def set_info(self):
if self.data is not None:
self.info_summary.setText('<b>%s</b> contains %s with %s' % (
self.data.name,
plural('{number} instance{s}', self.model.n_instances),
plural('{number} feature{s}', self.model.n_attributes)
))
self.info_attr.setText(
'<b>Attributes:</b><br>%s' %
self._format_variables_string(self.data.domain.attributes)
)
self.info_class.setText(
'<b>Class variables:</b><br>%s' %
self._format_variables_string(self.data.domain.class_vars)
)
self.info_meta.setText(
'<b>Metas:</b><br>%s' %
self._format_variables_string(self.data.domain.metas)
)
else:
self.info_summary.setText('No data on input.')
self.info_attr.setText('')
self.info_class.setText('')
self.info_meta.setText('')
def set_info(self):
if self.data is not None:
self.info_summary.setText('<b>%s</b> contains %s with %s' % (
self.data.name,
plural('{number} instance{s}', self.model.n_instances),
plural('{number} feature{s}', self.model.n_attributes)
))
self.info_attr.setText(
'<b>Attributes:</b><br>%s' %
self._format_variables_string(self.data.domain.attributes)
)
self.info_class.setText(
'<b>Class variables:</b><br>%s' %
self._format_variables_string(self.data.domain.class_vars)
)
self.info_meta.setText(
'<b>Metas:</b><br>%s' %
self._format_variables_string(self.data.domain.metas)
)
else:
self.info_summary.setText('No data on input.')
self.info_attr.setText('')
self.info_class.setText('')
self.info_meta.setText('')
def _format_variables_string(self, variables):
agg = []
for var_type_name, var_type in [('categorical', DiscreteVariable),
('numeric', ContinuousVariable),
('time', TimeVariable),
('string', StringVariable)]:
# Disable pylint here because a `TimeVariable` is also a
# `ContinuousVariable`, and should be labelled as such. That is why
# it is necessary to check the type this way instead of using
# `isinstance`, which would fail in the above case
var_type_list = [v for v in variables if type(v) is var_type] # pylint: disable=unidiomatic-typecheck
if var_type_list:
shown = var_type in self.model.HIDDEN_VAR_TYPES
agg.append(('%d %s%s' % (len(var_type_list), var_type_name,
['', ' (not shown)'][shown]),
len(var_type_list)))
if not agg:
return 'No variables'
attrs, counts = list(zip(*agg))
if len(attrs) > 1:
var_string = ', '.join(attrs[:-1]) + ' and ' + attrs[-1]
else:
var_string = attrs[0]
return plural('%s variable{s}' % var_string, sum(counts))
def _format_variables_string(self, variables):
agg = []
for var_type_name, var_type in [
('categorical', DiscreteVariable),
('numeric', ContinuousVariable),
('time', TimeVariable),
('string', StringVariable)
]:
# Disable pylint here because a `TimeVariable` is also a
# `ContinuousVariable`, and should be labelled as such. That is why
# it is necessary to check the type this way instead of using
# `isinstance`, which would fail in the above case
var_type_list = [v for v in variables if type(v) is var_type] # pylint: disable=unidiomatic-typecheck
if var_type_list:
shown = var_type in self.model.HIDDEN_VAR_TYPES
agg.append((
'%d %s%s' % (len(var_type_list), var_type_name, ['', ' (not shown)'][shown]),
len(var_type_list)
))
if not agg:
return 'No variables'
attrs, counts = list(zip(*agg))
if len(attrs) > 1:
var_string = ', '.join(attrs[:-1]) + ' and ' + attrs[-1]
else:
var_string = attrs[0]
return plural('%s variable{s}' % var_string, sum(counts))
def _set_report(self, data):
# Attributes are defined in a function called from __init__
# pylint: disable=attribute-defined-outside-init
domain = data.domain
count = self._count
self.data_desc = dd = OrderedDict()
dd["Name"] = self.data_set_name
if SqlTable is not None and isinstance(data, SqlTable):
connection_string = ' '.join(
'{}={}'.format(key, value)
for key, value in data.connection_params.items()
if value is not None and key != 'password')
self.location = "Table '{}', using connection:\n{}"\
.format(data.table_name, connection_string)
dd["Rows"] = data.approx_len()
else:
self.location = "Data is stored in memory"
dd["Rows"] = len(data)
def join_if(items):
return ", ".join(s.format(n) for s, n in items if n)
dd["Features"] = len(domain.attributes) > 0 and join_if((
("{} categorical", count(domain.attributes, DiscreteVariable)),
("{} numeric", count(domain.attributes, ContinuousVariable))
))
if domain.class_var:
name = domain.class_var.name
if domain.class_var.is_discrete:
dd["Target"] = "categorical outcome '{}'".format(name)
else:
dd["Target"] = "numeric target '{}'".format(name)
elif domain.class_vars:
disc_class = count(domain.class_vars, DiscreteVariable)
cont_class = count(domain.class_vars, ContinuousVariable)
tt = ""
if disc_class:
tt += report.plural("{number} categorical outcome{s}", disc_class)
if cont_class:
tt += report.plural("{number} numeric target{s}", cont_class)
dd["Meta attributes"] = len(domain.metas) > 0 and join_if((
("{} categorical", count(domain.metas, DiscreteVariable)),
("{} numeric", count(domain.metas, ContinuousVariable)),
("{} text", count(domain.metas, StringVariable))
))
def _set_report(self, data):
# Attributes are defined in a function called from __init__
# pylint: disable=attribute-defined-outside-init
domain = data.domain
count = self._count
self.data_desc = dd = OrderedDict()
dd["Name"] = self.data_set_name
