def test_parse_metadata_df(self):
mini_gctoo = mini_gctoo_for_testing.make()
# convert row_metadata to np.nan
mini_row_meta = mini_gctoo.row_metadata_df.replace([-666, "-666", -666.0], [np.nan, np.nan, np.nan])
logger.debug("mini_row_meta.shape: {}".format(mini_row_meta.shape))
logger.debug("mini_row_meta.index: {}".format(mini_row_meta.index))
logger.debug("mini_row_meta.columns: {}".format(mini_row_meta.columns))
logger.debug("mini_row_meta.dtypes: {}".format(mini_row_meta.dtypes))
gctx_file = h5py.File("functional_tests/mini_gctoo_for_testing.gctx", "r")
row_dset = gctx_file[row_meta_group_node]
col_dset = gctx_file[col_meta_group_node]
# with convert_neg_666
row_df = parse_gctx.parse_metadata_df("row", row_dset, True)
logger.debug("row_df.dtypes: {}".format(row_df.dtypes))
pandas_testing.assert_frame_equal(mini_row_meta, row_df)
# no convert_neg_666
mini_gctoo_with_neg_666 = mini_gctoo_for_testing.make(convert_neg_666=False)
col_df = parse_gctx.parse_metadata_df("col", col_dset, False)
pandas_testing.assert_frame_equal(mini_gctoo_with_neg_666.col_metadata_df, col_df)
# test that ID's are not converted to numeric
expected_rids = [str(i) for i in range(3)]
row_dset = {"id": MockHdf5Dset(expected_rids, str),
"other_meta": MockHdf5Dset(range(3, 6), str)}
r = parse_gctx.parse_metadata_df("row", row_dset, True)
logger.debug("test that ID's are not converted to numeric - r: {}".format(r))
logger.debug("r.index: {}".format(r.index))
self.assertEqual(set(expected_rids), set(r.index))
def test_gct_parsing(self):
# parse in gct, no other arguments
mg1 = mini_gctoo_for_testing.make()
mg2 = parse.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gct"
)
pandas_testing.assert_frame_equal(mg1.data_df, mg2.data_df)
pandas_testing.assert_frame_equal(mg1.row_metadata_df,
mg2.row_metadata_df)
pandas_testing.assert_frame_equal(mg1.col_metadata_df,
mg2.col_metadata_df)
# check convert_neg_666 worked correctly
self.assertTrue(mg2.col_metadata_df["mfc_plate_id"].isnull().all())
# parse w/o convert_neg_666
mg2_alt = parse.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gct",
convert_neg_666=False)
self.assertCountEqual(
mg2_alt.col_metadata_df["mfc_plate_id"].values.tolist(),
[-666] * 6)
# parse in gct with subsetting
my_rid = "LJP007_MCF10A_24H:TRT_CP:BRD-K93918653:3.33"
mg3 = parse.parse(
"cmapPy/pandasGEXpress/tests/functional_tests//mini_gctoo_for_testing.gct",
cidx=[0, 2],
rid=[my_rid])
self.assertEqual(mg3.data_df.shape, (1, 2))
self.assertCountEqual(mg3.data_df.values.flatten().tolist(), [1., 3.])
self.assertEqual(mg3.row_metadata_df.index[0], my_rid)
def test_get_ordered_idx(self):
mg = mini_gctoo_for_testing.make()
# case 1: id_type == None
case1 = parse_gctx.get_ordered_idx(None, [],
mg.row_metadata_df,
sort_idx=True)
self.assertEqual(
case1, list(range(0, 6)),
"Expected ordered idx to be {} but got {}".format(
list(range(0, 6)), case1))
# case 2: id_type == "id"
case2 = parse_gctx.get_ordered_idx(
"id", ['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'],
mg.col_metadata_df,
sort_idx=True)
self.assertEqual(
case2, [4],
"Expected ordered idx to be {} but got {}".format([4], case2))
# case 3: id_type == ridx
case3 = parse_gctx.get_ordered_idx("idx", [5, 1, 3],
mg.col_metadata_df,
sort_idx=True)
self.assertEqual(
case3, [1, 3, 5],
"Expected ordered idx to be {} but got {}".format([1, 3, 5],
case3))
def test_make_specified_size_gctoo(self):
mini_gctoo = mini_gctoo_for_testing.make()
logger.debug("mini gctoo data_df shape: {}".format(
mini_gctoo.data_df.shape))
logger.debug("mini gctoo row_meta shape: {}".format(
mini_gctoo.row_metadata_df.shape))
logger.debug("mini gctoo col_meta shape: {}".format(
mini_gctoo.col_metadata_df.shape))
# case 1: dim isn't 'row' or 'col'
with self.assertRaises(AssertionError) as context:
random_slice.make_specified_size_gctoo(mini_gctoo, 3, "aaaalll")
self.assertEqual(str(context.exception),
"dim specified must be either 'row' or 'col'")
# case 2: row subsetting - happy
row_subset = random_slice.make_specified_size_gctoo(
mini_gctoo, 3, "row")
self.assertEqual(
row_subset.data_df.shape, (3, 6),
"data_df after row slice is incorrect shape: {} vs (3,6)".format(
row_subset.data_df.shape))
self.assertEqual(
row_subset.row_metadata_df.shape, (3, 5),
"row_metadata_df after row slice is incorrect shape: {} vs (3,5)".
format(row_subset.row_metadata_df.shape))
self.assertEqual(
row_subset.col_metadata_df.shape, (6, 5),
"col_metadata_df after row slice is incorrect shape: {} vs (6,5)".
format(row_subset.col_metadata_df.shape))
# case 3: row subsetting - sample subset > og # of samples
with self.assertRaises(AssertionError) as context:
random_slice.make_specified_size_gctoo(mini_gctoo, 30, "row")
self.assertTrue(
"number of entries must be smaller than dimension being subsetted "
in str(context.exception))
# case 4: col subsetting - happy
col_subset = random_slice.make_specified_size_gctoo(
mini_gctoo, 3, "col")
self.assertEqual(
col_subset.data_df.shape, (6, 3),
"data_df after col slice is incorrect shape: {} vs (6,3)".format(
col_subset.data_df.shape))
self.assertEqual(
col_subset.row_metadata_df.shape, (6, 5),
"row_metadata_df after col slice is incorrect shape: {} vs (6, 5)".
format(col_subset.row_metadata_df.shape))
self.assertEqual(
col_subset.col_metadata_df.shape, (3, 5),
"col_metadata_df after col slice is incorrect shape: {} vs (3,5)".
format(col_subset.col_metadata_df.shape))
# case 5: col subsetting - sample subset > og # of samples
with self.assertRaises(AssertionError) as context:
random_slice.make_specified_size_gctoo(mini_gctoo, 7, "col")
self.assertTrue(
"number of entries must be smaller than dimension being subsetted "
in str(context.exception))
def test_parse_metadata_df(self):
mini_gctoo = mini_gctoo_for_testing.make()
# convert row_metadata to np.nan
mini_row_meta = mini_gctoo.row_metadata_df.replace([-666, "-666", -666.0], [np.nan, np.nan, np.nan])
gctx_file = h5py.File("functional_tests/mini_gctoo_for_testing.gctx", "r")
row_dset = gctx_file[row_meta_group_node]
col_dset = gctx_file[col_meta_group_node]
# with convert_neg_666
row_df = parse_gctx.parse_metadata_df("row", row_dset, True)
assert_frame_equal(mini_row_meta, row_df)
# no convert_neg_666
mini_gctoo_with_neg_666 = mini_gctoo_for_testing.make(convert_neg_666=False)
col_df = parse_gctx.parse_metadata_df("col", col_dset, False)
assert_frame_equal(mini_gctoo_with_neg_666.col_metadata_df, col_df)
def test_write_src(self):
# case 1: gctoo obj doesn't have src
mini1 = mini_gctoo_for_testing.make()
mini1.src = None
write_gctx.write(mini1, "no_src_example")
hdf5_file = h5py.File("no_src_example.gctx")
hdf5_src1 = hdf5_file.attrs[write_gctx.src_attr]
hdf5_file.close()
self.assertEqual(hdf5_src1, "no_src_example.gctx")
os.remove("no_src_example.gctx")
# case 2: gctoo obj does have src
mini2 = mini_gctoo_for_testing.make()
write_gctx.write(mini2, "with_src_example.gctx")
hdf5_file = h5py.File("with_src_example.gctx")
hdf5_src2 = hdf5_file.attrs[write_gctx.src_attr]
hdf5_file.close()
self.assertEqual(hdf5_src2, "mini_gctoo.gctx")
os.remove("with_src_example.gctx")
def test_write_version(self):
# TODO @oana refactor this test so it just calls the write_version method
# case 1: gctoo obj doesn't have version
mini1 = mini_gctoo_for_testing.make()
mini1.version = None
fn = "no_version_provided_example.gctx"
write_gctx.write(mini1, fn)
hdf5_file = h5py.File(fn)
hdf5_v1 = hdf5_file.attrs[write_gctx.version_attr]
hdf5_file.close()
self.assertEqual(hdf5_v1, write_gctx.version_number)
os.remove(fn)
# case 2: gctoo obj does have version, but it is not used when writing
mini2 = mini_gctoo_for_testing.make()
mini2.version = "MY_VERSION"
fn = "with_version_provided_example.gctx"
write_gctx.write(mini2, fn)
hdf5_file = h5py.File(fn)
hdf5_v2 = hdf5_file.attrs[write_gctx.version_attr]
hdf5_file.close()
self.assertEqual(hdf5_v2, write_gctx.version_number)
os.remove(fn)
def test_set_metadata_index_and_column_names(self):
mini_gctoo = mini_gctoo_for_testing.make()
mini_gctoo.row_metadata_df.index.name = None
mini_gctoo.row_metadata_df.columns.name = None
mini_gctoo.col_metadata_df.index.name = None
mini_gctoo.col_metadata_df.columns.name = None
# case 1: dim == "row"
parse_gctx.set_metadata_index_and_column_names("row", mini_gctoo.row_metadata_df)
self.assertEqual(mini_gctoo.row_metadata_df.index.name, "rid")
self.assertEqual(mini_gctoo.row_metadata_df.columns.name, "rhd")
# case 2: dim == "col"
parse_gctx.set_metadata_index_and_column_names("col", mini_gctoo.col_metadata_df)
self.assertEqual(mini_gctoo.col_metadata_df.index.name, "cid")
self.assertEqual(mini_gctoo.col_metadata_df.columns.name, "chd")
def test_gct_parsing(self):
# parse in gct, no other arguments
mg1 = mini_gctoo_for_testing.make()
mg2 = parse.parse("functional_tests/mini_gctoo_for_testing.gct")
pandas_testing.assert_frame_equal(mg1.data_df, mg2.data_df)
pandas_testing.assert_frame_equal(mg1.row_metadata_df,
mg2.row_metadata_df)
pandas_testing.assert_frame_equal(mg1.col_metadata_df,
mg2.col_metadata_df)
# check convert_neg_666 worked correctly
self.assertTrue(mg2.col_metadata_df["mfc_plate_id"].isnull().all())
# parse w/o convert_neg_666
mg2_alt = parse.parse("functional_tests/mini_gctoo_for_testing.gct",
convert_neg_666=False)
self.assertFalse(
mg2_alt.col_metadata_df["mfc_plate_id"].isnull().all())
# check unused rid argument handling
with self.assertRaises(Exception) as context:
mg3 = parse.parse("functional_tests/mini_gctoo_for_testing.gct",
rid=["a"])
self.assertTrue(
"parse_gct does not use the argument" in str(context.exception))
# check unused cid argument handling
with self.assertRaises(Exception) as context:
mg4 = parse.parse("functional_tests/mini_gctoo_for_testing.gct",
cid=["a"])
self.assertTrue(
"parse_gct does not use the argument" in str(context.exception))
# check unused ridx argument handling
with self.assertRaises(Exception) as context:
mg5 = parse.parse("functional_tests/mini_gctoo_for_testing.gct",
ridx=[0])
self.assertTrue(
"parse_gct does not use the argument" in str(context.exception))
# check unused cidx argument handling
with self.assertRaises(Exception) as context:
mg6 = parse.parse("functional_tests/mini_gctoo_for_testing.gct",
cidx=[0])
self.assertTrue(
"parse_gct does not use the argument" in str(context.exception))
def test_gctx_parsing(self):
# parse in gctx, no other arguments
mg1 = mini_gctoo_for_testing.make()
mg2 = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx")
pandas_testing.assert_frame_equal(mg1.data_df, mg2.data_df)
pandas_testing.assert_frame_equal(mg1.row_metadata_df, mg2.row_metadata_df)
pandas_testing.assert_frame_equal(mg1.col_metadata_df, mg2.col_metadata_df)
# check convert_neg_666 worked correctly
self.assertTrue(mg2.col_metadata_df["mfc_plate_id"].isnull().all())
# parse w/o convert_neg_666
mg2_alt = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx", convert_neg_666 = False)
self.assertFalse(mg2_alt.col_metadata_df["mfc_plate_id"].isnull().all())
# parsing w/rids & cids specified
test_rids = ['LJP007_MCF10A_24H:TRT_CP:BRD-K93918653:3.33', 'LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666']
test_cids = ['LJP007_MCF7_24H:TRT_POSCON:BRD-A61304759:10']
mg3 = subset_gctoo.subset_gctoo(mg1, rid=test_rids, cid=test_cids)
mg4 = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx",
rid=test_rids, cid=test_cids)
pandas_testing.assert_frame_equal(mg3.data_df, mg4.data_df)
pandas_testing.assert_frame_equal(mg3.row_metadata_df, mg4.row_metadata_df)
pandas_testing.assert_frame_equal(mg3.col_metadata_df, mg4.col_metadata_df)
# parsing w/ridx & cidx specified
mg5 = subset_gctoo.subset_gctoo(mg1, rid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'],
cid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'])
mg6 = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx", ridx=[4], cidx=[4])
pandas_testing.assert_frame_equal(mg5.data_df, mg6.data_df)
pandas_testing.assert_frame_equal(mg5.row_metadata_df, mg6.row_metadata_df)
pandas_testing.assert_frame_equal(mg5.col_metadata_df, mg6.col_metadata_df)
# parsing row metadata only
mg7 = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx", row_meta_only=True)
pandas_testing.assert_frame_equal(mg7, mg1.row_metadata_df)
# parsing col metadata only
mg8 = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx", col_meta_only=True)
pandas_testing.assert_frame_equal(mg8, mg1.col_metadata_df)
# parsing w/multiindex
mg9 = parse.parse("../functional_tests/mini_gctoo_for_testing.gctx", make_multiindex=True)
self.assertTrue(mg9.multi_index_df is not None)
def test_parse(self):
# parse whole thing
mg1 = mini_gctoo_for_testing.make()
mg2 = parse_gctx.parse("functional_tests/mini_gctoo_for_testing.gctx")
assert_frame_equal(mg1.data_df, mg2.data_df)
assert_frame_equal(mg1.row_metadata_df, mg2.row_metadata_df)
assert_frame_equal(mg1.col_metadata_df, mg2.col_metadata_df)
# test with string rid/cid
test_rids = ['LJP007_MCF10A_24H:TRT_CP:BRD-K93918653:3.33','LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666']
test_cids = ['LJP007_MCF7_24H:TRT_POSCON:BRD-A61304759:10']
mg3 = slice_gct.slice_gctoo(mg1, rid=test_rids, cid=test_cids)
mg4 = parse_gctx.parse("functional_tests/mini_gctoo_for_testing.gctx",
rid = test_rids, cid = test_cids)
assert_frame_equal(mg3.data_df, mg4.data_df)
assert_frame_equal(mg3.row_metadata_df, mg4.row_metadata_df)
assert_frame_equal(mg3.col_metadata_df, mg4.col_metadata_df)
# first, make & write out temp version of mini_gctoo with int rids/cids
new_mg = mini_gctoo_for_testing.make(convert_neg_666=False)
int_indexed_data_df = new_mg.data_df.copy()
int_indexed_data_df.index = range(0,6)
int_indexed_data_df.columns = range(10,16)
int_indexed_row_meta = new_mg.row_metadata_df.copy()
int_indexed_row_meta.index = range(0,6)
int_indexed_col_meta = new_mg.col_metadata_df.copy()
int_indexed_col_meta.index = range(10,16)
int_indexed_gctoo = GCToo.GCToo(data_df = int_indexed_data_df, row_metadata_df = int_indexed_row_meta,
col_metadata_df = int_indexed_col_meta)
write_gctx.write(int_indexed_gctoo, "int_indexed_mini_gctoo.gctx")
# test with numeric (repr as string) rid/cid
mg5 = GCToo.GCToo(data_df = int_indexed_data_df, row_metadata_df = int_indexed_row_meta,
col_metadata_df = int_indexed_col_meta)
mg5 = slice_gct.slice_gctoo(mg5, row_bool = [True, False, True, False, True, False],
col_bool = [True, False, False, True, True, True])
mg5.data_df.index.name = "rid"
mg5.data_df.columns.name = "cid"
mg5.row_metadata_df.index.name = "rid"
mg5.row_metadata_df.columns.name = "rhd"
mg5.col_metadata_df.index.name = "cid"
mg5.col_metadata_df.columns.name = "chd"
mg6 = parse_gctx.parse("int_indexed_mini_gctoo.gctx", rid = [0, 2, 4],
cid = [10,13,14,15], convert_neg_666=False)
os.remove("int_indexed_mini_gctoo.gctx")
assert_frame_equal(mg5.data_df, mg6.data_df)
assert_frame_equal(mg5.row_metadata_df, mg6.row_metadata_df)
assert_frame_equal(mg5.col_metadata_df, mg6.col_metadata_df)
# test with ridx/cidx
mg7 = slice_gct.slice_gctoo(mg1, rid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'],
cid='LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666')
mg8 = parse_gctx.parse("functional_tests/mini_gctoo_for_testing.gctx", ridx=[4], cidx=[4])
assert_frame_equal(mg7.data_df, mg8.data_df)
assert_frame_equal(mg7.row_metadata_df, mg8.row_metadata_df)
assert_frame_equal(mg7.col_metadata_df, mg8.col_metadata_df)
# test with rid/cidx
mg9 = parse_gctx.parse("functional_tests/mini_gctoo_for_testing.gctx", rid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'],
cidx = [4])
assert_frame_equal(mg7.data_df, mg9.data_df)
assert_frame_equal(mg7.row_metadata_df, mg9.row_metadata_df)
assert_frame_equal(mg7.col_metadata_df, mg9.col_metadata_df)
# test with ridx/cid
mg10 = parse_gctx.parse("functional_tests/mini_gctoo_for_testing.gctx", ridx=[4],
cid = ['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'])
assert_frame_equal(mg7.data_df, mg10.data_df)
assert_frame_equal(mg7.row_metadata_df, mg10.row_metadata_df)
assert_frame_equal(mg7.col_metadata_df, mg10.col_metadata_df)
def test_write_metadata(self):
"""
CASE 1:
- write metadata (has '-666') to file, do not convert -666
- parse in written metadata, don't convert -666
"""
mini_gctoo = mini_gctoo_for_testing.make(convert_neg_666=False)
hdf5_writer = h5py.File(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx", "w")
write_gctx.write_metadata(hdf5_writer, "row", mini_gctoo.row_metadata_df, False, 6)
write_gctx.write_metadata(hdf5_writer, "col", mini_gctoo.col_metadata_df, False, 6)
hdf5_writer.close()
logger.debug("Wrote mini_gctoo_metadata.gctx to {}".format(
os.path.join(FUNCTIONAL_TESTS_PATH, "mini_gctoo_metadata.gctx")))
# read in written metadata, then close and delete file
mini_gctoo_col_metadata = parse_gctx.get_column_metadata(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx",
convert_neg_666=False)
mini_gctoo_row_metadata = parse_gctx.get_row_metadata(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx",
convert_neg_666=False)
os.remove(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx")
# check row metadata
self.assertTrue(set(mini_gctoo.row_metadata_df.columns) == set(mini_gctoo_row_metadata.columns),
"Mismatch between expected row metadata columns {} and column values written to file: {}".format(
mini_gctoo.row_metadata_df.columns, mini_gctoo_row_metadata.columns))
self.assertTrue(set(mini_gctoo.row_metadata_df.index) == set(mini_gctoo.col_metadata_df.index),
"Mismatch between expect row metadata index {} and index values written to file: {}".format(
mini_gctoo.row_metadata_df.index, mini_gctoo_row_metadata.index))
for c in list(mini_gctoo.row_metadata_df.columns):
logger.debug("C1: For column name: {}".format(c))
logger.debug("C1: populated values: {}".format(set(mini_gctoo_row_metadata[c])))
logger.debug("C1: mini_gctoo values: {}".format(set(mini_gctoo.row_metadata_df[c])))
self.assertTrue(set(mini_gctoo.row_metadata_df[c]) == set(mini_gctoo_row_metadata[c]),
"Values in column {} differ between expected metadata and written row metadata: {} vs {}".format(
c, set(mini_gctoo.row_metadata_df[c]), set(mini_gctoo_row_metadata[c])))
# check col metadata
self.assertTrue(set(mini_gctoo.col_metadata_df.columns) == set(mini_gctoo_col_metadata.columns),
