ add_text)
else:
@@ -607,7 +606,7 @@ def check_peak_params(proposal, runNB, mnemonic, raw_trace=None,
no_change = no_change & (v == params[k])
if hasattr(no_change, '__len__'):
no_change = no_change.all()
- if no_change == False:
+ if no_change is False:
print('The provided parameters did not match the bunch '
'pattern and were adjusted.')
title += ' (adjusted)'
@@ -625,7 +624,7 @@ def check_peak_params(proposal, runNB, mnemonic, raw_trace=None,
raw_trace = get_dig_avg_trace(run, mnemonic)
fig, ax = plotPeakIntegrationWindow(raw_trace, params,
show_all=show_all)
- fig.suptitle(f'p{proposal} r{runNB} '+ title, size=12)
+ fig.suptitle(f'p{proposal} r{runNB} ' + title, size=12)
return params
@@ -667,12 +666,12 @@ def plotPeakIntegrationWindow(raw_trace, params, show_all=False):
for j in range(min(2, len(starts))):
if plot == 1:
j = -j
- label='baseline' if j == 0 else ''
+ label = 'baseline' if j == 0 else ''
ax[plot].axvline(baseStarts[i+j], ls='--', color='k')
ax[plot].axvline(baseStops[i+j], ls='--', color='k')
ax[plot].axvspan(baseStarts[i+j], baseStops[i+j],
alpha=0.5, color='grey', label=label)
- label='peak' if j == 0 else ''
+ label = 'peak' if j == 0 else ''
ax[plot].axvline(starts[i+j], ls='--', color='r')
ax[plot].axvline(stops[i+j], ls='--', color='r')
ax[plot].axvspan(starts[i+j], stops[i+j],
@@ -685,7 +684,7 @@ def plotPeakIntegrationWindow(raw_trace, params, show_all=False):
xmin = np.max([0, baseStarts[i] - 200])
xmax = np.min([stops[i] + 200, raw_trace.size])
ax[plot].plot(np.arange(xmin, xmax),
- raw_trace[xmin:xmax], color='C0', label=title)
+ raw_trace[xmin:xmax], color='C0', label='raw trace')
ax[plot].legend(fontsize=8)
ax[plot].set_xlim(xmin, xmax)
ax[plot].set_xlabel('digitizer samples')
@@ -962,7 +961,7 @@ def load_all_processed_peaks(proposal, runNB, data='usr/processed_runs',
join='inner')
return xr.load_dataset(fname)
else:
- print(f'{fname} not found.')
+ log.warning(f'{fname} not found.')
return merge_with
@@ -1007,13 +1006,15 @@ def check_processed_peak_params(proposal, runNB, mnemonic,
if mnemonic.replace('raw', 'peaks') not in ds:
log.warning(f'Mnemonic {mnemonic} not found in {fname}')
return {}
- params = {k.replace(f'{mnemonic}_', ''): ds.attrs[k] for\
+ params = {k.replace(f'{mnemonic}_', ''): ds.attrs[k] for
k in ds.attrs if f'{mnemonic}_' in k}
if plot:
title = 'Processed peak parameters'
- fig, ax = plotPeakIntegrationWindow(ds[mnemonic.replace('peaks', 'avg')],
- params, show_all=show_all)
- fig.suptitle(f'p{proposal} r{runNB} '+ title, size=12)
+ fig, ax = plotPeakIntegrationWindow(
+ ds[mnemonic.replace('peaks', 'avg')],
+ params,
+ show_all=show_all)
+ fig.suptitle(f'p{proposal} r{runNB} ' + title, size=12)
return params
else: