def test_notebook_2018_2019(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
def valid(cell):
if "nuplet[1] = 5" in cell:
return False
if "dico[0] ##" in cell:
return False
if "dico[ [4,6] ] = 6" in cell:
return False
return True
self.assertTrue(src.ensae_teaching_cs is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "notebook_eleves", "2018-2019")
test_notebook_execution_coverage(
__file__,
"",
folder,
valid=valid,
this_module_name="ensae_teaching_cs",
fLOG=fLOG,
copy_files=['titanic.csv/titanic.csv'])
def test_notebook_search_images(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
with redirect_stderr(StringIO()):
try:
from keras.applications.mobilenet import MobileNet # pylint: disable=E0401
assert MobileNet is not None
except (SyntaxError, ModuleNotFoundError) as e:
warnings.warn(
"tensorflow is probably not available yet on python 3.7: {0}"
.format(e))
return
self.assertTrue(mlinsights is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "explore")
test_notebook_execution_coverage(
__file__,
"keras",
folder,
'mlinsights',
copy_files=["data/dog-cat-pixabay.zip"],
fLOG=fLOG)
def test_notebook_maxtrix_dictionary(self):
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "td1a")
test_notebook_execution_coverage(__file__,
"matrix_dictionary",
folder,
this_module_name="ensae_teaching_cs",
fLOG=fLOG)
def test_run_slide(self):
fLOG(__file__, self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(python3_module_template is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks")
test_notebook_execution_coverage(
__file__, "slide", folder, 'python3_module_template', copy_files=[], fLOG=fLOG)
def test_notebook_(self):
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "td2a_ml")
test_notebook_execution_coverage(__file__,
"ml_lasso_rf_grid_search",
folder,
this_module_name="ensae_teaching_cs",
fLOG=fLOG)
def test_notebook_data_irep(self):
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "data")
test_notebook_execution_coverage(__file__,
"irep",
folder,
this_module_name="ensae_teaching_cs",
fLOG=fLOG)
def test_notebook_search_images(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(mlinsights is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "explore")
test_notebook_execution_coverage(__file__, "torch", folder, 'mlinsights',
copy_files=["data/dog-cat-pixabay.zip"], fLOG=fLOG)
def test_notebook_expose_reduce(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(sparkouille is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "expose")
test_notebook_execution_coverage(__file__, "reduce", folder,
this_module_name="sparkouille", fLOG=fLOG)
def test_notebook_search(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(papierstat is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "lectures")
test_notebook_execution_coverage(
__file__, "search", folder, 'papierstat', copy_files=[], fLOG=fLOG)
def test_notebook_example_pyquickhelper(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks")
test_notebook_execution_coverage(__file__, "compare_python_distribution", folder,
'pyquickhelper', fLOG=fLOG,
copy_files=["README.txt"])
def test_notebook_tsp(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(ensae_teaching_cs is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "expose")
test_notebook_execution_coverage(__file__, "TSP", folder,
this_module_name="ensae_teaching_cs", fLOG=fLOG)
def test_notebook_torch_perceptron_convolution_mnist(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(ensae_teaching_dl is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "101")
test_notebook_execution_coverage(__file__, "300_Convolution", folder,
this_module_name="ensae_teaching_dl", fLOG=fLOG)
def test_notebook_tsp(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(ensae_teaching_cs is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "1a")
test_notebook_execution_coverage(__file__, "coloriage", folder,
this_module_name="ensae_teaching_cs", fLOG=fLOG)
def test_notebook_onnx_pdist(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertNotEmpty(mlprodict is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks")
test_notebook_execution_coverage(__file__, "onnx_operator_cost", folder,
this_module_name="mlprodict", fLOG=fLOG)
def test_notebook_quantile(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(mlinsights is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "sklearn")
test_notebook_execution_coverage(
__file__, "quantile", folder, 'mlinsights', fLOG=fLOG)
def test_notebook_artificiel(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(pandas_streaming is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks")
test_notebook_execution_coverage(
__file__, "first_steps", folder, 'pandas_streaming', copy_files=[], fLOG=fLOG)
def test_notebook_sklearn(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(jupytalk is not None)
self.assertTrue(jyquickhelper is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "2019", "sklearn")
test_notebook_execution_coverage(
__file__, "sklearn", folder, 'jupytalk', copy_files=[], fLOG=fLOG)
def test_notebook_artificiel(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(papierstat is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "lectures")
test_notebook_execution_coverage(
__file__, "artificiel", folder, 'papierstat', copy_files=[], fLOG=fLOG,
filter_name=lambda n: 'token' not in n and 'multiclass' not in n)
def test_notebook_visualisation_enedis_bokeh(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import pyensae
self.assertTrue(papierstat is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "visualisation")
test_notebook_execution_coverage(
__file__, "enedis_cartes_bokeh", folder, 'papierstat', copy_files=[], fLOG=fLOG,
modules=[pyensae])