"Mismatch between expected col metadata columns {} and column values written to file: {}".format(
mini_gctoo.col_metadata_df.columns, mini_gctoo_col_metadata.columns))
self.assertTrue(set(mini_gctoo.col_metadata_df.index) == set(mini_gctoo.col_metadata_df.index),
"Mismatch between expect col metadata index {} and index values written to file: {}".format(
mini_gctoo.col_metadata_df.index, mini_gctoo_col_metadata.index))
for c in list(mini_gctoo.col_metadata_df.columns):
self.assertTrue(set(mini_gctoo.col_metadata_df[c]) == set(mini_gctoo_col_metadata[c]),
"Values in column {} differ between expected metadata and written col metadata!".format(c))
"""
CASE 2:
- write metadata (has NaN, not '-666') to file, do convert NaN back to '-666'
- parse in written metadata, don't convert -666
"""
# first convert mini_gctoo's row & col metadata dfs -666s to NaN
converted_row_metadata = mini_gctoo.row_metadata_df.replace([-666, "-666", -666.0],
[numpy.nan, numpy.nan, numpy.nan])
logger.debug("First row of converted_row_metadata: {}".format(converted_row_metadata.iloc[0]))
converted_col_metadata = mini_gctoo.col_metadata_df.replace([-666, "-666", -666.0],
[numpy.nan, numpy.nan, numpy.nan])
# write row and col metadata fields from mini_gctoo_for_testing instance to file
# Note this time does convert back to -666
hdf5_writer = h5py.File(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx", "w")
write_gctx.write_metadata(hdf5_writer, "row", converted_row_metadata, True, 6)
write_gctx.write_metadata(hdf5_writer, "col", converted_col_metadata, True, 6)
hdf5_writer.close()
# read in written metadata, then close and delete file
mini_gctoo_col_metadata = parse_gctx.get_column_metadata(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx",
convert_neg_666=False)
mini_gctoo_row_metadata = parse_gctx.get_row_metadata(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx",
convert_neg_666=False)
os.remove(FUNCTIONAL_TESTS_PATH + "/mini_gctoo_metadata.gctx")
# check row metadata
self.assertTrue(set(mini_gctoo.row_metadata_df.columns) == set(mini_gctoo_row_metadata.columns),
"Mismatch between expected row metadata columns {} and column values written to file: {}".format(
mini_gctoo.row_metadata_df.columns, mini_gctoo_row_metadata.columns))
self.assertTrue(set(mini_gctoo.row_metadata_df.index) == set(mini_gctoo.col_metadata_df.index),
"Mismatch between expect row metadata index {} and index values written to file: {}".format(
mini_gctoo.row_metadata_df.index, mini_gctoo_row_metadata.index))
for c in list(mini_gctoo.row_metadata_df.columns):
logger.debug("C2: For column name: {}".format(c))
logger.debug("C2: populated values: {}".format(set(mini_gctoo_row_metadata[c])))
logger.debug("C2: mini_gctoo values: {}".format(set(mini_gctoo.row_metadata_df[c])))
self.assertTrue(set(mini_gctoo.row_metadata_df[c]) == set(mini_gctoo_row_metadata[c]),
"Values in column {} differ between expected metadata and written row metadata!".format(c))
# check col metadata
self.assertTrue(set(mini_gctoo.col_metadata_df.columns) == set(mini_gctoo_col_metadata.columns),
"Mismatch between expected col metadata columns {} and column values written to file: {}".format(
mini_gctoo.col_metadata_df.columns, mini_gctoo_col_metadata.columns))
self.assertTrue(set(mini_gctoo.col_metadata_df.index) == set(mini_gctoo.col_metadata_df.index),
"Mismatch between expect col metadata index {} and index values written to file: {}".format(
