: N","session twice ses = clib.Session() for __ in range(2): with","as lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\" Make sure","disable=unused-argument \"\"\" Put 'bla' in the value buffer. \"\"\" value.value","land=\"black\") fig2 = Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) # Activate the","lib: vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", # The invalid","session. \"\"\" # Create an instance of Session without \"with\"","pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0,","= (5, 3) for dtype in dtypes: with clib.Session() as","lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with GMTTempFile()","in data via a virtual file with a Dataset. \"\"\"","lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with clib.Session() as lib: wesn1 =","x = np.linspace(0, 1, 5) y = np.logspace(2, 3, 4)","test_virtualfile_from_matrix_slice(): \"\"\" Test transforming a slice of a larger array","part of the code. with clib.Session() as lib: with mock(lib,","_lib: gmt_version = Version(_lib.info[\"version\"]) @contextmanager def mock(session, func, returns=None, mock_func=None):","vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} -C ->{}\".format(vfile, outfile.name))","expected = \"<matrix memory>: N = {}\\t{}\\n\".format(rows, bounds) assert output","the code won't get to the closing of the #","inducing a Segmentation Fault (which is a good thing because","assert output == expected def test_virtualfile_from_vectors_diff_size(): \"\"\" Test the function","dim. \"\"\" with clib.Session() as lib: # Grids from matrices","\"\"\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def","= np.array([\"pqrst\", \"uvwx\", \"yz!\", \"@#\", \"$\"], dtype=dtype) with clib.Session() as","\"\"\" Check that dataarray_to_matrix returns correct output with flipped x/y.","desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0],","\"GMT_IS_GRID\", # The invalid direction argument 0, ) with pytest.raises(GMTInvalidInput):","N = {}\\t{}\\n\".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike():","lib = clib.Session() test_cases = ((family, via) for family in","to gmt info vfargs = (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset) with","* shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3 data","GMT C API function to make it always return a","desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check","any memory problems. with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name))","data_matrix def test_create_data_grid_dim(): \"\"\" Create a grid ignoring range and","1, 0], # columns, rows, layers, dtype ) # Dataset","same memory session1 = clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer is not","= \"<vector memory>: N = {}\\t{}\\n\".format(size, bounds) assert output ==","to test that exceptions are raised when API functions fail","np.array([\"a\", \"bc\", \"def\", \"ghij\", \"klmno\"], dtype=dtype) strings2 = np.array([\"pqrst\", \"uvwx\",","* 2, size * 3, 1) with clib.Session() as lib:","memory>: N = {}\\t{}\\n\".format(shape[0], bounds) assert output == expected def","dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data)","range and inc. \"\"\" with clib.Session() as lib: # Grids","usually only fails with errors). \"\"\" if mock_func is None:","a GMT C API function to make it always return","lib, \"GMT_Close_VirtualFile\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't","along to gmt info vfargs = (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset)","second one with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with","shape = (7, 5) for dtype in dtypes: data =","def test_call_module_error_message(): \"\"\" Check is the GMT error message was","if nothing has been plotted. \"\"\" Figure() with pytest.raises(GMTCLibError): with","pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \"\"\" Extract","mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails():","from it # Use in a different session to avoid","lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not given","npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] -","assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\"","given bad input. \"\"\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy()","\"\"\" Test transforming matrix columns to virtual file dataset. \"\"\"","with string or object dtype into virtual file dataset. \"\"\"","== expected def test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors to a dataset","strings) as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\")","* shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as","\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case in test_cases: with","return get_libgmt_func(name, argtypes, restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\",","except GMTCLibError as error: assert \"Module 'info' failed with status","lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0,","x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check that dataarray_to_matrix","output == expected def test_virtualfile_from_matrix_slice(): \"\"\" Test transforming a slice","vectors data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1,","that always returns a given value. \"\"\" return returns mock_func","(NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib,","\"\"\" Check that dataarray_to_matrix returns correct output. \"\"\" data =","def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if dataarray_to_matrix returns correct output with","status check when closing the virtual file # Mock the","via in VIAS) for family, via in test_cases: composite =","\"\"\" Run a command to see if call_module works. \"\"\"","def mock_get_libgmt_func(name, argtypes=None, restype=None): \"\"\" Return our mock function. \"\"\"","\"some-file-name\", None, ) def test_dataarray_to_matrix_works(): \"\"\" Check that dataarray_to_matrix returns","== expected def test_virtualfile_from_vectors_diff_size(): \"\"\" Test the function fails for","name because if # output=='', GMT will just write to","geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) assert data_vector !=","np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9,","size * 3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,","np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9,","lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError as error: assert \"Module 'info' failed","function to make sure it doesn't fail badly. \"\"\" with","def test_info_dict(): \"\"\" Make sure the clib.Session.info dict is working.","Test the function fails for arrays of different sizes. \"\"\"","the current figure, not the last figure. fig1 = Figure()","\"\"\" vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, ) #","\"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\") def","a bad file name because if # output=='', GMT will","to return 0 (success) so that we don't open a","invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_DATASET\",","lib, mock(lib, \"GMT_Open_VirtualFile\", returns=0), mock( lib, \"GMT_Close_VirtualFile\", returns=1 ): with","# Mock the opening to return 0 (success) so that","with pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\") def test_call_module_error_message(): \"\"\" Check is the","that extract region fails if nothing has been plotted. \"\"\"","->{}\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output ==",") expected = \"<matrix memory>: N = {}\\t{}\\n\".format(shape[0], bounds) assert","as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile()","ses = clib.Session() with mock(ses, \"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\")","(success) so that we don't open a file that #","an invalid direction argument. \"\"\" with clib.Session() as lib: vfargs","def test_call_module_invalid_arguments(): \"\"\" Fails for invalid module arguments. \"\"\" with","mock GMT API function that always returns a given value.","fail if not given valid modifiers but is using them","\"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, ) # Mock Open_VirtualFile to test","test_method_no_session(): \"\"\" Fails when not in a session. \"\"\" #","dtype in dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size,","y = tuple(range(size, size * 2, 1)) z = range(size","an instance of Session without \"with\" so no session is",") def test_virtual_file(): \"\"\" Test passing in data via a","import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput,","in [\"rows\", \"columns\"] assert int(lib.get_default(\"API_CORES\")) >= 1 assert Version(lib.get_default(\"API_VERSION\")) >=","x = np.arange(size, dtype=dtype) y = np.arange(size, size * 2,","hard to make the C API function fail without causing","single family argument correctly. \"\"\" lib = clib.Session() for family","sure the clib.Session.info dict is working. \"\"\" # Check if","session and make sure they are not pointing to the","if name == b\"API_VERSION\": value.value = b\"5.4.3\" else: value.value =","def test_dataarray_to_matrix_works(): \"\"\" Check that dataarray_to_matrix returns correct output. \"\"\"","assert ses[\"GMT_MODULE_CMD\"] != -99999 assert ses[\"GMT_PAD_DEFAULT\"] != -99999 assert ses[\"GMT_DOUBLE\"]","test_create_data_dataset(): \"\"\" Run the function to make sure it doesn't","assert data_vector != data_matrix def test_create_data_grid_dim(): \"\"\" Create a grid","test_extract_region_fails(): \"\"\" Check that extract region fails if nothing has","> 2 dims. \"\"\" # Make a 3D regular grid","np.arange(10) grid = xr.DataArray(data, coords=[(\"z\", z), (\"y\", y), (\"x\", x)])","assert ses.info for key in ses.info: assert ses.info[key] == \"bla\"","\"float32 float64 int32 int64 uint32 uint64\".split() shape = (5, 3)","geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0],","dtype into virtual file dataset. \"\"\" size = 5 x","extract_region to make sure that it's # getting from the","fig1 = Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1,","errors. \"\"\" # Create two session and make sure they","make it always return a given value. Used to test","from matrices data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20,","outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max())","* 6, \"some-file-name\", None, ) def test_dataarray_to_matrix_works(): \"\"\" Check that","as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try","clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with","= {}\\t{}\\n\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object])","def test_create_data_grid_range(): \"\"\" Create a grid specifying range and inc","test_get_default_fails(): \"\"\" Make sure get_default raises an exception for invalid","dataset. \"\"\" size = 5 x = np.arange(size, dtype=np.int32) y","always return a given value. Used to test that exceptions","clib.Session() test_cases = ((family, via) for family in FAMILIES for","None, ) # Mock Open_VirtualFile to test the status check","in data.T] ) expected = \"<matrix memory>: N = {}\\t{}\\n\".format(shape[0],","test_virtual_file_bad_direction(): \"\"\" Test passing an invalid direction argument. \"\"\" with","\"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\" def test_call_module_invalid_arguments(): \"\"\" Fails","failed\") def test_virtualfile_from_vectors(): \"\"\" Test the automation for transforming vectors","with GMTTempFile() as out_fname: lib.call_module(\"info\", \"{} -C ->{}\".format(data_fname, out_fname.name)) assert","captured. \"\"\" with clib.Session() as lib: try: lib.call_module(\"info\", \"bogus-data.bla\") except","matrices data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1,","npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\"","have failed\") def test_virtualfile_from_vectors(): \"\"\" Test the automation for transforming","# names. Use a mock instead just to exercise this","y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \"\"\" Make","clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999 assert ses[\"GMT_MODULE_CMD\"] != -99999 assert","correct output with flipped x. \"\"\" data = np.diag(v=np.arange(3)) x","\"bogus-data.bla\") except GMTCLibError as error: assert \"Module 'info' failed with","the session is closed when the exception is raised. with","grid = xr.DataArray(data, coords=[(\"z\", z), (\"y\", y), (\"x\", x)]) with","def test_extract_region_fails(): \"\"\" Check that extract region fails if nothing","transforming vectors to virtual file dataset. \"\"\" dtypes = \"float32","our mock function. \"\"\" if name == func: return mock_func","!= -99999 assert ses[\"GMT_PAD_DEFAULT\"] != -99999 assert ses[\"GMT_DOUBLE\"] != -99999","pandas Series. \"\"\" dtypes = \"float32 float64 int32 int64 uint32","Create a grid specifying range and inc instead of dim.","bounds) assert output == expected def test_virtualfile_from_matrix_slice(): \"\"\" Test transforming","dims. \"\"\" # Make a 3D regular grid data =","ses.destroy() def test_call_module(): \"\"\" Run a command to see if","with the second one with clib.Session() as lib: lib.call_module(\"figure\", \"{}","valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant(","\"get_libgmt_func\", get_libgmt_func) def test_getitem(): \"\"\" Test that I can get","in str(error) def test_method_no_session(): \"\"\" Fails when not in a","it doesn't fail badly. \"\"\" with clib.Session() as lib: #","data.T] ) expected = \"<matrix memory>: N = {}\\t{}\\n\".format(rows, bounds)","message was captured. \"\"\" with clib.Session() as lib: try: lib.call_module(\"info\",","vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name)) output","region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),","to test the status check when entering the context. #","y, z)] ) expected = \"<vector memory>: N = {}\\t{}\\n\".format(size,","lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], # columns,","and destroy session are called without errors. \"\"\" # Create","def test_parse_constant_single(): \"\"\" Parsing a single family argument correctly. \"\"\"","output with flipped x. \"\"\" data = np.diag(v=np.arange(3)) x =","family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\" dataset = lib.create_data( family=family,","or segfaults from getting all of the # properties. with","ses.create(\"test-session\") with mock(ses, \"GMT_Destroy_Session\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def","as lib: lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0, 1, 0],","b\"bla\" return 0 lib = clib.Session() with mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults):","with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{}","output = out_fname.read().strip() assert output == \"11.5309 61.7074 -2.9289 7.8648","# Now try it with the second one with clib.Session()","3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z)","dataset using pandas Series. \"\"\" dtypes = \"float32 float64 int32","((family, via) for family in FAMILIES for via in VIAS)","file # Mock the opening to return 0 (success) so","return a given value. Used to test that exceptions are","status code\" in str(error) assert \"gmtinfo [ERROR]: Cannot find file","an exception for non-zero return codes. \"\"\" # It's hard","columns, rows, layers, dtype ) # Dataset from matrices data_matrix","output == expected def test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors to a","assert \"Module 'info' failed with status code\" in str(error) assert","make sure it doesn't fail badly. \"\"\" with clib.Session() as","->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max())","pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \"\"\" Test that","composite = \"|\".join([family, via]) expected = lib[family] + lib[via] parsed","dtype in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with","\"\"\" Test the wrappers for the C API. \"\"\" import","write data raises an exception for non-zero return codes. \"\"\"","->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\" for","input and output. \"\"\" # Passing in invalid mode with","disable=unused-argument \"\"\" Return an old version. \"\"\" if name ==","y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if dataarray_to_matrix returns","# pylint: disable=pointless-statement ses.create(\"session1\") assert ses.session_pointer is not None ses.destroy()","instead just to exercise this part of the code. with","twice ses = clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError):","mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1,","stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data,","session2.destroy() # Create and destroy a session twice ses =","with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} -C ->{}\".format(vfile, outfile.name)) output","# Should also fail if not given valid modifiers but","this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None ) def","find file bogus-data.bla\" in str(error) def test_method_no_session(): \"\"\" Fails when","x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1)))","2, 1, dtype=dtype), z=np.arange(size * 2, size * 3, 1,","lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0,","{}\\t{}\\n\".format(shape[0], bounds) assert output == expected def test_virtual_file_fails(): \"\"\" Check","geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1, 0], # columns, rows, layers,","\"\"\" Test transforming a slice of a larger array to","in zip(x, y, strings)) assert output == expected @pytest.mark.parametrize(\"dtype\", [str,","fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) # Activate the first figure and extract","raised, the code won't get to the closing of the","GMTCLibError as error: assert \"Module 'info' failed with status code\"","expected def test_virtualfile_from_vectors_transpose(): \"\"\" Test transforming matrix columns to virtual","with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\",","* 2, 1, dtype=dtype), z=np.arange(size * 2, size * 3,","b\"bla\" return 0 ses = clib.Session() ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\",","the same time. \"\"\" # Make two figures before calling","assert session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer session1.destroy()","\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (data.x, data.y, data.z) ] )",">= 1 assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def test_get_default_fails(): \"\"\" Make","expected def test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors to a dataset using","memory session1 = clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer is not None","ses.create(\"test-session-name\") # Should fail if trying to create a session","mock_api_function(*args): # pylint: disable=unused-argument \"\"\" A mock GMT API function","Check if the function fails when given bad input. \"\"\"","(5, 3) for dtype in dtypes: with clib.Session() as lib:","\"\"\" # Mock GMT_Get_Default to return an old version def","= {}\\t{}\\n\".format(rows, bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): \"\"\"","\"|\".join([family, via]) expected = lib[family] + lib[via] parsed = lib._parse_constant(composite,","2, 1)) z = range(size * 2, size * 3,","function. \"\"\" if name == func: return mock_func return get_libgmt_func(name,","assert int(lib.get_default(\"API_CORES\")) >= 1 assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def test_get_default_fails():","value): # pylint: disable=unused-argument \"\"\" Put 'bla' in the value","0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], )","Check if dataarray_to_matrix returns correct output with flipped x. \"\"\"","-99999 assert ses[\"GMT_MODULE_CMD\"] != -99999 assert ses[\"GMT_PAD_DEFAULT\"] != -99999 assert","dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2],","to return always the same string def mock_defaults(api, name, value):","Make sure the clib.Session raises an exception if GMT is","= np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\",","output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for","def mock(session, func, returns=None, mock_func=None): \"\"\" Mock a GMT C","assert \"gmtinfo [ERROR]: Cannot find file bogus-data.bla\" in str(error) def","lib: # Grids from matrices using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\",","the region from it # Use in a different session","with clib.Session() as lib: # Grids from matrices using range","\"\"\" Make sure get_default works without crashing and gives reasonable","libgmt usually only fails with errors). \"\"\" if mock_func is","output=='', GMT will just write to stdout and spaces are","session before destroying the old one. ses.create(\"test1\") with pytest.raises(GMTCLibError): ses.create(\"test2\")","to return an old version def mock_defaults(api, name, value): #","a session. \"\"\" # Create an instance of Session without","that # we won't close later. with clib.Session() as lib,","= np.linspace(0, 1, 5) y = np.logspace(2, 3, 4) grid","with mock(lib, \"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\",","Cannot find file bogus-data.bla\" in str(error) def test_method_no_session(): \"\"\" Fails","expected def test_virtualfile_from_vectors_diff_size(): \"\"\" Test the function fails for arrays","3, 1, dtype=dtype), ) ) with clib.Session() as lib: with","\"\"\" ses = clib.Session() with mock(ses, \"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError):","out_fname.read().strip() assert output == \"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\"","Make sure get_default raises an exception for invalid names. \"\"\"","ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \"\"\" Test that create","a good thing because libgmt usually only fails with errors).","y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if dataarray_to_matrix returns correct output","zero return codes. \"\"\" vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\",","def test_fails_for_wrong_version(): \"\"\" Make sure the clib.Session raises an exception","= os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname = \"test_call_module.txt\" with clib.Session() as lib:","a given value. \"\"\" return returns mock_func = mock_api_function get_libgmt_func","regular grid data = np.ones((10, 12, 11), dtype=\"float32\") x =","\"\"\" Test passing in data via a virtual file with","stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data,","= tuple(range(size, size * 2, 1)) z = range(size *","== expected def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like vectors to a","to make it always return a given value. Used to","dataarray_to_matrix returns correct output with flipped x/y. \"\"\" data =","Check if there are no errors or segfaults from getting","with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name)) output =","given value. \"\"\" return returns mock_func = mock_api_function get_libgmt_func =","clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0,","returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should not get to this","when given bad input. \"\"\" lib = clib.Session() test_cases =","grid specifying range and inc instead of dim. \"\"\" with","!= -99999 assert ses[\"GMT_MODULE_CMD\"] != -99999 assert ses[\"GMT_PAD_DEFAULT\"] != -99999","the # virtual file. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\",","function fail without causing a Segmentation # Fault. Can't test","Test the status check when closing the virtual file #","->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i))","Test passing in two columns of string or object dtype","matrices using range and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0,",") assert output == expected def test_virtualfile_from_vectors_transpose(): \"\"\" Test transforming","= clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\") with mock(ses, \"GMT_Destroy_Session\", returns=1):","output with flipped y. \"\"\" data = np.diag(v=np.arange(3)) x =","y, strings1, strings2) as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\",","def test_virtualfile_from_vectors_transpose(): \"\"\" Test transforming matrix columns to virtual file","np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \"\"\" Check that write","3) for dtype in dtypes: with clib.Session() as lib: family","test_virtual_file_fails(): \"\"\" Check that opening and closing virtual files raises","dataset to a virtual file and pass it along to","as lib: assert lib.info # Mock GMT_Get_Default to return always","bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like","region1) # Now try it with the second one with","too old. \"\"\" # Mock GMT_Get_Default to return an old","def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like vectors to a dataset. \"\"\"","\"GMT_Destroy_Session\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \"\"\" Run","because libgmt usually only fails with errors). \"\"\" if mock_func","N = {}\\t{}\\n\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\"dtype\", [str,","called without errors. \"\"\" # Create two session and make","dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1]","output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for col","always returns a given value. \"\"\" return returns mock_func =","a Segmentation Fault (which is a good thing because libgmt","pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \"\"\" Run a command to","via]) expected = lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES,","This should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS ) # But","zip(x, y, strings)) assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object])","doesn't fail badly. \"\"\" with clib.Session() as lib: # Dataset","\"\"\" lib = clib.Session() for family in FAMILIES: parsed =","test_create_destroy_session(): \"\"\" Test that create and destroy session are called","instead of dim. \"\"\" with clib.Session() as lib: # Grids","Check that extract region fails if nothing has been plotted.","not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create","bogus-data.bla\" in str(error) def test_method_no_session(): \"\"\" Fails when not in","# we won't close later. with clib.Session() as lib, mock(lib,","y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\"y\", y),","entering the context. # If the exception is raised, the","it's not easy to get some API functions to fail","test the status check when entering the context. # If","dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to a virtual","1, 0], # columns, rows, layers, dtype ) data =","= \"GMT_IS_POINT\" dataset = lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0],","a Segmentation # Fault. Can't test this if by giving","session1.create(name=\"test_session1\") assert session1.session_pointer is not None session2 = clib.Session() session2.create(name=\"test_session2\")","output with flipped x/y. \"\"\" data = np.diag(v=np.arange(3)) x =","int32 int64 uint32 uint64\".split() size = 10 for dtype in","get some API functions to fail without inducing a Segmentation","y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def","bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col in data.T] )","= \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for col in data.T] ) expected","pass print(\"Shouldn't get to this code either\") def test_virtual_file_bad_direction(): \"\"\"","a session before destroying the old one. ses.create(\"test1\") with pytest.raises(GMTCLibError):","outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for","segfaults from getting all of the # properties. with clib.Session()","z = np.arange(size * 2, size * 3, 1, dtype=dtype)","clib.Session() as lib: vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", #","work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't.","as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile:","import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \"data\") with clib.Session() as _lib:","correct output with flipped x/y. \"\"\" data = np.diag(v=np.arange(3)) x","in the value buffer. \"\"\" value.value = b\"bla\" return 0","clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with clib.Session() as lib:","using them anyway. # This should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES,","ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint:","inc=[0.1, 0.2], ) # If the data pointer returned is","column with string or object dtype into virtual file dataset.","# columns, rows, layers, dtype ) # Dataset from matrices","import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import","file that # we won't close later. with clib.Session() as","uint32 uint64\".split() size = 10 for dtype in dtypes: x","\"\"\" Check if dataarray_to_matrix returns correct output with flipped x.","of Session without \"with\" so no session is created. lib","y = np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\"y\", y),","dtype=dtype), ) ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y,","1, dtype=np.int32) strings1 = np.array([\"a\", \"bc\", \"def\", \"ghij\", \"klmno\"], dtype=dtype)","* 3, 1, dtype=dtype), ) ) with clib.Session() as lib:","valid file # names. Use a mock instead just to","coords=[(\"z\", z), (\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def","N = {}\\t{}\\n\".format(size, bounds) assert output == expected def test_extract_region_fails():","it fails for > 2 dims. \"\"\" # Make a","test_virtual_file(): \"\"\" Test passing in data via a virtual file","{}\\t{}\\n\".format(rows, bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): \"\"\" Pass","as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile()","old version def mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\"","[ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case in","= 13 for dtype in dtypes: data = pd.DataFrame( data=dict(","coords=[(\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \"\"\"","can get correct constants from the C lib. \"\"\" ses",") assert data_vector != data_matrix def test_create_data_grid_dim(): \"\"\" Create a","good thing because libgmt usually only fails with errors). \"\"\"","x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size *","import numpy as np import numpy.testing as npt import pandas","np.arange(size, dtype=dtype) y = np.arange(size, size * 2, 1, dtype=dtype)","dictionary assert ses.info for key in ses.info: assert ses.info[key] ==","the last figure. fig1 = Figure() region1 = np.array([0, 10,","not the last figure. fig1 = Figure() region1 = np.array([0,","(\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region,","with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \"\"\" Run a command","the virtual file # Mock the opening to return 0","# This should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS ) #","== \"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\" def test_call_module_invalid_arguments(): \"\"\"","reasonable results. \"\"\" with clib.Session() as lib: assert lib.get_default(\"API_GRID_LAYOUT\") in","def test_create_data_fails(): \"\"\" Check that create_data raises exceptions for invalid","returns=0), mock( lib, \"GMT_Close_VirtualFile\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs):","dataarray_to_matrix returns correct output with flipped y. \"\"\" data =","k in zip(x, y, strings)) assert output == expected @pytest.mark.parametrize(\"dtype\",","= 5 cols = 3 data = full_data[:rows, :cols] with","= \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for i in (x, y, z)]","= Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\"M6i\",","pylint: disable=pointless-statement def test_create_destroy_session(): \"\"\" Test that create and destroy","\"\"\" Return our mock function. \"\"\" if name == func:","bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for i in (x, y,","lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as","ignoring range and inc. \"\"\" with clib.Session() as lib: #","calling extract_region to make sure that it's # getting from","fig1.coast(region=region1, projection=\"M6i\", frame=True, land=\"black\") fig2 = Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True)","just write to stdout and spaces are valid file #","with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True)","dtype=dtype) y = np.arange(size, size * 2, 1, dtype=dtype) z","= {}\\t{}\\n\".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): \"\"\"","pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \"\"\" Parsing a","as lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with clib.Session() as lib: wesn2","np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y):","col.max()) for col in data.T] ) expected = \"<matrix memory>:","y, z) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{}","Test transforming a slice of a larger array to virtual","= np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5,","as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name))","mock_get_libgmt_func(name, argtypes=None, restype=None): \"\"\" Return our mock function. \"\"\" if","create a session before destroying the old one. ses.create(\"test1\") with","0 lib = clib.Session() with mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults): with pytest.raises(GMTVersionError):","and gives reasonable results. \"\"\" with clib.Session() as lib: assert","= clib.Session() with mock(ses, \"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") #","# Grids from matrices using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\",","def test_get_default_fails(): \"\"\" Make sure get_default raises an exception for","from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError,","\"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\", get_libgmt_func) def test_getitem(): \"\"\" Test","invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_GRID\",","lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\",","with clib.Session() as lib: with mock(lib, \"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError):","Check that dataarray_to_matrix returns correct output with flipped x/y. \"\"\"","test this if by giving a bad file name because","b\"API_VERSION\": value.value = b\"5.4.3\" else: value.value = b\"bla\" return 0","assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == \"11.5309 61.7074","Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures():","pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\") def test_call_module_error_message(): \"\"\" Check is the GMT","in VIAS) for family, via in test_cases: composite = \"|\".join([family,","region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),","family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0,","pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not","== expected def test_extract_region_fails(): \"\"\" Check that extract region fails","get_default raises an exception for invalid names. \"\"\" with clib.Session()","@contextmanager def mock(session, func, returns=None, mock_func=None): \"\"\" Mock a GMT","region fails if nothing has been plotted. \"\"\" Figure() with","fails for > 2 dims. \"\"\" # Make a 3D","y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment():","object dtype into virtual file dataset. \"\"\" size = 5","correctly. \"\"\" lib = clib.Session() test_cases = ((family, via) for","!= data_matrix def test_create_data_grid_dim(): \"\"\" Create a grid ignoring range","\"\"\" Parsing a composite constant argument (separated by |) correctly.","with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't get to this code either\") def","= xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) matrix, region, inc =","inc. \"\"\" with clib.Session() as lib: # Grids from matrices","fails for arrays of different sizes. \"\"\" x = np.arange(5)","of the code. with clib.Session() as lib: with mock(lib, \"GMT_Write_Data\",","mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\"version\"] !=","lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single():","# Check if there are no errors or segfaults from","num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\"y\",","in str(error) assert \"gmtinfo [ERROR]: Cannot find file bogus-data.bla\" in","def test_virtual_file_fails(): \"\"\" Check that opening and closing virtual files","Make sure the session is closed when the exception is","for family in FAMILIES for via in VIAS) for family,","Mock GMT_Get_Default to return an old version def mock_defaults(api, name,","[str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test passing in two columns","\"float32 float64 int32 int64 uint32 uint64\".split() size = 10 for","import contextmanager import numpy as np import numpy.testing as npt","int32 int64 uint32 uint64\".split() shape = (5, 3) for dtype","lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile,","y = np.arange(size, size * 2, 1, dtype=np.int32) strings1 =","# getting from the current figure, not the last figure.","lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with clib.Session() as lib: wesn2 =","lib: lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0, 1, 0], ranges=[150.0,","dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as","== expected def test_virtualfile_from_matrix_slice(): \"\"\" Test transforming a slice of","lib.put_matrix(dataset, matrix=data) # Add the dataset to a virtual file","an exception if GMT is too old. \"\"\" # Mock","session2 = clib.Session() session2.create(name=\"test_session2\") assert session2.session_pointer is not None assert","int32 int64 uint32 uint64\".split() shape = (10, 6) for dtype","that write data raises an exception for non-zero return codes.","N = {}\\t{}\\n\".format(shape[0], bounds) assert output == expected def test_virtual_file_fails():","uint64\".split() shape = (5, 3) for dtype in dtypes: with","2, size * 3, 1) with clib.Session() as lib: with","with clib.Session() as _lib: gmt_version = Version(_lib.info[\"version\"]) @contextmanager def mock(session,","lib: try: lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError as error: assert \"Module","with clib.Session() as lib: lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0,","Use a mock instead just to exercise this part of","as lib: with pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\") def test_call_module_error_message(): \"\"\" Check","via a virtual file with a Dataset. \"\"\" dtypes =","lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with GMTTempFile() as outfile:","valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not given valid","\"<vector memory>: N = {}\\t{}\\n\".format(size, bounds) assert output == expected","frame=True, land=\"black\") fig2 = Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) # Activate","Return our mock function. \"\"\" if name == func: return","mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults): # Check for an empty dictionary assert","strings2) as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\")","pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\" Check that it fails for","command to see if call_module works. \"\"\" data_fname = os.path.join(TEST_DATA_DIR,","spaces are valid file # names. Use a mock instead","as xr from packaging.version import Version from pygmt import Figure,","expected = \"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i, j, k in zip(x, y,","1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]),","invalid input and output. \"\"\" # Passing in invalid mode","== expected def test_virtualfile_from_vectors_transpose(): \"\"\" Test transforming matrix columns to","try: lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError as error: assert \"Module 'info'","virtual file dataset. \"\"\" dtypes = \"float32 float64 int32 int64","dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with","|) correctly. \"\"\" lib = clib.Session() test_cases = ((family, via)","restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\", get_libgmt_func) def test_getitem():","a command to see if call_module works. \"\"\" data_fname =","transforming a matrix to virtual file dataset. \"\"\" dtypes =","without causing a Segmentation # Fault. Can't test this if","dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size,",") # Mock Open_VirtualFile to test the status check when","with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with clib.Session() as","\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case,","matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),",">= Version(\"6.2.0\") def test_get_default_fails(): \"\"\" Make sure get_default raises an","family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) def test_create_data_grid_range():","Check that create_data raises exceptions for invalid input and output.","(family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile()","the function fails for arrays of different sizes. \"\"\" x","abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check that dataarray_to_matrix returns","Make sure get_default works without crashing and gives reasonable results.","bounds) assert output == expected def test_extract_region_fails(): \"\"\" Check that","xarray as xr from packaging.version import Version from pygmt import","given bad input. \"\"\" lib = clib.Session() test_cases = [","dataarray_to_matrix returns correct output with flipped x. \"\"\" data =","np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)])","GMT_Get_Default to return always the same string def mock_defaults(api, name,","= b\"5.4.3\" else: value.value = b\"bla\" return 0 lib =","lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with","object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test passing in one column with","expected def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like vectors to a dataset.","y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\"y\", y),","max(i)) for i in (x, y, z)] ) expected =","Version(_lib.info[\"version\"]) @contextmanager def mock(session, func, returns=None, mock_func=None): \"\"\" Mock a","geometry = \"GMT_IS_POINT\" dataset = lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1],","\"\"\" Make sure the clib.Session raises an exception if GMT","\"\"\" Extract region should handle multiple figures existing at the","exception if GMT is too old. \"\"\" # Mock GMT_Get_Default","= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,","GMT is too old. \"\"\" # Mock GMT_Get_Default to return","np.arange(size, size * 2, 1, dtype=dtype) z = np.arange(size *","when not in a session. \"\"\" # Create an instance","in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session()","= (10, 6) for dtype in dtypes: full_data = np.arange(shape[0]","of dim. \"\"\" with clib.Session() as lib: # Grids from","npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] -","2, 1, dtype=np.int32) strings = np.array([\"a\", \"bc\", \"defg\", \"hijklmn\", \"opqrst\"],","def test_dataarray_to_matrix_inc_fails(): \"\"\" Check that it fails for variable increments.","so no session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError):","\"uvwx\", \"yz!\", \"@#\", \"$\"], dtype=dtype) with clib.Session() as lib: with","lib: # Grids from matrices using range and int lib.create_data(","not get to this code\") # Test the status check","\"\"\" # It's hard to make the C API function","are not pointing to the same memory session1 = clib.Session()","== func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \"get_libgmt_func\",","pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \"\"\" Check that","= np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9,","[\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (x, y, z)] ) expected","file name because if # output=='', GMT will just write","clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with","a slice of a larger array to virtual file dataset.","Use in a different session to avoid any memory problems.","\"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(),","it always return a given value. Used to test that","strings1 = np.array([\"a\", \"bc\", \"def\", \"ghij\", \"klmno\"], dtype=dtype) strings2 =","inc=[0.1, 0.2], ) # Passing in invalid geometry with pytest.raises(GMTInvalidInput):","avoid any memory problems. with clib.Session() as lib: lib.call_module(\"figure\", \"{}","y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment():","num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\"y\",","250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If the data","[\"rows\", \"columns\"] assert int(lib.get_default(\"API_CORES\")) >= 1 assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\")","with clib.Session() as lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0,","13 x = list(range(0, size, 1)) y = tuple(range(size, size","pygmt import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session","# Test the status check when closing the virtual file","transforming matrix columns to virtual file dataset. \"\"\" dtypes =","\"\"\" Test the function fails for arrays of different sizes.","not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def","value.value = b\"bla\" return 0 lib = clib.Session() with mock(lib,","clib.Session() as lib: # Dataset from vectors data_vector = lib.create_data(","= Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) # Activate the first figure","if call_module works. \"\"\" data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname =","0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If","flipped x. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0,","non- zero return codes. \"\"\" vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\",","= outfile.read(keep_tabs=True) bounds = \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i","lib[family] def test_parse_constant_composite(): \"\"\" Parsing a composite constant argument (separated","int64 uint32 uint64\".split() size = 10 for dtype in dtypes:","pd import pytest import xarray as xr from packaging.version import","Dataset. \"\"\" dtypes = \"float32 float64 int32 int64 uint32 uint64\".split()","when entering the context. # If the exception is raised,","with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\") def test_call_module_error_message():","dtype=np.int32) strings = np.array([\"a\", \"bc\", \"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype) with","figures existing at the same time. \"\"\" # Make two","= np.arange(size, size * 2, 1, dtype=np.int32) strings = np.array([\"a\",","strings2 = np.array([\"pqrst\", \"uvwx\", \"yz!\", \"@#\", \"$\"], dtype=dtype) with clib.Session()","(\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\" Check that","create and destroy session are called without errors. \"\"\" #","a composite constant argument (separated by |) correctly. \"\"\" lib","with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError): with","But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None )","0], # columns, rows, layers, dtype ) # Dataset from","\"\"\" Make sure the clib.Session.info dict is working. \"\"\" #","mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2, 0], ) def test_virtual_file(): \"\"\" Test","mock instead just to exercise this part of the code.","# Fault. Can't test this if by giving a bad","as lib: # Grids from matrices using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\",","raises an exception if GMT is too old. \"\"\" #","bounds) assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype):","20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \"\"\" Check that create_data","grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid)","with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\"This should have failed\") def","and output. \"\"\" # Passing in invalid mode with pytest.raises(GMTInvalidInput):","pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError,","# Create two session and make sure they are not","expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test passing in","output. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3)","outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for i in (x,","\"\"\" # Make two figures before calling extract_region to make","lib = clib.Session() with mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with","\"\"\" Fails when not in a session. \"\"\" # Create","expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test passing in","uint32 uint64\".split() size = 13 for dtype in dtypes: data","\"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (x, y, z)] )","extract the region from it # Use in a different","as lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\" dataset =","- y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\" Check that it fails for","GMT error message was captured. \"\"\" with clib.Session() as lib:","[1] * 6, \"some-file-name\", None, ) def test_dataarray_to_matrix_works(): \"\"\" Check","output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test","memory>: N = {}\\t{}\\n\".format(size, bounds) assert output == expected def","to a dataset using pandas Series. \"\"\" dtypes = \"float32","[\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col in data.T] ) expected = \"{}\\n\".format(bounds)","as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0]))","test_getitem(): \"\"\" Test that I can get correct constants from","with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\"This should have failed\") def test_virtualfile_from_vectors():","without \"with\" so no session is created. lib = clib.Session()","\"\"\" with clib.Session() as lib: vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\",","desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]),","test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test passing in one column with string or","that I can get correct constants from the C lib.","import xarray as xr from packaging.version import Version from pygmt","correct output with flipped y. \"\"\" data = np.diag(v=np.arange(3)) x",") from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \"data\") with","int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1,","mock_func=mock_defaults): # Check for an empty dictionary assert ses.info for","dtype=dtype).reshape(shape) rows = 5 cols = 3 data = full_data[:rows,","assert output == expected def test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors to","Pass vectors to a dataset using pandas Series. \"\"\" dtypes","stdout and spaces are valid file # names. Use a","* 2, 1, dtype=np.int32) strings = np.array([\"a\", \"bc\", \"defg\", \"hijklmn\",","= lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert","x. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3)","= lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \"\"\"","\"\"\" with clib.Session() as lib: # Grids from matrices using","file dataset. \"\"\" size = 5 x = np.arange(size, dtype=np.int32)","and make sure they are not pointing to the same","restype=None): \"\"\" Return our mock function. \"\"\" if name ==","\"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [","x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3)","results. \"\"\" with clib.Session() as lib: assert lib.get_default(\"API_GRID_LAYOUT\") in [\"rows\",","= \"float32 float64 int32 int64 uint32 uint64\".split() size = 10","# Create and destroy a session twice ses = clib.Session()","don't open a file that # we won't close later.","with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile() as outfile:","1)) y = tuple(range(size, size * 2, 1)) z =","\"GMT_Get_Default\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\"version\"] != \"5.4.3\"","if by giving a bad file name because if #","inc instead of dim. \"\"\" with clib.Session() as lib: #","= \"float32 float64 int32 int64 uint32 uint64\".split() shape = (5,","get_libgmt_func(name, argtypes, restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\", get_libgmt_func)","that create and destroy session are called without errors. \"\"\"","x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\" Check that it","session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a session twice","= \"test_call_module.txt\" with clib.Session() as lib: with GMTTempFile() as out_fname:","fail without causing a Segmentation # Fault. Can't test this","or object dtype into virtual file dataset. \"\"\" size =",") # But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES,","1)) z = range(size * 2, size * 3, 1)","i.max()) for i in (data.x, data.y, data.z) ] ) expected","test_info_dict(): \"\"\" Make sure the clib.Session.info dict is working. \"\"\"","in a different session to avoid any memory problems. with","= np.array([\"a\", \"bc\", \"def\", \"ghij\", \"klmno\"], dtype=dtype) strings2 = np.array([\"pqrst\",","\"\"\" # Check if there are no errors or segfaults","output == expected def test_extract_region_fails(): \"\"\" Check that extract region","\"\"\" import os from contextlib import contextmanager import numpy as","np.array([\"a\", \"bc\", \"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype) with clib.Session() as lib:","string def mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\" Put","is None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib:","def mock_api_function(*args): # pylint: disable=unused-argument \"\"\" A mock GMT API",") def test_create_data_grid_range(): \"\"\" Create a grid specifying range and","print(\"Should not get to this code\") # Test the status","two figures before calling extract_region to make sure that it's","6, \"some-file-name\", None, ) def test_dataarray_to_matrix_works(): \"\"\" Check that dataarray_to_matrix","are no errors or segfaults from getting all of the","11), dtype=\"float32\") x = np.arange(11) y = np.arange(12) z =","x = list(range(0, size, 1)) y = tuple(range(size, size *","1, 0], ) assert data_vector != data_matrix def test_create_data_grid_dim(): \"\"\"","assert output == expected def test_virtual_file_fails(): \"\"\" Check that opening","uint32 uint64\".split() shape = (10, 6) for dtype in dtypes:","clib.Session() with mock(ses, \"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should","works. \"\"\" data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname = \"test_call_module.txt\" with",") with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\"This should have failed\") def","to get some API functions to fail without inducing a","\"\"\" # Create an instance of Session without \"with\" so","with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement","\"GMT_Open_VirtualFile\", returns=0), mock( lib, \"GMT_Close_VirtualFile\", returns=1 ): with pytest.raises(GMTCLibError): with","= np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with","for col in data.T] ) expected = \"<matrix memory>: N","slice of a larger array to virtual file dataset. \"\"\"","inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])","test_extract_region_two_figures(): \"\"\" Extract region should handle multiple figures existing at","clib.Session() as lib: with mock(lib, \"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError): lib.write_data(","= \"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i, j, k in zip(x, y, strings))","@pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test passing in one","pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data(","Grids from matrices using range and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\",","== expected def test_parse_constant_fails(): \"\"\" Check if the function fails","this code either\") def test_virtual_file_bad_direction(): \"\"\" Test passing an invalid","plotted. \"\"\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region()","and inc instead of dim. \"\"\" with clib.Session() as lib:","constant argument (separated by |) correctly. \"\"\" lib = clib.Session()","no session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\",","int64 uint32 uint64\".split() shape = (5, 3) for dtype in","Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib:","np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid =","func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func)","instance of Session without \"with\" so no session is created.","lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile,","and extract the region from it # Use in a","The invalid direction argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs):","increments. \"\"\" data = np.ones((4, 5), dtype=\"float64\") x = np.linspace(0,","lib: # Dataset from vectors data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\",","\"\"\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\") with mock(ses,","Session without \"with\" so no session is created. lib =","np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\"M6i\", frame=True, land=\"black\") fig2 =","vfargs = (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset) with lib.open_virtual_file(*vfargs) as vfile:","# properties. with clib.Session() as lib: assert lib.info # Mock","gmt info vfargs = (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset) with lib.open_virtual_file(*vfargs)","assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999 assert ses[\"GMT_MODULE_CMD\"] != -99999 assert ses[\"GMT_PAD_DEFAULT\"]","disable=unused-argument \"\"\" A mock GMT API function that always returns","clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with","with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile:","import Version from pygmt import Figure, clib from pygmt.clib.conversion import","Test the wrappers for the C API. \"\"\" import os","file and pass it along to gmt info vfargs =","np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)])","given bad input. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError):","np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3","- x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check that","file with a Dataset. \"\"\" dtypes = \"float32 float64 int32","y): print(\"This should have failed\") def test_virtualfile_from_matrix(): \"\"\" Test transforming","direction argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\"This should","session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy()","def test_virtualfile_from_matrix_slice(): \"\"\" Test transforming a slice of a larger","virtual file with a Dataset. \"\"\" dtypes = \"float32 float64","clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs):","@pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test passing in two","clib.Session() ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults): # Check for an","clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now","lib.get_default(\"API_GRID_LAYOUT\") in [\"rows\", \"columns\"] assert int(lib.get_default(\"API_CORES\")) >= 1 assert Version(lib.get_default(\"API_VERSION\"))","as output or non-zero status codes. Needed because it's not","Run a command to see if call_module works. \"\"\" data_fname","is working. \"\"\" # Check if there are no errors","dtype=\"float64\") x = np.linspace(0, 1, 5) y = np.logspace(2, 3,","i, j, k in zip(x, y, strings1, strings2) ) assert","strings = np.array([\"a\", \"bc\", \"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype) with clib.Session()","# output=='', GMT will just write to stdout and spaces","\"\"\" Put 'bla' in the value buffer. \"\"\" value.value =","as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\"This should have","with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as outfile:","Fault. Can't test this if by giving a bad file","GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__),","will just write to stdout and spaces are valid file","figures before calling extract_region to make sure that it's #","lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\",","invalid direction argument. \"\"\" with clib.Session() as lib: vfargs =","exception for invalid names. \"\"\" with clib.Session() as lib: with","(separated by |) correctly. \"\"\" lib = clib.Session() test_cases =","family, via in test_cases: composite = \"|\".join([family, via]) expected =","int32 int64 uint32 uint64\".split() shape = (7, 5) for dtype","= clib.Session() test_cases = [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\",","= {}\\t{}\\n\".format(shape[0], bounds) assert output == expected def test_virtual_file_fails(): \"\"\"","returns=1): with pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1] * 6,","clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as","with clib.Session() as lib: try: lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError as","1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z)","lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) assert","* 3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,","y = np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[(\"z\",","): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't get to this","to make sure it doesn't fail badly. \"\"\" with clib.Session()","clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module(\"info\", \"{} -C","for dtype in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)","-99999 assert ses[\"GMT_DOUBLE\"] != -99999 with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint:","(\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \"\"\" Make sure","dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32) strings","C lib. \"\"\" ses = clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999","Create two session and make sure they are not pointing","float64 int32 int64 uint32 uint64\".split() shape = (10, 6) for","session1.session_pointer is not None session2 = clib.Session() session2.create(name=\"test_session2\") assert session2.session_pointer","of a larger array to virtual file dataset. \"\"\" dtypes","mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) assert data_vector != data_matrix","\"bc\", \"def\", \"ghij\", \"klmno\"], dtype=dtype) strings2 = np.array([\"pqrst\", \"uvwx\", \"yz!\",","outfile.read(keep_tabs=True) expected = \"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\" for h, i, j,","test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct output with flipped","= np.arange(size, size * 2, 1, dtype=np.int32) strings1 = np.array([\"a\",","ses.info for key in ses.info: assert ses.info[key] == \"bla\" ses.destroy()","= ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, ) # Mock Open_VirtualFile","\"\"\" Fails when given bad input. \"\"\" with clib.Session() as","a grid ignoring range and inc. \"\"\" with clib.Session() as","* 2, size * 3, 1, dtype=dtype) with clib.Session() as","\"\"\" with clib.Session() as lib: assert lib.get_default(\"API_GRID_LAYOUT\") in [\"rows\", \"columns\"]","def test_create_destroy_session(): \"\"\" Test that create and destroy session are","argument correctly. \"\"\" lib = clib.Session() for family in FAMILIES:","y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\" Check","Mock GMT_Get_Default to return always the same string def mock_defaults(api,","disable=pointless-statement def test_parse_constant_single(): \"\"\" Parsing a single family argument correctly.","name == b\"API_VERSION\": value.value = b\"5.4.3\" else: value.value = b\"bla\"","and closing virtual files raises an exception for non- zero","trying to create a session before destroying the old one.","ses.create(\"test1\") with pytest.raises(GMTCLibError): ses.create(\"test2\") def test_destroy_session_fails(): \"\"\" Fail to destroy","a 3D regular grid data = np.ones((10, 12, 11), dtype=\"float32\")","two session and make sure they are not pointing to","j, k in zip(x, y, strings)) assert output == expected","= mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \"\"\"","0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\"This should have failed\")","output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i",") def test_create_data_fails(): \"\"\" Check that create_data raises exceptions for","\"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict():","def test_get_default(): \"\"\" Make sure get_default works without crashing and","\"\"\" # Create two session and make sure they are","as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected =","one column with string or object dtype into virtual file","Check that write data raises an exception for non-zero return","without inducing a Segmentation Fault (which is a good thing","i in (x, y, z)] ) expected = \"<vector memory>:","vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", # The invalid direction","= 13 x = list(range(0, size, 1)) y = tuple(range(size,","with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \"\"\"","\"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should fail if trying","assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\"","os.path.join(os.path.dirname(__file__), \"data\") with clib.Session() as _lib: gmt_version = Version(_lib.info[\"version\"]) @contextmanager","lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1, 0], ranges=[150.0,","and destroy a session twice ses = clib.Session() for __","ses[\"GMT_PAD_DEFAULT\"] != -99999 assert ses[\"GMT_DOUBLE\"] != -99999 with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"]","is a good thing because libgmt usually only fails with","not None session2 = clib.Session() session2.create(name=\"test_session2\") assert session2.session_pointer is not","assert parsed == expected def test_parse_constant_fails(): \"\"\" Check if the","Make two figures before calling extract_region to make sure that","lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2, 0], ) def","Check that it fails for > 2 dims. \"\"\" #","= np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[(\"z\", z),","dtypes: with clib.Session() as lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry =","data.z) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile,","figure, not the last figure. fig1 = Figure() region1 =","test_dataarray_to_matrix_dims_fails(): \"\"\" Check that it fails for > 2 dims.","np.arange(11) y = np.arange(12) z = np.arange(10) grid = xr.DataArray(data,","valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \"\"\" Run the function to","lib.virtualfile_from_vectors(x, y): print(\"This should have failed\") def test_virtualfile_from_matrix(): \"\"\" Test","session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\")","= clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer is not None session2 =","def test_create_data_grid_dim(): \"\"\" Create a grid ignoring range and inc.","a dataset. \"\"\" size = 13 x = list(range(0, size,","a mock instead just to exercise this part of the","clib.Session() as lib: # Grids from matrices using dim lib.create_data(","pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \"\"\" Run","it with the second one with clib.Session() as lib: lib.call_module(\"figure\",","test_parse_constant_single(): \"\"\" Parsing a single family argument correctly. \"\"\" lib","lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) def","lib.info[\"version\"] != \"5.4.3\" # Make sure the session is closed","= np.arange(size, dtype=np.int32) y = np.arange(size, size * 2, 1,","no errors or segfaults from getting all of the #","there are no errors or segfaults from getting all of","= out_fname.read().strip() assert output == \"11.5309 61.7074 -2.9289 7.8648 0.1412","-\".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0,","outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for","and inc. \"\"\" with clib.Session() as lib: # Grids from","with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=0), mock( lib, \"GMT_Close_VirtualFile\",","for non- zero return codes. \"\"\" vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\",","dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): \"\"\" Create a","print(\"Shouldn't get to this code either\") def test_virtual_file_bad_direction(): \"\"\" Test","\"{}\\n\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size(): \"\"\" Test the","the closing of the # virtual file. with clib.Session() as","os from contextlib import contextmanager import numpy as np import","region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(),","range and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0, -20.0,","pandas as pd import pytest import xarray as xr from","returns=None, mock_func=None): \"\"\" Mock a GMT C API function to","shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile:","# Activate the first figure and extract the region from","test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like vectors to a dataset. \"\"\" size","\"\"\" if name == b\"API_VERSION\": value.value = b\"5.4.3\" else: value.value","FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError,","as lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1, 0],","mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\" Return an old","(\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region,","error: assert \"Module 'info' failed with status code\" in str(error)","tuple(range(size, size * 2, 1)) z = range(size * 2,","def test_method_no_session(): \"\"\" Fails when not in a session. \"\"\"","Make sure the clib.Session.info dict is working. \"\"\" # Check","names. Use a mock instead just to exercise this part","value.value = b\"5.4.3\" else: value.value = b\"bla\" return 0 lib","\"GMT_IS_POINT\" dataset = lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1,","lib.open_virtual_file(*vfargs): print(\"Should not get to this code\") # Test the","I can get correct constants from the C lib. \"\"\"","= np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid","clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\"",") # Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session()","raises exceptions for invalid input and output. \"\"\" # Passing","Activate the first figure and extract the region from it","region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\"M6i\", frame=True, land=\"black\")","try it with the second one with clib.Session() as lib:","a virtual file with a Dataset. \"\"\" dtypes = \"float32","lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should not","def test_getitem(): \"\"\" Test that I can get correct constants","failed with status code\" in str(error) assert \"gmtinfo [ERROR]: Cannot","files raises an exception for non- zero return codes. \"\"\"","to this code either\") def test_virtual_file_bad_direction(): \"\"\" Test passing an","anyway. # This should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS )","-20.0, 20.0], inc=[0.1, 0.2], ) # If the data pointer","with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as outfile:","ses[\"GMT_DOUBLE\"] != -99999 with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint: disable=pointless-statement def","expected = lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS)","Return an old version. \"\"\" if name == b\"API_VERSION\": value.value","\"\"\" Check if the function fails when given bad input.","\"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\" dataset = lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\",","dim=[10, 20, 1, 0], ) assert data_vector != data_matrix def","given valid modifiers but is using them anyway. # This","uint64\".split() size = 10 for dtype in dtypes: x =","destroy session when given bad input. \"\"\" ses = clib.Session()","in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size","valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): \"\"\" Parsing a","pointer as output or non-zero status codes. Needed because it's","create_data raises exceptions for invalid input and output. \"\"\" #","for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement","it along to gmt info vfargs = (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\",","correctly. \"\"\" lib = clib.Session() for family in FAMILIES: parsed","family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed ==","version def mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\" Return","problems. with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with clib.Session()","# Make sure the session is closed when the exception","FAMILIES for via in VIAS) for family, via in test_cases:","Series. \"\"\" dtypes = \"float32 float64 int32 int64 uint32 uint64\".split()","specifying range and inc instead of dim. \"\"\" with clib.Session()","if name == func: return mock_func return get_libgmt_func(name, argtypes, restype)","str(error) assert \"gmtinfo [ERROR]: Cannot find file bogus-data.bla\" in str(error)","2, size * 3, 1, dtype=dtype), ) ) with clib.Session()","but is using them anyway. # This should work... lib._parse_constant(","None, ) def test_dataarray_to_matrix_works(): \"\"\" Check that dataarray_to_matrix returns correct","Test transforming a matrix to virtual file dataset. \"\"\" dtypes","\"\"\" data = np.ones((4, 5), dtype=\"float64\") x = np.linspace(0, 1,","\"hijklmn\", \"opqrst\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,","\"\"\" Test passing in one column with string or object","pointing to the same memory session1 = clib.Session() session1.create(name=\"test_session1\") assert","via) for family in FAMILIES for via in VIAS) for","= 10 for dtype in dtypes: x = np.arange(size, dtype=dtype)","codes. Needed because it's not easy to get some API","ses.create(\"session1\") assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer","with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{}","col in data.T] ) expected = \"{}\\n\".format(bounds) assert output ==","the status check when closing the virtual file # Mock","20.0], inc=[0.1, 0.2], ) # Passing in invalid geometry with","= np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid","x/y. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3)","5 cols = 3 data = full_data[:rows, :cols] with clib.Session()","to the closing of the # virtual file. with clib.Session()","clib.Session() as lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0, 0, 1,","object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test passing in two columns of","i, j, k in zip(x, y, strings)) assert output ==","modifiers but is using them anyway. # This should work...","= pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1,","dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2)","dtype=dtype) strings2 = np.array([\"pqrst\", \"uvwx\", \"yz!\", \"@#\", \"$\"], dtype=dtype) with","size = 13 for dtype in dtypes: data = pd.DataFrame(","# pylint: disable=unused-argument \"\"\" A mock GMT API function that","different sizes. \"\"\" x = np.arange(5) y = np.arange(6) with","Segmentation Fault (which is a good thing because libgmt usually","from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from",") # If the data pointer returned is None (NULL","Should also fail if not given valid modifiers but is","[ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (data.x, data.y, data.z) ]","without errors. \"\"\" # Create two session and make sure","get_libgmt_func) def test_getitem(): \"\"\" Test that I can get correct","getting from the current figure, not the last figure. fig1","lib.open_virtual_file(*vfargs): print(\"This should have failed\") def test_virtualfile_from_vectors(): \"\"\" Test the","stop=9, num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) matrix,","pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def","z)] ) expected = \"<vector memory>: N = {}\\t{}\\n\".format(size, bounds)","int32 int64 uint32 uint64\".split() size = 13 for dtype in","in one column with string or object dtype into virtual","family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) assert data_vector","output == expected def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like vectors to","\"\"\" # Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session()","for via in VIAS) for family, via in test_cases: composite","Make a 3D regular grid data = np.ones((10, 12, 11),","virtual file # Mock the opening to return 0 (success)","ses = clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999 assert ses[\"GMT_MODULE_CMD\"] !=","y. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3)","matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),","inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])","direction argument. \"\"\" with clib.Session() as lib: vfargs = (","print(\"This should have failed\") def test_virtualfile_from_matrix(): \"\"\" Test transforming a","that it fails for variable increments. \"\"\" data = np.ones((4,","with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\" Check that it fails","valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): \"\"\" Check if","lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join(","ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \"\"\"","\"GMT_IN|GMT_IS_REFERENCE\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile:","GMT_Get_Default to return an old version def mock_defaults(api, name, value):","= 5 x = np.arange(size, dtype=np.int32) y = np.arange(size, size","npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] -","a Dataset. \"\"\" dtypes = \"float32 float64 int32 int64 uint32","A mock GMT API function that always returns a given","x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3)","get to the closing of the # virtual file. with","inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])","without crashing and gives reasonable results. \"\"\" with clib.Session() as","constants from the C lib. \"\"\" ses = clib.Session() assert","bad file name because if # output=='', GMT will just","y = np.arange(size, size * 2, 1, dtype=dtype) z =","\"Module 'info' failed with status code\" in str(error) assert \"gmtinfo","as np import numpy.testing as npt import pandas as pd","are raised when API functions fail by producing a NULL","mock(lib, \"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should not get","clib.Session() as lib: assert lib.info # Mock GMT_Get_Default to return","ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If the","value): # pylint: disable=unused-argument \"\"\" Return an old version. \"\"\"","test_cases = ((family, via) for family in FAMILIES for via","Fault (which is a good thing because libgmt usually only","Check that it fails for variable increments. \"\"\" data =","with clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) #","test_cases = [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for","old one. ses.create(\"test1\") with pytest.raises(GMTCLibError): ses.create(\"test2\") def test_destroy_session_fails(): \"\"\" Fail","test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors to a dataset using pandas Series.","bad input. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"meh\",","if not given valid modifiers but is using them anyway.","wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails():","else: value.value = b\"bla\" return 0 lib = clib.Session() with","= np.ones((4, 5), dtype=\"float64\") x = np.linspace(0, 1, 5) y","for key in ses.info: assert ses.info[key] == \"bla\" ses.destroy() def","= np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9,","# virtual file. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1):","->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(),","last figure. fig1 = Figure() region1 = np.array([0, 10, -20,","assert ses.info[key] == \"bla\" ses.destroy() def test_fails_for_wrong_version(): \"\"\" Make sure","API. \"\"\" import os from contextlib import contextmanager import numpy","Create a grid ignoring range and inc. \"\"\" with clib.Session()","= clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer #","20, 1, 0], # columns, rows, layers, dtype ) #","to stdout and spaces are valid file # names. Use","from matrices using range and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\",","Fails when not in a session. \"\"\" # Create an","assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def test_get_default_fails(): \"\"\" Make sure get_default","\"\"\" Test transforming a matrix to virtual file dataset. \"\"\"","via in test_cases: composite = \"|\".join([family, via]) expected = lib[family]","for dtype in dtypes: with clib.Session() as lib: family =","mock function. \"\"\" if name == func: return mock_func return","lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\" Make sure the clib.Session.info dict is","return an old version def mock_defaults(api, name, value): # pylint:","outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for col in data.T]","GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR","def test_extract_region_two_figures(): \"\"\" Extract region should handle multiple figures existing","Check that opening and closing virtual files raises an exception","= np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid","module arguments. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\",","np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)])","\"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y","np.arange(5) y = np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput):","print(\"This should have failed\") def test_virtualfile_from_vectors(): \"\"\" Test the automation","vectors to a dataset using pandas Series. \"\"\" dtypes =","matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),","vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, ) # Mock","assert parsed == lib[family] def test_parse_constant_composite(): \"\"\" Parsing a composite","-2.9289 7.8648 0.1412 0.9338\" def test_call_module_invalid_arguments(): \"\"\" Fails for invalid","the # properties. with clib.Session() as lib: assert lib.info #","by |) correctly. \"\"\" lib = clib.Session() test_cases = ((family,","it's # getting from the current figure, not the last","20.0], inc=[0.1, 0.2], ) # If the data pointer returned","FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def","pylint: disable=pointless-statement def test_create_session_fails(): \"\"\" Check that an exception is","buffer. \"\"\" value.value = b\"bla\" return 0 ses = clib.Session()","= lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], #","np.arange(size, dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32)","= np.array([\"a\", \"bc\", \"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype) with clib.Session() as","\"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\" for h, i, j, k in zip(x,","def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct output with","check when closing the virtual file # Mock the opening","expected = \"<vector memory>: N = {}\\t{}\\n\".format(size, bounds) assert output","return 0 lib = clib.Session() with mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults): with","axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] -","valid modifiers but is using them anyway. # This should","dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with","session1 = clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer is not None session2","that it fails for > 2 dims. \"\"\" # Make","a session. \"\"\" ses = clib.Session() with mock(ses, \"GMT_Create_Session\", returns=None):","in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family]","to make the C API function fail without causing a","from packaging.version import Version from pygmt import Figure, clib from","composite constant argument (separated by |) correctly. \"\"\" lib =","(data.x, data.y, data.z) ] ) expected = \"<vector memory>: N","outfile: lib.call_module(\"info\", \"{} -C ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds","same string def mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\"","fails with errors). \"\"\" if mock_func is None: def mock_api_function(*args):","y, strings) as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile}","test_dataarray_to_matrix_inc_fails(): \"\"\" Check that it fails for variable increments. \"\"\"","test_create_data_grid_range(): \"\"\" Create a grid specifying range and inc instead","\"<matrix memory>: N = {}\\t{}\\n\".format(rows, bounds) assert output == expected","non-zero status codes. Needed because it's not easy to get","family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], # columns, rows,","# Create an instance of Session without \"with\" so no","clib.Session() test_cases = [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ]","should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS ) # But this","is raised, the code won't get to the closing of","matrices using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1,","lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join( f\"{h}\\t{i}\\t{j}","data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0],","with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile()","= np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x,","1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as","x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if dataarray_to_matrix","make sure they are not pointing to the same memory","family in FAMILIES for via in VIAS) for family, via","1 assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def test_get_default_fails(): \"\"\" Make sure","0], ) def test_create_data_grid_range(): \"\"\" Create a grid specifying range","\"<matrix memory>: N = {}\\t{}\\n\".format(shape[0], bounds) assert output == expected","passing in data via a virtual file with a Dataset.","code won't get to the closing of the # virtual","dataset. \"\"\" size = 13 x = list(range(0, size, 1))","input. \"\"\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\") with","np.ones((10, 12, 11), dtype=\"float32\") x = np.arange(11) y = np.arange(12)","\"\"\" Check that it fails for > 2 dims. \"\"\"","clib.Session() as lib: # Grids from matrices using range and","array-like vectors to a dataset. \"\"\" size = 13 x","Check that dataarray_to_matrix returns correct output. \"\"\" data = np.diag(v=np.arange(3))","== \"bla\" ses.destroy() def test_fails_for_wrong_version(): \"\"\" Make sure the clib.Session","one with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with clib.Session()","assert lib.info # Mock GMT_Get_Default to return always the same","should have failed\") def test_virtualfile_from_matrix(): \"\"\" Test transforming a matrix","or non-zero status codes. Needed because it's not easy to","file bogus-data.bla\" in str(error) def test_method_no_session(): \"\"\" Fails when not","\"bc\", \"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype) with clib.Session() as lib: with","returns correct output with flipped x/y. \"\"\" data = np.diag(v=np.arange(3))","pylint: disable=pointless-statement def test_parse_constant_single(): \"\"\" Parsing a single family argument","uint64\".split() shape = (10, 6) for dtype in dtypes: full_data",") data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) #","Pass array-like vectors to a dataset. \"\"\" size = 13","disable=pointless-statement def test_create_destroy_session(): \"\"\" Test that create and destroy session","!= -99999 with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint: disable=pointless-statement def test_create_destroy_session():","(which is a good thing because libgmt usually only fails","\"\"\" # Make a 3D regular grid data = np.ones((10,","= np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\",","y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\" Check that it fails for >","automation for transforming vectors to virtual file dataset. \"\"\" dtypes","np.linspace(0, 1, 5) y = np.logspace(2, 3, 4) grid =","->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max())","\"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1] * 6, \"some-file-name\", None, ) def","family argument correctly. \"\"\" lib = clib.Session() for family in","is the GMT error message was captured. \"\"\" with clib.Session()","\"\"\" Check that extract region fails if nothing has been","this if by giving a bad file name because if","output or non-zero status codes. Needed because it's not easy","test_virtualfile_from_vectors_transpose(): \"\"\" Test transforming matrix columns to virtual file dataset.","session are called without errors. \"\"\" # Create two session","get to this code\") # Test the status check when","def test_virtual_file(): \"\"\" Test passing in data via a virtual","= os.path.join(os.path.dirname(__file__), \"data\") with clib.Session() as _lib: gmt_version = Version(_lib.info[\"version\"])","dtypes = \"float32 float64 int32 int64 uint32 uint64\".split() shape =","def test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct output with","\"points.txt\") out_fname = \"test_call_module.txt\" with clib.Session() as lib: with GMTTempFile()","for arrays of different sizes. \"\"\" x = np.arange(5) y","abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check that dataarray_to_matrix returns","stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data,","range(size * 2, size * 3, 1) with clib.Session() as","two columns of string or object dtype into virtual file","family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2, 0], ) def test_virtual_file():","func, returns=None, mock_func=None): \"\"\" Mock a GMT C API function","dim=[11, 10, 2, 0], ) def test_virtual_file(): \"\"\" Test passing","None: def mock_api_function(*args): # pylint: disable=unused-argument \"\"\" A mock GMT","{}\\t{}\\n\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def","columns, rows, layers, dtype ) data = np.arange(shape[0] * shape[1],","created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError):","larger array to virtual file dataset. \"\"\" dtypes = \"float32","dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as","file # names. Use a mock instead just to exercise","for i in (data.x, data.y, data.z) ] ) expected =","GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected","Can't test this if by giving a bad file name","x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\" Check that it","\"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2, 0],","with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \"\"\" Parsing","= \"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\" for h, i, j, k in","with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should not get to this code\")","invalid module arguments. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError):","a single family argument correctly. \"\"\" lib = clib.Session() for","if # output=='', GMT will just write to stdout and","lib.call_module(\"info\", \"{} -C ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds =","a larger array to virtual file dataset. \"\"\" dtypes =","= np.arange(10) grid = xr.DataArray(data, coords=[(\"z\", z), (\"y\", y), (\"x\",","7.8648 0.1412 0.9338\" def test_call_module_invalid_arguments(): \"\"\" Fails for invalid module","ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \"\"\" Check that an","in data.T] ) expected = \"<matrix memory>: N = {}\\t{}\\n\".format(rows,","with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\"This","test_virtualfile_from_matrix(): \"\"\" Test transforming a matrix to virtual file dataset.","into virtual file dataset. \"\"\" size = 5 x =","mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \"\"\" Return","the same memory session1 = clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer is","the same string def mock_defaults(api, name, value): # pylint: disable=unused-argument","for variable increments. \"\"\" data = np.ones((4, 5), dtype=\"float64\") x","as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should","mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\", get_libgmt_func) def test_getitem(): \"\"\" Test that","cols = 3 data = full_data[:rows, :cols] with clib.Session() as","fail badly. \"\"\" with clib.Session() as lib: # Dataset from","!= -99999 assert ses[\"GMT_DOUBLE\"] != -99999 with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] #","empty dictionary assert ses.info for key in ses.info: assert ses.info[key]","assert lib.info[\"version\"] != \"5.4.3\" # Make sure the session is","bounds) assert output == expected def test_virtual_file_fails(): \"\"\" Check that","virtual file dataset. \"\"\" size = 5 x = np.arange(size,","f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i,","\"gmtinfo [ERROR]: Cannot find file bogus-data.bla\" in str(error) def test_method_no_session():","{k}\\n\" for h, i, j, k in zip(x, y, strings1,","-10]) fig1.coast(region=region1, projection=\"M6i\", frame=True, land=\"black\") fig2 = Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\",","data = np.ones((10, 12, 11), dtype=\"float32\") x = np.arange(11) y","(x, y, z)] ) expected = \"<vector memory>: N =","create a session. \"\"\" ses = clib.Session() with mock(ses, \"GMT_Create_Session\",","pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session()","lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \"\"\" Check","pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \"data\") with clib.Session() as","flipped y. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4,","h, i, j, k in zip(x, y, strings1, strings2) )","y, strings)) assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def","0], # columns, rows, layers, dtype ) data = np.arange(shape[0]","\"\"\" if name == func: return mock_func return get_libgmt_func(name, argtypes,","data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size","raises an exception for invalid names. \"\"\" with clib.Session() as","def test_create_data_dataset(): \"\"\" Run the function to make sure it","size * 2, 1, dtype=dtype) z = np.arange(size * 2,","make sure that it's # getting from the current figure,","lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \"\"\" Parsing a single","y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct output","exception for non-zero return codes. \"\"\" # It's hard to","when failing to create a session. \"\"\" ses = clib.Session()","= Version(_lib.info[\"version\"]) @contextmanager def mock(session, func, returns=None, mock_func=None): \"\"\" Mock","!= session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a session","mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): \"\"\" Create","later. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=0), mock( lib,","2, 0], ) def test_virtual_file(): \"\"\" Test passing in data","with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as","a virtual file and pass it along to gmt info","lib: assert lib.info[\"version\"] != \"5.4.3\" # Make sure the session","with clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module(\"info\", \"{}","61.7074 -2.9289 7.8648 0.1412 0.9338\" def test_call_module_invalid_arguments(): \"\"\" Fails for","full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols","x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3)","from vectors data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20,","pytest.raises(GMTVersionError): with lib: assert lib.info[\"version\"] != \"5.4.3\" # Make sure","j, k in zip(x, y, strings1, strings2) ) assert output","wrappers for the C API. \"\"\" import os from contextlib","test_call_module_error_message(): \"\"\" Check is the GMT error message was captured.","\"\"\" Test the automation for transforming vectors to virtual file","have failed\") def test_virtualfile_from_matrix(): \"\"\" Test transforming a matrix to","npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\"","data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add","\"columns\"] assert int(lib.get_default(\"API_CORES\")) >= 1 assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def","is too old. \"\"\" # Mock GMT_Get_Default to return an","pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\"This should have failed\") def test_virtualfile_from_vectors(): \"\"\"","that create_data raises exceptions for invalid input and output. \"\"\"","1, dtype=np.int32) strings = np.array([\"a\", \"bc\", \"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype)","= np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols =","clib.Session.info dict is working. \"\"\" # Check if there are","file. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError):","API functions to fail without inducing a Segmentation Fault (which","to the same memory session1 = clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer","import pytest import xarray as xr from packaging.version import Version","with errors). \"\"\" if mock_func is None: def mock_api_function(*args): #","clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\") def test_call_module_error_message(): \"\"\"","clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS","an exception for invalid names. \"\"\" with clib.Session() as lib:","fig2 = Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) # Activate the first","the exception is raised, the code won't get to the","the second one with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name))","out_fname: lib.call_module(\"info\", \"{} -C ->{}\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output =","def mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\" Return an","\"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i, j, k in zip(x, y, strings)) assert","dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size * 2,","as lib: with GMTTempFile() as out_fname: lib.call_module(\"info\", \"{} -C ->{}\".format(data_fname,","setattr(session, \"get_libgmt_func\", get_libgmt_func) def test_getitem(): \"\"\" Test that I can","output == expected def test_virtual_file_fails(): \"\"\" Check that opening and","with lib.virtualfile_from_vectors(x, y): print(\"This should have failed\") def test_virtualfile_from_matrix(): \"\"\"","correct output. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4,","lib: with mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11,","as lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\" Fails","error message was captured. \"\"\" with clib.Session() as lib: try:","= lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], )","= \"float32 float64 int32 int64 uint32 uint64\".split() shape = (10,","dataarray_to_matrix returns correct output. \"\"\" data = np.diag(v=np.arange(3)) x =","* shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as","assert output == expected def test_virtualfile_from_matrix_slice(): \"\"\" Test transforming a","-20, -10]) fig1.coast(region=region1, projection=\"M6i\", frame=True, land=\"black\") fig2 = Figure() fig2.basemap(region=\"US.HI+r5\",","full_data[:rows, :cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile:","TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \"data\") with clib.Session() as _lib: gmt_version =","with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \"\"\" Extract region","an empty dictionary assert ses.info for key in ses.info: assert","working. \"\"\" # Check if there are no errors or","clib.Session() as lib: try: lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError as error:","arguments. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\")","value.value = b\"bla\" return 0 ses = clib.Session() ses.create(\"test-session\") with",":cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with","= [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case","contextmanager import numpy as np import numpy.testing as npt import","= np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the","as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output","exception is raised, the code won't get to the closing","the clib.Session raises an exception if GMT is too old.","for family, via in test_cases: composite = \"|\".join([family, via]) expected","2, 1, dtype=dtype) z = np.arange(size * 2, size *","returns a given value. \"\"\" return returns mock_func = mock_api_function","\"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput):","disable=protected-access \"\"\" Test the wrappers for the C API. \"\"\"","sure get_default works without crashing and gives reasonable results. \"\"\"","geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def","\"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", # The invalid direction argument 0, )","test_dataarray_to_matrix_works(): \"\"\" Check that dataarray_to_matrix returns correct output. \"\"\" data","strings1, strings2) as vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile}","= np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5,","to a dataset. \"\"\" size = 13 x = list(range(0,","( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, ) # Mock Open_VirtualFile to","\"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1] *","pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype),","nothing has been plotted. \"\"\" Figure() with pytest.raises(GMTCLibError): with clib.Session()","test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should","\"GMT_Close_VirtualFile\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't get","* 2, size * 3, 1, dtype=dtype), ) ) with","passing in two columns of string or object dtype into","= xr.DataArray(data, coords=[(\"z\", z), (\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput):","# pylint: disable=protected-access \"\"\" Test the wrappers for the C","test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if dataarray_to_matrix returns correct output with flipped","expected def test_virtual_file_fails(): \"\"\" Check that opening and closing virtual","strings1, strings2) ) assert output == expected def test_virtualfile_from_vectors_transpose(): \"\"\"","to a virtual file and pass it along to gmt","from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \"data\") with clib.Session()","float64 int32 int64 uint32 uint64\".split() size = 10 for dtype","time. \"\"\" # Make two figures before calling extract_region to","mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], # columns, rows, layers, dtype","dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size, size *","\"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y","as lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with clib.Session() as lib: wesn1","shape = (10, 6) for dtype in dtypes: full_data =","ses.info: assert ses.info[key] == \"bla\" ses.destroy() def test_fails_for_wrong_version(): \"\"\" Make","mock(ses, \"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should fail if","\"GMT_Open_VirtualFile\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should not get to","lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2],","in dtypes: with clib.Session() as lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry","size * 2, 1)) z = range(size * 2, size","data.z) ] ) expected = \"<vector memory>: N = {}\\t{}\\n\".format(size,","as lib: with mock(lib, \"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\",","= ((family, via) for family in FAMILIES for via in","\"klmno\"], dtype=dtype) strings2 = np.array([\"pqrst\", \"uvwx\", \"yz!