def test_save_matrixes(all_dsc):
all_dsc.save_datasets(f_name)
dsto = DatasetContainer()
dsto.read_datasets(f_name)
nm = dsto.get_id_name_map()
mat_ds = dsto[nm[0][0]]
print(mat_ds.values)
def test_save_tree(dsc3):
dsc3.save_datasets(f_name)
dsto = DatasetContainer()
dsto.read_datasets(f_name)
assert len(dsto) == 3
dsnext = DataSet()
with pytest.raises(ValueError):
dsdummy = dsto[dsnext.id]
def prefmap_dsc():
'''Get liking and sensory std. test data sets '''
dsc = DatasetContainer()
for mi in CHEESE:
dsc.add(imp_ds(mi))
return dsc
def conjoint_dsc():
'''Get Conjoint std. test data sets '''
dsc = DatasetContainer()
for mi in CONJOINT:
dsc.add(imp_ds(*mi))
return dsc
def dsc3():
dsl = []
for i in range(3):
name = "Dataset{index}".format(index=i)
dtype = DS_TYPES[i % 2]
ds = DataSet(display_name=name, kind=dtype)
dsl.append(ds)
dst = tuple(dsl)
dsc = DatasetContainer()
dsc.add(*dst)
return dsc
def all_dsc():
'''Data set container/collection mock'''
dsc = DatasetContainer()
# ad = CONJOINT + VINE + CHEESE
ad = CHEESE + CONJOINT
for mi in ad:
dsc.add(imp_ds(mi))
dsc.add(discrete_ds())
dsc.add(discrete_nans_ds())
return dsc
def test_update_propagation(discrete_ds):
# Assemble object graph
dsc = DatasetContainer()
bsp = CalcContainer(dsc=dsc)
bspc = BasicStatPluginController(bsp)
# Verify that empty dsc gives empty selection list
print("Available", bspc.available_ds)
assert len(bspc.available_ds) == 0
# Simulate data set added
dsc.add(discrete_ds)
# Verify that the added data set i available in the selection list
print("Available", bspc.available_ds)
assert len(bspc.available_ds) == 1
# Simulat that data set i selected for computation
bspc.selected_ds.append(bspc.available_ds[0][0])
print("Selected", bspc.selected_ds)
print("Calculations", bspc.model.calculations)
# Simulat removal of data set
del dsc[bspc.available_ds[0][0]]
# Verify that it is also removed from selection list
assert len(bspc.available_ds) == 0
def retrieve_dataset(self,
dataset,
timestamp_min=None,
timestamp_max=None,
time_resolution=None):
"""Retrieve a dataset from the database.
Parameters
----------
dataset : string
The dataset to retrieve from the database. Must be one of the
following:
* timestamp
* heartrate
* intensity
* activity
* steps
timestamp_min : datetime.datetime, None
The lower limit (included) to return data for. If None, no
lower limit will be set.
timestamp_max : datetime.datetime, None
The upper limit (not included) to return data for If None, no
upper limit will be set.
time_resolution : datetime.timedelta, None
The time resolution of the dataset container returned. If None,
the default of 1 minute will be used.
Returns
-------
res : DatasetContainer
The container with the retrieved dataset.