mini_gctoo.col_metadata_df.index, mini_gctoo_col_metadata.index))
for c in list(mini_gctoo.col_metadata_df.columns):
self.assertTrue(set(mini_gctoo.col_metadata_df[c]) == set(mini_gctoo_col_metadata[c]),
"Values in column {} differ between expected metadata and written col metadata!".format(c))
def test_parse(self):
# parse whole thing
mg1 = mini_gctoo_for_testing.make()
mg2 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx"
)
pandas_testing.assert_frame_equal(mg1.data_df, mg2.data_df)
pandas_testing.assert_frame_equal(mg1.row_metadata_df,
mg2.row_metadata_df)
pandas_testing.assert_frame_equal(mg1.col_metadata_df,
mg2.col_metadata_df)
# test with string rid/cid
test_rids = [
'LJP007_MCF10A_24H:TRT_CP:BRD-K93918653:3.33',
'LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'
]
test_cids = ['LJP007_MCF7_24H:TRT_POSCON:BRD-A61304759:10']
mg3 = subset_gctoo.subset_gctoo(mg1, rid=test_rids, cid=test_cids)
mg4 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
rid=test_rids,
cid=test_cids)
pandas_testing.assert_frame_equal(mg3.data_df, mg4.data_df)
pandas_testing.assert_frame_equal(mg3.row_metadata_df,
mg4.row_metadata_df)
pandas_testing.assert_frame_equal(mg3.col_metadata_df,
mg4.col_metadata_df)
# first, make & write out temp version of mini_gctoo with int rids/cids
new_mg = mini_gctoo_for_testing.make(convert_neg_666=False)
int_indexed_data_df = new_mg.data_df.copy()
int_indexed_data_df.index = [str(i) for i in range(0, 6)]
int_indexed_data_df.columns = [str(i) for i in range(10, 16)]
int_indexed_row_meta = new_mg.row_metadata_df.copy()
int_indexed_row_meta.index = int_indexed_data_df.index
int_indexed_col_meta = new_mg.col_metadata_df.copy()
int_indexed_col_meta.index = int_indexed_data_df.columns
int_indexed_gctoo = GCToo.GCToo(data_df=int_indexed_data_df,
row_metadata_df=int_indexed_row_meta,
col_metadata_df=int_indexed_col_meta)
write_gctx.write(int_indexed_gctoo, "int_indexed_mini_gctoo.gctx")
# test with numeric (repr as string) rid/cid
mg5 = GCToo.GCToo(data_df=int_indexed_data_df,
row_metadata_df=int_indexed_row_meta,
col_metadata_df=int_indexed_col_meta)
mg5 = subset_gctoo.subset_gctoo(
mg5,
row_bool=[True, False, True, False, True, False],
col_bool=[True, False, False, True, True, True])
mg5.data_df.index.name = "rid"
mg5.data_df.columns.name = "cid"
mg5.row_metadata_df.index.name = "rid"
mg5.row_metadata_df.columns.name = "rhd"
mg5.col_metadata_df.index.name = "cid"
mg5.col_metadata_df.columns.name = "chd"
mg6 = parse_gctx.parse("int_indexed_mini_gctoo.gctx",
rid=["0", "2", "4"],
cid=["10", "13", "14", "15"],
convert_neg_666=False)
os.remove("int_indexed_mini_gctoo.gctx")
pandas_testing.assert_frame_equal(mg5.data_df, mg6.data_df)
pandas_testing.assert_frame_equal(mg5.row_metadata_df,
mg6.row_metadata_df)
pandas_testing.assert_frame_equal(mg5.col_metadata_df,
mg6.col_metadata_df)
# test with ridx/cidx
mg7 = subset_gctoo.subset_gctoo(
mg1,
rid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'],
cid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'])
mg8 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
ridx=[4],
cidx=[4])
pandas_testing.assert_frame_equal(mg7.data_df, mg8.data_df)
pandas_testing.assert_frame_equal(mg7.row_metadata_df,
mg8.row_metadata_df)
pandas_testing.assert_frame_equal(mg7.col_metadata_df,
mg8.col_metadata_df)
# test with rid/cidx
mg9 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
rid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'],
cidx=[4])
