IPKM/python3-damaris
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* Make it work in bookworm, redid some of the changes from last commit

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* Changed default number types to int16 for ADC_Result and float32 for
  Accumulations
This commit is contained in:
Markus Rosenstihl
2026-03-09 10:55:55 +01:00
parent 29f003c99e
commit 28e6c9d1a0
10 changed files with 79 additions and 87 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/data/ADC_Result.py
+13 -14
View File
@@ -73,9 +73,9 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
if samples <= 0: raise ValueError("ValueError: You cant create an ADC-Result with less than 1 sample!")
for i in range(channels):
self.y.append(numpy.zeros((samples,), dtype="Int16"))
self.y.append(numpy.zeros((samples,), dtype="int16"))
self.x = numpy.zeros((samples,), dtype="float64")
self.x = numpy.zeros((samples,), dtype="float32")
self.index.append((0, samples-1))
self.cont_data = True
@@ -231,8 +231,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
if self.description is not None:
for (key,value) in self.description.items():
if key != None:
accu_group._v_attrs.__setattr__("description_"+key, str(value))
accu_group._v_attrs.__setattr__("description_"+key,str(value))
accu_group._v_attrs.__setattr__("sampling_rate",self.sampling_rate)
# save interval information
@@ -246,8 +245,8 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
name="indices",
description={"start": tables.UInt64Col(),
"length": tables.UInt64Col(),
"start_time": tables.Float64Col(),
"dwelltime": tables.Float64Col()},
"start_time": tables.Float32Col(),
"dwelltime": tables.Float32Col()},
title="indices of adc data intervals",
filters=filter,
expectedrows=len(self.index))
@@ -341,7 +340,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(numpy.array(self.y[i], dtype="float64") + other)
tmp_y.append(numpy.array(self.y[i], dtype="float32") + other)
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -362,7 +361,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(numpy.array(self.y[i], dtype="float64") - other)
tmp_y.append(numpy.array(self.y[i], dtype="float32") - other)
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -378,7 +377,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(other - numpy.array(self.y[i], dtype="float64"))
tmp_y.append(other - numpy.array(self.y[i], dtype="float32"))
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -395,7 +394,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(numpy.array(self.y[i], dtype="float64") * other)
tmp_y.append(numpy.array(self.y[i], dtype="float32") * other)
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -415,7 +414,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(numpy.array(self.y[i], dtype="float64") ** other)
tmp_y.append(numpy.array(self.y[i], dtype="float32") ** other)
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -431,7 +430,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(numpy.array(self.y[i], dtype="float64") / other)
tmp_y.append(numpy.array(self.y[i], dtype="float32") / other)
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -447,7 +446,7 @@ class ADC_Result(Resultable, Drawable, DamarisFFT, Signalpath):
tmp_y = []
for i in range(self.get_number_of_channels()):
tmp_y.append(other / numpy.array(self.y[i], dtype="float64"))
tmp_y.append(other / numpy.array(self.y[i], dtype="float32"))
r = ADC_Result(x = self.x[:], y = tmp_y, index = self.index[:], sampl_freq = self.sampling_rate, desc = self.description, job_id = self.job_id, job_date = self.job_date)
self.lock.release()
@@ -517,7 +516,7 @@ def read_from_hdf(hdf_node):
# now do the real data
adc_data=hdf_node.adc_data.read()
adc.x=numpy.arange(adc_data.shape[0], dtype="float64")/adc.sampling_rate
adc.x=numpy.arange(adc_data.shape[0], dtype="float32")/adc.sampling_rate
for ch in range(adc_data.shape[1]):
adc.y.append(adc_data[:,ch])
src/data/Accumulation.py
+30 -30
View File
@@ -131,19 +131,19 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
return error (std.dev/sqrt(n)) of mean
"""
if not self.uses_statistics(): return numpy.zeros((len(self.y[0]),),dtype="float64")
if not self.uses_statistics(): return numpy.zeros((len(self.y[0]),),dtype="float32")
if not self.contains_data(): return []
self.lock.acquire()
if self.n < 2:
retval=numpy.zeros((len(self.y[0]),),dtype="float64")
retval=numpy.zeros((len(self.y[0]),),dtype="float32")
self.lock.release()
return retval
try:
variance_over_n = (self.y_square[channel] - (self.y[channel]**2 / float(self.n)))/float((self.n-1)*self.n)
except IndexError:
print("Warning Accumulation.get_ydata(channel): Channel index does not exist.")
variance_over_n = numpy.zeros((len(self.y[0]),), dtype="float64")
variance_over_n = numpy.zeros((len(self.y[0]),), dtype="float32")
self.lock.release()
# sample standard deviation / sqrt(n)
return numpy.nan_to_num(numpy.sqrt(variance_over_n))
@@ -160,7 +160,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
tmp_y = self.y[channel] / self.n
except IndexError:
print("Warning Accumulation.get_ydata(channel): Channel index does not exist.")
tmp_y = numpy.zeros((len(self.y[0]),), dtype="float64")
tmp_y = numpy.zeros((len(self.y[0]),), dtype="float32")
self.lock.release()
return tmp_y
@@ -466,13 +466,13 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
# prepare saving data
channel_no=len(self.y)
timedata=numpy.empty((len(self.y[0]),channel_no*2), dtype = "float64")
timedata=numpy.empty((len(self.y[0]),channel_no*2), dtype = "float32")
for ch in range(channel_no):
timedata[:,ch*2]=self.get_ydata(ch)
if self.uses_statistics():
timedata[:,ch*2+1]=self.get_yerr(ch)
else:
timedata[:,ch*2+1]=numpy.zeros((len(self.y[0]),),dtype = "float64")
timedata[:,ch*2+1]=numpy.zeros((len(self.y[0]),),dtype = "float32")
# save data
time_slice_data=None
@@ -486,7 +486,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
time_slice_data=hdffile.create_carray(accu_group,
name="accu_data",
shape=timedata.shape,
atom=tables.Float64Atom(shape=chunkshape,
atom=tables.Float32Atom(shape=chunkshape,
flavor="numpy"),
filters=filter,
title="accu data")
@@ -495,7 +495,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
name="accu_data",
shape=timedata.shape,
chunkshape=chunkshape,
atom=tables.Float64Atom(),
atom=tables.Float32Atom(),
filters=filter,
title="accu data")
@@ -564,9 +564,9 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
tmp_y.append(self.y[i] + (other*self.n))
if self.uses_statistics():
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, y_2 = tmp_ysquare, n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = self.use_error)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, y_2 = tmp_ysquare, n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = self.use_error)
else:
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = self.use_error)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = self.use_error)
r.job_id = self.job_id # added by Oleg Petrov
self.lock.release()
return r
@@ -587,14 +587,14 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
self.lock.acquire()
for i in range(other.get_number_of_channels()):
tmp_y.append(numpy.array(other.y[i], dtype="float64"))
tmp_y.append(numpy.array(other.y[i], dtype="float32"))
if self.uses_statistics(): tmp_ysquare.append(tmp_y[i] ** 2)
if self.uses_statistics():
r = Accumulation(x = numpy.array(other.x, dtype="float64"), y = tmp_y, y_2 = tmp_ysquare, n = 1, index = other.index, sampl_freq = other.sampling_rate, error = True)
r = Accumulation(x = numpy.array(other.x, dtype="float32"), y = tmp_y, y_2 = tmp_ysquare, n = 1, index = other.index, sampl_freq = other.sampling_rate, error = True)
else:
r = Accumulation(x = numpy.array(other.x, dtype="float64"), y = tmp_y, index = other.index, sampl_freq = other.sampling_rate, n = 1, error = False)
r = Accumulation(x = numpy.array(other.x, dtype="float32"), y = tmp_y, index = other.index, sampl_freq = other.sampling_rate, n = 1, error = False)
r.time_period=[other.job_date,other.job_date]
r.job_id = other.job_id # added by Oleg Petrov
r.common_descriptions=other.description.copy()
@@ -616,12 +616,12 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
for i in range(self.get_number_of_channels()):
tmp_y.append(self.y[i] + other.y[i])
if self.uses_statistics(): tmp_ysquare.append(self.y_square[i] + (numpy.array(other.y[i], dtype="float64") ** 2))
if self.uses_statistics(): tmp_ysquare.append(self.y_square[i] + (numpy.array(other.y[i], dtype="float32") ** 2))
if self.uses_statistics():
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, y_2 = tmp_ysquare, n = self.n + 1, index = self.index, sampl_freq = self.sampling_rate, error = True)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, y_2 = tmp_ysquare, n = self.n + 1, index = self.index, sampl_freq = self.sampling_rate, error = True)
else:
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, n = self.n + 1, index = self.index, sampl_freq = self.sampling_rate, error = False)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, n = self.n + 1, index = self.index, sampl_freq = self.sampling_rate, error = False)
r.time_period=[min(self.time_period[0],other.job_date),
max(self.time_period[1],other.job_date)]
r.job_id = other.job_id # added by Oleg Petrov
@@ -649,9 +649,9 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
self.lock.acquire()
if self.uses_statistics():
r = Accumulation(x = numpy.array(other.x, dtype="float64"), y = tmp_y, y_2 = tmp_ysquare, n = other.n, index = other.index, sampl_freq = other.sampling_rate, error = True)
r = Accumulation(x = numpy.array(other.x, dtype="float32"), y = tmp_y, y_2 = tmp_ysquare, n = other.n, index = other.index, sampl_freq = other.sampling_rate, error = True)
else:
r = Accumulation(x = numpy.array(other.x, dtype="float64"), y = tmp_y, n = other.n, index = other.index, sampl_freq = other.sampling_rate, error = False)
r = Accumulation(x = numpy.array(other.x, dtype="float32"), y = tmp_y, n = other.n, index = other.index, sampl_freq = other.sampling_rate, error = False)
for i in range(other.get_number_of_channels()):
tmp_y.append(other.y[i])
tmp_ysquare.append(other.y_square[i])
@@ -684,9 +684,9 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
tmp_ysquare.append(self.y_square[i] + other.y_square[i])
if self.uses_statistics():
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, y_2 = tmp_ysquare, n = other.n + self.n, index = self.index, sampl_freq = self.sampling_rate, error = True)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, y_2 = tmp_ysquare, n = other.n + self.n, index = self.index, sampl_freq = self.sampling_rate, error = True)
else:
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, n = other.n + self.n, index = self.index, sampl_freq = self.sampling_rate, error = False)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, n = other.n + self.n, index = self.index, sampl_freq = self.sampling_rate, error = False)
r.time_period=[min(self.time_period[0],other.time_period[0]),
max(self.time_period[1],other.time_period[1])]
@@ -745,11 +745,11 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
self.n += 1
self.index = other.index[0:]
self.sampling_rate = other.sampling_rate
self.x = numpy.array(other.x, dtype="float64")
self.x = numpy.array(other.x, dtype="float32")
self.cont_data = True
for i in range(other.get_number_of_channels()):
self.y.append(numpy.array(other.y[i], dtype="float64"))
self.y.append(numpy.array(other.y[i], dtype="float32"))
if self.uses_statistics(): self.y_square.append(self.y[i] ** 2)
self.set_title(self.__title_pattern % self.n)
@@ -774,7 +774,7 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
for i in range(self.get_number_of_channels()):
self.y[i] += other.y[i]
if self.uses_statistics(): self.y_square[i] += numpy.array(other.y[i], dtype="float64") ** 2
if self.uses_statistics(): self.y_square[i] += numpy.array(other.y[i], dtype="float32") ** 2
self.n += 1
self.time_period=[min(self.time_period[0],other.job_date),
@@ -804,11 +804,11 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
self.n += other.n
self.index = other.index[0:]
self.sampling_rate = other.sampling_rate
self.x = numpy.array(other.x, dtype="float64")
self.x = numpy.array(other.x, dtype="float32")
self.cont_data = True
for i in range(other.get_number_of_channels()):
self.y.append(numpy.array(other.y[i], dtype="float64"))
self.y.append(numpy.array(other.y[i], dtype="float32"))
if self.uses_statistics(): self.y_square.append(self.y[i] ** 2)
self.set_title(self.__title_pattern % self.n)
@@ -869,12 +869,12 @@ class Accumulation(Errorable, Drawable, DamarisFFT, Signalpath):
self.lock.acquire()
for i in range(self.get_number_of_channels()):
tmp_y.append(numpy.array(-self.y[i], dtype="float64"))
tmp_y.append(numpy.array(-self.y[i], dtype="float32"))
if self.uses_statistics():
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, y_2 = numpy.array(self.y_square), n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = True)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, y_2 = numpy.array(self.y_square), n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = True)
else:
r = Accumulation(x = numpy.array(self.x, dtype="float64"), y = tmp_y, n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = False)
r = Accumulation(x = numpy.array(self.x, dtype="float32"), y = tmp_y, n = self.n, index = self.index, sampl_freq = self.sampling_rate, error = False)
self.lock.release()
return r
@@ -951,7 +951,7 @@ def read_from_hdf(hdf_node):
# now do the real data
accu_data=hdf_node.accu_data.read()
accu.x=numpy.arange(accu_data.shape[0], dtype="float64")/accu.sampling_rate
accu.x=numpy.arange(accu_data.shape[0], dtype="float32")/accu.sampling_rate
# assume error information, todo: save this information explicitly
accu.y_square=[]
accu.use_error=False
@@ -959,7 +959,7 @@ def read_from_hdf(hdf_node):
for ch in range(accu_data.shape[1]/2):
accu.y.append(accu_data[:,ch*2]*accu.n)
if accu.n<2 or numpy.all(accu_data[:,ch*2+1]==0.0):
accu.y_square.append(numpy.zeros((accu_data.shape[0]) ,dtype="float64"))
accu.y_square.append(numpy.zeros((accu_data.shape[0]) ,dtype="float32"))
else:
accu.use_error=True
accu.y_square.append((accu_data[:,ch*2+1]**2)*float((accu.n-1.0)*accu.n)+(accu_data[:,ch*2]**2)*accu.n)
src/data/DataPool.py
+1 -8
View File
@@ -8,18 +8,11 @@ import collections
import threading
import traceback
import io
if sys.version_info.major == 3 and sys.version_info.minor >= 10:
from collections.abc import MutableMapping
else:
from collections import MutableMapping
from . import ADC_Result
from . import Accumulation
from . import MeasurementResult
class DataPool(MutableMapping):
class DataPool(collections.abc.MutableMapping):
"""
dictionary with sending change events
"""
src/data/MeasurementResult.py
+5 -5
View File
@@ -168,7 +168,7 @@ class MeasurementResult(Drawable.Drawable, collections.UserDict):
sorted array of all dictionary entries without Accumulated Value objects with n==0
"""
keys=numpy.array([k for k in list(self.data.keys()) if not (isinstance(self.data[k], AccumulatedValue) and self.data[k].n==0)],
dtype="float64")
dtype="Float64")
keys.sort()
return keys
@@ -177,18 +177,18 @@ class MeasurementResult(Drawable.Drawable, collections.UserDict):
def get_xydata(self):
k=self.get_xdata()
v=numpy.array([self.data[key].mean() for key in k], dtype="float64")
v=numpy.array([self.data[key].mean() for key in k], dtype="Float64")
return [k,v]
def get_errorplotdata(self):
k=self.get_xdata()
v=numpy.array([self.data[key].mean() for key in k], dtype="float64")
e=numpy.array([self.data[key].mean_error() for key in k], dtype="float64")
v=numpy.array([self.data[key].mean() for key in k], dtype="Float64")
e=numpy.array([self.data[key].mean_error() for key in k], dtype="Float64")
return [k,v,e]
def get_lineplotdata(self):
k=self.get_xdata()
v=numpy.array(self.y, dtype="float64")
v=numpy.array(self.y, dtype="Float64")
return [k, v]
def uses_statistics(self):
src/gui/DamarisGUI.py
+16 -21
View File
@@ -24,9 +24,9 @@ gi.require_version('GtkSource', '3.0')
# gui graphics
from gi.repository import GObject as gobject
import sqlite3,uuid
from pkg_resources import parse_version
#gobject.threads_init( )
from gi.repository import Gtk as gtk
gtk_version_missmatch = gtk.check_version( 3, 0, 0 )
@@ -64,10 +64,9 @@ max_points_to_display = 0
import matplotlib.axes
import matplotlib.figure
#for printing issues
#if hasattr( gtk, "PrintOperation" ):
# import matplotlib.backends.backend_cairo
if hasattr( gtk, "PrintOperation" ):
import matplotlib.backends.backend_cairo
print('backend:', matplotlib.get_backend()) # must print GTK3Agg
# import our own stuff
from damaris.gui import ExperimentWriter, ExperimentHandling
from damaris.gui import ResultReader, ResultHandling
@@ -180,7 +179,7 @@ class DamarisGUI:
# my notebook
self.main_notebook = self.xml_gui.get_object( "main_notebook" )
self.log = LogWindow( self.xml_gui, self )
self.log = LogWindow( self.xml_gui , self)
self.sw = ScriptWidgets( self.xml_gui )
@@ -194,7 +193,7 @@ class DamarisGUI:
# lock file to prevent other DAMARIS to start immediatly
self.lockfile = LockFile() # = os.path.expanduser("~/.damaris.lock")
self.id = None
#to stop queued experiments
self.stop_experiment_flag = threading.Event()
@@ -289,7 +288,6 @@ class DamarisGUI:
self.toolbar_pause_button = self.xml_gui.get_object( "toolbar_pause_button" )
# print button
# disabled 2026-02-24
#self.toolbar_print_button = self.xml_gui.get_object( "toolbar_print_button" )
#if not hasattr( gtk, "PrintOperation" ):
# self.toolbar_print_button.set_sensitive( False )
@@ -543,7 +541,7 @@ class DamarisGUI:
for r in still_running:
r.quit_flag.set( )
print("waiting for threads stoping...", end=' ')
still_running = [x for x in [ self.si.exp_handling, self.si.res_handling, self.si.back_driver ] if x is not None and x.is_alive()]
still_running = [x for x in [ self.si.exp_handling, self.si.res_handling, self.si.back_driver ] if x is not None and x.is_alive( )]
for t in still_running:
t.join( )
print("done")
@@ -626,7 +624,7 @@ class DamarisGUI:
r_text = None
b_text = None
if self.si.exp_handling is not None:
if not self.si.exp_handling.is_alive():
if not self.si.exp_handling.is_alive( ):
self.si.exp_handling.join( )
if self.si.exp_handling.raised_exception:
print("experiment script failed at line %d (function %s): %s" % (self.si.exp_handling.location[ 0 ],
@@ -644,7 +642,7 @@ class DamarisGUI:
e_text += experimenttimetext
if self.si.res_handling is not None:
if not self.si.res_handling.is_alive():
if not self.si.res_handling.is_alive( ):
self.si.res_handling.join( )
if self.si.res_handling.raised_exception:
print("result script failed at line %d (function %s): %s" % (self.si.res_handling.location[ 0 ],
@@ -659,7 +657,7 @@ class DamarisGUI:
r_text = "Result Script Running (%d)" % r
if self.si.back_driver is not None:
if not self.si.back_driver.is_alive():
if not self.si.back_driver.is_alive( ):
if self.si.back_driver.raised_exception:
b_text = "Backend Failed"
else:
@@ -673,7 +671,7 @@ class DamarisGUI:
b_text += backendtimetext
if self.dump_thread is not None:
if self.dump_thread.is_alive():
if self.dump_thread.is_alive( ):
sys.stdout.write( "." )
self.dump_dots += 1
if self.dump_dots > 80:
@@ -715,7 +713,7 @@ class DamarisGUI:
return True
else:
if self.save_thread is not None:
if self.save_thread.is_alive():
if self.save_thread.is_alive( ):
sys.stdout.write( "." )
self.dump_dots += 1
if self.dump_dots > 80:
@@ -1088,7 +1086,7 @@ class DamarisGUI:
if requested_doc in self.doc_urls and self.doc_urls[ requested_doc ] is not None:
if self.doc_browser is not None:
if not self.doc_browser.is_alive():
if not self.doc_browser.is_alive( ):
self.doc_browser.join( )
if self.doc_browser.my_webbrowser is not None:
print("new browser tab")
@@ -1151,8 +1149,7 @@ class LogWindow:
self.textview.connect( "key-press-event", self.textview_keypress)
self.textbuffer = self.textview.get_buffer( )
self.logstream = log
print("here i am")
#self.logstream.gui_log = self
self.logstream.gui_log = self
self.last_timetag = None
self( "Started in directory %s\n" % os.getcwd( ) )
@@ -2478,11 +2475,9 @@ class MonitorWidgets:
self.display_table.attach( self.matplot_canvas, 0, 6, 0, 1, gtk.AttachOptions.EXPAND | gtk.AttachOptions.FILL, gtk.AttachOptions.EXPAND | gtk.AttachOptions.FILL, 0, 0 )