\", \"@#\", \"$\"], dtype=dtype)","codes. \"\"\" # It's hard to make the C API","write to stdout and spaces are valid file # names.","Test transforming matrix columns to virtual file dataset. \"\"\" dtypes","mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session,","clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\") with mock(ses, \"GMT_Destroy_Session\", returns=1): with","lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\"This should have failed\")","Test the automation for transforming vectors to virtual file dataset.","rows, layers, dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)","np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5,","y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def","get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \"\"\" Return our","fail without inducing a Segmentation Fault (which is a good","\"bla\" ses.destroy() def test_fails_for_wrong_version(): \"\"\" Make sure the clib.Session raises","mock(ses, \"GMT_Destroy_Session\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \"\"\"","= range(size * 2, size * 3, 1) with clib.Session()","5) y = np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\"y\",","0.9338\" def test_call_module_invalid_arguments(): \"\"\" Fails for invalid module arguments. \"\"\"","2, 1, dtype=np.int32) strings1 = np.array([\"a\", \"bc\", \"def\", \"ghij\", \"klmno\"],","\"\"\" Check that write data raises an exception for non-zero","just to exercise this part of the code. with clib.Session()","- y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct","variable increments. \"\"\" data = np.ones((4, 5), dtype=\"float64\") x =","= np.arange(size, size * 2, 1, dtype=dtype) z = np.arange(size","= {}\\t{}\\n\".format(size, bounds) assert output == expected def test_extract_region_fails(): \"\"\"","= session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \"\"\" Return our mock","the context. # If the exception is raised, the code","returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should fail if trying to","exercise this part of the code. with clib.Session() as lib:","\"\"\" Run the function to make sure it doesn't fail","crashing and gives reasonable results. \"\"\" with clib.Session() as lib:","to destroy session when given bad input. \"\"\" ses =","lib.call_module(\"meh\", \"\") def test_call_module_error_message(): \"\"\" Check is the GMT error","rows, layers, dtype ) # Dataset from matrices data_matrix =","in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\"session1\") assert","x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(),","250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing in invalid","# pylint: disable=unused-argument \"\"\" Return an old version. \"\"\" if","Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def test_get_default_fails(): \"\"\" Make sure get_default raises","existing at the same time. \"\"\" # Make two figures","\"5.4.3\" # Make sure the session is closed when the","np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset","z = range(size * 2, size * 3, 1) with","them anyway. # This should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS","shape = (5, 3) for dtype in dtypes: with clib.Session()","session when given bad input. \"\"\" ses = clib.Session() with","in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data(","returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2, 0], )","sure get_default raises an exception for invalid names. \"\"\" with","None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails():","test_call_module_invalid_name(): \"\"\" Fails when given bad input. \"\"\" with clib.Session()","Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) # Activate the first figure and","lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\",","\"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (data.x, data.y, data.z)","with clib.Session() as lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\"","size = 5 x = np.arange(size, dtype=np.int32) y = np.arange(size,","\"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1] * 6, \"some-file-name\", None, ) def test_dataarray_to_matrix_works():","1, 5) y = np.logspace(2, 3, 4) grid = xr.DataArray(data,","with pytest.raises(GMTVersionError): with lib: assert lib.info[\"version\"] != \"5.4.3\" # Make","dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1]","->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max())","lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with the second","clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\" Make","as error: assert \"Module 'info' failed with status code\" in","with flipped y. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0,","always the same string def mock_defaults(api, name, value): # pylint:","lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer","np.arange(size, size * 2, 1, dtype=np.int32) strings1 = np.array([\"a\", \"bc\",","grid ignoring range and inc. \"\"\" with clib.Session() as lib:","returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't get to","dtype in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows","lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with clib.Session() as lib: wesn1 = lib.extract_region()","dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5","pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1] * 6, \"some-file-name\", None,","clib.Session() session2.create(name=\"test_session2\") assert session2.session_pointer is not None assert session2.session_pointer !=","Check is the GMT error message was captured. \"\"\" with","region should handle multiple figures existing at the same time.","that an exception is raised when failing to create a","return 0 (success) so that we don't open a file","current figure, not the last figure. fig1 = Figure() region1","data.T] ) expected = \"<matrix memory>: N = {}\\t{}\\n\".format(shape[0], bounds)","with clib.Session() as lib: # Grids from matrices using dim","shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset():","as outfile: lib.call_module(\"info\", \"{} -C ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True)","dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import (","in test_cases: composite = \"|\".join([family, via]) expected = lib[family] +","grid data = np.ones((10, 12, 11), dtype=\"float32\") x = np.arange(11)","# pylint: disable=pointless-statement def test_create_session_fails(): \"\"\" Check that an exception","to create a session before destroying the old one. ses.create(\"test1\")","\"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(),","\"\"\" size = 5 x = np.arange(size, dtype=np.int32) y =","before calling extract_region to make sure that it's # getting","def test_parse_constant_fails(): \"\"\" Check if the function fails when given","with status code\" in str(error) assert \"gmtinfo [ERROR]: Cannot find","# Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as","lib: with mock(lib, \"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\",","data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname = \"test_call_module.txt\" with clib.Session() as","\"test_call_module.txt\" with clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module(\"info\",","col in data.T] ) expected = \"<matrix memory>: N =","for i, j, k in zip(x, y, strings)) assert output","pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \"\"\" Make sure get_default works without","the opening to return 0 (success) so that we don't","\"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col in data.T] ) expected =","\"\"\" return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def","expected def test_parse_constant_fails(): \"\"\" Check if the function fails when","easy to get some API functions to fail without inducing","the C API. \"\"\" import os from contextlib import contextmanager","failed\") def test_virtualfile_from_matrix(): \"\"\" Test transforming a matrix to virtual","np.arange(size, size * 2, 1, dtype=np.int32) strings = np.array([\"a\", \"bc\",","# Mock GMT_Get_Default to return an old version def mock_defaults(api,","clib.Session raises an exception if GMT is too old. \"\"\"","sure the clib.Session raises an exception if GMT is too","expected def test_virtualfile_from_matrix_slice(): \"\"\" Test transforming a slice of a","5), dtype=\"float64\") x = np.linspace(0, 1, 5) y = np.logspace(2,","test_fails_for_wrong_version(): \"\"\" Make sure the clib.Session raises an exception if","lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\",","the clib.Session.info dict is working. \"\"\" # Check if there","we won't close later. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\",","using range and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0,","\"\"\" Check that dataarray_to_matrix returns correct output with flipped y.","matrix to virtual file dataset. \"\"\" dtypes = \"float32 float64","by producing a NULL pointer as output or non-zero status","with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't get to this code","thing because libgmt usually only fails with errors). \"\"\" if","as lib: assert lib.get_default(\"API_GRID_LAYOUT\") in [\"rows\", \"columns\"] assert int(lib.get_default(\"API_CORES\")) >=","z) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile,","uint32 uint64\".split() shape = (7, 5) for dtype in dtypes:","= np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\"M6i\", frame=True, land=\"black\") fig2","with clib.Session() as lib: with mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\",","argtypes, restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\", get_libgmt_func) def","] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS)","lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as","\"\") def test_call_module_error_message(): \"\"\" Check is the GMT error message","np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid =","if GMT is too old. \"\"\" # Mock GMT_Get_Default to","pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers","[\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for col in data.T] ) expected = \"<matrix","geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\",","to this code\") # Test the status check when closing","\"float32 float64 int32 int64 uint32 uint64\".split() size = 13 for","when API functions fail by producing a NULL pointer as","lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\" Make sure the","\"\"\" ses = clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999 assert ses[\"GMT_MODULE_CMD\"]","Dataset from matrices data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10,","and spaces are valid file # names. Use a mock","->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i, j,","for an empty dictionary assert ses.info for key in ses.info:","clib.Session() as _lib: gmt_version = Version(_lib.info[\"version\"]) @contextmanager def mock(session, func,","failing to create a session. \"\"\" ses = clib.Session() with","all of the # properties. with clib.Session() as lib: assert","lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def",") # Dataset from matrices data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\",","transforming a slice of a larger array to virtual file","only fails with errors). \"\"\" if mock_func is None: def","return codes. \"\"\" vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None,","with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\"session1\") assert ses.session_pointer is","== b\"API_VERSION\": value.value = b\"5.4.3\" else: value.value = b\"bla\" return","data raises an exception for non-zero return codes. \"\"\" #","for col in data.T] ) expected = \"{}\\n\".format(bounds) assert output","# Use in a different session to avoid any memory","250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \"\"\" Check","{}\\t{}\\n\".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass","mock(session, func, returns=None, mock_func=None): \"\"\" Mock a GMT C API","status check when entering the context. # If the exception","for dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype),","\"\"\" value.value = b\"bla\" return 0 ses = clib.Session() ses.create(\"test-session\")","Check for an empty dictionary assert ses.info for key in",") expected = \"<vector memory>: N = {}\\t{}\\n\".format(size, bounds) assert","function that always returns a given value. \"\"\" return returns","disable=pointless-statement def test_create_session_fails(): \"\"\" Check that an exception is raised","was captured. \"\"\" with clib.Session() as lib: try: lib.call_module(\"info\", \"bogus-data.bla\")","\"\"\" dtypes = \"float32 float64 int32 int64 uint32 uint64\".split() size","with clib.Session() as lib: # Dataset from vectors data_vector =","4) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput):","gives reasonable results. \"\"\" with clib.Session() as lib: assert lib.get_default(\"API_GRID_LAYOUT\")","pytest.raises(GMTCLibError): ses.create(\"test2\") def test_destroy_session_fails(): \"\"\" Fail to destroy session when","as lib: try: lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError as error: assert","\"float32 float64 int32 int64 uint32 uint64\".split() shape = (7, 5)","sure it doesn't fail badly. \"\"\" with clib.Session() as lib:","as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile:","clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with clib.Session() as lib:","GMT API function that always returns a given value. \"\"\"","clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as","= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,","outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for","import numpy.testing as npt import pandas as pd import pytest","family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0,","parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def","\"\"\" size = 13 x = list(range(0, size, 1)) y","\"\"\" Check that it fails for variable increments. \"\"\" data","as npt import pandas as pd import pytest import xarray","lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it","pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\" Fails when given bad","won't get to the closing of the # virtual file.","with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile:","# Add the dataset to a virtual file and pass","* 2, 1, dtype=np.int32) strings1 = np.array([\"a\", \"bc\", \"def\", \"ghij\",","for dtype in dtypes: x = np.arange(size, dtype=dtype) y =","shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile:","functions fail by producing a NULL pointer as output or","not given valid modifiers but is using them anyway. #","argument (separated by |) correctly. \"\"\" lib = clib.Session() test_cases","from the current figure, not the last figure. fig1 =","lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \"\"\" Run the","for transforming vectors to virtual file dataset. \"\"\" dtypes =","are called without errors. \"\"\" # Create two session and","session2.create(name=\"test_session2\") assert session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer","an old version. \"\"\" if name == b\"API_VERSION\": value.value =","= \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col in data.T] ) expected","the value buffer. \"\"\" value.value = b\"bla\" return 0 ses","memory>: N = {}\\t{}\\n\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\"dtype\",","data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2,","\"\"\" Fail to destroy session when given bad input. \"\"\"","dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])","desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1]","\"{} -C ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join(","np import numpy.testing as npt import pandas as pd import","clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \"\"\" Extract region should","lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\" Fails when","= 3 data = full_data[:rows, :cols] with clib.Session() as lib:","output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test","* 2, 1, dtype=dtype) z = np.arange(size * 2, size","sure they are not pointing to the same memory session1","# Dataset from matrices data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\",","code either\") def test_virtual_file_bad_direction(): \"\"\" Test passing an invalid direction","file dataset. \"\"\" dtypes = \"float32 float64 int32 int64 uint32","= lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1, 0], #","getting all of the # properties. with clib.Session() as lib:","0.1412 0.9338\" def test_call_module_invalid_arguments(): \"\"\" Fails for invalid module arguments.","# But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None","f\"{h}\\t{i}\\t{j} {k}\\n\" for h, i, j, k in zip(x, y,","Fails when given bad input. \"\"\" with clib.Session() as lib:","as pd import pytest import xarray as xr from packaging.version","in zip(x, y, strings1, strings2) ) assert output == expected","get to this code either\") def test_virtual_file_bad_direction(): \"\"\" Test passing","the code. with clib.Session() as lib: with mock(lib, \"GMT_Write_Data\", returns=1):","invalid names. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\")","z=np.arange(size * 2, size * 3, 1, dtype=dtype), ) )","has been plotted. \"\"\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as","num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) matrix, region,","\"\"\" Parsing a single family argument correctly. \"\"\" lib =","Test that I can get correct constants from the C","with lib.open_virtual_file(*vfargs): print(\"This should have failed\") def test_virtualfile_from_vectors(): \"\"\" Test","x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(),","np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5,","# Make a 3D regular grid data = np.ones((10, 12,","Segmentation # Fault. Can't test this if by giving a","mock(lib, \"GMT_Open_VirtualFile\", returns=0), mock( lib, \"GMT_Close_VirtualFile\", returns=1 ): with pytest.raises(GMTCLibError):","= \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (data.x, data.y,","of the # virtual file. with clib.Session() as lib, mock(lib,","Test passing an invalid direction argument. \"\"\" with clib.Session() as","with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile()","\"\"\" with clib.Session() as lib: try: lib.call_module(\"info\", \"bogus-data.bla\") except GMTCLibError","data pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError): with","1, 0], ) def test_create_data_grid_range(): \"\"\" Create a grid specifying","def test_virtualfile_from_matrix(): \"\"\" Test transforming a matrix to virtual file","= \"<matrix memory>: N = {}\\t{}\\n\".format(shape[0], bounds) assert output ==","x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]])","shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to a","def test_call_module(): \"\"\" Run a command to see if call_module","outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join(f\"{i}\\t{j}\\t{k}\\n\"","\"GMT_Get_Default\", mock_func=mock_defaults): # Check for an empty dictionary assert ses.info","\"\"\" Make sure get_default raises an exception for invalid names.","the automation for transforming vectors to virtual file dataset. \"\"\"","(\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0,","int64 uint32 uint64\".split() shape = (10, 6) for dtype in","a dataset using pandas Series. \"\"\" dtypes = \"float32 float64","as _lib: gmt_version = Version(_lib.info[\"version\"]) @contextmanager def mock(session, func, returns=None,","session. \"\"\" ses = clib.Session() with mock(ses, \"GMT_Create_Session\", returns=None): with","bad input. \"\"\" lib = clib.Session() test_cases = [ \"SOME_random_STRING\",","and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", ranges=[150.0, 250.0, -20.0, 20.0],","= ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", # The invalid direction argument","dim=[shape[1], shape[0], 1, 0], # columns, rows, layers, dtype )","\"\"\" A mock GMT API function that always returns a","import pandas as pd import pytest import xarray as xr","f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\"","before destroying the old one. ses.create(\"test1\") with pytest.raises(GMTCLibError): ses.create(\"test2\") def","columns to virtual file dataset. \"\"\" dtypes = \"float32 float64","import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import","5) for dtype in dtypes: data = np.arange(shape[0] * shape[1],","pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib, \"GMT_Create_Data\",","destroy a session twice ses = clib.Session() for __ in","0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing","returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \"\"\" Run a","\"\"\" Test passing in two columns of string or object","with mock(ses, \"GMT_Create_Session\", returns=None): with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should fail","that dataarray_to_matrix returns correct output. \"\"\" data = np.diag(v=np.arange(3)) x","* 3, 1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,","matrix=data) # Add the dataset to a virtual file and","= clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999 assert ses[\"GMT_MODULE_CMD\"] != -99999","= \"float32 float64 int32 int64 uint32 uint64\".split() shape = (7,","test_virtualfile_from_vectors_diff_size(): \"\"\" Test the function fails for arrays of different","* shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to","strings2) ) assert output == expected def test_virtualfile_from_vectors_transpose(): \"\"\" Test","in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data(","lib. \"\"\" ses = clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] != -99999 assert","to see if call_module works. \"\"\" data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\")","figure and extract the region from it # Use in","Parsing a single family argument correctly. \"\"\" lib = clib.Session()","out_fname = \"test_call_module.txt\" with clib.Session() as lib: with GMTTempFile() as","wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with","'bla' in the value buffer. \"\"\" value.value = b\"bla\" return","should have failed\") def test_virtualfile_from_vectors(): \"\"\" Test the automation for","abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\" Check that it fails","\"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with pytest.raises(GMTInvalidInput):","lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\",","pylint: disable=unused-argument \"\"\" Return an old version. \"\"\" if name","Needed because it's not easy to get some API functions","os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname = \"test_call_module.txt\" with clib.Session() as lib: with","memory problems. with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig1._name)) with","name, value): # pylint: disable=unused-argument \"\"\" Return an old version.","clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=0), mock( lib, \"GMT_Close_VirtualFile\", returns=1","int(lib.get_default(\"API_CORES\")) >= 1 assert Version(lib.get_default(\"API_VERSION\")) >= Version(\"6.2.0\") def test_get_default_fails(): \"\"\"","outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (x,","(7, 5) for dtype in dtypes: data = np.arange(shape[0] *","value buffer. \"\"\" value.value = b\"bla\" return 0 ses =","size * 2, 1, dtype=np.int32) strings = np.array([\"a\", \"bc\", \"defg\",","y = np.arange(size, size * 2, 1, dtype=np.int32) strings =","test_virtualfile_from_vectors(): \"\"\" Test the automation for transforming vectors to virtual","destroy session are called without errors. \"\"\" # Create two","exception is raised when failing to create a session. \"\"\"","desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\" Check","# pylint: disable=pointless-statement def test_create_destroy_session(): \"\"\" Test that create and","Version from pygmt import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix","def test_virtualfile_from_vectors(): \"\"\" Test the automation for transforming vectors to","= \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\" dataset = lib.create_data( family=family, geometry=geometry,","with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\") with mock(ses, \"GMT_Destroy_Session\", returns=1): with pytest.raises(GMTCLibError):","open a file that # we won't close later. with","test_create_session_fails(): \"\"\" Check that an exception is raised when failing","matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region,","outfile.read(keep_tabs=True) expected = \"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i, j, k in zip(x,","inc=[0.1, 0.2], ) def test_create_data_fails(): \"\"\" Check that create_data raises","= np.ones((10, 12, 11), dtype=\"float32\") x = np.arange(11) y =","!= \"5.4.3\" # Make sure the session is closed when","shape[0], 1, 0], # columns, rows, layers, dtype ) data","check when entering the context. # If the exception is","def test_parse_constant_composite(): \"\"\" Parsing a composite constant argument (separated by","\"@#\", \"$\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,","GMTTempFile() as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True)","functions to fail without inducing a Segmentation Fault (which is","\"\"\" Check that an exception is raised when failing to","= (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with","\"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, ) # Mock Open_VirtualFile to test the","npt import pandas as pd import pytest import xarray as","uint32 uint64\".split() shape = (5, 3) for dtype in dtypes:","lib.call_module(\"info\", \"{} -C ->{}\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip()","API function that always returns a given value. \"\"\" return","when closing the virtual file # Mock the opening to","ses.info[key] == \"bla\" ses.destroy() def test_fails_for_wrong_version(): \"\"\" Make sure the","clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\"This should","for h, i, j, k in zip(x, y, strings1, strings2)","lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} -C","correct constants from the C lib. \"\"\" ses = clib.Session()","data.T] ) expected = \"{}\\n\".format(bounds) assert output == expected def","\"\"\" Pass vectors to a dataset using pandas Series. \"\"\"","np.arange(size * 2, size * 3, 1, dtype=dtype) with clib.Session()","dataset = lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1, 0],","size * 2, 1, dtype=np.int32) strings1 = np.array([\"a\", \"bc\", \"def\",","returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None,","\"{} -C ->{}\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert","with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\",","info vfargs = (family, geometry, \"GMT_IN|GMT_IS_REFERENCE\", dataset) with lib.open_virtual_file(*vfargs) as","\"defg\", \"hijklmn\", \"opqrst\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,","npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\"","lib = clib.Session() for family in FAMILIES: parsed = lib._parse_constant(family,","that exceptions are raised when API functions fail by producing","5 x = np.arange(size, dtype=np.int32) y = np.arange(size, size *","xr.DataArray(data, coords=[(\"z\", z), (\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid)","Dataset from vectors data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10,","xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default():","float64 int32 int64 uint32 uint64\".split() size = 13 for dtype","[ERROR]: Cannot find file bogus-data.bla\" in str(error) def test_method_no_session(): \"\"\"","clib.Session() as lib: assert lib.get_default(\"API_GRID_LAYOUT\") in [\"rows\", \"columns\"] assert int(lib.get_default(\"API_CORES\"))","test_call_module(): \"\"\" Run a command to see if call_module works.","size = 13 x = list(range(0, size, 1)) y =","dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1]","outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output = outfile.read(keep_tabs=True) expected = \"\".join(","rows = 5 cols = 3 data = full_data[:rows, :cols]","lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region()","Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES,","= np.arange(11) y = np.arange(12) z = np.arange(10) grid =","C API function fail without causing a Segmentation # Fault.","ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing in","-C ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(),","# pylint: disable=pointless-statement def test_parse_constant_single(): \"\"\" Parsing a single family","x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \"\"\" Make sure get_default","mock_func=None): \"\"\" Mock a GMT C API function to make","raises an exception for non- zero return codes. \"\"\" vfargs","using pandas Series. \"\"\" dtypes = \"float32 float64 int32 int64","giving a bad file name because if # output=='', GMT","pylint: disable=protected-access \"\"\" Test the wrappers for the C API.","flipped x/y. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0,","test_create_data_grid_dim(): \"\"\" Create a grid ignoring range and inc. \"\"\"","\"\"\" Mock a GMT C API function to make it","is not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() #","session is closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError):","3, 1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,","( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile","= np.arange(size, dtype=dtype) y = np.arange(size, size * 2, 1,","output == \"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\" def test_call_module_invalid_arguments():",") with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as","using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0],","desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check","Create and destroy a session twice ses = clib.Session() for","dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size *","lib = clib.Session() test_cases = [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\",","\"yz!\", \"@#\", \"$\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,","bounds = \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (data.x,","= outfile.read(keep_tabs=True) expected = \"\".join(f\"{i}\\t{j}\\t{k}\\n\" for i, j, k in","-150.0, 15.0, 25.0])) def test_write_data_fails(): \"\"\" Check that write data","y), (\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data))","lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): \"\"\" Parsing","if dataarray_to_matrix returns correct output with flipped x. \"\"\" data","outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds =","passing an invalid direction argument. \"\"\" with clib.Session() as lib:","\"\"\" Check that opening and closing virtual files raises an","in two columns of string or object dtype into virtual","Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\"M6i\", frame=True,","region from it # Use in a different session to","= xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def","xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid)","the C lib. \"\"\" ses = clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"] !=","data_vector != data_matrix def test_create_data_grid_dim(): \"\"\" Create a grid ignoring","also fail if not given valid modifiers but is using","strings)) assert output == expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype):","status codes. Needed because it's not easy to get some","as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile()","dtype=\"float32\") x = np.arange(11) y = np.arange(12) z = np.arange(10)","different session to avoid any memory problems. with clib.Session() as","= \"<matrix memory>: N = {}\\t{}\\n\".format(rows, bounds) assert output ==","\"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\" Fails when given bad input. \"\"\"","if there are no errors or segfaults from getting all","errors or segfaults from getting all of the # properties.","virtual file. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=1): with","session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a","non-zero return codes. \"\"\" # It's hard to make the","= clib.Session() session2.create(name=\"test_session2\") assert session2.session_pointer is not None assert session2.session_pointer","= clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer #","clib.Session() as lib: with mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\",","context. # If the exception is raised, the code won't","sure that it's # getting from the current figure, not","size, 1)) y = tuple(range(size, size * 2, 1)) z","with a Dataset. \"\"\" dtypes = \"float32 float64 int32 int64","pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions","sure the session is closed when the exception is raised.","stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data,","dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\" Check that it fails for variable","if trying to create a session before destroying the old","Now try it with the second one with clib.Session() as","packaging.version import Version from pygmt import Figure, clib from pygmt.clib.conversion","VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, )","get correct constants from the C lib. \"\"\" ses =","\"\"\" lib = clib.Session() test_cases = ((family, via) for family","to make sure that it's # getting from the current","= np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid","3 data = full_data[:rows, :cols] with clib.Session() as lib: with","= (7, 5) for dtype in dtypes: data = np.arange(shape[0]","\"GMT_IN|GMT_IS_REFERENCE\", None, ) # Mock Open_VirtualFile to test the status","def test_destroy_session_fails(): \"\"\" Fail to destroy session when given bad","data.y, data.z) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{}","dtype=dtype) z = np.arange(size * 2, size * 3, 1,","size * 2, 1, dtype=dtype), z=np.arange(size * 2, size *","with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \"\"\" Check","as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with","assert lib.get_default(\"API_GRID_LAYOUT\") in [\"rows\", \"columns\"] assert int(lib.get_default(\"API_CORES\")) >= 1 assert","in ses.info: assert ses.info[key] == \"bla\" ses.destroy() def test_fails_for_wrong_version(): \"\"\"","ses.destroy() ses.create(\"test-session\") with mock(ses, \"GMT_Destroy_Session\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy()","Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib:","mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None):","in FAMILIES for via in VIAS) for family, via in","as lib: vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", # The","pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\"Should not get to this code\") #","parsed == expected def test_parse_constant_fails(): \"\"\" Check if the function","(\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \"\"\"","xr from packaging.version import Version from pygmt import Figure, clib","with flipped x/y. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4,","not easy to get some API functions to fail without","opening and closing virtual files raises an exception for non-","\"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\", \"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\", \"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case in test_cases:","with lib.open_virtual_file(*vfargs): print(\"Should not get to this code\") # Test","Mock a GMT C API function to make it always","vectors to a dataset. \"\"\" size = 13 x =","z = np.arange(10) grid = xr.DataArray(data, coords=[(\"z\", z), (\"y\", y),","# If the exception is raised, the code won't get","int64 uint32 uint64\".split() size = 13 for dtype in dtypes:","pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\"Shouldn't get to this code either\")","when given bad input. \"\"\" with clib.Session() as lib: with","test_call_module_invalid_arguments(): \"\"\" Fails for invalid module arguments. \"\"\" with clib.Session()","y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size * 2, size","test_destroy_session_fails(): \"\"\" Fail to destroy session when given bad input.","as out_fname: lib.call_module(\"info\", \"{} -C ->{}\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output","to fail without inducing a Segmentation Fault (which is a","= full_data[:rows, :cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as","pylint: disable=unused-argument \"\"\" Put 'bla' in the value buffer. \"\"\"","Grids from matrices using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10,","with clib.Session() as lib: lib.call_module(\"figure\", \"{} -\".format(fig2._name)) with clib.Session() as","version. \"\"\" if name == b\"API_VERSION\": value.value = b\"5.4.3\" else:","* 2, 1)) z = range(size * 2, size *","ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults): # Check for an empty","multiple figures existing at the same time. \"\"\" # Make","for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) #","test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail","clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint:","Mock Open_VirtualFile to test the status check when entering the","ses.destroy() def test_fails_for_wrong_version(): \"\"\" Make sure the clib.Session raises an","x = np.arange(5) y = np.arange(6) with clib.Session() as lib:","is None: def mock_api_function(*args): # pylint: disable=unused-argument \"\"\" A mock","names. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def","that it's # getting from the current figure, not the","dtype ) # Dataset from matrices data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\",","for invalid module arguments. \"\"\" with clib.Session() as lib: with","fails if nothing has been plotted. \"\"\" Figure() with pytest.raises(GMTCLibError):","0], ) def test_virtual_file(): \"\"\" Test passing in data via","= b\"bla\" return 0 ses = clib.Session() ses.create(\"test-session\") with mock(ses,","Parsing a composite constant argument (separated by |) correctly. \"\"\"","= clib.Session() ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults): # Check for","same time. \"\"\" # Make two figures before calling extract_region","lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed","GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \"data\")","test_create_data_fails(): \"\"\" Check that create_data raises exceptions for invalid input","an exception for non- zero return codes. \"\"\" vfargs =","arrays of different sizes. \"\"\" x = np.arange(5) y =","10, 2, 0], ) def test_virtual_file(): \"\"\" Test passing in","lib.create_data( family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1, 0], # columns,","npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,","is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement","fails for variable increments. \"\"\" data = np.ones((4, 5), dtype=\"float64\")","assert output == \"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\" def","input. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"meh\", \"\")","float64 int32 int64 uint32 uint64\".split() shape = (5, 3) for","been plotted. \"\"\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib:","+ lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed ==","pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\"GMT_IS_GRID\", geometry=\"Not_a_valid_geometry\", mode=\"GMT_CONTAINER_ONLY\", dim=[0,","def test_virtual_file_bad_direction(): \"\"\" Test passing an invalid direction argument. \"\"\"","output = outfile.read(keep_tabs=True) expected = \"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\" for h,","frame=True) # Activate the first figure and extract the region","given value. Used to test that exceptions are raised when",") expected = \"{}\\n\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size():",") ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z)","dim=[10, 20, 1, 0], # columns, rows, layers, dtype )","exception for non- zero return codes. \"\"\" vfargs = (","producing a NULL pointer as output or non-zero status codes.","15.0, 25.0])) def test_write_data_fails(): \"\"\" Check that write data raises","def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test passing in one column with string","is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with","\"\"\" dtypes = \"float32 float64 int32 int64 uint32 uint64\".split() shape","input. \"\"\" lib = clib.Session() test_cases = [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\",","with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name():",") def test_create_data_dataset(): \"\"\" Run the function to make sure","output == expected def test_virtualfile_from_vectors_transpose(): \"\"\" Test transforming matrix columns","fail by producing a NULL pointer as output or non-zero","zip(x, y, strings1, strings2) ) assert output == expected def","0.2], ) # If the data pointer returned is None","\"\"\" Test passing an invalid direction argument. \"\"\" with clib.Session()","Test that create and destroy session are called without errors.","\"{} -\".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2,","Should fail if trying to create a session before destroying","25.0])) def test_write_data_fails(): \"\"\" Check that write data raises an","name, value): # pylint: disable=unused-argument \"\"\" Put 'bla' in the","dataset. \"\"\" dtypes = \"float32 float64 int32 int64 uint32 uint64\".split()","either\") def test_virtual_file_bad_direction(): \"\"\" Test passing an invalid direction argument.","# Dataset from vectors data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\",","\"\"\" Create a grid specifying range and inc instead of","= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,","clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\"gmtdefaults\", \"\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint:","npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \"\"\" Check that","in dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size, size","Test passing in one column with string or object dtype","b\"5.4.3\" else: value.value = b\"bla\" return 0 lib = clib.Session()","exceptions are raised when API functions fail by producing a","return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name,","not pointing to the same memory session1 = clib.Session() session1.create(name=\"test_session1\")","the wrappers for the C API. \"\"\" import os from","the function fails when given bad input. \"\"\" lib =",") def test_dataarray_to_matrix_works(): \"\"\" Check that dataarray_to_matrix returns correct output.","a different session to avoid any memory problems. with clib.Session()","properties. with clib.Session() as lib: assert lib.info # Mock GMT_Get_Default","region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),","size = 10 for dtype in dtypes: x = np.arange(size,","for > 2 dims. \"\"\" # Make a 3D regular","argument. \"\"\" with clib.Session() as lib: vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\",","assert output == expected def test_extract_region_fails(): \"\"\" Check that extract","y), (\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data,","a given value. Used to test that exceptions are raised","ses.destroy() ses.destroy() def test_call_module(): \"\"\" Run a command to see","won't close later. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=0),","pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should fail if trying to create a","vfile: with GMTTempFile() as outfile: lib.call_module(\"convert\", f\"{vfile} ->{outfile.name}\") output =","as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{} -C ->{}\".format(vfile,","desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]),","opening to return 0 (success) so that we don't open","Test passing in data via a virtual file with a","as lib: lib.extract_region() def test_extract_region_two_figures(): \"\"\" Extract region should handle","= np.arange(5) y = np.arange(6) with clib.Session() as lib: with","setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield setattr(session, \"get_libgmt_func\", get_libgmt_func) def test_getitem(): \"\"\"","\"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def","is raised when failing to create a session. \"\"\" ses","layers, dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset,","old. \"\"\" # Mock GMT_Get_Default to return an old version","float64 int32 int64 uint32 uint64\".split() shape = (7, 5) for","to avoid any memory problems. with clib.Session() as lib: lib.call_module(\"figure\",","# pylint: disable=unused-argument \"\"\" Put 'bla' in the value buffer.","key in ses.info: assert ses.info[key] == \"bla\" ses.destroy() def test_fails_for_wrong_version():","npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1]","list(range(0, size, 1)) y = tuple(range(size, size * 2, 1))","lib: assert lib.info # Mock GMT_Get_Default to return always the","with lib: assert lib.info[\"version\"] != \"5.4.3\" # Make sure the","API functions fail by producing a NULL pointer as output","range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\"session1\") assert ses.session_pointer","np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid =","projection=\"M6i\", frame=True, land=\"black\") fig2 = Figure() fig2.basemap(region=\"US.HI+r5\", projection=\"M6i\", frame=True) #","is closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError): assert","np.ones((4, 5), dtype=\"float64\") x = np.linspace(0, 1, 5) y =","for family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed","columns of string or object dtype into virtual file dataset.","data.y, data.z) ] ) expected = \"<vector memory>: N =","test_cases: composite = \"|\".join([family, via]) expected = lib[family] + lib[via]","Add the dataset to a virtual file and pass it","2 dims. \"\"\" # Make a 3D regular grid data","= outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for i in","# Mock GMT_Get_Default to return always the same string def","= lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails():","(10, 6) for dtype in dtypes: full_data = np.arange(shape[0] *","Extract region should handle multiple figures existing at the same","code. with clib.Session() as lib: with mock(lib, \"GMT_Write_Data\", returns=1): with","{}\\t{}\\n\".format(size, bounds) assert output == expected def test_extract_region_fails(): \"\"\" Check","numpy.testing as npt import pandas as pd import pytest import","\"\"\" with clib.Session() as lib: # Dataset from vectors data_vector","pass it along to gmt info vfargs = (family, geometry,","= {}\\t{}\\n\".format(shape[0], bounds) assert output == expected def test_virtualfile_from_matrix_slice(): \"\"\"","= \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (x, y, z)]","with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0,","bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors","0 ses = clib.Session() ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults): #","codes. \"\"\" vfargs = ( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IN|GMT_IS_REFERENCE\", None, )","np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data)","Run the function to make sure it doesn't fail badly.","valid_modifiers=None ) def test_create_data_dataset(): \"\"\" Run the function to make","= lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with the","lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\" Fails when given bad input.","def test_call_module_invalid_name(): \"\"\" Fails when given bad input. \"\"\" with","clib.Session() as lib: lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0, 1,","0.2], ) def test_create_data_fails(): \"\"\" Check that create_data raises exceptions","raises an exception for non-zero return codes. \"\"\" # It's","value. \"\"\" return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func","\"\"\" data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname = \"test_call_module.txt\" with clib.Session()","when given bad input. \"\"\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError):","dtypes = \"float32 float64 int32 int64 uint32 uint64\".split() size =","dtype=dtype), z=np.arange(size * 2, size * 3, 1, dtype=dtype), )","mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\" Put 'bla' in","because it's not easy to get some API functions to","a NULL pointer as output or non-zero status codes. Needed","with pytest.raises(GMTCLibError): ses.create(\"test-session-name\") # Should fail if trying to create","desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] -","in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows =","( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", \"GMT_IS_POINT\", \"GMT_IS_GRID\", # The invalid direction argument 0,","\"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i),","function fails when given bad input. \"\"\" lib = clib.Session()","== expected def test_virtual_file_fails(): \"\"\" Check that opening and closing","int64 uint32 uint64\".split() shape = (7, 5) for dtype in","geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2, 0], ) def test_virtual_file(): \"\"\"","with mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10,","as outfile: lib.call_module(\"info\", \"{} ->{}\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds","mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[11, 10, 2,","the old one. ses.create(\"test1\") with pytest.raises(GMTCLibError): ses.create(\"test2\") def test_destroy_session_fails(): \"\"\"","y), (\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data))","Check that dataarray_to_matrix returns correct output with flipped y. \"\"\"","\"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for col in data.T] ) expected =","the status check when entering the context. # If the","mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1, 0], # columns, rows, layers, dtype","3D regular grid data = np.ones((10, 12, 11), dtype=\"float32\") x","Fails for invalid module arguments. \"\"\" with clib.Session() as lib:","with flipped x. \"\"\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4,","outfile.read(keep_tabs=True) bounds = \"\\t\".join( [ \"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in","= outfile.read(keep_tabs=True) expected = \"\".join( f\"{h}\\t{i}\\t{j} {k}\\n\" for h, i,","size * 3, 1, dtype=dtype) with clib.Session() as lib: with","in a session. \"\"\" # Create an instance of Session","output. \"\"\" # Passing in invalid mode with pytest.raises(GMTInvalidInput): with","virtual files raises an exception for non- zero return codes.","session to avoid any memory problems. with clib.Session() as lib:","npt.assert_allclose(wesn1, region1) # Now try it with the second one","see if call_module works. \"\"\" data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname","that dataarray_to_matrix returns correct output with flipped y. \"\"\" data","test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct output with flipped","i.max()) for i in (x, y, z)] ) expected =","projection=\"M6i\", frame=True) # Activate the first figure and extract the","memory>: N = {}\\t{}\\n\".format(rows, bounds) assert output == expected def","None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create and","__ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\"session1\")","y), (\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data)","Check that an exception is raised when failing to create","valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): \"\"\" Check","to virtual file dataset. \"\"\" dtypes = \"float32 float64 int32","of the # properties. with clib.Session() as lib: assert lib.info","-C ->{}\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output","so that we don't open a file that # we","ses = clib.Session() ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults): # Check","= clib.Session() test_cases = ((family, via) for family in FAMILIES","col.max()) for col in data.T] ) expected = \"{}\\n\".format(bounds) assert","test_write_data_fails(): \"\"\" Check that write data raises an exception for","close later. with clib.Session() as lib, mock(lib, \"GMT_Open_VirtualFile\", returns=0), mock(","= outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(col.min(), col.max()) for col in",") expected = \"<matrix memory>: N = {}\\t{}\\n\".format(rows, bounds) assert","= \"float32 float64 int32 int64 uint32 uint64\".split() size = 13","np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid =","== expected @pytest.mark.parametrize(\"dtype\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \"\"\" Test passing","as lib: # Grids from matrices using range and int","API function fail without causing a Segmentation # Fault. Can't","test that exceptions are raised when API functions fail by","the data pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError):","from matrices using dim lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20,","\"\"\" Test that create and destroy session are called without","uint64\".split() shape = (7, 5) for dtype in dtypes: data","uint64\".split() size = 13 for dtype in dtypes: data =","ses = clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer","clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile:","== lib[family] def test_parse_constant_composite(): \"\"\" Parsing a composite constant argument","if the function fails when given bad input. \"\"\" lib","with pytest.raises(GMTCLibError): lib.call_module(\"info\", \"bogus-data.bla\") def test_call_module_invalid_name(): \"\"\" Fails when given","y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct output","argtypes=None, restype=None): \"\"\" Return our mock function. \"\"\" if name","os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == \"11.5309 61.7074 -2.9289","as lib: with mock(lib, \"GMT_Create_Data\", returns=None): lib.create_data( family=\"GMT_IS_DATASET\", geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\",","geometry=\"GMT_IS_SURFACE\", mode=\"Not_a_valid_mode\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0],","code\") # Test the status check when closing the virtual","pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\" Make sure the clib.Session.info dict","layers, dtype ) # Dataset from matrices data_matrix = lib.create_data(","family=family, geometry=geometry, mode=\"GMT_CONTAINER_ONLY\", dim=[shape[1], shape[0], 1, 0], # columns, rows,","test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test passing in two columns of string or","x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])])","= np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\",","6) for dtype in dtypes: full_data = np.arange(shape[0] * shape[1],","def mock_defaults(api, name, value): # pylint: disable=unused-argument \"\"\" Put 'bla'","1, dtype=dtype) z = np.arange(size * 2, size * 3,","Mock the opening to return 0 (success) so that we","'info' failed with status code\" in str(error) assert \"gmtinfo [ERROR]:","mode=\"Not_a_valid_mode\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1,","a file that # we won't close later. with clib.Session()","they are not pointing to the same memory session1 =","GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR =","closing virtual files raises an exception for non- zero return","the GMT error message was captured. \"\"\" with clib.Session() as","bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(i.min(), i.max()) for i in (x, y,","# Grids from matrices using range and int lib.create_data( family=\"GMT_IS_GRID|GMT_VIA_MATRIX\",","errors). \"\"\" if mock_func is None: def mock_api_function(*args): # pylint:","x = np.arange(11) y = np.arange(12) z = np.arange(10) grid","lib: lib.extract_region() def test_extract_region_two_figures(): \"\"\" Extract region should handle multiple","- x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \"\"\" Check that","\"float32 float64 int32 int64 uint32 uint64\".split() shape = (10, 6)","raised when API functions fail by producing a NULL pointer","get_default works without crashing and gives reasonable results. \"\"\" with","in (data.x, data.y, data.z) ] ) expected = \"<vector memory>:","are valid file # names. Use a mock instead just","outfile.name)) output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for","with mock(ses, \"GMT_Destroy_Session\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module():","\"\"\" Test that I can get correct constants from the","raised when failing to create a session. \"\"\" ses =","closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError): assert lib.session_pointer","returns correct output with flipped y. \"\"\" data = np.diag(v=np.arange(3))","\"GMT_WRITE_SET\", [1] * 6, \"some-file-name\", None, ) def test_dataarray_to_matrix_works(): \"\"\"","a matrix to virtual file dataset. \"\"\" dtypes = \"float32","at the same time. \"\"\" # Make two figures before","an exception is raised when failing to create a session.","def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \"\"\" Test passing in two columns of string","for invalid names. \"\"\" with clib.Session() as lib: with pytest.raises(GMTCLibError):","for i in (x, y, z)] ) expected = \"<vector","lib: with GMTTempFile() as out_fname: lib.call_module(\"info\", \"{} -C ->{}\".format(data_fname, out_fname.name))","\"with\" so no session is created. lib = clib.Session() with","return always the same string def mock_defaults(api, name, value): #","= clib.Session() for family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES)","\"NOT_A_PROPER_FAMILY|ALSO_INVALID\", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES,","\"\"\" x = np.arange(5) y = np.arange(6) with clib.Session() as","# If the data pointer returned is None (NULL pointer)","\"\"\" lib = clib.Session() test_cases = [ \"SOME_random_STRING\", \"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\", \"GMT_IS_DATASET|NOT_A_PROPER_VIA\",","virtual file and pass it along to gmt info vfargs","sizes. \"\"\" x = np.arange(5) y = np.arange(6) with clib.Session()","y = np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with","- x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if","np.array([\"pqrst\", \"uvwx\", \"yz!\", \"@#\", \"$\"], dtype=dtype) with clib.Session() as lib:","{}\\t{}\\n\".format(shape[0], bounds) assert output == expected def test_virtualfile_from_matrix_slice(): \"\"\" Test","should handle multiple figures existing at the same time. \"\"\"","with pytest.raises(GMTInvalidInput): lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \"\"\"","in data.T] ) expected = \"{}\\n\".format(bounds) assert output == expected","range and inc instead of dim. \"\"\" with clib.Session() as","session1.destroy() session2.destroy() # Create and destroy a session twice ses","call_module works. \"\"\" data_fname = os.path.join(TEST_DATA_DIR, \"points.txt\") out_fname = \"test_call_module.txt\"","\"\"\" Pass array-like vectors to a dataset. \"\"\" size =","y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails():","function to make it always return a given value. Used","for the C API. \"\"\" import os from contextlib import","mock_func is None: def mock_api_function(*args): # pylint: disable=unused-argument \"\"\" A","13 for dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size,","# It's hard to make the C API function fail","if mock_func is None: def mock_api_function(*args): # pylint: disable=unused-argument \"\"\"","for dtype in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)","and pass it along to gmt info vfargs = (family,","closing of the # virtual file. with clib.Session() as lib,","return 0 ses = clib.Session() ses.create(\"test-session\") with mock(ses, \"GMT_Get_Default\", mock_func=mock_defaults):","clib.Session() session1.create(name=\"test_session1\") assert session1.session_pointer is not None session2 = clib.Session()","it # Use in a different session to avoid any","= lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): \"\"\"","for non-zero return codes. \"\"\" # It's hard to make","\"\"\" Check is the GMT error message was captured. \"\"\"","old version. \"\"\" if name == b\"API_VERSION\": value.value = b\"5.4.3\"","\"\"\" Create a grid ignoring range and inc. \"\"\" with","badly. \"\"\" with clib.Session() as lib: # Dataset from vectors","# Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as","None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with","1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) #","exceptions for invalid input and output. \"\"\" # Passing in","valid_modifiers=VIAS) # Should also fail if not given valid modifiers","GMT will just write to stdout and spaces are valid","lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1] * 6, \"some-file-name\", None, )","output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for i","1, dtype=dtype), z=np.arange(size * 2, size * 3, 1, dtype=dtype),","out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == \"11.5309","= \"{}\\n\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size(): \"\"\" Test","\"ghij\", \"klmno\"], dtype=dtype) strings2 = np.array([\"pqrst\", \"uvwx\", \"yz!\", \"@#\", \"$\"],","def test_create_session_fails(): \"\"\" Check that an exception is raised when","function fails for arrays of different sizes. \"\"\" x =","clib.Session() with mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert","API function to make it always return a given value.","code\" in str(error) assert \"gmtinfo [ERROR]: Cannot find file bogus-data.bla\"","def test_virtualfile_from_vectors_pandas(): \"\"\" Pass vectors to a dataset using pandas","# Make two figures before calling extract_region to make sure","it fails for variable increments. \"\"\" data = np.ones((4, 5),","data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y =","from getting all of the # properties. with clib.Session() as","lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\" dataset = lib.create_data(","return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \"get_libgmt_func\", mock_get_libgmt_func) yield","to create a session. \"\"\" ses = clib.Session() with mock(ses,","yield setattr(session, \"get_libgmt_func\", get_libgmt_func) def test_getitem(): \"\"\" Test that I","Create an instance of Session without \"with\" so no session","fail if trying to create a session before destroying the","lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected","expected def test_extract_region_fails(): \"\"\" Check that extract region fails if","\"data\") with clib.Session() as _lib: gmt_version = Version(_lib.info[\"version\"]) @contextmanager def","clib.Session() as lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\" geometry = \"GMT_IS_POINT\" dataset","shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3 data =","first figure and extract the region from it # Use","ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \"\"\"","mock(lib, \"GMT_Write_Data\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \"GMT_IS_VECTOR\", \"GMT_IS_POINT\", \"GMT_WRITE_SET\", [1]","mock( lib, \"GMT_Close_VirtualFile\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass","from contextlib import contextmanager import numpy as np import numpy.testing","NULL pointer as output or non-zero status codes. Needed because","10 for dtype in dtypes: x = np.arange(size, dtype=dtype) y","with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \"\"\" Test","is not None session2 = clib.Session() session2.create(name=\"test_session2\") assert session2.session_pointer is","for invalid input and output. \"\"\" # Passing in invalid","pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\"This should have failed\") def test_virtualfile_from_matrix():","grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) matrix, region, inc","z), (\"y\", y), (\"x\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails():","# columns, rows, layers, dtype ) data = np.arange(shape[0] *","passing in one column with string or object dtype into","ses[\"GMT_MODULE_CMD\"] != -99999 assert ses[\"GMT_PAD_DEFAULT\"] != -99999 assert ses[\"GMT_DOUBLE\"] !=","= outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col in","fails when given bad input. \"\"\" lib = clib.Session() test_cases","bad input. \"\"\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\")","data_matrix = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_MATRIX\", geometry=\"GMT_IS_POINT\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0],","name == func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session,","data = np.ones((4, 5), dtype=\"float64\") x = np.linspace(0, 1, 5)","-99999 with pytest.raises(GMTCLibError): ses[\"A_WHOLE_LOT_OF_JUNK\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \"\"\"","] ) expected = \"<vector memory>: N = {}\\t{}\\n\".format(size, bounds)","gmt_version = Version(_lib.info[\"version\"]) @contextmanager def mock(session, func, returns=None, mock_func=None): \"\"\"","(\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region,","lib.extract_region() def test_extract_region_two_figures(): \"\"\" Extract region should handle multiple figures","assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer #","dtype=np.int32) strings1 = np.array([\"a\", \"bc\", \"def\", \"ghij\", \"klmno\"], dtype=dtype) strings2","with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\" Make sure the clib.Session.info","Put 'bla' in the value buffer. \"\"\" value.value = b\"bla\"","desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check","ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\"test-session\") with mock(ses, \"GMT_Destroy_Session\",","with clib.Session() as lib: assert lib.info # Mock GMT_Get_Default to","import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import","from the C lib. \"\"\" ses = clib.Session() assert ses[\"GMT_SESSION_EXTERNAL\"]","because if # output=='', GMT will just write to stdout","outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col in data.T]","with mock(lib, \"GMT_Get_Default\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\"version\"]","import os from contextlib import contextmanager import numpy as np","dataarray_to_matrix(grid) def test_get_default(): \"\"\" Make sure get_default works without crashing","If the data pointer returned is None (NULL pointer) with","dtype in dtypes: with clib.Session() as lib: family = \"GMT_IS_DATASET|GMT_VIA_MATRIX\"","test_parse_constant_composite(): \"\"\" Parsing a composite constant argument (separated by |)","- y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \"\"\" Check that dataarray_to_matrix returns correct","data via a virtual file with a Dataset. \"\"\" dtypes","geometry=\"GMT_IS_SURFACE\", mode=\"GMT_CONTAINER_ONLY\", dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): \"\"\"","0.2], ) # Passing in invalid geometry with pytest.raises(GMTInvalidInput): with","= list(range(0, size, 1)) y = tuple(range(size, size * 2,","disable=pointless-statement ses.create(\"session1\") assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError):","string or object dtype into virtual file dataset. \"\"\" size","output = outfile.read(keep_tabs=True) bounds = \"\\t\".join( [\"{:.0f}\\t{:.0f}\".format(col.min(), col.max()) for col","test_parse_constant_fails(): \"\"\" Check if the function fails when given bad","x = np.arange(size, dtype=np.int32) y = np.arange(size, size * 2,","desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] -","- y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \"\"\" Check if dataarray_to_matrix returns correct","np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[(\"z\", z), (\"y\",","stop=5, num=3) grid = xr.DataArray(data, coords=[(\"y\", y), (\"x\", x)]) matrix,","output == expected def test_virtualfile_from_vectors_diff_size(): \"\"\" Test the function fails","# Mock Open_VirtualFile to test the status check when entering","as lib: # Dataset from vectors data_vector = lib.create_data( family=\"GMT_IS_DATASET|GMT_VIA_VECTOR\",","with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module(\"info\", \"{}","= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),","x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(),","assert output == expected def test_virtualfile_from_vectors_arraylike(): \"\"\" Pass array-like vectors","figure. fig1 = Figure() region1 = np.array([0, 10, -20, -10])","this part of the code. with clib.Session() as lib: with","\"GMT_IS_DATASET|GMT_VIA_MATRIX\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \"\"\" Run the function","data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib:","the function to make sure it doesn't fail badly. \"\"\"","12, 11), dtype=\"float32\") x = np.arange(11) y = np.arange(12) z","with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\"NOT_A_VALID_NAME\") def test_info_dict(): \"\"\"","a grid specifying range and inc instead of dim. \"\"\"","is using them anyway. # This should work... lib._parse_constant( \"GMT_IS_DATASET|GMT_VIA_MATRIX\",","make the C API function fail without causing a Segmentation","Open_VirtualFile to test the status check when entering the context.","coords=[(\"y\", y), (\"x\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix,","argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\"This should have","1, dtype=dtype), ) ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x,","handle multiple figures existing at the same time. \"\"\" #","[\"<{:.0f}/{:.0f}>\".format(min(i), max(i)) for i in (x, y, z)] ) expected"],"string":"[\n \"lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): \\\"\\\"\\\"\",\n \"pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer is not None ses.destroy() with\",\n \"GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile, outfile.name)) output =\",\n \"It's hard to make the C API function fail without\",\n \"with clib.Session() as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"] assert\",\n \"with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check for an empty dictionary\",\n \"we don't open a file that # we won't close\",\n \"extract region fails if nothing has been plotted. \\\"\\\"\\\" Figure()\",\n \"with pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib, \\\"GMT_Create_Data\\\", returns=None):\",\n \"this code\\\") # Test the status check when closing the\",\n \"20, 1, 0], ) assert data_vector != data_matrix def test_create_data_grid_dim():\",\n \"str(error) def test_method_no_session(): \\\"\\\"\\\" Fails when not in a session.