pandas_testing.assert_frame_equal(mg7.data_df, mg9.data_df)
pandas_testing.assert_frame_equal(mg7.row_metadata_df,
mg9.row_metadata_df)
pandas_testing.assert_frame_equal(mg7.col_metadata_df,
mg9.col_metadata_df)
# test with ridx/cid
mg10 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
ridx=[4],
cid=['LJP007_MCF7_24H:CTL_VEHICLE:DMSO:-666'])
pandas_testing.assert_frame_equal(mg7.data_df, mg10.data_df)
pandas_testing.assert_frame_equal(mg7.row_metadata_df,
mg10.row_metadata_df)
pandas_testing.assert_frame_equal(mg7.col_metadata_df,
mg10.col_metadata_df)
# test with row_meta_only
mg11 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
row_meta_only=True)
pandas_testing.assert_frame_equal(mg11, mg1.row_metadata_df)
# test with col_meta_only
mg12 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
col_meta_only=True)
pandas_testing.assert_frame_equal(mg12, mg1.col_metadata_df)
# test with sort_row_meta False and ridx
mg13 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
)
# test with sort_col_meta False and cidx
mg13 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests//mini_gctoo_for_testing.gctx",
cidx=[4, 1, 3],
sort_col_meta=False)
pandas_testing.assert_frame_equal(mg13.data_df,
mg1.data_df.iloc[:, [4, 1, 3]])
pandas_testing.assert_frame_equal(
mg13.col_metadata_df, mg1.col_metadata_df.iloc[[4, 1, 3], :])
pandas_testing.assert_frame_equal(mg13.row_metadata_df,
mg1.row_metadata_df)
# test with sort_row_meta False and ridx
mg14 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests//mini_gctoo_for_testing.gctx",
ridx=[3, 0, 1],
sort_row_meta=False)
pandas_testing.assert_frame_equal(mg14.data_df,
mg1.data_df.iloc[[3, 0, 1], :])
pandas_testing.assert_frame_equal(mg14.col_metadata_df,
mg1.col_metadata_df)
pandas_testing.assert_frame_equal(
mg14.row_metadata_df, mg1.row_metadata_df.iloc[[3, 0, 1], :])
# test with sort_col_meta False and cidx and col_meta_only
mg15 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests//mini_gctoo_for_testing.gctx",
cidx=[4, 1, 3],
sort_col_meta=False,
col_meta_only=True)
pandas_testing.assert_frame_equal(
mg15, mg1.col_metadata_df.iloc[[4, 1, 3], :])
# test with sort_row_meta False and ridx and row_meta_only
mg16 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests//mini_gctoo_for_testing.gctx",
ridx=[3, 0, 1],
sort_row_meta=False,
row_meta_only=True)
pandas_testing.assert_frame_equal(
mg16, mg1.row_metadata_df.iloc[[3, 0, 1], :])
# test with sort_col_meta False and cid
cid_unsorted = [
'LJP007_MCF7_24H:TRT_POSCON:BRD-K81418486:10',
'LJP007_MCF10A_24H:TRT_CP:BRD-K93918653:3.33'
]
mg17 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests//mini_gctoo_for_testing.gctx",
cid=cid_unsorted,
sort_col_meta=False)
pandas_testing.assert_frame_equal(mg17.data_df,
mg1.data_df.iloc[:, [2, 0]])
pandas_testing.assert_frame_equal(mg17.col_metadata_df,
mg1.col_metadata_df.iloc[[2, 0], :])
pandas_testing.assert_frame_equal(mg17.row_metadata_df,
mg1.row_metadata_df)
# test with sort_row_meta False and rid
rid_unsorted = [
'LJP007_MCF7_24H:TRT_CP:BRD-K64857848:10',
'MISC003_A375_24H:TRT_CP:BRD-K93918653:3.33'
]
mg18 = parse_gctx.parse(
"cmapPy/pandasGEXpress/tests/functional_tests/mini_gctoo_for_testing.gctx",
rid=rid_unsorted,
sort_row_meta=False)
pandas_testing.assert_frame_equal(mg18.data_df,
mg1.data_df.iloc[[5, 1], :])
pandas_testing.assert_frame_equal(mg18.col_metadata_df,
mg1.col_metadata_df)
pandas_testing.assert_frame_equal(mg18.row_metadata_df,
mg1.row_metadata_df.iloc[[5, 1], :])