class Error(widget.OWWidget.Error):
number_of_edges = widget.Msg(
'Estimated number of edges is too high ({})')
class Error(widget.OWWidget.Error):
no_features = widget.Msg("At least 1 feature is required")
no_instances = widget.Msg("At least 1 data instance is required")
sparse_data = widget.Msg("Sparse data is not supported")
class Error(widget.OWWidget.Error):
empty_data = widget.Msg("Empty dataset")
no_disc_vars = widget.Msg("No categorical data")
class Warning(widget.OWWidget.Warning):
model_not_appropriate = widget.Msg(
'Model or its settings are not appropriate for this type of data.')
class Error(widget.OWWidget.Error):
no_vars_selected = widget.Msg('No independent variables selected')
no_class_selected = widget.Msg('No dependent variable selected')
class Warning(widget.OWWidget.Warning):
empty_input = widget.Msg("Empty result on input. Nothing to display.")
class Error(widget.OWWidget.Error):
proj_and_domain_match = widget.Msg(
"Projection and Data domains do not match")
no_valid_data = widget.Msg("No projection due to invalid data")
class Warning(OWAnchorProjectionWidget.Warning):
invalid_embedding = widget.Msg("No projection for selected features")
removed_vars = widget.Msg("Categorical variables with more than"
" two values are not shown.")
max_vars_selected = widget.Msg(
"Maximum number of selected variables reached.")
class Warning(widget.OWWidget.Warning):
topic_precedence = widget.Msg(
'Input signal Topic takes priority over Corpus')
class Warning(widget.OWWidget.Warning):
no_cont_features = widget.Msg("Plotting requires numeric features")
not_enough_components = widget.Msg("Input projection has less than 2 components")
trivial_components = widget.Msg(
"All components of the PCA are trivial (explain 0 variance). "
"Input data is constant (or near constant).")
class Error(widget.OWWidget.Error):
unsupported_extension = widget.Msg(
"Selected extension is not supported.")
class Info(widget.OWWidget.Information):
bow_weights = widget.Msg("Showing bag of words weights.")
class Warning(widget.OWWidget.Warning):
no_silhouettes = widget.Msg(
"Silhouette scores are not computed for >{} samples".format(
SILHOUETTE_MAX_SAMPLES))
not_enough_data = widget.Msg(
"Too few ({}) unique data instances for {} clusters")
class Warning(widget.OWWidget.Warning):
read_error = widget.Msg("{} 无法读取")
class Warning(OWAnchorProjectionWidget.Warning):
removed_features = widget.Msg("Categorical features with more than"
" two values are not shown.")
class Error(OWWidget.Error):
error = widget.Msg("{}")
class Warning(widget.OWWidget.Warning):
duplicate_names = widget.Msg("Duplicate variable names in output.")
class Error(widget.OWWidget.Error):
no_features = widget.Msg("At least 1 feature is required")
no_instances = widget.Msg("At least 1 data instance is required")
class Error(widget.OWWidget.Error):
failed = widget.Msg("Clustering failed\nError: {}")
not_enough_data = widget.Msg(
"Too few ({}) unique data instances for {} clusters")
no_attributes = widget.Msg("Data is missing features.")
class Error(widget.OWWidget.Error):
no_webcam = widget.Msg("Couldn't acquire webcam")
class Error(widget.OWWidget.Error):
unexpected_error = widget.Msg('Unexpected error: {}')
class Error(widget.OWWidget.Error):
need_discrete_data = widget.Msg(
"Need some discrete data to work with.")
no_disc_features = widget.Msg(
"Discrete features required but data has none.")
class Information(widget.OWWidget.Information):
nothing_significant = widget.Msg(
'Chosen parameters reveal no significant groups')
class Warning(widget.OWWidget.Warning):
cont_attrs = widget.Msg(
"Data has continuous attributes which will be skipped.")
err_reg_expression = widget.Msg("Error in {} regular expression: {}")
class Warning(widget.OWWidget.Warning):
trivial_components = widget.Msg(
"All components of the PCA are trivial (explain 0 variance). "
"Input data is constant (or near constant).")
class Error(widget.OWWidget.Error):
file_not_found = widget.Msg("File not found.")
missing_reader = widget.Msg("Missing reader.")
sheet_error = widget.Msg("Error listing available sheets.")
unknown = widget.Msg("Read error:\n{}")
class Warning(widget.OWWidget.Warning):
file_too_big = widget.Msg(
"The file is too large to load automatically."
" Press Reload to load.")
class Error(widget.OWWidget.Error):
duplicate_var_name = widget.Msg("A variable name is duplicated.")
class Error(widget.OWWidget.Error):
no_time_variable = widget.Msg('Data contains no time variable')
class Warning(widget.OWWidget.Warning):
large_number_of_nodes = widget.Msg(
'Large number of nodes/edges; performance will be hindered')
