本文整理汇总了Python中Orange.data.Table.sample_time方法的典型用法代码示例。如果您正苦于以下问题：Python Table.sample_time方法的具体用法？Python Table.sample_time怎么用？Python Table.sample_time使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Orange.data.Table的用法示例。
在下文中一共展示了Table.sample_time方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: set_train_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_train_data(self, data):
"""
Set the input training dataset.
"""
self.error(0)
self.information(0)
if data and not data.domain.class_var:
self.error(0, "Train data input requires a class variable")
data = None
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.information(0, "Train data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.warning(4)
self.train_data_missing_vals = data is not None and \
np.isnan(data.Y).any()
if self.train_data_missing_vals or self.test_data_missing_vals:
self.warning(4, self._get_missing_data_warning(
self.train_data_missing_vals, self.test_data_missing_vals
))
if data:
data = RemoveNaNClasses(data)
self.data = data
self.closeContext()
if data is not None:
self._update_class_selection()
self.openContext(data.domain.class_var)
self._invalidate()示例2: set_test_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_test_data(self, data):
"""
Set the input separate testing dataset.
"""
self.error(1)
self.information(1)
if data and not data.domain.class_var:
self.error(1, "Test data input requires a class variable")
data = None
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.information(1, "Test data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.warning(4)
self.test_data_missing_vals = data is not None and \
np.isnan(data.Y).any()
if self.train_data_missing_vals or self.test_data_missing_vals:
self.warning(4, self._get_missing_data_warning(
self.train_data_missing_vals, self.test_data_missing_vals
))
if data:
data = RemoveNaNClasses(data)
self.test_data = data
if self.resampling == OWTestLearners.TestOnTest:
self._invalidate()示例3: set_train_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_train_data(self, data):
"""
Set the input training dataset.
Parameters
----------
data : Optional[Orange.data.Table]
"""
self.Information.data_sampled.clear()
self.Error.train_data_empty.clear()
self.Error.class_required.clear()
self.Error.too_many_classes.clear()
self.Error.no_class_values.clear()
self.Error.only_one_class_var_value.clear()
if data is not None and not len(data):
self.Error.train_data_empty()
data = None
if data:
conds = [not data.domain.class_vars,
len(data.domain.class_vars) > 1,
np.isnan(data.Y).all(),
data.domain.has_discrete_class and len(data.domain.class_var.values) == 1]
errors = [self.Error.class_required,
self.Error.too_many_classes,
self.Error.no_class_values,
self.Error.only_one_class_var_value]
for cond, error in zip(conds, errors):
if cond:
error()
data = None
break
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.Information.data_sampled()
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.train_data_missing_vals = \
data is not None and np.isnan(data.Y).any()
if self.train_data_missing_vals or self.test_data_missing_vals:
self.Warning.missing_data(self._which_missing_data())
if data:
data = HasClass()(data)
else:
self.Warning.missing_data.clear()
self.data = data
self.closeContext()
self._update_scorers()
self._update_controls()
if data is not None:
self._update_class_selection()
self.openContext(data.domain)
if self.fold_feature_selected and bool(self.feature_model):
self.resampling = OWTestLearners.FeatureFold
self._invalidate()示例4: set_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_data(self, data):
self.closeContext()
self.clear_messages()
self.clear()
self.information()
self.data = None
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.information("Data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
if isinstance(data, Table):
if len(data.domain.attributes) == 0:
self.Error.no_features()
self.clear_outputs()
return
if len(data) == 0:
self.Error.no_instances()
self.clear_outputs()
return
self.openContext(data)
self._init_projector()
self.data = data
self.fit()示例5: set_test_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_test_data(self, data):
"""
Set the input separate testing dataset.
"""
self.Information.test_data_sampled.clear()
if data and not data.domain.class_var:
self.Error.class_required()
data = None
else:
self.Error.class_required_test.clear()
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.Information.test_data_sampled()
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.test_data_missing_vals = data is not None and np.isnan(data.Y).any()
if self.train_data_missing_vals or self.test_data_missing_vals:
self.Warning.missing_data(self._which_missing_data())
if data:
data = RemoveNaNClasses(data)
else:
self.Warning.missing_data.clear()
self.test_data = data
if self.resampling == OWTestLearners.TestOnTest:
self._invalidate()示例6: set_train_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_train_data(self, data):
"""
Set the input training dataset.
