def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
# get scan number and polarization channel from filename
name = ''
fhandle = open(filename, 'r')
fline = fhandle.readline()
while not '[Data]' in fline:
if 'Input file indices:' in fline:
name += fline.split(':')[1].strip()
if 'Extracted states:' in fline:
name += ' (%s)' % (fline.split(':')[1].strip().split(' ')[0])
fline = fhandle.readline()
if not fline:
ShowWarningDialog(
self.parent, 'Could not load the file: ' + filename +
' \nWrong format.\n')
return
try:
load_array = np.loadtxt(fhandle,
delimiter=self.delimiter,
comments=self.comment,
skiprows=self.skip_rows)
except Exception, e:
ShowWarningDialog(
self.parent, 'Could not load the file: ' + filename +
' \nPlease check the format.\n\n numpy.loadtxt' +
' gave the following error:\n' + str(e))
return
def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
try:
load_array = np.loadtxt(filename,
delimiter=self.delimiter,
comments=self.comment,
skiprows=self.skip_rows)
except Exception as e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n numpy.loadtxt'\
+ ' gave the following error:\n' + str(e))
else:
# For the freak case of only one data point
if len(load_array.shape) < 2:
load_array = np.array([load_array])
# Check so we have enough columns
if load_array.shape[1] - 1 < max(self.x_col, self.y_col):
ShowWarningDialog(
self.parent,
'The data file does not contain enough number of columns. It has '
+ str(load_array[1]) +
' columns. Rember that the column index start at zero!')
self.SetStatusText('Could not load data - not enough columns')
return
# The data is set by the default Template.__init__ function
# Know the loaded data goes into *_raw so that they are not
# changed by the transforms
self.data = self.parent.data_cont.get_data()
self.data[data_item_number].x_raw = load_array[:, self.x_col]
self.data[data_item_number].y_raw = load_array[:, self.y_col]
# Check if we have errors in the data - if not handle it with nan's
if load_array.shape[1] - 1 < self.e_col:
self.data[
data_item_number].error_raw = load_array[:, self.
y_col] * np.nan
self.SetStatusText(
'Could not load error column - setting it to nan')
else:
self.data[data_item_number].error_raw = load_array[:,
self.e_col]
# Run the commands on the data - this also sets the x,y, error members of the data item.
self.data[data_item_number].run_command()
self.UpdateDataList()
# Send an update that new data has been loaded
self.SendUpdateDataEvent()
def LoadData(self, data_item_number, filename):
"""LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
"""
try:
datafile = Data(str(filename),
debug=True) # does all the hard work here
except Exception as e:
ShowWarningDialog(
self.parent,
"Could not load the file: " + filename +
" \nPlease check the format.\n\n Stoner.Data" +
" gave the following error:\n" + str(e),
)
else:
# For the freak case of only one data point
try:
if datafile.setas.cols["axes"] == 0:
self.x_col = datafile.find_col(self.x_col)
self.y_col = datafile.find_col(self.y_col)
self.e_col = datafile.find_col(self.e_col)
datafile.etsas(x=self.x_col, y=self.y_col, e=self.e_col)
else:
self.x_col = datafile.setas.cols["xcol"]
self.y_col = datafile.setas.cols["ycol"][0]
if len(datafile.setas.cols["yerr"]) > 0:
self.e_col = datafile.setas.cols["yerr"][0]
else:
datafile.add_column(np.ones(len(datafile)))
datafile.setas[-1] = "e"
except Exception as e:
ShowWarningDialog(
self.parent,
"The data file does not contain" +
"all the columns specified in the opions\n" + e.message,
)
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Know the loaded data goes into *_raw so that they are not
# changed by the transforms
datafile.y = np.where(datafile.y == 0.0, 1e-8, datafile.y)
self.data[data_item_number].x_raw = datafile.x
self.data[data_item_number].y_raw = datafile.y
self.data[data_item_number].error_raw = datafile.e
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
self.data[data_item_number].run_command()
# Send an update that new data has been loaded
self.SendUpdateDataEvent()
def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
# get scan number and polarization channel from filename
name=os.path.basename(filename)[:-4]
fhandle = open(filename, 'r')
fline = fhandle.readline()
while not 'q_z' in fline:
if 'Input file indices:' in fline:
name += fline.split(':')[1].strip()
if 'Extracted states:' in fline:
name += ' (%s)'%(fline.split(':')[1].strip().split(' ')[0])
fline = fhandle.readline()
if not fline:
ShowWarningDialog(self.parent, 'Could not load the file: ' + filename+' \nWrong format.\n')
return
try:
load_array = np.loadtxt(fhandle, delimiter=self.delimiter, comments=self.comment, skiprows=self.skip_rows)
except Exception as e:
ShowWarningDialog(self.parent, 'Could not load the file: ' + filename +
' \nPlease check the format.\n\n numpy.loadtxt' + ' gave the following error:\n' + str(e))
return
else:
# For the freak case of only one data point
if len(load_array.shape) < 2:
load_array = np.array([load_array])
# Check so we have enough columns
if load_array.shape[1] - 1 < max(self.x_col, self.y_col, self.e_col):
ShowWarningDialog(self.parent, 'The data file does not contain' + 'enough number of columns. It has '
+ str(load_array[1]) + ' columns. Rember that the column index start at zero!')