def test_notebook_csharp_in_notebook(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(csharpy is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks")
test_notebook_execution_coverage(__file__,
"csharp_in_notebook",
folder,
this_module_name="csharpy",
fLOG=fLOG)
def test_notebook_topk(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertNotEmpty(mlprodict is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks")
to_copy = ["800px-Tour_Eiffel_Wikimedia_Commons_(cropped).jpg"]
test_notebook_execution_coverage(__file__, "transfer_learning", folder,
this_module_name="mlprodict", fLOG=fLOG,
copy_files=to_copy)
def test_notebook_pydata_pydy(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import pymyinstall
self.assertTrue(jupytalk is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "2016", "pydata")
test_notebook_execution_coverage(__file__, "pydy", folder,
this_module_name="jupytalk", fLOG=fLOG,
copy_files=["pydy.svg"], modules=[pymyinstall])
def test_notebook_sklearn_grammar(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertNotEmpty(mlprodict is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks")
test_notebook_execution_coverage(__file__,
"sklearn_grammar",
folder,
this_module_name="mlprodict",
fLOG=fLOG,
copy_files=["README.txt"])
def test_notebook_example_pyquickhelper(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(pymlbenchmark is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks")
test_notebook_execution_coverage(__file__,
"context",
folder,
this_module_name="pymlbenchmark",
fLOG=fLOG,
copy_files=["README.txt"])
def test_notebook_artificiel_token(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import nltk
nltk.download('punkt')
nltk.download('stopwords')
self.assertTrue(papierstat is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "lectures")
test_notebook_execution_coverage(
__file__, "artificiel_tokenize", folder, 'papierstat', copy_files=[], fLOG=fLOG)
def test_notebook_msexp_onnx(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import pymyinstall
self.assertTrue(jupytalk is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "2018", "msexp")
files = [_ for _ in os.listdir(
folder) if '.png' in _ or '.csv' in _ or '.jpg' in _]
test_notebook_execution_coverage(__file__, "onnx", folder,
this_module_name="jupytalk", fLOG=fLOG,
copy_files=files, modules=[pymyinstall])
def test_notebook_encours_wines_2019(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(papierstat is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "encours")
test_notebook_execution_coverage(__file__,
"2019",
folder,
'papierstat',
copy_files=[],
fLOG=fLOG,
filter_name=lambda n: "2019" in n)
def test_notebook_training(self):
from pyquickhelper.ipythonhelper import test_notebook_execution_coverage
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(onnxcustom is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks")
test_notebook_execution_coverage(__file__,
"training",
folder,
'onnxcustom',
copy_files=[],
fLOG=fLOG)
def test_notebook_sentiment(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
def valid(cell):
if "dico[0] ##" in cell:
return False
return True
self.assertTrue(ensae_teaching_cs is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "td2a_ml")
test_notebook_execution_coverage(__file__, "sentiment", folder, valid=valid,
this_module_name="ensae_teaching_cs", fLOG=fLOG)
def test_notebook_pydata_pydy(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import pymyinstall
self.assertTrue(jupytalk is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "2016", "pydata")
test_notebook_execution_coverage(__file__,
"pydy",
folder,
this_module_name="jupytalk",
fLOG=fLOG,
copy_files=["pydy.svg"],
modules=[pymyinstall])
def test_run_re2(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import jyquickhelper as jyq # pylint: disable=C0415
self.assertNotEmpty(jyq)
self.assertNotEmpty(wrapclib)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks")
test_notebook_execution_coverage(__file__,
"re2",
folder,
this_module_name='wrapclib',
fLOG=fLOG)
def test_notebook_sql_map_reduce(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
import pymyinstall # pylint: disable=C0415
self.assertTrue(sparkouille is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "sql")
test_notebook_execution_coverage(__file__,
"sql_map_reduce",
folder,
this_module_name="sparkouille",
fLOG=fLOG,
copy_files=["README.txt"],
modules=[pymyinstall])
def test_notebook_lectures_linreg(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(papierstat is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "lectures")
test_notebook_execution_coverage(__file__,
"logreg",
folder,
'papierstat',
copy_files=[],
fLOG=fLOG,
filter_name=lambda n: "" in n,
valid=lambda cell: sys.platform !=
"win32" or "dtreeviz" not in cell)
def test_notebook_logregclus(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
self.assertTrue(mlinsights is not None)
folder = os.path.join(os.path.dirname(__file__), "..", "..", "_doc",
"notebooks", "sklearn")
try:
test_notebook_execution_coverage(__file__,
"logistic_regression_clustering",
folder,
'mlinsights',
fLOG=fLOG)
except Exception as e:
if compare_module_version(sklver, "0.24") < 0:
return
raise e
def test_notebook_2018_2019(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
def valid(cell):
if "nuplet[1] = 5" in cell:
return False
if "dico[0] ##" in cell:
return False
if "dico[ [4,6] ] = 6" in cell:
return False
return True
self.assertTrue(ensae_teaching_cs is not None)
folder = os.path.join(os.path.dirname(__file__),
"..", "..", "_doc", "notebooks", "notebook_eleves", "2018-2019")
test_notebook_execution_coverage(__file__, "", folder, valid=valid,
this_module_name="ensae_teaching_cs", fLOG=fLOG,
copy_files=['titanic.csv/titanic.csv'])