"""
self.query_dataset(dataset,
timestamp_min=timestamp_min,
timestamp_max=timestamp_max)
res = DatasetContainer(dataset, time_resolution=time_resolution)
for ts, val in self.results:
res.append(datetime.fromtimestamp(ts), val)
return res
from dataset_container import DatasetContainer
dsc = DatasetContainer()
dsc.read_datasets('/home/thomas/.config/ConsumerCheck.pkl')
nm = dsc.get_id_name_map()
print(nm)
prefmap_plugin_view = make_plugin_view(
'Prefmap', prefmap_nodes, selection_view, prefmap_view)
if __name__ == '__main__':
print("Prefmap GUI test start")
from tests.conftest import imp_ds
one_branch = False
# Folder, File name, Display name, DS type
ds_C_meta = ('Cheese', 'ConsumerLiking.txt',
'Cheese liking', 'Consumer liking')
ds_S_meta = ('Cheese', 'SensoryData.txt',
'Cheese profiling', 'Descriptive analysis / sensory profiling')
C = imp_ds(ds_C_meta)
S = imp_ds(ds_S_meta)
if one_branch:
prefmap = Prefmap(ds_C=C, ds_S=S)
pc = PrefmapController(prefmap)
test = TestOneNode(one_model=pc)
test.configure_traits(view=dummy_view(prefmap_nodes))
else:
dsc = DatasetContainer()
dsc.add(C)
dsc.add(S)
prefmap = PrefmapCalcContainer(dsc=dsc)
ppc = PrefmapPluginController(prefmap)
ppc.configure_traits(
view=prefmap_plugin_view)
class MainUi(HasTraits):
"""Main application class"""
dsc = DatasetContainer()
# en_advanced = Bool(False)
win_handle = Any()
splash = None
# Object representating the basic stat
basic_stat = Instance(BasicStatPluginController)
# Object representing the PCA and the GUI tab
pca = Instance(PcaPluginController)
# Object representing the Prefmap and the GUI tab
prefmap = Instance(PrefmapPluginController)
# Object representing the PlsrPcr and the GUI tab
plscr = Instance(PlsrPcrPluginController)
# Object representing the Conjoint and the GUI tab
conjoint = Instance(ConjointPluginController)
# Object representing the IndDiff and the GUI tab
ind_diff = Instance(IndDiffPluginController)
# Create an action that open dialog for dataimport
import_action = Action(name='Add &Data set', action='import_data')
# Create an action that exits the application.
exit_action = Action(name='E&xit', action='_on_close')
about_action = Action(name='&About', action='view_about')
user_manual_action = Action(name='&User manual', action='view_user_manual')
close_action = Action(name='&Remove Data sets', action='_close_ds')
advanced_action = Action(name='&Advanced settings',
checked_when='en_advanced',
style='toggle',
action='_toggle_advanced')
def _basic_stat_default(self):
basic_statisitc = BasicStatCalcContainer(dsc=self.dsc)
return BasicStatPluginController(basic_statisitc)
def _pca_default(self):
pca = PcaCalcContainer(dsc=self.dsc)
return PcaPluginController(pca)
def _prefmap_default(self):
prefmap = PrefmapCalcContainer(dsc=self.dsc)
return PrefmapPluginController(prefmap)
def _plscr_default(self):
plscr = PlsrPcrCalcContainer(dsc=self.dsc)
return PlsrPcrPluginController(plscr)
def _conjoint_default(self):
conjoint = ConjointCalcContainer(dsc=self.dsc)
return ConjointPluginController(conjoint)
def _ind_diff_default(self):
ind_diff = IndDiffCalcContainer(dsc=self.dsc)
return IndDiffPluginController(ind_diff)
def _toggle_advanced(self):
self.en_advanced = not self.en_advanced
print(self.en_advanced)
# The main view
traits_ui_view = View(
Group(Item('dsc',
editor=tree_editor,
label="Data sets",
show_label=False),
Item('basic_stat',
editor=InstanceEditor(view=bs_plugin_view),
style='custom',
label="Basic stat liking",
show_label=False),
Item('pca',
editor=InstanceEditor(view=pca_plugin_view),
style='custom',
label="PCA",
show_label=False),
Item('prefmap',
editor=InstanceEditor(view=prefmap_plugin_view),
style='custom',
label="Prefmap",
show_label=False),
Item('plscr',
editor=InstanceEditor(view=plscr_plugin_view),
style='custom',
label="PLSR/PCR",
show_label=False),
Item('conjoint',
editor=InstanceEditor(view=conjoint_plugin_view),
style='custom',
label="Conjoint",
show_label=False),
Item('ind_diff',
editor=InstanceEditor(view=ind_diff_plugin_view),
style='custom',
label="Individual differences",
show_label=False),
layout='tabbed'), # end UI tabs group
resizable=True,
width=1000,
height=600,
title='ConsumerCheck',
menubar=MenuBar(
Menu(
import_action,
close_action,
# exit_action,
name='&File'),
## Menu(advanced_action, name='&Settings'),
Menu(about_action, user_manual_action, name='&Help'),
),
handler=MainViewHandler)
def synth_dsc():
dsc = DatasetContainer()
dsc.add(simple_ds(), discrete_ds(), discrete_nans_ds(), zero_var_ds(),
iris_ds())
return dsc