Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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66 lines
1.3 KiB
66 lines
1.3 KiB
4 years ago
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import pytest
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import pandas.util._test_decorators as td
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import pandas._testing as tm
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from pandas.io.parsers import read_csv
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@pytest.fixture
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def frame(float_frame):
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"""
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Returns the first ten items in fixture "float_frame".
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"""
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return float_frame[:10]
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@pytest.fixture
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def tsframe():
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return tm.makeTimeDataFrame()[:5]
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@pytest.fixture(params=[True, False])
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def merge_cells(request):
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return request.param
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@pytest.fixture
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def df_ref(datapath):
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"""
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Obtain the reference data from read_csv with the Python engine.
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"""
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filepath = datapath("io", "data", "csv", "test1.csv")
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df_ref = read_csv(filepath, index_col=0, parse_dates=True, engine="python")
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return df_ref
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@pytest.fixture(params=[".xls", ".xlsx", ".xlsm", ".ods", ".xlsb"])
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def read_ext(request):
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"""
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Valid extensions for reading Excel files.
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"""
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return request.param
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@pytest.fixture(autouse=True)
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def check_for_file_leaks():
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"""
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Fixture to run around every test to ensure that we are not leaking files.
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See also
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--------
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_test_decorators.check_file_leaks
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"""
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# GH#30162
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psutil = td.safe_import("psutil")
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if not psutil:
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yield
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else:
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proc = psutil.Process()
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flist = proc.open_files()
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yield
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flist2 = proc.open_files()
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assert flist == flist2
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