def set_data(self, data):
"""
Set the input dataset and check if data is valid.
Args:
data (Orange.data.table): data instances
"""
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
def settings(data):
# get the default encoded state, replacing the position with Inf
state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
state = {key: (source_ind, np.inf) for key, (source_ind, _) in state.items()}
self.openContext(data.domain)
selected_keys = [key
for key, (sind, _) in self.variable_state.items()
if sind == 0]
if set(selected_keys).issubset(set(state.keys())):
pass
# update the defaults state (the encoded state must contain
# all variables in the input domain)
state.update(self.variable_state)
# ... and restore it with saved positions taking precedence over
# the defaults
selected, other = VariablesSelection.decode_var_state(
state, [list(self.model_selected), list(self.model_other)])
return selected, other
def is_sparse(data):
if data.is_sparse():
self.Error.sparse_data()
data = None
return data
def are_features(data):
domain = data.domain
vars = [var for var in chain(domain.class_vars, domain.metas, domain.attributes)
if var.is_primitive()]
if len(vars) < 3:
self.Error.no_features()
data = None
return data
def are_instances(data):
if len(data) < 2:
self.Error.no_instances()
data = None
return data
self.clear_messages()
self.btn_vizrank.setEnabled(False)
self.closeContext()
self.clear()
self.information()
self.Error.clear()
for f in [sql, is_sparse, are_features, are_instances]:
if data is None:
break
data = f(data)
if data is not None:
self.data = data
self.init_attr_values()
domain = data.domain
vars = [v for v in chain(domain.metas, domain.attributes)
if v.is_primitive()]
self.model_selected[:] = vars[:5]
self.model_other[:] = vars[5:] + list(domain.class_vars)
self.model_selected[:], self.model_other[:] = settings(data)
self._selection = np.zeros(len(data), dtype=np.uint8)
self.invalidate_plot()
else:
self.data = None
def set_data(self, data):
"""
Set the input dataset and check if data is valid.
Args:
data (Orange.data.table): data instances
"""
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
def settings(data):
# get the default encoded state, replacing the position with Inf
state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
state = {
key: (source_ind, np.inf) for key, (source_ind, _) in state.items()
}
self.openContext(data.domain)
selected_keys = [
key for key, (sind, _) in self.variable_state.items() if sind == 0
]
if set(selected_keys).issubset(set(state.keys())):
pass
# update the defaults state (the encoded state must contain
# all variables in the input domain)
state.update(self.variable_state)
# ... and restore it with saved positions taking precedence over
# the defaults
selected, other = VariablesSelection.decode_var_state(
state, [list(self.model_selected), list(self.model_other)]
)
return selected, other
def is_sparse(data):
if data.is_sparse():
self.Error.sparse_data()
data = None
return data
def are_features(data):
domain = data.domain
vars = [
var
for var in chain(domain.class_vars, domain.metas, domain.attributes)
if var.is_primitive()
]
if len(vars) < 3:
self.Error.no_features()
data = None
return data
def are_instances(data):
if len(data) < 2:
self.Error.no_instances()
data = None
return data
self.clear_messages()
self.btn_vizrank.setEnabled(False)
self.closeContext()
self.clear()
self.information()
self.Error.clear()
for f in [sql, is_sparse, are_features, are_instances]:
if data is None:
break
data = f(data)
if data is not None:
self.data = data
self.init_attr_values()
domain = data.domain
vars = [
v for v in chain(domain.metas, domain.attributes) if v.is_primitive()
]
self.model_selected[:] = vars[:5]
self.model_other[:] = vars[5:] + list(domain.class_vars)
self.model_selected[:], self.model_other[:] = settings(data)
self._selection = np.zeros(len(data), dtype=np.uint8)
self.invalidate_plot()
else:
self.data = None
def set_data(self, data):
"""
Set the input dataset.
Args:
data (Orange.data.table): data instances
"""
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
def settings(data):
# get the default encoded state, replacing the position with Inf
state = VariablesSelection.encode_var_state(
[list(self.model_selected),
list(self.model_other)])
state = {
key: (source_ind, np.inf)
for key, (source_ind, _) in state.items()
}
self.openContext(data.domain)
selected_keys = [
key for key, (sind, _) in self.variable_state.items()
if sind == 0
]
if set(selected_keys).issubset(set(state.keys())):
pass
if self.__pending_selection_restore is not None:
self._selection = np.array(self.__pending_selection_restore,
dtype=int)
self.__pending_selection_restore = None
# update the defaults state (the encoded state must contain
# all variables in the input domain)
state.update(self.variable_state)
# ... and restore it with saved positions taking precedence over
# the defaults
selected, other = VariablesSelection.decode_var_state(
state, [list(self.model_selected),
list(self.model_other)])
return selected, other
self.closeContext()
self.clear()
self.Warning.no_cont_features.clear()
self.information()
data = sql(data)
if data is not None:
domain = data.domain
vars = [
var for var in chain(domain.variables, domain.metas)
if var.is_continuous
]
if not len(vars):
self.Warning.no_cont_features()
data = None
self.data = data
self.init_attr_values()
if data is not None and len(data):
self._initialize(data)
self.model_selected[:], self.model_other[:] = settings(data)
self.vizrank.stop_and_reset()
self.vizrank.attrs = self.data.domain.attributes if self.data is not None else []
def set_data(self, data):
"""
Set the input dataset.
Args:
data (Orange.data.table): data instances
"""
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
def settings(data):
# get the default encoded state, replacing the position with Inf
state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
state = {key: (source_ind, np.inf) for key, (source_ind, _) in state.items()}
self.openContext(data.domain)
selected_keys = [key for key, (sind, _) in self.variable_state.items() if sind == 0]
if set(selected_keys).issubset(set(state.keys())):
pass
if self.__pending_selection_restore is not None:
self._selection = np.array(self.__pending_selection_restore, dtype=int)
self.__pending_selection_restore = None
# update the defaults state (the encoded state must contain
# all variables in the input domain)
state.update(self.variable_state)
# ... and restore it with saved positions taking precedence over
# the defaults
selected, other = VariablesSelection.decode_var_state(
state, [list(self.model_selected), list(self.model_other)])
return selected, other
self.closeContext()
self.clear()
self.Warning.no_cont_features.clear()
self.information()
data = sql(data)
if data is not None:
domain = data.domain
vars = [var for var in chain(domain.variables, domain.metas) if var.is_continuous]
if not len(vars):
self.Warning.no_cont_features()
data = None
self.data = data
self.init_attr_values()
if data is not None and len(data):
self._initialize(data)
self.model_selected[:], self.model_other[:] = settings(data)
self.vizrank.stop_and_reset()
self.vizrank.attrs = self.data.domain.attributes if self.data is not None else []