if SqlTable is not None and isinstance(data, SqlTable):
connection_string = ' '.join(
'{}={}'.format(key, value)
for key, value in data.connection_params.items()
if value is not None and key != 'password')
self.location = "Table '{}', using connection:\n{}"\
.format(data.table_name, connection_string)
dd["Rows"] = data.approx_len()
else:
self.location = "Data is stored in memory"
dd["Rows"] = len(data)
def join_if(items):
return ", ".join(s.format(n) for s, n in items if n)
dd["Features"] = len(domain.attributes) > 0 and join_if((
("{} categorical", count(domain.attributes, DiscreteVariable)),
("{} numeric", count(domain.attributes, ContinuousVariable))
))
if domain.class_var:
name = domain.class_var.name
if domain.class_var.is_discrete:
dd["Target"] = "categorical outcome '{}'".format(name)
else:
dd["Target"] = "numeric target '{}'".format(name)
elif domain.class_vars:
disc_class = count(domain.class_vars, DiscreteVariable)
cont_class = count(domain.class_vars, ContinuousVariable)
tt = ""
if disc_class:
tt += report.plural("{number} categorical outcome{s}", disc_class)
if cont_class:
tt += report.plural("{number} numeric target{s}", cont_class)
dd["Meta attributes"] = len(domain.metas) > 0 and join_if((
("{} categorical", count(domain.metas, DiscreteVariable)),
("{} numeric", count(domain.metas, ContinuousVariable)),
("{} text", count(domain.metas, StringVariable))
))
def send_report(self):
pca = report.bool_str(self.apply_pca)
if self.apply_pca:
pca += report.plural(', {number} component{s}', self.pca_components)
self.report_items((
('PCA preprocessing', pca),
('Metric', METRICS[self.metric_idx][0]),
('k neighbors', self.k_neighbors),
('Resolution', self.resolution),
))
def send_report(self):
pca = report.bool_str(self.apply_pca)
if self.apply_pca:
pca += report.plural(", {number} component{s}", self.pca_components)
self.report_items((
("PCA preprocessing", pca),
("Metric", METRICS[self.metric_idx][0]),
("k neighbors", self.k_neighbors),
("Resolution", self.resolution),
))
def send_report(self):
pca = report.bool_str(self.apply_pca)
if self.apply_pca:
pca += report.plural(', {number} component{s}',
self.pca_components)
self.report_items((
('PCA preprocessing', pca),
('Metric', METRICS[self.metric_idx][0]),
('k neighbors', self.k_neighbors),
('Resolution', self.resolution),
))
def send_report(self):
pca = report.bool_str(self.apply_pca)
if self.apply_pca:
pca += report.plural(", {number} component{s}", self.pca_components)
self.report_items((
("Normalize data", report.bool_str(self.normalize)),
("PCA preprocessing", pca),
("Metric", METRICS[self.metric_idx][0]),
("k neighbors", self.k_neighbors),
("Resolution", self.resolution),
))
def set_info(self):
if self.data is not None:
self.info_summary.setText(
'<b>%s</b>包含%s个具有%s特征的实例' %
(self.data.name, plural('{number}', self.model.n_instances),
plural('{number}', self.model.n_attributes)))
self.info_attr.setText(
'<b>属性:</b><br>%s' %
self._format_variables_string(self.data.domain.attributes))
self.info_class.setText(
'<b>分类变量:</b><br>%s' %
self._format_variables_string(self.data.domain.class_vars))
self.info_meta.setText(
'<b>元变量:</b><br>%s' %
self._format_variables_string(self.data.domain.metas))
else:
self.info_summary.setText('没有输入数据。')
self.info_attr.setText('')
self.info_class.setText('')
self.info_meta.setText('')
def send_report(self):
items = OrderedDict()
for feature in self.featuremodel:
if isinstance(feature, DiscreteDescriptor):
items[feature.name] = "{} (categorical with values {}{})".format(
feature.expression, feature.values,
"; ordered" * feature.ordered)
elif isinstance(feature, ContinuousDescriptor):
items[feature.name] = "{} (numeric)".format(feature.expression)
else:
items[feature.name] = "{} (text)".format(feature.expression)
self.report_items(
report.plural("Constructed feature{s}", len(items)), items)
def send_report(self):
items = OrderedDict()
for feature in self.featuremodel:
if isinstance(feature, DiscreteDescriptor):
items[feature.name] = "{} (categorical with values {}{})".format(
feature.expression, feature.values,
"; ordered" * feature.ordered)
elif isinstance(feature, ContinuousDescriptor):
items[feature.name] = "{} (numeric)".format(feature.expression)
else:
items[feature.name] = "{} (text)".format(feature.expression)
self.report_items(
report.plural("Constructed feature{s}", len(items)), items)
def send_report(self):
items = OrderedDict()
for feature in self.featuremodel:
if isinstance(feature, DiscreteDescriptor):
desc = "categorical"
if feature.values:
desc += " with values " \
+ ", ".join(f"'{val}'" for val in feature.values)
if feature.ordered:
desc += "; ordered"
elif isinstance(feature, ContinuousDescriptor):
desc = "numeric"
elif isinstance(feature, DateTimeDescriptor):
desc = "date/time"
else:
desc = "text"
items[feature.name] = f"{feature.expression} ({desc})"
self.report_items(report.plural("Constructed feature{s}", len(items)),
items)
def data(self, data):
def n_or_none(i):
return i or "(none)"
def count(s, tpe):
return sum(isinstance(x, tpe) for x in s)
def pack_table(info):
return '<table>\n' + "\n".join(
'<tr><td align="right" width="90">%s:</td>\n'
'<td width="40">%s</td></tr>\n' %
(d, textwrap.shorten(str(v), width=30, placeholder="..."))