\",\n \"= outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in\",\n \"expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output\",\n \"value. Used to test that exceptions are raised when API\",\n \"\\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The invalid direction argument 0, ) with\",\n \"# Check for an empty dictionary assert ses.info for key\",\n \"= b\\\"bla\\\" return 0 lib = clib.Session() with mock(lib, \\\"GMT_Get_Default\\\",\",\n \"matrix columns to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32\",\n \"\\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i in (x, y, z)] )\",\n \"parsed == lib[family] def test_parse_constant_composite(): \\\"\\\"\\\" Parsing a composite constant\",\n \"def test_write_data_fails(): \\\"\\\"\\\" Check that write data raises an exception\",\n \"N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def test_virtualfile_from_matrix_slice():\",\n \"bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col in data.T] )\",\n \"return codes. \\\"\\\"\\\" # It's hard to make the C\",\n \"20, 1, 0], ) def test_create_data_grid_range(): \\\"\\\"\\\" Create a grid\",\n \"0 (success) so that we don't open a file that\",\n \"that we don't open a file that # we won't\",\n \"lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >= 1\",\n \"inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),\",\n \"2, size * 3, 1, dtype=dtype) with clib.Session() as lib:\",\n \"output = outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j, k\",\n \"C API. \\\"\\\"\\\" import os from contextlib import contextmanager import\",\n \"i in (data.x, data.y, data.z) ] ) expected = \\\"<vector\",\n \"lib.info # Mock GMT_Get_Default to return always the same string\",\n \"test_get_default(): \\\"\\\"\\\" Make sure get_default works without crashing and gives\",\n \"x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix\",\n \"x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9, num=3)\",\n \"from pygmt import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from\",\n \"lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for\",\n \"-20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \\\"\\\"\\\" Check that\",\n \"# Should fail if trying to create a session before\",\n \"= np.arange(size * 2, size * 3, 1, dtype=dtype) with\",\n \"dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings) as\",\n \"assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert ses[\\\"GMT_DOUBLE\\\"] != -99999 with pytest.raises(GMTCLibError):\",\n \"assert session1.session_pointer is not None session2 = clib.Session() session2.create(name=\\\"test_session2\\\") assert\",\n \"If the exception is raised, the code won't get to\",\n \"of string or object dtype into virtual file dataset. \\\"\\\"\\\"\",\n \"npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\"\",\n \"# The invalid direction argument 0, ) with pytest.raises(GMTInvalidInput): with\",\n \"\\\"opqrst\\\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings)\",\n \"expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h, i, j, k\",\n \"pylint: disable=unused-argument \\\"\\\"\\\" A mock GMT API function that always\",\n \"geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as\",\n \"Fail to destroy session when given bad input. \\\"\\\"\\\" ses\",\n \"clib.Session() for family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert\",\n \"N = {}\\\\t{}\\\\n\\\".format(rows, bounds) assert output == expected def test_virtualfile_from_vectors_pandas():\",\n \"assert ses[\\\"GMT_DOUBLE\\\"] != -99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement\",\n \"invalid direction argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This\",\n \"mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\",\",\n \"GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session() as _lib: gmt_version\",\n \"destroying the old one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails():\",\n \"ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\" Fail to destroy session when given\",\n \"npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1]\",\n \"pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer is not\",\n \"that opening and closing virtual files raises an exception for\",\n \"Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\" Make sure get_default raises an exception\",\n \"= \\\"|\\\".join([family, via]) expected = lib[family] + lib[via] parsed =\",\n \"dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32) strings1\",\n \"numpy as np import numpy.testing as npt import pandas as\",\n \"size * 3, 1, dtype=dtype), ) ) with clib.Session() as\",\n \"that dataarray_to_matrix returns correct output with flipped x/y. \\\"\\\"\\\" data\",\n \"with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\" Make sure get_default works\",\n \"GMTTempFile() as out_fname: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name)\",\n \"== expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing\",\n \"with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\" Fail to destroy session\",\n \"\\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\"\",\n \"returns correct output with flipped x. \\\"\\\"\\\" data = np.diag(v=np.arange(3))\",\n \"contextlib import contextmanager import numpy as np import numpy.testing as\",\n \"- x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that\",\n \"[str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing in one column\",\n \"\\\"\\\"\\\" Return an old version. \\\"\\\"\\\" if name == b\\\"API_VERSION\\\":\",\n \"\\\"$\\\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1,\",\n \"dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\",\",\n \"C API function to make it always return a given\",\n \"np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T)\",\n \"def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the function fails for arrays of\",\n \"vectors to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64\",\n \"family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], )\",\n \"expected = \\\"{}\\\\n\\\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\"\",\n \"lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get to this code either\\\") def test_virtual_file_bad_direction():\",\n \"-99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert ses[\\\"GMT_DOUBLE\\\"] != -99999 with\",\n \"works without crashing and gives reasonable results. \\\"\\\"\\\" with clib.Session()\",\n \"k in zip(x, y, strings1, strings2) ) assert output ==\",\n \"y, strings1, strings2) ) assert output == expected def test_virtualfile_from_vectors_transpose():\",\n \"def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that it fails for > 2\",\n \"\\\"\\\"\\\" if mock_func is None: def mock_api_function(*args): # pylint: disable=unused-argument\",\n \"-20.0, 20.0], inc=[0.1, 0.2], ) # Passing in invalid geometry\",\n \"of different sizes. \\\"\\\"\\\" x = np.arange(5) y = np.arange(6)\",\n \"returns correct output. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0,\",\n \"some API functions to fail without inducing a Segmentation Fault\",\n \"VIAS) for family, via in test_cases: composite = \\\"|\\\".join([family, via])\",\n \"mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\" #\",\n \"from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from\",\n \"lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\" Check is\",\n \"with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] * 6, \\\"some-file-name\\\",\",\n \"the dataset to a virtual file and pass it along\",\n \"3, 4) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) with\",\n \"array to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64\",\n \"to exercise this part of the code. with clib.Session() as\",\n \"0], ) assert data_vector != data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\" Create\",\n \"a session twice ses = clib.Session() for __ in range(2):\",\n \"valid_modifiers=VIAS ) # But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\",\",\n \"\\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\",\",\n \"dict is working. \\\"\\\"\\\" # Check if there are no\",\n \"assert output == expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming matrix\",\n \"\\\"{} -\\\".format(fig1._name)) with clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1,\",\n \"parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite():\",\n \"assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create and destroy\",\n \"\\\"\\\"\\\" Check that create_data raises exceptions for invalid input and\",\n \"as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ):\",\n \"lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile() as\",\n \"y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment():\",\n \"pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError): ses.destroy()\",\n \"session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\" Return our mock function.\",\n \"pytest import xarray as xr from packaging.version import Version from\",\n \"with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile:\",\n \"the first figure and extract the region from it #\",\n \"\\\"\\\"\\\" Fails for invalid module arguments. \\\"\\\"\\\" with clib.Session() as\",\n \"with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if\",\n \"10, -20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2 = Figure()\",\n \"causing a Segmentation # Fault. Can't test this if by\",\n \"ses.session_pointer # pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer is not None\",\n \"geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], # columns, rows, layers,\",\n \"with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with GMTTempFile() as\",\n \"None session2 = clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is not None\",\n \"with clib.Session() as lib: vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\",\",\n \"one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\" Fail to\",\n \"returned is None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as\",\n \"the C API function fail without causing a Segmentation #\",\n \"-\\\".format(fig1._name)) with clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1)\",\n \"data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y =\",\n \"= clib.Session() with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib:\",\n \"dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], )\",\n \"Used to test that exceptions are raised when API functions\",\n \"not in a session. \\\"\\\"\\\" # Create an instance of\",\n \"closing the virtual file # Mock the opening to return\",\n \"by giving a bad file name because if # output=='',\",\n \"in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also\",\n \"an old version def mock_defaults(api, name, value): # pylint: disable=unused-argument\",\n \"ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] !=\",\n \"data = full_data[:rows, :cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data)\",\n \"in (x, y, z)] ) expected = \\\"<vector memory>: N\",\n \"session twice ses = clib.Session() for __ in range(2): with\",\n \"as lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\" Make sure\",\n \"disable=unused-argument \\\"\\\"\\\" Put 'bla' in the value buffer. \\\"\\\"\\\" value.value\",\n \"land=\\\"black\\\") fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) # Activate the\",\n \"lib: vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The invalid\",\n \"session. \\\"\\\"\\\" # Create an instance of Session without \\\"with\\\"\",\n \"pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0,\",\n \"= (5, 3) for dtype in dtypes: with clib.Session() as\",\n \"lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with GMTTempFile()\",\n \"in data via a virtual file with a Dataset. \\\"\\\"\\\"\",\n \"lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with clib.Session() as lib: wesn1 =\",\n \"x = np.linspace(0, 1, 5) y = np.logspace(2, 3, 4)\",\n \"test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming a slice of a larger array\",\n \"part of the code. with clib.Session() as lib: with mock(lib,\",\n \"_lib: gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session, func, returns=None, mock_func=None):\",\n \"vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile, outfile.name))\",\n \"expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(rows, bounds) assert output\",\n \"the code won't get to the closing of the #\",\n \"inducing a Segmentation Fault (which is a good thing because\",\n \"assert output == expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the function\",\n \"dim. \\\"\\\"\\\" with clib.Session() as lib: # Grids from matrices\",\n \"\\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def\",\n \"= np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype) with clib.Session() as\",\n \"\\\"\\\"\\\" Check that dataarray_to_matrix returns correct output with flipped x/y.\",\n \"desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0],\",\n \"\\\"GMT_IS_GRID\\\", # The invalid direction argument 0, ) with pytest.raises(GMTInvalidInput):\",\n \"N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike():\",\n \"lib = clib.Session() test_cases = ((family, via) for family in\",\n \"to gmt info vfargs = (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with\",\n \"* shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3 data\",\n \"GMT C API function to make it always return a\",\n \"desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check\",\n \"any memory problems. with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name))\",\n \"data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\" Create a grid ignoring range and\",\n \"1, 0], # columns, rows, layers, dtype ) # Dataset\",\n \"same memory session1 = clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is not\",\n \"= \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output ==\",\n \"to test that exceptions are raised when API functions fail\",\n \"np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\",\",\n \"* 2, size * 3, 1) with clib.Session() as lib:\",\n \"memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def\",\n \"dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data)\",\n \"range and inc. \\\"\\\"\\\" with clib.Session() as lib: # Grids\",\n \"usually only fails with errors). \\\"\\\"\\\" if mock_func is None:\",\n \"a GMT C API function to make it always return\",\n \"lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't\",\n \"along to gmt info vfargs = (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset)\",\n \"second one with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with\",\n \"shape = (7, 5) for dtype in dtypes: data =\",\n \"def test_call_module_error_message(): \\\"\\\"\\\" Check is the GMT error message was\",\n \"if nothing has been plotted. \\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError): with\",\n \"pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\" Extract\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails():\",\n \"from it # Use in a different session to avoid\",\n \"lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not given\",\n \"npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] -\",\n \"assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\"\",\n \"given bad input. \\\"\\\"\\\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy()\",\n \"\\\"\\\"\\\" Test transforming matrix columns to virtual file dataset. \\\"\\\"\\\"\",\n \"with string or object dtype into virtual file dataset. \\\"\\\"\\\"\",\n \"== expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors to a dataset\",\n \"strings) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\")\",\n \"* shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as\",\n \"\\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case in test_cases: with\",\n \"return get_libgmt_func(name, argtypes, restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\",\",\n \"except GMTCLibError as error: assert \\\"Module 'info' failed with status\",\n \"lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0,\",\n \"x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix\",\n \"output == expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming a slice\",\n \"vectors data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1,\",\n \"that always returns a given value. \\\"\\\"\\\" return returns mock_func\",\n \"(NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib,\",\n \"\\\"\\\"\\\" Check that dataarray_to_matrix returns correct output. \\\"\\\"\\\" data =\",\n \"def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if dataarray_to_matrix returns correct output with\",\n \"status check when closing the virtual file # Mock the\",\n \"via in VIAS) for family, via in test_cases: composite =\",\n \"\\\"\\\"\\\" Run a command to see if call_module works. \\\"\\\"\\\"\",\n \"def mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\" Return our mock function. \\\"\\\"\\\"\",\n \"\\\"some-file-name\\\", None, ) def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that dataarray_to_matrix returns\",\n \"== expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the function fails for\",\n \"name because if # output=='', GMT will just write to\",\n \"geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) assert data_vector !=\",\n \"np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9,\",\n \"size * 3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,\",\n \"np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9,\",\n \"lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError as error: assert \\\"Module 'info' failed\",\n \"function to make sure it doesn't fail badly. \\\"\\\"\\\" with\",\n \"def test_info_dict(): \\\"\\\"\\\" Make sure the clib.Session.info dict is working.\",\n \"Test the function fails for arrays of different sizes. \\\"\\\"\\\"\",\n \"the current figure, not the last figure. fig1 = Figure()\",\n \"\\\"\\\"\\\" vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) #\",\n \"\\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def\",\n \"a bad file name because if # output=='', GMT will\",\n \"to return 0 (success) so that we don't open a\",\n \"invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\",\",\n \"lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ): with\",\n \"# Mock the opening to return 0 (success) so that\",\n \"with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\" Check is the\",\n \"that extract region fails if nothing has been plotted. \\\"\\\"\\\"\",\n \"->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output ==\",\n \") expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert\",\n \"as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile()\",\n \"ses = clib.Session() with mock(ses, \\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\")\",\n \"(success) so that we don't open a file that #\",\n \"an invalid direction argument. \\\"\\\"\\\" with clib.Session() as lib: vfargs\",\n \"def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for invalid module arguments. \\\"\\\"\\\" with\",\n \"mock GMT API function that always returns a given value.\",\n \"fail if not given valid modifiers but is using them\",\n \"\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) # Mock Open_VirtualFile to test\",\n \"test_method_no_session(): \\\"\\\"\\\" Fails when not in a session. \\\"\\\"\\\" #\",\n \"dtype in dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size,\",\n \"y = tuple(range(size, size * 2, 1)) z = range(size\",\n \"an instance of Session without \\\"with\\\" so no session is\",\n \") def test_virtual_file(): \\\"\\\"\\\" Test passing in data via a\",\n \"import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput,\",\n \"in [\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >=\",\n \"x = np.arange(size, dtype=dtype) y = np.arange(size, size * 2,\",\n \"hard to make the C API function fail without causing\",\n \"single family argument correctly. \\\"\\\"\\\" lib = clib.Session() for family\",\n \"sure the clib.Session.info dict is working. \\\"\\\"\\\" # Check if\",\n \"session and make sure they are not pointing to the\",\n \"if name == b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\" else: value.value =\",\n \"def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output. \\\"\\\"\\\"\",\n \"assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert ses[\\\"GMT_DOUBLE\\\"]\",\n \"test_create_data_dataset(): \\\"\\\"\\\" Run the function to make sure it doesn't\",\n \"assert data_vector != data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\" Create a grid\",\n \"test_extract_region_fails(): \\\"\\\"\\\" Check that extract region fails if nothing has\",\n \"> 2 dims. \\\"\\\"\\\" # Make a 3D regular grid\",\n \"np.arange(10) grid = xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\", y), (\\\"x\\\", x)])\",\n \"assert ses.info for key in ses.info: assert ses.info[key] == \\\"bla\\\"\",\n \"\\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape = (5, 3)\",\n \"geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0],\",\n \"dtype into virtual file dataset. \\\"\\\"\\\" size = 5 x\",\n \"extract_region to make sure that it's # getting from the\",\n \"fig1 = Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1,\",\n \"errors. \\\"\\\"\\\" # Create two session and make sure they\",\n \"make it always return a given value. Used to test\",\n \"from matrices data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20,\",\n \"outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max())\",\n \"* 6, \\\"some-file-name\\\", None, ) def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that\",\n \"as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try\",\n \"clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with\",\n \"= {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object])\",\n \"def test_create_data_grid_range(): \\\"\\\"\\\" Create a grid specifying range and inc\",\n \"test_get_default_fails(): \\\"\\\"\\\" Make sure get_default raises an exception for invalid\",\n \"dataset. \\\"\\\"\\\" size = 5 x = np.arange(size, dtype=np.int32) y\",\n \"always return a given value. Used to test that exceptions\",\n \"clib.Session() test_cases = ((family, via) for family in FAMILIES for\",\n \"None, ) # Mock Open_VirtualFile to test the status check\",\n \"in data.T] ) expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0],\",\n \"test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing an invalid direction argument. \\\"\\\"\\\" with\",\n \"\\\"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails\",\n \"failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the automation for transforming vectors\",\n \"with GMTTempFile() as out_fname: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname, out_fname.name)) assert\",\n \"captured. \\\"\\\"\\\" with clib.Session() as lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except\",\n \"matrices data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1,\",\n \"npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\"\",\n \"have failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the automation for transforming\",\n \"# names. Use a mock instead just to exercise this\",\n \"y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\" Make\",\n \"clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert\",\n \"correct output with flipped x. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x\",\n \"\\\"bogus-data.bla\\\") except GMTCLibError as error: assert \\\"Module 'info' failed with\",\n \"the session is closed when the exception is raised. with\",\n \"grid = xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\", y), (\\\"x\\\", x)]) with\",\n \"def test_extract_region_fails(): \\\"\\\"\\\" Check that extract region fails if nothing\",\n \"transforming vectors to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32\",\n \"our mock function. \\\"\\\"\\\" if name == func: return mock_func\",\n \"!= -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert ses[\\\"GMT_DOUBLE\\\"] != -99999\",\n \"pandas Series. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32\",\n \"Create a grid specifying range and inc instead of dim.\",\n \"bounds) assert output == expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming\",\n \"dims. \\\"\\\"\\\" # Make a 3D regular grid data =\",\n \"ses.destroy() def test_call_module(): \\\"\\\"\\\" Run a command to see if\",\n \"with the second one with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{}\",\n \"valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant(\",\n \"\\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem(): \\\"\\\"\\\" Test that I can get\",\n \"in str(error) def test_method_no_session(): \\\"\\\"\\\" Fails when not in a\",\n \"it doesn't fail badly. \\\"\\\"\\\" with clib.Session() as lib: #\",\n \"data.T] ) expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(rows, bounds)\",\n \"message was captured. \\\"\\\"\\\" with clib.Session() as lib: try: lib.call_module(\\\"info\\\",\",\n \"vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name)) output\",\n \"region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),\",\n \"to test the status check when entering the context. #\",\n \"y, z)] ) expected = \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size,\",\n \"lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], # columns,\",\n \"and destroy session are called without errors. \\\"\\\"\\\" # Create\",\n \"def test_parse_constant_single(): \\\"\\\"\\\" Parsing a single family argument correctly. \\\"\\\"\\\"\",\n \"output with flipped x. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x =\",\n \"family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\" dataset = lib.create_data( family=family,\",\n \"or segfaults from getting all of the # properties. with\",\n \"ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def\",\n \"as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1, 0],\",\n \"b\\\"bla\\\" return 0 lib = clib.Session() with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults):\",\n \"with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{}\",\n \"output = out_fname.read().strip() assert output == \\\"11.5309 61.7074 -2.9289 7.8648\",\n \"# Now try it with the second one with clib.Session()\",\n \"3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z)\",\n \"dataset using pandas Series. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32\",\n \"((family, via) for family in FAMILIES for via in VIAS)\",\n \"file # Mock the opening to return 0 (success) so\",\n \"return a given value. Used to test that exceptions are\",\n \"status code\\\" in str(error) assert \\\"gmtinfo [ERROR]: Cannot find file\",\n \"an exception for non-zero return codes. \\\"\\\"\\\" # It's hard\",\n \"columns, rows, layers, dtype ) # Dataset from matrices data_matrix\",\n \"output == expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors to a\",\n \"assert \\\"Module 'info' failed with status code\\\" in str(error) assert\",\n \"make sure it doesn't fail badly. \\\"\\\"\\\" with clib.Session() as\",\n \"->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max())\",\n \"pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\" Test that\",\n \"composite = \\\"|\\\".join([family, via]) expected = lib[family] + lib[via] parsed\",\n \"dtype in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with\",\n \"\\\"\\\"\\\" Test the wrappers for the C API. \\\"\\\"\\\" import\",\n \"write data raises an exception for non-zero return codes. \\\"\\\"\\\"\",\n \"->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for\",\n \"input and output. \\\"\\\"\\\" # Passing in invalid mode with\",\n \"disable=unused-argument \\\"\\\"\\\" Return an old version. \\\"\\\"\\\" if name ==\",\n \"y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if dataarray_to_matrix returns\",\n \"# pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer is not None ses.destroy()\",\n \"instead just to exercise this part of the code. with\",\n \"twice ses = clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError):\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1,\",\n \"stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data,\",\n \"session2.destroy() # Create and destroy a session twice ses =\",\n \"with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile, outfile.name)) output\",\n \"# Should also fail if not given valid modifiers but\",\n \"this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None ) def\",\n \"find file bogus-data.bla\\\" in str(error) def test_method_no_session(): \\\"\\\"\\\" Fails when\",\n \"x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1)))\",\n \"2, 1, dtype=dtype), z=np.arange(size * 2, size * 3, 1,\",\n \"lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0,\",\n \"{}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def test_virtual_file_fails(): \\\"\\\"\\\" Check\",\n \"geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1, 0], # columns, rows, layers,\",\n \"\\\"\\\"\\\" Test transforming a slice of a larger array to\",\n \"in zip(x, y, strings)) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str,\",\n \"fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) # Activate the first figure and extract\",\n \"raised, the code won't get to the closing of the\",\n \"GMTCLibError as error: assert \\\"Module 'info' failed with status code\\\"\",\n \"expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming matrix columns to virtual\",\n \"with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\",\",\n \"* 2, 1, dtype=dtype), z=np.arange(size * 2, size * 3,\",\n \"b\\\"bla\\\" return 0 ses = clib.Session() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\",\",\n \"the same time. \\\"\\\"\\\" # Make two figures before calling\",\n \"assert session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer session1.destroy()\",\n \"\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (data.x, data.y, data.z) ] )\",\n \">= 1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\" Make\",\n \"expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors to a dataset using\",\n \"memory session1 = clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is not None\",\n \"ses.create(\\\"test-session-name\\\") # Should fail if trying to create a session\",\n \"mock_api_function(*args): # pylint: disable=unused-argument \\\"\\\"\\\" A mock GMT API function\",\n \"Check if the function fails when given bad input. \\\"\\\"\\\"\",\n \"(5, 3) for dtype in dtypes: with clib.Session() as lib:\",\n \"\\\"\\\"\\\" # Mock GMT_Get_Default to return an old version def\",\n \"= {}\\\\t{}\\\\n\\\".format(rows, bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\"\",\n \"\\\"|\\\".join([family, via]) expected = lib[family] + lib[via] parsed = lib._parse_constant(composite,\",\n \"2, 1)) z = range(size * 2, size * 3,\",\n \"function. \\\"\\\"\\\" if name == func: return mock_func return get_libgmt_func(name,\",\n \"assert int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def test_get_default_fails():\",\n \"value): # pylint: disable=unused-argument \\\"\\\"\\\" Put 'bla' in the value\",\n \"0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], )\",\n \"Check if dataarray_to_matrix returns correct output with flipped x. \\\"\\\"\\\"\",\n \"-99999 assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert\",\n \"dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2],\",\n \"to return always the same string def mock_defaults(api, name, value):\",\n \"Make sure the clib.Session raises an exception if GMT is\",\n \"= np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\",\",\n \"output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for\",\n \"def mock(session, func, returns=None, mock_func=None): \\\"\\\"\\\" Mock a GMT C\",\n \"assert \\\"gmtinfo [ERROR]: Cannot find file bogus-data.bla\\\" in str(error) def\",\n \"lib: # Grids from matrices using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\",\",\n \"the region from it # Use in a different session\",\n \"with clib.Session() as lib: # Grids from matrices using range\",\n \"\\\"\\\"\\\" Make sure get_default works without crashing and gives reasonable\",\n \"libgmt usually only fails with errors). \\\"\\\"\\\" if mock_func is\",\n \"output=='', GMT will just write to stdout and spaces are\",\n \"session before destroying the old one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\")\",\n \"to return an old version def mock_defaults(api, name, value): #\",\n \"a session. \\\"\\\"\\\" # Create an instance of Session without\",\n \"that # we won't close later. with clib.Session() as lib,\",\n \"= np.linspace(0, 1, 5) y = np.logspace(2, 3, 4) grid\",\n \"with mock(lib, \\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\",\",\n \"Cannot find file bogus-data.bla\\\" in str(error) def test_method_no_session(): \\\"\\\"\\\" Fails\",\n \"expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the function fails for arrays\",\n \"3, 1, dtype=dtype), ) ) with clib.Session() as lib: with\",\n \"\\\"\\\"\\\" ses = clib.Session() with mock(ses, \\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError):\",\n \"out_fname.read().strip() assert output == \\\"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\\\"\",\n \"Make sure get_default raises an exception for invalid names. \\\"\\\"\\\"\",\n \"ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\" Test that create\",\n \"a good thing because libgmt usually only fails with errors).