def Load_and_init_Viewer(self):
if self.debug:
print("function Viewer_Ini called")
# retrieve or initialize directory path
settings = QSettings()
dir_path = settings.value('dir_name', os.path.curdir)
# load a table directly
df, err_msg, dir_path = util.load_data(dir_path, self.debug)
if err_msg == 'cancelled':
return
else:
# save the last directory
settings.setValue('dir_name', dir_path)
if err_msg:
msgBox = QMessageBox()
msgBox.setWindowTitle('Data Import Error')
msgBox.setText(err_msg)
msgBox.setDetailedText(
'''Have a look at the example data directory at\n
github.com/tensionhead/pyBOAT''')
msgBox.exec()
return
self.nViewers += 1
# initialize new DataViewer with the loaded data
self.DataViewers[self.nViewers] = DataViewer(data=df,
pos_offset=self.nViewers *
20,
debug=self.debug)
def Load_and_init_Viewer(self):
if self.debug:
print("function Viewer_Ini called")
# load a table directly
df, err_msg = load_data(self.debug)
if err_msg:
self.error = MessageWindow(err_msg, "Loading error")
return
self.nViewers += 1
# initialize new DataViewer with the loaded data
self.DataViewers[self.nViewers] = DataViewer(data=df, debug=self.debug)
def import_file(self):
"""
Reads the values from the config grid
and prepares kwargs for the pandas read_... functions
NaN interpolation is done here if requested
"""
kwargs = {}
if self.cb_header.isChecked():
header = None # pandas will assign numeric column names
else:
header = "infer"
if not self.cb_use_ext.isChecked():
sep = self.sep_edit.text()
# empty field
if sep == "":
sep = None
kwargs["sep"] = sep
if self.debug:
print(f"Separator is {sep}, with type {type(sep)}")
NaN_value = self.NaN_edit.text()
# empty field
if NaN_value == "":
NaN_value = None
if self.debug:
print(f"NaN value is {NaN_value}, with type {type(NaN_value)}")
# assemble key-words for pandas read_... functions
kwargs["header"] = header
kwargs["na_values"] = NaN_value
if self.debug:
print(f"kwargs for load_data: {kwargs}")
# -----------------------------------------------------
df, err_msg = load_data(debug=self.debug, **kwargs)
if err_msg:
self.error = MessageWindow(err_msg, "Loading error")
return
# -----------------------------------------------------
if self.cb_NaN.isChecked():
N_NaNs = df.isna().to_numpy().sum()
if N_NaNs > 0:
msg = f"Found {N_NaNs} missing values in total\nlinearly interpolating through.."
self.Interpolation = MessageWindow(msg, "NaN Interpolation")
else:
self.Interpolation = MessageWindow("No missing values found!",
"NaN Interpolation")
name = df.name
df = interpol_NaNs(df)
df.name = name # restore name
# initialize new DataViewer with the loaded data
# doesn't help as ini window gets destroyed..
self.parent.DataViewers[self.parent.nViewers] = DataViewer(
data=df, debug=self.debug)
self.parent.nViewers += 1
self.close()
def import_file(self):
"""
Reads the values from the config grid
and prepares kwargs for the pandas read_... functions
NaN interpolation is done here if requested
"""
kwargs = {}
if self.cb_header.isChecked():
header = None # pandas will assign numeric column names
else:
header = "infer"
if not self.cb_use_ext.isChecked():
sep = self.sep_edit.text()
# empty field
if sep == "":
sep = None
kwargs["sep"] = sep
if self.debug:
print(f"Separator is {sep}, with type {type(sep)}")
NaN_value = self.NaN_edit.text()
# empty field
if NaN_value == "":
NaN_value = None
if self.debug:
print(f"NaN value is {NaN_value}, with type {type(NaN_value)}")
# assemble key-words for pandas read_... functions
kwargs["header"] = header
kwargs["na_values"] = NaN_value
if self.debug:
print(f"kwargs for load_data: {kwargs}")
# retrieve or initialize directory path
settings = QSettings()
dir_path = settings.value('dir_name', os.path.curdir)
# -----------------------------------------------------
df, err_msg, dir_path = util.load_data(dir_path,
debug=self.debug,
**kwargs)
if err_msg != 'cancelled':
# save the last directory
settings.setValue('dir_name', dir_path)
elif err_msg == 'cancelled':
return
if err_msg:
msgBox = QMessageBox()
msgBox.setWindowTitle('Data Import Error')
msgBox.setText(err_msg)
msgBox.exec()
return
# -----------------------------------------------------
if self.cb_NaN.isChecked():
N_NaNs = df.isna().to_numpy().sum()
if N_NaNs > 0:
msg = f"Found {N_NaNs} missing values in total\nlinearly interpolating through.."
msgBox = QMessageBox()
msgBox.setWindowTitle('NaNs detected')
msgBox.setText(msg)
msgBox.exec()
else:
msgBox = QMessageBox()
msgBox.setWindowTitle("NaN Interpolation")
msgBox.setText("No missing values found!")
msgBox.exec()
name = df.name
df = util.interpol_NaNs(df)
df.name = name # restore name
# initialize new DataViewer with the loaded data
self.parent.nViewers += 1
self.parent.DataViewers[self.parent.nViewers] = DataViewer(
data=df, pos_offset=self.parent.nViewers * 20, debug=self.debug)
self.close()