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 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.adv.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)
page1.Chain(page2).Chain(page3).Chain(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.
'''
# 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 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[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].extra_data_raw[
'xe'] = load_array[:, self.xe_col]
self.data[data_item_number].extra_commands['xe'] = 'xe'
self.data[data_item_number].extra_data_raw[
'ai'] = load_array[:, self.ai_col]
self.data[data_item_number].extra_commands['ai'] = 'ai'
# 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.SendUpdateDataEvent()
self.UpdateDataList()
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, 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]\
],\
names = 'h, k, l, I, eI, LB, dL')
# 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')
self.data[-1].set_extra_data('LB', tmp['LB'], 'LB')
self.data[-1].set_extra_data('dL', tmp['dL'], 'dL')
# Increase the index
i += len(tmp)
# Update the data list
self.UpdateDataList()
# Send an update that new data has been loaded
self.SendUpdateDataEvent()