"""
self.Information.data_sampled.clear()
if data and not data.domain.class_var:
self.Error.class_required()
data = None
else:
self.Error.class_required.clear()
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.Information.data_sampled()
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.train_data_missing_vals = data is not None and np.isnan(data.Y).any()
if self.train_data_missing_vals or self.test_data_missing_vals:
self.Warning.missing_data(self._which_missing_data())
if data:
data = RemoveNaNClasses(data)
else:
self.Warning.missing_data.clear()
self.data = data
self.closeContext()
if data is not None:
self._update_class_selection()
self.openContext(data.domain.class_var)
self._invalidate()示例7: set_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_data(self, data):
self.information(1)
self.__timer.stop()
self.sampling.setVisible(False)
self.sql_data = None
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.information(1, "Large SQL table (showing a sample)")
self.sql_data = data
data_sample = data.sample_time(0.8, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
self.sampling.setVisible(True)
if self.auto_sample:
self.__timer.start()
if data is not None and (len(data) == 0 or len(data.domain) == 0):
data = None
if self.data and data and self.data.checksum() == data.checksum():
return
self.closeContext()
same_domain = self.data and data and data.domain.checksum() == self.data.domain.checksum()
self.data = data
self.data_metas_X = self.move_primitive_metas_to_X(data)
if not same_domain:
self.init_attr_values()
self.vizrank._initialize()
self.vizrank_button.setEnabled(
self.data is not None and self.data.domain.class_var is not None and len(self.data.domain.attributes) > 1
)
self.openContext(self.data)示例8: set_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_data(self, data):
self.information(1)
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.information(1, "Data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
if data is not None and (len(data) == 0 or len(data.domain) == 0):
data = None
if self.data and data and self.data.checksum() == data.checksum():
return
self.closeContext()
same_domain = \
self.data and data and \
data.domain.checksum() == self.data.domain.checksum()
self.data = data
self.data_metas_X = self.move_primitive_metas_to_X(data)
# TODO: adapt scatter plot to work on SqlTables (avoid use of X and Y)
if isinstance(self.data, SqlTable):
self.data.download_data()
if not same_domain:
self.init_attr_values()
self.vizrank._initialize()
self.vizrank_button.setEnabled(
self.data is not None and self.data.domain.class_var is not None
and len(self.data.domain.attributes) > 1)
self.openContext(self.data)示例9: set_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_data(self, data):
self.clear_messages()
self.Information.sampled_sql.clear()
self.__timer.stop()
self.sampling.setVisible(False)
self.sql_data = None
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.Information.sampled_sql()
self.sql_data = data
data_sample = data.sample_time(0.8, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
self.sampling.setVisible(True)
if self.auto_sample:
self.__timer.start()
if data is not None and (len(data) == 0 or len(data.domain) == 0):
data = None
if self.data and data and self.data.checksum() == data.checksum():
return
self.closeContext()
same_domain = (self.data and data and
data.domain.checksum() == self.data.domain.checksum())
self.data = data
if not same_domain:
self.init_attr_values()
self.openContext(self.data)
self._vizrank_color_change()
def findvar(name, iterable):
"""Find a Orange.data.Variable in `iterable` by name"""
for el in iterable:
if isinstance(el, Orange.data.Variable) and el.name == name:
return el
return None
# handle restored settings from < 3.3.9 when attr_* were stored
# by name
if isinstance(self.attr_x, str):
self.attr_x = findvar(self.attr_x, self.xy_model)
if isinstance(self.attr_y, str):
self.attr_y = findvar(self.attr_y, self.xy_model)
if isinstance(self.graph.attr_label, str):
self.graph.attr_label = findvar(
self.graph.attr_label, self.graph.gui.label_model)
if isinstance(self.graph.attr_color, str):
self.graph.attr_color = findvar(
self.graph.attr_color, self.graph.gui.color_model)
if isinstance(self.graph.attr_shape, str):
self.graph.attr_shape = findvar(
self.graph.attr_shape, self.graph.gui.shape_model)
if isinstance(self.graph.attr_size, str):
self.graph.attr_size = findvar(
self.graph.attr_size, self.graph.gui.size_model)示例10: sql
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def sql(data):
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.information("Data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
return data示例11: sql
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def sql(data):
self.Information.sql_sampled_data.clear()
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.Information.sql_sampled_data()
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
return data示例12: set_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_data(self, data):
self.information(0)
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
elif not remotely:
self.information(0, "Data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
self.data = data
self.fit()示例13: set_test_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_test_data(self, data):
# type: (Orange.data.Table) -> None
"""
Set the input separate testing dataset.
Parameters
----------
data : Optional[Orange.data.Table]
"""
self.Information.test_data_sampled.clear()
self.Error.test_data_empty.clear()
if data is not None and not len(data):
self.Error.test_data_empty()
data = None
if data and not data.domain.class_var:
self.Error.class_required_test()
data = None
else:
self.Error.class_required_test.clear()
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.Information.test_data_sampled()
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.test_data_missing_vals = \
data is not None and np.isnan(data.Y).any()
if self.train_data_missing_vals or self.test_data_missing_vals:
self.Warning.missing_data(self._which_missing_data())
if data:
data = HasClass()(data)
else:
self.Warning.missing_data.clear()
self.test_data = data
if self.resampling == OWTestLearners.TestOnTest:
self._invalidate()示例14: set_test_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_test_data(self, data):
"""
Set the input separate testing dataset.
"""
self.error(1)
self.information(1)
if data and not data.domain.class_var:
self.error(1, "Test data input requires a class variable")
data = None
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
else:
self.information(1, "Test data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(AUTO_DL_LIMIT, partial=True)
data = Table(data_sample)
self.test_data = data
if self.resampling == OWTestLearners.TestOnTest:
self._invalidate()示例15: set_data
# 需要导入模块: from Orange.data import Table [as 别名]
# 或者: from Orange.data.Table import sample_time [as 别名]
def set_data(self, data):
self.closeContext()
self.clear_messages()
self.clear()
self.start_button.setEnabled(False)
self.information()
self.data = None
if isinstance(data, SqlTable):
if data.approx_len() < AUTO_DL_LIMIT:
data = Table(data)
elif not remotely:
self.information("Data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
else: # data was big and remote available
self.sampling_box.setVisible(True)
self.start_button.setText("Start remote computation")
self.start_button.setEnabled(True)
if not isinstance(data, SqlTable):
self.sampling_box.setVisible(False)
if isinstance(data, Table):
if len(data.domain.attributes) == 0:
self.Error.no_features()
self.clear_outputs()
return
if len(data) == 0:
self.Error.no_instances()
self.clear_outputs()
return
self.openContext(data)
sparse_data = data is not None and data.is_sparse()
self.normalize_box.setDisabled(sparse_data)
self.update_buttons(sparse_data=sparse_data)
self.data = data
self.fit()