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Know the loaded data goes into *_raw so that they are not
# changed by the transforms
self.data = self.parent.data_cont.get_data()
self.data[data_item_number].x_raw=load_array[:, self.x_col]
self.data[data_item_number].y_raw=load_array[:, self.y_col]
self.data[data_item_number].error_raw=load_array[:, self.e_col]
self.data[data_item_number].set_extra_data('res', load_array[:,self.xe_col], 'res')
# Name the dataset accordign to file name
self.data[data_item_number].name = name
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
self.data[data_item_number].run_command()
# Send an update that new data has been loaded
self.UpdateDataList()
self.SendUpdateDataEvent()
def LoadDataFile(self, selected_items):
''' Called when GenX wants to load data'''
if len(selected_items) == 0:
ShowWarningDialog(self.parent, 'Please select a data set before trying to load a spec file.')
return False
old_data = self.datalist[selected_items[0]].copy()
self.dataset = self.datalist[selected_items[0]]
wizard = wx.wizard.Wizard(self.parent, -1, "Load Spec File",
style = wx.DEFAULT_DIALOG_STYLE|wx.RESIZE_BORDER)
#page1 = TitledPage(wizard, "Page1")
page1 = LoadSpecScanPage(wizard, self,
default_filename = self.specfile_name)
page2 = SelectCountersPage(wizard, self)
page3 = CustomManipulationPage(wizard, self)
page4 = SetNamePage(wizard, self)
wx.wizard.WizardPageSimple_Chain(page1, page2)
wx.wizard.WizardPageSimple_Chain(page2, page3)
wx.wizard.WizardPageSimple_Chain(page3, page4)
wizard.FitToPage(page1)
#print dir(wizard)
#print 'data: ', self.datalist[0].x
if wizard.RunWizard(page1):
return True
else:
self.datalist[selected_items[0]].safe_copy(old_data)
return False
def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
try:
load_array = np.loadtxt(filename,
delimiter=self.delimiter,
comments=self.comment,
skiprows=self.skip_rows)
except Exception as e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n numpy.loadtxt'\
+ ' gave the following error:\n' + str(e))
else:
# For the freak case of only one data point
if len(load_array.shape) < 2:
load_array = np.array([load_array])
# Check so we have enough columns
if load_array.shape[1]-1 < max(self.q_col, self.res_col, \
self.I_col, self.eI_col):
ShowWarningDialog(self.parent, 'The data file does not contain'\
+ 'enough number of columns. It has ' + str(load_array.shape[1])\
+ ' columns. Rember that the column index start at zero!')
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Note that the loaded data goes into *_raw so that they are not
# changed by the transforms
#print load_array
self.data[data_item_number].x_raw = load_array[:, self.q_col]
self.data[data_item_number].y_raw = load_array[:, self.I_col]
self.data[data_item_number].error_raw = load_array[:, self.eI_col]
self.data[data_item_number].set_extra_data(
'res', load_array[:, self.res_col], 'res')
self.data[data_item_number].res = load_array[:, self.res_col] * 1.0
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
self.data[data_item_number].run_command()
#print self.data[data_item_number].x
# Send an update that new data has been loaded
self.SendUpdateDataEvent()
def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
try:
load_array = np.loadtxt(filename, delimiter = self.delimiter,
comments = self.comment, skiprows = self.skip_rows)
except Exception, e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n numpy.loadtxt'\
+ ' gave the following error:\n' + str(e))
def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
try:
datafile = SC.DataFile(
str(filename)) # does all the hard work here
except Exception, e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n Stoner.DataFile'\
+ ' gave the following error:\n' + str(e))
delimiter=self.delimiter,
comments=self.comment,
skiprows=self.skip_rows)
except Exception, e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n numpy.loadtxt'\
+ ' gave the following error:\n' + str(e))
else:
# For the freak case of only one data point
if len(load_array.shape) < 2:
load_array = np.array([load_array])
# Check so we have enough columns
if load_array.shape[1]-1 < max(self.h_col, self.k_col,\
self.l_col, self.I_col, self.eI_col, self.LB_col, self.dL_col):
ShowWarningDialog(self.parent, 'The data file does not contain'\
+ 'enough number of columns. It has ' + str(load_array.shape[1])\
+ ' columns. Rember that the column index start at zero!')