for d, v in info) + "</table>\n"
if data is None:
self.data_set_size = "No data"
self.features = self.targets = self.meta_attributes = "None"
self.location = ""
self.data_desc = None
self.data_attributes = ""
return
sparseness = [
s for s, m in (("features", data.X_density), ("meta attributes",
data.metas_density),
("targets", data.Y_density)) if m() > 1
]
if sparseness:
sparseness = "<p>Sparse representation: %s</p>" % ", ".join(
sparseness)
else:
sparseness = ""
domain = data.domain
self.data_set_size = pack_table(
(("Rows", '~{}'.format(data.approx_len())),
("Columns", len(domain) + len(domain.metas)))) + sparseness
def update_size():
self.data_set_size = pack_table(
(("Rows", len(data)),
("Columns", len(domain) + len(domain.metas)))) + sparseness
threading.Thread(target=update_size).start()
if not domain.attributes:
self.features = "None"
else:
disc_features = count(domain.attributes, DiscreteVariable)
cont_features = count(domain.attributes, ContinuousVariable)
self.features = pack_table((("Discrete", n_or_none(disc_features)),
("Numeric", n_or_none(cont_features))))
if not domain.metas:
self.meta_attributes = "None"
else:
disc_metas = count(domain.metas, DiscreteVariable)
cont_metas = count(domain.metas, ContinuousVariable)
str_metas = count(domain.metas, StringVariable)
self.meta_attributes = pack_table(
(("Discrete", n_or_none(disc_metas)),
("Numeric", n_or_none(cont_metas)), ("Textual",
n_or_none(str_metas))))
class_var = domain.class_var
if class_var:
if class_var.is_continuous:
self.targets = "Numeric target variable"
else:
self.targets = "Discrete outcome with %i values" % \
len(class_var.values)
elif domain.class_vars:
disc_class = count(domain.class_vars, DiscreteVariable)
cont_class = count(domain.class_vars, ContinuousVariable)
if not cont_class:
self.targets = "Multi-target data,\n%i categorical targets" % \
n_or_none(disc_class)
elif not disc_class:
self.targets = "Multi-target data,\n%i numeric targets" % \
n_or_none(cont_class)
else:
self.targets = "<p>Multi-target data</p>\n" + pack_table(
(("Categorical", disc_class), ("Numeric", cont_class)))
self.data_desc = dd = OrderedDict()
if SqlTable is not None and isinstance(data, SqlTable):
connection_string = ' '.join(
'%s=%s' % (key, value)
for key, value in data.connection_params.items()
if value is not None and key != 'password')
self.location = "Table '%s', using connection:\n%s" % (
data.table_name, connection_string)
dd["Rows"] = data.approx_len()
else:
self.location = "Data is stored in memory"
dd["Rows"] = len(data)
def join_if(items):
return ", ".join(s.format(n) for s, n in items if n)
dd["Features"] = len(domain.attributes) and join_if(
(("{} categorical", disc_features), ("{} numeric", cont_features)))
if domain.class_var:
name = domain.class_var.name
if domain.class_var.is_discrete:
dd["Target"] = "categorical outcome '{}'".format(name)
else:
dd["Target"] = "numeric target '{}'".format(name)
elif domain.class_vars:
tt = ""
if disc_class:
tt += report.plural("{number} categorical outcome{s}",
disc_class)
if cont_class:
tt += report.plural("{number} numeric target{s}", cont_class)
dd["Meta attributes"] = len(domain.metas) > 0 and join_if(
(("{} categorical", disc_metas), ("{} numeric", cont_metas),
("{} textual", str_metas)))
if data.attributes:
self.data_attributes = pack_table(data.attributes.items())
else:
self.data_attributes = ""