self.matplot_canvas.show( )
# Matplot Toolbar hinzufuegen (Display_Table, 2. Zeile)
if parse_version(matplotlib.__version__) >= parse_version("3.6"):
self.matplot_toolbar = matplotlib.backends.backend_gtk3.NavigationToolbar2GTK3( self.matplot_canvas )
else: #
self.matplot_toolbar = matplotlib.backends.backend_gtk3.NavigationToolbar2GTK3( self.matplot_canvas, self.main_window )
# Matplot Toolbar hinzufuegen (Display_Table, 2. Zeile)
self.matplot_toolbar = matplotlib.backends.backend_gtk3.NavigationToolbar2GTK3( self.matplot_canvas,
self.main_window )
self.display_table.attach( self.matplot_toolbar, 0, 1, 1, 2, gtk.AttachOptions.FILL | gtk.AttachOptions.EXPAND, 0, 0, 0 )
self.matplot_toolbar.show( )
src/gui/ResultReader.py
+3 -3
View File
@@ -114,7 +114,7 @@ class ResultReader:
self.result_description = {}
self.in_description_section=True
self.in_description_data=()
for an_item in elem.iter():
for an_item in elem:
self.in_description_data = (an_item.get("key"), an_item.get("type"), an_item.text)
# make item contents to dictionary item:
k,t,v=self.in_description_data
@@ -213,7 +213,7 @@ class ResultReader:
self.adc_result_sample_counter>0:
# fill the ADC_Result with collected data
# x data
self.result.x=numpy.arange(self.adc_result_sample_counter, dtype="float64")/\
self.result.x=numpy.arange(self.adc_result_sample_counter, dtype="float32")/\
self.result.get_sampling_rate()
self.result.y = []
nChannels = self.result.get_nChannels()
@@ -293,7 +293,7 @@ class ResultReader:
self.__filetype == ResultReader.ADCDATA_TYPE and \
self.adc_result_sample_counter>0:
# fill the ADC_Result with collected data
self.result.x=numpy.arange(self.adc_result_sample_counter, dtype="float64")/\
self.result.x=numpy.arange(self.adc_result_sample_counter, dtype="float32")/\
self.result.get_sampling_rate()
self.result.y=[]
self.result.index=[]
src/gui/damaris.xml
+4 -2
View File
@@ -644,6 +644,7 @@ Public License instead of this License.
<property name="visible">True</property>
</object>
</child>
<!--
<child>
<object class="GtkToolButton" id="toolbar_print_button">
@@ -654,8 +655,9 @@ Public License instead of this License.
<packing>
<property name="homogeneous">True</property>
</packing>
</child>
-->
</child>
-->
<child>
<object class="GtkSeparatorToolItem" id="toolbutton2">
<property name="visible">True</property>
src/gui/script_interface.py
+3 -3
View File
@@ -70,7 +70,7 @@ class ScriptInterface:
next_dump_time+=dump_interval
if self.exp_handling is not None:
if not self.exp_handling.isAlive():
if not self.exp_handling.is_alive():
self.exp_handling.join()
if self.exp_handling.raised_exception:
print(": experiment script failed at line %d (function %s): %s"%(self.exp_handling.location[0],
@@ -81,7 +81,7 @@ class ScriptInterface:
self.exp_handling = None
if self.res_handling is not None:
if not self.res_handling.isAlive():
if not self.res_handling.is_alive():
self.res_handling.join()
if self.res_handling.raised_exception:
print(": result script failed at line %d (function %s): %s"%(self.res_handling.location[0],
@@ -92,7 +92,7 @@ class ScriptInterface:
self.res_handling = None
if self.back_driver is not None:
if not self.back_driver.isAlive():
if not self.back_driver.is_alive():
print(": backend finished")
self.back_driver=None
src/tools/goniometer.py
+1 -1
View File
@@ -56,7 +56,7 @@ class goniometer:
def _recv(self):
retstr = self.serial.readline().strip().replace("\x00","")
search_result = re.search(r"<(\d+)>", retstr)
search_result = re.search("<(\d+)>", retstr)
if search_result != None:
angle = float(search_result.group(1))/36.0
self.current_angle = angle
tests/res_test.py
+3
View File
@@ -1,6 +1,9 @@
def result():
accu = Accumulation(error=False)
for num,ts in enumerate(results):
data["accu"] = accu
data["ts %i"%num] = ts+0
data["fft"] = (ts+0).fft()
data["ppm"] = (ts+0).fft().ppm(300e6)
accu+=ts
#print ts