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Note that the loaded data goes into *_raw so that they are not
# changed by the transforms
# Create an record array so we can sort the data properly
data = np.rec.fromarrays([\
load_array[:,self.h_col].round().astype(type(1)),\
load_array[:,self.k_col].round().astype(type(1)),\
load_array[:,self.l_col], load_array[:,self.I_col],\
load_array[:,self.eI_col],\
load_array[:,self.LB_col], load_array[:,self.dL_col]\
],\
'''
try:
datafile = SC.DataFile(
str(filename)) # does all the hard work here
except Exception, e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n Stoner.DataFile'\
+ ' gave the following error:\n' + str(e))
else:
# For the freak case of only one data point
try:
self.x_col = datafile.find_col(self.x_col)
self.y_col = datafile.find_col(self.y_col)
self.e_col = datafile.find_col(self.e_col)
except KeyError:
ShowWarningDialog(self.parent, 'The data file does not contain'\
+ 'all the columns specified in the opions\n')
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Know the loaded data goes into *_raw so that they are not
# changed by the transforms
datafile = SC.AnalyseFile(datafile)
datafile = datafile.apply(
lambda x: x1E - 8 if [self.y_col] == 0.0 else x[self.y_col],
self.y_col,
header=datafile.column_headers[self.y_col]) # clear out zeroes
self.data[data_item_number].x_raw = datafile.column(self.x_col)
self.data[data_item_number].y_raw = datafile.column(self.y_col)
self.data[data_item_number].error_raw = datafile.column(self.e_col)
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
def LoadData(self, data_item_number, filename):
'''LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
'''
try:
load_array = np.loadtxt(filename,
delimiter=self.delimiter,
comments=self.comment,
skiprows=self.skip_rows)
except Exception as e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n numpy.loadtxt'\
+ ' gave the following error:\n' + str(e))
else:
# For the freak case of only one data point
if len(load_array.shape) < 2:
load_array = np.array([load_array])
# Check so we have enough columns
if load_array.shape[1]-1 < max(self.h_col, self.k_col, self.l_col,\
self.I_col, self.eI_col):
ShowWarningDialog(self.parent, 'The data file does not contain'\
+ 'enough number of columns. It has ' + str(load_array.shape[1])\
+ ' columns. Rember that the column index start at zero!')
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Note that the loaded data goes into *_raw so that they are not
# changed by the transforms
# Create an record array so we can sort the data properly
data = np.rec.fromarrays([\
load_array[:,self.h_col].round().astype(type(1)),\
load_array[:,self.k_col].round().astype(type(1)),\
load_array[:,self.l_col], load_array[:,self.I_col],\
load_array[:,self.eI_col]\
],\
names = 'h, k, l, I, eI')
# Sort the data
data.sort(order=('h', 'k', 'l'))
i = 0
while i < len(data):
# Find all the data for each rod
tmp = data.compress(np.bitwise_and(data['h'] == data[i]['h'],\
data['k'] == data[i]['k']))
self.data.add_new('(%i, %i)' % (tmp['h'][0], tmp['k'][0]))
self.data[-1].x_raw = tmp['l']
self.data[-1].y_raw = tmp['I']
self.data[-1].error_raw = tmp['eI']
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
self.data[-1].run_command()
self.data[-1].set_extra_data('h', tmp['h'], 'h')
self.data[-1].set_extra_data('k', tmp['k'], 'k')
# Increase the index
i += len(tmp)
# Update the data list
self.UpdateDataList()
# Send an update that new data has been loaded
self.SendUpdateDataEvent()