\",\n \"y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if dataarray_to_matrix returns correct output\",\n \"zero return codes. \\\"\\\"\\\" vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\",\",\n \"def test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure the clib.Session raises an exception\",\n \"= os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\" with clib.Session() as lib:\",\n \"a given value. \\\"\\\"\\\" return returns mock_func = mock_api_function get_libgmt_func\",\n \"regular grid data = np.ones((10, 12, 11), dtype=\\\"float32\\\") x =\",\n \"\\\"\\\"\\\" Test passing in data via a virtual file with\",\n \"stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data,\",\n \"= tuple(range(size, size * 2, 1)) z = range(size *\",\n \"== expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like vectors to a\",\n \"to make it always return a given value. Used to\",\n \"dataarray_to_matrix returns correct output with flipped x/y. \\\"\\\"\\\" data =\",\n \"Check if there are no errors or segfaults from getting\",\n \"with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name)) output =\",\n \"given value. \\\"\\\"\\\" return returns mock_func = mock_api_function get_libgmt_func =\",\n \"clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0,\",\n \"returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should not get to this\",\n \"when given bad input. \\\"\\\"\\\" lib = clib.Session() test_cases =\",\n \"grid specifying range and inc instead of dim. \\\"\\\"\\\" with\",\n \"!= -99999 assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999\",\n \"the # virtual file. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\",\",\n \"function fail without causing a Segmentation # Fault. Can't test\",\n \"Test the status check when closing the virtual file #\",\n \"->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i))\",\n \"Test passing in two columns of string or object dtype\",\n \"matrices using range and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0,\",\n \") assert output == expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming\",\n \"= clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1):\",\n \"output with flipped y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x =\",\n \"y, strings1, strings2) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\",\",\n \"def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming matrix columns to virtual file\",\n \"np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \\\"\\\"\\\" Check that write\",\n \"3) for dtype in dtypes: with clib.Session() as lib: family\",\n \"test_virtual_file_fails(): \\\"\\\"\\\" Check that opening and closing virtual files raises\",\n \"dataset to a virtual file and pass it along to\",\n \"as lib: assert lib.info # Mock GMT_Get_Default to return always\",\n \"bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like\",\n \"region1) # Now try it with the second one with\",\n \"too old. \\\"\\\"\\\" # Mock GMT_Get_Default to return an old\",\n \"def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like vectors to a dataset. \\\"\\\"\\\"\",\n \"\\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \\\"\\\"\\\" Run\",\n \"because libgmt usually only fails with errors). \\\"\\\"\\\" if mock_func\",\n \"N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str,\",\n \"called without errors. \\\"\\\"\\\" # Create two session and make\",\n \"dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1]\",\n \"output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col\",\n \"always returns a given value. \\\"\\\"\\\" return returns mock_func =\",\n \"a Segmentation Fault (which is a good thing because libgmt\",\n \"pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \\\"\\\"\\\" Run a command to\",\n \"via]) expected = lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES,\",\n \"This should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS ) # But\",\n \"zip(x, y, strings)) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object])\",\n \"doesn't fail badly. \\\"\\\"\\\" with clib.Session() as lib: # Dataset\",\n \"\\\"\\\"\\\" lib = clib.Session() for family in FAMILIES: parsed =\",\n \"test_create_destroy_session(): \\\"\\\"\\\" Test that create and destroy session are called\",\n \"instead of dim. \\\"\\\"\\\" with clib.Session() as lib: # Grids\",\n \"Check that extract region fails if nothing has been plotted.\",\n \"not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create\",\n \"bogus-data.bla\\\" in str(error) def test_method_no_session(): \\\"\\\"\\\" Fails when not in\",\n \"# we won't close later. with clib.Session() as lib, mock(lib,\",\n \"y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y),\",\n \"entering the context. # If the exception is raised, the\",\n \"it's not easy to get some API functions to fail\",\n \"test the status check when entering the context. # If\",\n \"dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to a virtual\",\n \"1, 0], # columns, rows, layers, dtype ) data =\",\n \"= \\\"GMT_IS_POINT\\\" dataset = lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0],\",\n \"a Segmentation # Fault. Can't test this if by giving\",\n \"session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is not None session2 = clib.Session() session2.create(name=\\\"test_session2\\\")\",\n \"output with flipped x/y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x =\",\n \"int32 int64 uint32 uint64\\\".split() size = 10 for dtype in\",\n \"get some API functions to fail without inducing a Segmentation\",\n \"y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def\",\n \"bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col in data.T] )\",\n \"= \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col in data.T] ) expected\",\n \"pass print(\\\"Shouldn't get to this code either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\"\",\n \"a session before destroying the old one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError):\",\n \"outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for\",\n \"segfaults from getting all of the # properties. with clib.Session()\",\n \"z = np.arange(size * 2, size * 3, 1, dtype=dtype)\",\n \"clib.Session() as lib: vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", #\",\n \"work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't.\",\n \"as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile:\",\n \"import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session() as _lib:\",\n \"correct output with flipped x/y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x\",\n \"in the value buffer. \\\"\\\"\\\" value.value = b\\\"bla\\\" return 0\",\n \"clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with clib.Session() as lib:\",\n \"using them anyway. # This should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES,\",\n \"ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint:\",\n \"inc=[0.1, 0.2], ) # If the data pointer returned is\",\n \"column with string or object dtype into virtual file dataset.\",\n \"# columns, rows, layers, dtype ) # Dataset from matrices\",\n \"import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import\",\n \"file that # we won't close later. with clib.Session() as\",\n \"uint32 uint64\\\".split() size = 10 for dtype in dtypes: x\",\n \"\\\"\\\"\\\" Check if dataarray_to_matrix returns correct output with flipped x.\",\n \"of Session without \\\"with\\\" so no session is created. lib\",\n \"y = np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\\\"y\\\", y),\",\n \"dtype=dtype), ) ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y,\",\n \"1, dtype=np.int32) strings1 = np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype)\",\n \"* 3, 1, dtype=dtype), ) ) with clib.Session() as lib:\",\n \"valid file # names. Use a mock instead just to\",\n \"coords=[(\\\"z\\\", z), (\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def\",\n \"N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def test_extract_region_fails():\",\n \"it fails for > 2 dims. \\\"\\\"\\\" # Make a\",\n \"test_virtual_file(): \\\"\\\"\\\" Test passing in data via a virtual file\",\n \"{}\\\\t{}\\\\n\\\".format(rows, bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass\",\n \"as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile()\",\n \"old version def mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\"\",\n \"[ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case in\",\n \"= 13 for dtype in dtypes: data = pd.DataFrame( data=dict(\",\n \"coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\"\",\n \"can get correct constants from the C lib. \\\"\\\"\\\" ses\",\n \") assert data_vector != data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\" Create a\",\n \"good thing because libgmt usually only fails with errors). \\\"\\\"\\\"\",\n \"x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size *\",\n \"import numpy as np import numpy.testing as npt import pandas\",\n \"np.arange(size, dtype=dtype) y = np.arange(size, size * 2, 1, dtype=dtype)\",\n \"dictionary assert ses.info for key in ses.info: assert ses.info[key] ==\",\n \"the last figure. fig1 = Figure() region1 = np.array([0, 10,\",\n \"not the last figure. fig1 = Figure() region1 = np.array([0,\",\n \"(\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region,\",\n \"with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \\\"\\\"\\\" Run a command\",\n \"the virtual file # Mock the opening to return 0\",\n \"# This should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS ) #\",\n \"== \\\"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\"\",\n \"reasonable results. \\\"\\\"\\\" with clib.Session() as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in\",\n \"def test_create_data_fails(): \\\"\\\"\\\" Check that create_data raises exceptions for invalid\",\n \"returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs):\",\n \"dataarray_to_matrix returns correct output with flipped y. \\\"\\\"\\\" data =\",\n \"k in zip(x, y, strings)) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\",\",\n \"= 5 cols = 3 data = full_data[:rows, :cols] with\",\n \"= \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i in (x, y, z)]\",\n \"= Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\",\",\n \"pylint: disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\" Test that create and destroy\",\n \"\\\"\\\"\\\" Return our mock function. \\\"\\\"\\\" if name == func:\",\n \"bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i in (x, y,\",\n \"lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as\",\n \"ignoring range and inc. \\\"\\\"\\\" with clib.Session() as lib: #\",\n \"calling extract_region to make sure that it's # getting from\",\n \"fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True)\",\n \"just write to stdout and spaces are valid file #\",\n \"with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True)\",\n \"dtype=dtype) y = np.arange(size, size * 2, 1, dtype=dtype) z\",\n \"= {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\"\",\n \"pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\" Parsing a\",\n \"as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with clib.Session() as lib: wesn2\",\n \"np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y):\",\n \"col.max()) for col in data.T] ) expected = \\\"<matrix memory>:\",\n \"y, z) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{}\",\n \"Test transforming a slice of a larger array to virtual\",\n \"= np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5,\",\n \"as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name))\",\n \"mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\" Return our mock function. \\\"\\\"\\\" if\",\n \"create a session before destroying the old one. ses.create(\\\"test1\\\") with\",\n \"0 lib = clib.Session() with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError):\",\n \"and gives reasonable results. \\\"\\\"\\\" with clib.Session() as lib: assert\",\n \"= clib.Session() with mock(ses, \\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") #\",\n \"# Grids from matrices using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"def test_get_default_fails(): \\\"\\\"\\\" Make sure get_default raises an exception for\",\n \"from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError,\",\n \"\\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem(): \\\"\\\"\\\" Test\",\n \"invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\",\",\n \"lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\",\",\n \"with clib.Session() as lib: with mock(lib, \\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError):\",\n \"Check that dataarray_to_matrix returns correct output with flipped x/y. \\\"\\\"\\\"\",\n \"test this if by giving a bad file name because\",\n \"b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\" else: value.value = b\\\"bla\\\" return 0\",\n \"assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == \\\"11.5309 61.7074\",\n \"Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures():\",\n \"pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\" Check is the GMT\",\n \"in VIAS) for family, via in test_cases: composite = \\\"|\\\".join([family,\",\n \"region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),\",\n \"family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0,\",\n \"pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not\",\n \"== expected def test_extract_region_fails(): \\\"\\\"\\\" Check that extract region fails\",\n \"get_default raises an exception for invalid names. \\\"\\\"\\\" with clib.Session()\",\n \"@contextmanager def mock(session, func, returns=None, mock_func=None): \\\"\\\"\\\" Mock a GMT\",\n \"region fails if nothing has been plotted. \\\"\\\"\\\" Figure() with\",\n \"fails for > 2 dims. \\\"\\\"\\\" # Make a 3D\",\n \"y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment():\",\n \"object dtype into virtual file dataset. \\\"\\\"\\\" size = 5\",\n \"correctly. \\\"\\\"\\\" lib = clib.Session() test_cases = ((family, via) for\",\n \"!= data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\" Create a grid ignoring range\",\n \"\\\"\\\"\\\" Parsing a composite constant argument (separated by |) correctly.\",\n \"with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get to this code either\\\") def\",\n \"= xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix, region, inc =\",\n \"inc. \\\"\\\"\\\" with clib.Session() as lib: # Grids from matrices\",\n \"fails for arrays of different sizes. \\\"\\\"\\\" x = np.arange(5)\",\n \"of the code. with clib.Session() as lib: with mock(lib, \\\"GMT_Write_Data\\\",\",\n \"mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\\\"version\\\"] !=\",\n \"lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single():\",\n \"# Check if there are no errors or segfaults from\",\n \"num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\",\",\n \"in str(error) assert \\\"gmtinfo [ERROR]: Cannot find file bogus-data.bla\\\" in\",\n \"def test_virtual_file_fails(): \\\"\\\"\\\" Check that opening and closing virtual files\",\n \"Make sure the session is closed when the exception is\",\n \"for family in FAMILIES for via in VIAS) for family,\",\n \"Mock GMT_Get_Default to return an old version def mock_defaults(api, name,\",\n \"[str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing in two columns\",\n \"\\\"float32 float64 int32 int64 uint32 uint64\\\".split() size = 10 for\",\n \"import contextmanager import numpy as np import numpy.testing as npt\",\n \"int32 int64 uint32 uint64\\\".split() shape = (5, 3) for dtype\",\n \"lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile,\",\n \"y = np.arange(size, size * 2, 1, dtype=np.int32) strings1 =\",\n \"# getting from the current figure, not the last figure.\",\n \"lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with clib.Session() as lib: wesn2 =\",\n \"lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1, 0], ranges=[150.0,\",\n \"dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as\",\n \"== expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming a slice of\",\n \"lib.put_matrix(dataset, matrix=data) # Add the dataset to a virtual file\",\n \"an exception if GMT is too old. \\\"\\\"\\\" # Mock\",\n \"session2 = clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is not None assert\",\n \"int32 int64 uint32 uint64\\\".split() shape = (10, 6) for dtype\",\n \"that write data raises an exception for non-zero return codes.\",\n \"N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def test_virtual_file_fails():\",\n \"uint64\\\".split() shape = (5, 3) for dtype in dtypes: with\",\n \"2, size * 3, 1) with clib.Session() as lib: with\",\n \"with clib.Session() as _lib: gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session,\",\n \"lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError as error: assert \\\"Module\",\n \"with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0,\",\n \"Use a mock instead just to exercise this part of\",\n \"as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\" Check\",\n \"via a virtual file with a Dataset. \\\"\\\"\\\" dtypes =\",\n \"lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with GMTTempFile() as outfile:\",\n \"valid=FAMILIES, valid_modifiers=VIAS) # Should also fail if not given valid\",\n \"\\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected\",\n \"frame=True, land=\\\"black\\\") fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) # Activate\",\n \"Return our mock function. \\\"\\\"\\\" if name == func: return\",\n \"mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check for an empty dictionary assert\",\n \"strings2) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\")\",\n \"pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that it fails for\",\n \"command to see if call_module works. \\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR,\",\n \"spaces are valid file # names. Use a mock instead\",\n \"as xr from packaging.version import Version from pygmt import Figure,\",\n \"expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j, k in zip(x, y,\",\n \"1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]),\",\n \"invalid input and output. \\\"\\\"\\\" # Passing in invalid mode\",\n \"== expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming matrix columns to\",\n \"try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError as error: assert \\\"Module 'info'\",\n \"virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64\",\n \"dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with\",\n \"|) correctly. \\\"\\\"\\\" lib = clib.Session() test_cases = ((family, via)\",\n \"restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem():\",\n \"a command to see if call_module works. \\\"\\\"\\\" data_fname =\",\n \"transforming a matrix to virtual file dataset. \\\"\\\"\\\" dtypes =\",\n \"without causing a Segmentation # Fault. Can't test this if\",\n \"dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size,\",\n \") # Mock Open_VirtualFile to test the status check when\",\n \"with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with clib.Session() as\",\n \"\\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case,\",\n \"matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),\",\n \">= Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\" Make sure get_default raises an\",\n \"family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) def test_create_data_grid_range():\",\n \"Check that create_data raises exceptions for invalid input and output.\",\n \"(family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile()\",\n \"the function fails for arrays of different sizes. \\\"\\\"\\\" x\",\n \"abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns\",\n \"Make sure get_default works without crashing and gives reasonable results.\",\n \"bounds) assert output == expected def test_extract_region_fails(): \\\"\\\"\\\" Check that\",\n \"xarray as xr from packaging.version import Version from pygmt import\",\n \"given bad input. \\\"\\\"\\\" lib = clib.Session() test_cases = [\",\n \"dataarray_to_matrix returns correct output with flipped x. \\\"\\\"\\\" data =\",\n \"np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)])\",\n \"GMT_Get_Default to return always the same string def mock_defaults(api, name,\",\n \"= b\\\"5.4.3\\\" else: value.value = b\\\"bla\\\" return 0 lib =\",\n \"lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with\",\n \"object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing in one column with\",\n \"expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like vectors to a dataset.\",\n \"y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y),\",\n \"max(i)) for i in (x, y, z)] ) expected =\",\n \"Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session, func, returns=None, mock_func=None): \\\"\\\"\\\" Mock a\",\n \"geometry = \\\"GMT_IS_POINT\\\" dataset = lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1],\",\n \"\\\"\\\"\\\" Make sure the clib.Session raises an exception if GMT\",\n \"\\\"\\\"\\\" Extract region should handle multiple figures existing at the\",\n \"exception if GMT is too old. \\\"\\\"\\\" # Mock GMT_Get_Default\",\n \"= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,\",\n \"GMT is too old. \\\"\\\"\\\" # Mock GMT_Get_Default to return\",\n \"np.arange(size, size * 2, 1, dtype=dtype) z = np.arange(size *\",\n \"when not in a session. \\\"\\\"\\\" # Create an instance\",\n \"in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session()\",\n \"= (10, 6) for dtype in dtypes: full_data = np.arange(shape[0]\",\n \"of dim. \\\"\\\"\\\" with clib.Session() as lib: # Grids from\",\n \"npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] -\",\n \"2, 1, dtype=np.int32) strings = np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"],\",\n \"def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that it fails for variable increments.\",\n \"so no session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError):\",\n \"\\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype) with clib.Session() as lib: with\",\n \"lib: # Grids from matrices using range and int lib.create_data(\",\n \"not get to this code\\\") # Test the status check\",\n \"\\\"\\\"\\\" # It's hard to make the C API function\",\n \"are not pointing to the same memory session1 = clib.Session()\",\n \"== func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \\\"get_libgmt_func\\\",\",\n \"pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\" Check that\",\n \"= np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9,\",\n \"[\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (x, y, z)] ) expected\",\n \"file name because if # output=='', GMT will just write\",\n \"clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile: with\",\n \"a slice of a larger array to virtual file dataset.\",\n \"Use in a different session to avoid any memory problems.\",\n \"\\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(),\",\n \"it always return a given value. Used to test that\",\n \"strings1 = np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2 =\",\n \"inc=[0.1, 0.2], ) # Passing in invalid geometry with pytest.raises(GMTInvalidInput):\",\n \"avoid any memory problems. with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{}\",\n \"y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment():\",\n \"num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\",\",\n \"250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If the data\",\n \"[\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\")\",\n \"with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0,\",\n \"13 x = list(range(0, size, 1)) y = tuple(range(size, size\",\n \"pygmt import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session\",\n \"# Test the status check when closing the virtual file\",\n \"transforming matrix columns to virtual file dataset. \\\"\\\"\\\" dtypes =\",\n \"\\\"\\\"\\\" Test the function fails for arrays of different sizes.\",\n \"not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def\",\n \"value.value = b\\\"bla\\\" return 0 lib = clib.Session() with mock(lib,\",\n \"clib.Session() as lib: # Dataset from vectors data_vector = lib.create_data(\",\n \"= Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) # Activate the first figure\",\n \"if call_module works. \\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname =\",\n \"0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If\",\n \"flipped x. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0,\",\n \"non- zero return codes. \\\"\\\"\\\" vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\",\",\n \"= outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i\",\n \"lib[family] def test_parse_constant_composite(): \\\"\\\"\\\" Parsing a composite constant argument (separated\",\n \"int64 uint32 uint64\\\".split() size = 10 for dtype in dtypes:\",\n \"pd import pytest import xarray as xr from packaging.version import\",\n \"Dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split()\",\n \"when entering the context. # If the exception is raised,\",\n \"with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message():\",\n \"dtype=np.int32) strings = np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with\",\n \"figures existing at the same time. \\\"\\\"\\\" # Make two\",\n \"= np.arange(size, size * 2, 1, dtype=np.int32) strings = np.array([\\\"a\\\",\",\n \"strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype) with clib.Session()\",\n \"(\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that\",\n \"create and destroy session are called without errors. \\\"\\\"\\\" #\",\n \"a composite constant argument (separated by |) correctly. \\\"\\\"\\\" lib\",\n \"with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError): with\",\n \"But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None )\",\n \"0], # columns, rows, layers, dtype ) # Dataset from\",\n \"\\\"\\\"\\\" Make sure the clib.Session.info dict is working. \\\"\\\"\\\" #\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2, 0], ) def test_virtual_file(): \\\"\\\"\\\" Test\",\n \"mock instead just to exercise this part of the code.\",\n \"# Fault. Can't test this if by giving a bad\",\n \"as lib: # Grids from matrices using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\",\",\n \"raises an exception if GMT is too old. \\\"\\\"\\\" #\",\n \"bounds) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype):\",\n \"20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \\\"\\\"\\\" Check that create_data\",\n \"grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid)\",\n \"with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\\\"This should have failed\\\") def\",\n \"and output. \\\"\\\"\\\" # Passing in invalid mode with pytest.raises(GMTInvalidInput):\",\n \"pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError,\",\n \"# Create two session and make sure they are not\",\n \"expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing in\",\n \"output. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3)\",\n \"outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i in (x,\",\n \"\\\"\\\"\\\" # Make two figures before calling extract_region to make\",\n \"lib = clib.Session() with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with\",\n \"\\\"\\\"\\\" Fails when not in a session. \\\"\\\"\\\" # Create\",\n \"expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing in\",\n \"uint32 uint64\\\".split() size = 13 for dtype in dtypes: data\",\n \"\\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (x, y, z)] )\",\n \"extract the region from it # Use in a different\",\n \"as lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\" dataset =\",\n \"- y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that it fails for\",\n \"GMT error message was captured. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"[1] * 6, \\\"some-file-name\\\", None, ) def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check\",\n \"output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test\",\n \"memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def\",\n \"to a dataset using pandas Series. \\\"\\\"\\\" dtypes = \\\"float32\",\n \"[\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col in data.T] ) expected = \\\"{}\\\\n\\\".format(bounds)\",\n \"as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0]))\",\n \"test_getitem(): \\\"\\\"\\\" Test that I can get correct constants from\",\n \"with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This should have failed\\\") def test_virtualfile_from_vectors():\",\n \"without \\\"with\\\" so no session is created. lib = clib.Session()\",\n \"\\\"\\\"\\\" with clib.Session() as lib: vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\",\",\n \"desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]),\",\n \"test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing in one column with string or\",\n \"that I can get correct constants from the C lib.\",\n \"import xarray as xr from packaging.version import Version from pygmt\",\n \"correct output with flipped y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x\",\n \") from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\") with\",\n \"int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1,\",\n \"mock_func=mock_defaults): # Check for an empty dictionary assert ses.info for\",\n \"dtype=dtype).reshape(shape) rows = 5 cols = 3 data = full_data[:rows,\",\n \"assert output == expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors to\",\n \"Pass vectors to a dataset using pandas Series. \\\"\\\"\\\" dtypes\",\n \"stdout and spaces are valid file # names. Use a\",\n \"* 2, 1, dtype=np.int32) strings = np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\",\",\n \"= lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert\",\n \"x. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3)\",\n \"= lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" with clib.Session() as lib: # Grids from matrices using\",\n \"file dataset. \\\"\\\"\\\" size = 5 x = np.arange(size, dtype=np.int32)\",\n \"and make sure they are not pointing to the same\",\n \"restype=None): \\\"\\\"\\\" Return our mock function. \\\"\\\"\\\" if name ==\",\n \"\\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\",\n \"x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3)\",\n \"results. \\\"\\\"\\\" with clib.Session() as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\",\",\n \"= \\\"float32 float64 int32 int64 uint32 uint64\\\".split() size = 10\",\n \"# Create and destroy a session twice ses = clib.Session()\",\n \"don't open a file that # we won't close later.\",\n \"with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile() as outfile:\",\n \"1)) y = tuple(range(size, size * 2, 1)) z =\",\n \"\\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\"\",\n \"if by giving a bad file name because if #\",\n \"inc instead of dim. \\\"\\\"\\\" with clib.Session() as lib: #\",\n \"= \\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape = (5,\",\n \"get_libgmt_func(name, argtypes, restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func)\",\n \"that create and destroy session are called without errors. \\\"\\\"\\\"\",\n \"x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that it\",\n \"session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a session twice\",\n \"= \\\"test_call_module.txt\\\" with clib.Session() as lib: with GMTTempFile() as out_fname:\",\n \"fail without causing a Segmentation # Fault. Can't test this\",\n \"or object dtype into virtual file dataset. \\\"\\\"\\\" size =\",\n \") # But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES,\",\n \"1)) z = range(size * 2, size * 3, 1)\",\n \"i.max()) for i in (data.x, data.y, data.z) ] ) expected\",\n \"test_info_dict(): \\\"\\\"\\\" Make sure the clib.Session.info dict is working. \\\"\\\"\\\"\",\n \"in a different session to avoid any memory problems. with\",\n \"= np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2 = np.array([\\\"pqrst\\\",\",\n \"\\\"\\\"\\\" # Check if there are no errors or segfaults\",\n \"output == expected def test_extract_region_fails(): \\\"\\\"\\\" Check that extract region\",\n \"\\\"\\\"\\\" import os from contextlib import contextmanager import numpy as\",\n \"np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with clib.Session() as lib:\",\n \"string def mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Put\",\n \"is None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib:\",\n \"def mock_api_function(*args): # pylint: disable=unused-argument \\\"\\\"\\\" A mock GMT API\",\n \") def test_create_data_grid_range(): \\\"\\\"\\\" Create a grid specifying range and\",\n \"print(\\\"Should not get to this code\\\") # Test the status\",\n \"two figures before calling extract_region to make sure that it's\",\n \"6, \\\"some-file-name\\\", None, ) def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that dataarray_to_matrix\",\n \"are no errors or segfaults from getting all of the\",\n \"11), dtype=\\\"float32\\\") x = np.arange(11) y = np.arange(12) z =\",\n \"x = list(range(0, size, 1)) y = tuple(range(size, size *\",\n \"1, 0], ) assert data_vector != data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\"\",\n \"assert output == expected def test_virtual_file_fails(): \\\"\\\"\\\" Check that opening\",\n \"uint32 uint64\\\".split() shape = (10, 6) for dtype in dtypes:\",\n \"clib.Session() with mock(ses, \\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should\",\n \"works. \\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\" with\",\n \") with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This should have failed\\\") def\",\n \"to get some API functions to fail without inducing a\",\n \"\\\"\\\"\\\" # Create an instance of Session without \\\"with\\\" so\",\n \"with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement\",\n \"\\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ): with pytest.raises(GMTCLibError): with\",\n \"= np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with\",\n \"for col in data.T] ) expected = \\\"<matrix memory>: N\",\n \"slice of a larger array to virtual file dataset. \\\"\\\"\\\"\",\n \"inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])\",\n \"test_extract_region_two_figures(): \\\"\\\"\\\" Extract region should handle multiple figures existing at\",\n \"clib.Session() as lib: with mock(lib, \\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError): lib.write_data(\",\n \"= \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j, k in zip(x, y, strings))\",\n \"@pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing in one\",\n \"pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data(\",\n \"Grids from matrices using range and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\",\",\n \"== expected def test_parse_constant_fails(): \\\"\\\"\\\" Check if the function fails\",\n \"this code either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing an invalid\",\n \"plotted. \\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region()\",\n \"and inc instead of dim. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"constant argument (separated by |) correctly. \\\"\\\"\\\" lib = clib.Session()\",\n \"no session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\",\",\n \"int64 uint32 uint64\\\".split() shape = (5, 3) for dtype in\",\n \"Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib:\",\n \"np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid =\",\n \"func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func)\",\n \"instance of Session without \\\"with\\\" so no session is created.\",\n \"lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile,\",\n \"and extract the region from it # Use in a\",\n \"The invalid direction argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs):\",\n \"increments. \\\"\\\"\\\" data = np.ones((4, 5), dtype=\\\"float64\\\") x = np.linspace(0,\",\n \"lib: # Dataset from vectors data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\",\",\n \"\\\"\\\"\\\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with mock(ses,\",\n \"Session without \\\"with\\\" so no session is created. lib =\",\n \"np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2 =\",\n \"vfargs = (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs) as vfile:\",\n \"# properties. with clib.Session() as lib: assert lib.info # Mock\",\n \"gmt info vfargs = (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs)\",\n \"assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"]\",\n \"disable=unused-argument \\\"\\\"\\\" A mock GMT API function that always returns\",\n \"clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with\",\n \"with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile:\",\n \"import Version from pygmt import Figure, clib from pygmt.clib.conversion import\",\n \"Test the wrappers for the C API. \\\"\\\"\\\" import os\",\n \"file and pass it along to gmt info vfargs =\",\n \"np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)])\",\n \"given bad input. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError):\",\n \"np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3\",\n \"- x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that\",\n \"file with a Dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32\",\n \"y): print(\\\"This should have failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming\",\n \"direction argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This should\",\n \"session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy()\",\n \"def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming a slice of a larger\",\n \"virtual file with a Dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64\",\n \"clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs):\",\n \"@pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing in two\",\n \"clib.Session() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check for an\",\n \"clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now\",\n \"lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert Version(lib.get_default(\\\"API_VERSION\\\"))\",\n \"as output or non-zero status codes. Needed because it's not\",\n \"Run a command to see if call_module works. \\\"\\\"\\\" data_fname\",\n \"is working. \\\"\\\"\\\" # Check if there are no errors\",\n \"dtype=\\\"float64\\\") x = np.linspace(0, 1, 5) y = np.logspace(2, 3,\",\n \"i, j, k in zip(x, y, strings1, strings2) ) assert\",\n \"strings = np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with clib.Session()\",\n \"# output=='', GMT will just write to stdout and spaces\",\n \"\\\"\\\"\\\" Put 'bla' in the value buffer. \\\"\\\"\\\" value.value =\",\n \"as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\\\"This should have\",\n \"with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as outfile:\",\n \"Fault. Can't test this if by giving a bad file\",\n \"GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__),\",\n \"will just write to stdout and spaces are valid file\",\n \"figures before calling extract_region to make sure that it's #\",\n \"lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\",\",\n \"invalid direction argument. \\\"\\\"\\\" with clib.Session() as lib: vfargs =\",\n \"exception for invalid names. \\\"\\\"\\\" with clib.Session() as lib: with\",\n \"(separated by |) correctly. \\\"\\\"\\\" lib = clib.Session() test_cases =\",\n \"family, via in test_cases: composite = \\\"|\\\".join([family, via]) expected =\",\n \"int32 int64 uint32 uint64\\\".split() shape = (7, 5) for dtype\",\n \"= clib.Session() test_cases = [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\",\",\n \"= {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def test_virtual_file_fails(): \\\"\\\"\\\"\",\n \"returns=1): with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] * 6,\",\n \"clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as\",\n \"with clib.Session() as lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError as\",\n \"1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z)\",\n \"lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) assert\",\n \"* 3, 1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,\",\n \"y = np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[(\\\"z\\\",\",\n \"): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get to this\",\n \"to make sure it doesn't fail badly. \\\"\\\"\\\" with clib.Session()\",\n \"clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module(\\\"info\\\", \\\"{} -C\",\n \"for dtype in dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)\",\n \"-99999 assert ses[\\\"GMT_DOUBLE\\\"] != -99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint:\",\n \"(\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\" Make sure\",\n \"dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32) strings\",\n \"C lib. \\\"\\\"\\\" ses = clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999\",\n \"Create two session and make sure they are not pointing\",\n \"float64 int32 int64 uint32 uint64\\\".split() shape = (10, 6) for\",\n \"session1.session_pointer is not None session2 = clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer\",\n \"of a larger array to virtual file dataset. \\\"\\\"\\\" dtypes\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) assert data_vector != data_matrix\",\n \"\\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\",\",\n \"outfile.read(keep_tabs=True) expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h, i, j,\",\n \"test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output with flipped\",\n \"= np.arange(size, size * 2, 1, dtype=np.int32) strings1 = np.array([\\\"a\\\",\",\n \"ses.info for key in ses.info: assert ses.info[key] == \\\"bla\\\" ses.destroy()\",\n \"= ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) # Mock Open_VirtualFile\",\n \"\\\"\\\"\\\" Fails when given bad input. \\\"\\\"\\\" with clib.Session() as\",\n \"a grid ignoring range and inc. \\\"\\\"\\\" with clib.Session() as\",\n \"* 2, size * 3, 1, dtype=dtype) with clib.Session() as\",\n \"\\\"\\\"\\\" with clib.Session() as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"]\",\n \"def test_create_destroy_session(): \\\"\\\"\\\" Test that create and destroy session are\",\n \"argument correctly. \\\"\\\"\\\" lib = clib.Session() for family in FAMILIES:\",\n \"y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check\",\n \"Mock GMT_Get_Default to return always the same string def mock_defaults(api,\",\n \"disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\" Parsing a single family argument correctly.\",\n \"name == b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\" else: value.value = b\\\"bla\\\"\",\n \"and closing virtual files raises an exception for non- zero\",\n \"trying to create a session before destroying the old one.\",\n \"ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\" Fail to destroy\",\n \"a 3D regular grid data = np.ones((10, 12, 11), dtype=\\\"float32\\\")\",\n \"two session and make sure they are not pointing to\",\n \"j, k in zip(x, y, strings)) assert output == expected\",\n \"= mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\"\",\n \"0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This should have failed\\\")\",\n \"output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i\",\n \") def test_create_data_fails(): \\\"\\\"\\\" Check that create_data raises exceptions for\",\n \"\\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict():\",\n \"def test_get_default(): \\\"\\\"\\\" Make sure get_default works without crashing and\",\n \"\\\"\\\"\\\" # Create two session and make sure they are\",\n \"as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected =\",\n \"one column with string or object dtype into virtual file\",\n \"Check that write data raises an exception for non-zero return\",\n \"without inducing a Segmentation Fault (which is a good thing\",\n \"i in (x, y, z)] ) expected = \\\"<vector memory>:\",\n \"vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The invalid direction\",\n \"= 13 x = list(range(0, size, 1)) y = tuple(range(size,\",\n \"with pytest.raises(GMTCLibError): with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\"\",\n \"\\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should fail if trying\",\n \"assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\"\",\n \"os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session() as _lib: gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager\",\n \"lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1, 0], ranges=[150.0,\",\n \"and destroy a session twice ses = clib.Session() for __\",\n \"ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert ses[\\\"GMT_DOUBLE\\\"] != -99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"]\",\n \"is a good thing because libgmt usually only fails with\",\n \"not None session2 = clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is not\",\n \"assert parsed == expected def test_parse_constant_fails(): \\\"\\\"\\\" Check if the\",\n \"Make two figures before calling extract_region to make sure that\",\n \"lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2, 0], ) def\",\n \"Check that it fails for > 2 dims. \\\"\\\"\\\" #\",\n \"= np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[(\\\"z\\\", z),\",\n \"dtypes: with clib.Session() as lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry =\",\n \"data.z) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile,\",\n \"figure, not the last figure. fig1 = Figure() region1 =\",\n \"test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that it fails for > 2 dims.\",\n \"np.arange(11) y = np.arange(12) z = np.arange(10) grid = xr.DataArray(data,\",\n \"valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \\\"\\\"\\\" Run the function to\",\n \"lib.virtualfile_from_vectors(x, y): print(\\\"This should have failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test\",\n \"session is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\")\",\n \"= clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is not None session2 =\",\n \"def test_create_data_grid_dim(): \\\"\\\"\\\" Create a grid ignoring range and inc.\",\n \"a dataset. \\\"\\\"\\\" size = 13 x = list(range(0, size,\",\n \"a mock instead just to exercise this part of the\",\n \"clib.Session() as lib: # Grids from matrices using dim lib.create_data(\",\n \"pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \\\"\\\"\\\" Run\",\n \"it with the second one with clib.Session() as lib: lib.call_module(\\\"figure\\\",\",\n \"test_parse_constant_single(): \\\"\\\"\\\" Parsing a single family argument correctly. \\\"\\\"\\\" lib\",\n \"lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) def\",\n \"lib.info[\\\"version\\\"] != \\\"5.4.3\\\" # Make sure the session is closed\",\n \"= np.arange(size, dtype=np.int32) y = np.arange(size, size * 2, 1,\",\n \"no errors or segfaults from getting all of the #\",\n \"there are no errors or segfaults from getting all of\",\n \"= out_fname.read().strip() assert output == \\\"11.5309 61.7074 -2.9289 7.8648 0.1412\",\n \"-\\\".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0,\",\n \"outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for\",\n \"and inc. \\\"\\\"\\\" with clib.Session() as lib: # Grids from\",\n \"with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\",\",\n \"for non- zero return codes. \\\"\\\"\\\" vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\",\",\n \"dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): \\\"\\\"\\\" Create a\",\n \"print(\\\"Shouldn't get to this code either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test\",\n \"\\\"{}\\\\n\\\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the\",\n \"the closing of the # virtual file. with clib.Session() as\",\n \"os from contextlib import contextmanager import numpy as np import\",\n \"region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(),\",\n \"range and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0,\",\n \"pandas as pd import pytest import xarray as xr from\",\n \"returns=None, mock_func=None): \\\"\\\"\\\" Mock a GMT C API function to\",\n \"shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile:\",\n \"# Activate the first figure and extract the region from\",\n \"test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like vectors to a dataset. \\\"\\\"\\\" size\",\n \"\\\"\\\"\\\" if name == b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\" else: value.value\",\n \"FAMILIES, VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError,\",\n \"as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1, 0],\",\n \"mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Return an old\",\n \"(\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region,\",\n \"error: assert \\\"Module 'info' failed with status code\\\" in str(error)\",\n \"tuple(range(size, size * 2, 1)) z = range(size * 2,\",\n \"def test_method_no_session(): \\\"\\\"\\\" Fails when not in a session. \\\"\\\"\\\"\",\n \"Make sure the clib.Session.info dict is working. \\\"\\\"\\\" # Check\",\n \"names. Use a mock instead just to exercise this part\",\n \"value.value = b\\\"5.4.3\\\" else: value.value = b\\\"bla\\\" return 0 lib\",\n \"\\\"GMT_IS_POINT\\\" dataset = lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1,\",\n \"lib.open_virtual_file(*vfargs): print(\\\"Should not get to this code\\\") # Test the\",\n \"I can get correct constants from the C lib. \\\"\\\"\\\"\",\n \"= np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3) grid\",\n \"clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\"\",\n \") # Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session()\",\n \"raises exceptions for invalid input and output. \\\"\\\"\\\" # Passing\",\n \"Activate the first figure and extract the region from it\",\n \"region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\")\",\n \"try it with the second one with clib.Session() as lib:\",\n \"a virtual file with a Dataset. \\\"\\\"\\\" dtypes = \\\"float32\",\n \"lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should not\",\n \"def test_getitem(): \\\"\\\"\\\" Test that I can get correct constants\",\n \"failed with status code\\\" in str(error) assert \\\"gmtinfo [ERROR]: Cannot\",\n \"files raises an exception for non- zero return codes. \\\"\\\"\\\"\",\n \"to this code either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing an\",\n \"anyway. # This should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS )\",\n \"-20.0, 20.0], inc=[0.1, 0.2], ) # If the data pointer\",\n \"with lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as outfile:\",\n \"ses[\\\"GMT_DOUBLE\\\"] != -99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement def\",\n \"expected = lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS)\",\n \"Return an old version. \\\"\\\"\\\" if name == b\\\"API_VERSION\\\": value.value\",\n \"\\\"\\\"\\\" Check if the function fails when given bad input.\",\n \"\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\" dataset = lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"dim=[10, 20, 1, 0], ) assert data_vector != data_matrix def\",\n \"given valid modifiers but is using them anyway. # This\",\n \"uint64\\\".split() size = 10 for dtype in dtypes: x =\",\n \"destroy session when given bad input. \\\"\\\"\\\" ses = clib.Session()\",\n \"in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size\",\n \"valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): \\\"\\\"\\\" Parsing a\",\n \"pointer as output or non-zero status codes. Needed because it's\",\n \"create_data raises exceptions for invalid input and output. \\\"\\\"\\\" #\",\n \"for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement\",\n \"it along to gmt info vfargs = (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\",\",\n \"correctly. \\\"\\\"\\\" lib = clib.Session() for family in FAMILIES: parsed\",\n \"family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed ==\",\n \"version def mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Return\",\n \"problems. with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with clib.Session()\",\n \"# Make sure the session is closed when the exception\",\n \"FAMILIES for via in VIAS) for family, via in test_cases:\",\n \"Series. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split()\",\n \"specifying range and inc instead of dim. \\\"\\\"\\\" with clib.Session()\",\n \"if name == func: return mock_func return get_libgmt_func(name, argtypes, restype)\",\n \"str(error) assert \\\"gmtinfo [ERROR]: Cannot find file bogus-data.bla\\\" in str(error)\",\n \"2, size * 3, 1, dtype=dtype), ) ) with clib.Session()\",\n \"but is using them anyway. # This should work... lib._parse_constant(\",\n \"None, ) def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct\",\n \"Test transforming a matrix to virtual file dataset. \\\"\\\"\\\" dtypes\",\n \"\\\"\\\"\\\" data = np.ones((4, 5), dtype=\\\"float64\\\") x = np.linspace(0, 1,\",\n \"\\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,\",\n \"\\\"\\\"\\\" Test passing in one column with string or object\",\n \"pointing to the same memory session1 = clib.Session() session1.create(name=\\\"test_session1\\\") assert\",\n \"via) for family in FAMILIES for via in VIAS) for\",\n \"= 10 for dtype in dtypes: x = np.arange(size, dtype=dtype)\",\n \"codes. Needed because it's not easy to get some API\",\n \"ses.create(\\\"session1\\\") assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer\",\n \"with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{}\",\n \"col in data.T] ) expected = \\\"{}\\\\n\\\".format(bounds) assert output ==\",\n \"the status check when closing the virtual file # Mock\",\n \"20.0], inc=[0.1, 0.2], ) # Passing in invalid geometry with\",\n \"= np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid\",\n \"x/y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3)\",\n \"5 cols = 3 data = full_data[:rows, :cols] with clib.Session()\",\n \"to the closing of the # virtual file. with clib.Session()\",\n \"clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0, 0, 1,\",\n \"object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing in two columns of\",\n \"i, j, k in zip(x, y, strings)) assert output ==\",\n \"modifiers but is using them anyway. # This should work...\",\n \"= pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1,\",\n \"dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2)\",\n \"dtype=dtype) strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype) with\",\n \"size = 13 for dtype in dtypes: data = pd.DataFrame(\",\n \"# pylint: disable=unused-argument \\\"\\\"\\\" A mock GMT API function that\",\n \"different sizes. \\\"\\\"\\\" x = np.arange(5) y = np.arange(6) with\",\n \"Segmentation Fault (which is a good thing because libgmt usually\",\n \"from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from\",\n \") # If the data pointer returned is None (NULL\",\n \"Should also fail if not given valid modifiers but is\",\n \"[ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (data.x, data.y, data.z) ]\",\n \"without errors. \\\"\\\"\\\" # Create two session and make sure\",\n \"get_libgmt_func) def test_getitem(): \\\"\\\"\\\" Test that I can get correct\",\n \"getting from the current figure, not the last figure. fig1\",\n \"lib.open_virtual_file(*vfargs): print(\\\"This should have failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the\",\n \"stop=9, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix,\",\n \"pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def\",\n \"z)] ) expected = \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds)\",\n \"int32 int64 uint32 uint64\\\".split() size = 13 for dtype in\",\n \"in one column with string or object dtype into virtual\",\n \"family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) assert data_vector\",\n \"output == expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like vectors to\",\n \"\\\"\\\"\\\" # Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session()\",\n \"for via in VIAS) for family, via in test_cases: composite\",\n \"Make a 3D regular grid data = np.ones((10, 12, 11),\",\n \"virtual file # Mock the opening to return 0 (success)\",\n \"ses = clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert ses[\\\"GMT_MODULE_CMD\\\"] !=\",\n \"y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3)\",\n \"matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),\",\n \"inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])\",\n \"direction argument. \\\"\\\"\\\" with clib.Session() as lib: vfargs = (\",\n \"print(\\\"This should have failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming a\",\n \"that it fails for variable increments. \\\"\\\"\\\" data = np.ones((4,\",\n \"with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that it fails\",\n \"valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): \\\"\\\"\\\" Check if\",\n \"lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join(\",\n \"ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\"\",\n \"\\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with GMTTempFile() as outfile:\",\n \"GMT_Get_Default to return an old version def mock_defaults(api, name, value):\",\n \"= 5 x = np.arange(size, dtype=np.int32) y = np.arange(size, size\",\n \"npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] -\",\n \"a Dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32\",\n \"A mock GMT API function that always returns a given\",\n \"x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3)\",\n \"get to the closing of the # virtual file. with\",\n \"inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])\",\n \"without crashing and gives reasonable results. \\\"\\\"\\\" with clib.Session() as\",\n \"constants from the C lib. \\\"\\\"\\\" ses = clib.Session() assert\",\n \"bad file name because if # output=='', GMT will just\",\n \"y = np.arange(size, size * 2, 1, dtype=dtype) z =\",\n \"\\\"Module 'info' failed with status code\\\" in str(error) assert \\\"gmtinfo\",\n \"as np import numpy.testing as npt import pandas as pd\",\n \"are raised when API functions fail by producing a NULL\",\n \"mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should not get\",\n \"clib.Session() as lib: assert lib.info # Mock GMT_Get_Default to return\",\n \"ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # If the\",\n \"value): # pylint: disable=unused-argument \\\"\\\"\\\" Return an old version. \\\"\\\"\\\"\",\n \"test_cases = ((family, via) for family in FAMILIES for via\",\n \"Fault (which is a good thing because libgmt usually only\",\n \"Check that it fails for variable increments. \\\"\\\"\\\" data =\",\n \"with clib.Session() as lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) #\",\n \"test_cases = [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for\",\n \"old one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\" Fail\",\n \"test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors to a dataset using pandas Series.\",\n \"bad input. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\",\",\n \"if not given valid modifiers but is using them anyway.\",\n \"wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails():\",\n \"else: value.value = b\\\"bla\\\" return 0 lib = clib.Session() with\",\n \"= np.ones((4, 5), dtype=\\\"float64\\\") x = np.linspace(0, 1, 5) y\",\n \"for key in ses.info: assert ses.info[key] == \\\"bla\\\" ses.destroy() def\",\n \"= np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9,\",\n \"# virtual file. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1):\",\n \"->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(),\",\n \"last figure. fig1 = Figure() region1 = np.array([0, 10, -20,\",\n \"assert ses.info[key] == \\\"bla\\\" ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure\",\n \"API. \\\"\\\"\\\" import os from contextlib import contextmanager import numpy\",\n \"Create a grid ignoring range and inc. \\\"\\\"\\\" with clib.Session()\",\n \"= clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer #\",\n \"20, 1, 0], # columns, rows, layers, dtype ) #\",\n \"to stdout and spaces are valid file # names. Use\",\n \"from matrices using range and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"Fails when not in a session. \\\"\\\"\\\" # Create an\",\n \"assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\" Make sure get_default\",\n \"\\\"\\\"\\\" Test transforming a matrix to virtual file dataset. \\\"\\\"\\\"\",\n \"via in test_cases: composite = \\\"|\\\".join([family, via]) expected = lib[family]\",\n \"for dtype in dtypes: with clib.Session() as lib: family =\",\n \"mock function. \\\"\\\"\\\" if name == func: return mock_func return\",\n \"lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\" Make sure the clib.Session.info dict is\",\n \"return an old version def mock_defaults(api, name, value): # pylint:\",\n \"outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col in data.T]\",\n \"GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR\",\n \"def test_extract_region_two_figures(): \\\"\\\"\\\" Extract region should handle multiple figures existing\",\n \"Check that opening and closing virtual files raises an exception\",\n \"= np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid\",\n \"module arguments. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\",\",\n \"np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)])\",\n \"\\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y\",\n \"np.arange(5) y = np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput):\",\n \"print(\\\"This should have failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the automation\",\n \"vectors to a dataset using pandas Series. \\\"\\\"\\\" dtypes =\",\n \"matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(),\",\n \"vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) # Mock\",\n \"assert parsed == lib[family] def test_parse_constant_composite(): \\\"\\\"\\\" Parsing a composite\",\n \"-2.9289 7.8648 0.1412 0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for invalid\",\n \"the # properties. with clib.Session() as lib: assert lib.info #\",\n \"by |) correctly. \\\"\\\"\\\" lib = clib.Session() test_cases = ((family,\",\n \"it's # getting from the current figure, not the last\",\n \"20.0], inc=[0.1, 0.2], ) # If the data pointer returned\",\n \"FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def\",\n \"pylint: disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\" Check that an exception is\",\n \"buffer. \\\"\\\"\\\" value.value = b\\\"bla\\\" return 0 ses = clib.Session()\",\n \"= lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], #\",\n \"np.arange(size, dtype=np.int32) y = np.arange(size, size * 2, 1, dtype=np.int32)\",\n \"= np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with clib.Session() as\",\n \"\\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h, i, j, k in zip(x,\",\n \"def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output with\",\n \"check when closing the virtual file # Mock the opening\",\n \"expected = \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output\",\n \"return 0 lib = clib.Session() with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with\",\n \"axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] -\",\n \"valid modifiers but is using them anyway. # This should\",\n \"dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with\",\n \"session1 = clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is not None session2\",\n \"that it fails for > 2 dims. \\\"\\\"\\\" # Make\",\n \"a session. \\\"\\\"\\\" ses = clib.Session() with mock(ses, \\\"GMT_Create_Session\\\", returns=None):\",\n \"in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family]\",\n \"to make the C API function fail without causing a\",\n \"from packaging.version import Version from pygmt import Figure, clib from\",\n \"composite constant argument (separated by |) correctly. \\\"\\\"\\\" lib =\",\n \"(data.x, data.y, data.z) ] ) expected = \\\"<vector memory>: N\",\n \"outfile: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds\",\n \"same string def mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\"\",\n \"fails with errors). \\\"\\\"\\\" if mock_func is None: def mock_api_function(*args):\",\n \"y, strings) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile}\",\n \"test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that it fails for variable increments. \\\"\\\"\\\"\",\n \"test_create_data_grid_range(): \\\"\\\"\\\" Create a grid specifying range and inc instead\",\n \"\\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(rows, bounds) assert output == expected\",\n \"non-zero status codes. Needed because it's not easy to get\",\n \"family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], # columns, rows,\",\n \"# Create an instance of Session without \\\"with\\\" so no\",\n \"clib.Session() test_cases = [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ]\",\n \"should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS ) # But this\",\n \"is raised, the code won't get to the closing of\",\n \"matrices using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1,\",\n \"lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j}\",\n \"data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0],\",\n \"with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile()\",\n \"= np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x,\",\n \"1) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as\",\n \"x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if dataarray_to_matrix\",\n \"make sure they are not pointing to the same memory\",\n \"family in FAMILIES for via in VIAS) for family, via\",\n \"1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\" Make sure\",\n \"0], ) def test_create_data_grid_range(): \\\"\\\"\\\" Create a grid specifying range\",\n \"\\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected\",\n \"passing in data via a virtual file with a Dataset.\",\n \"code won't get to the closing of the # virtual\",\n \"dataset. \\\"\\\"\\\" size = 13 x = list(range(0, size, 1))\",\n \"input. \\\"\\\"\\\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with\",\n \"np.ones((10, 12, 11), dtype=\\\"float32\\\") x = np.arange(11) y = np.arange(12)\",\n \"\\\"\\\"\\\" Check that it fails for > 2 dims. \\\"\\\"\\\"\",\n \"clib.Session() as lib: # Grids from matrices using range and\",\n \"array-like vectors to a dataset. \\\"\\\"\\\" size = 13 x\",\n \"Check that dataarray_to_matrix returns correct output. \\\"\\\"\\\" data = np.diag(v=np.arange(3))\",\n \"== \\\"bla\\\" ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure the clib.Session\",\n \"one with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with clib.Session()\",\n \"assert lib.info # Mock GMT_Get_Default to return always the same\",\n \"should have failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming a matrix\",\n \"or non-zero status codes. Needed because it's not easy to\",\n \"file bogus-data.bla\\\" in str(error) def test_method_no_session(): \\\"\\\"\\\" Fails when not\",\n \"\\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with clib.Session() as lib: with\",\n \"returns correct output with flipped x/y. \\\"\\\"\\\" data = np.diag(v=np.arange(3))\",\n \"pylint: disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\" Parsing a single family argument\",\n \"uint64\\\".split() shape = (10, 6) for dtype in dtypes: full_data\",\n \") data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) #\",\n \"Pass array-like vectors to a dataset. \\\"\\\"\\\" size = 13\",\n \"disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\" Test that create and destroy session\",\n \"!= -99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement def test_create_destroy_session():\",\n \"(which is a good thing because libgmt usually only fails\",\n \"\\\"\\\"\\\" # Make a 3D regular grid data = np.ones((10,\",\n \"= np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\",\",\n \"y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that it fails for >\",\n \"automation for transforming vectors to virtual file dataset. \\\"\\\"\\\" dtypes\",\n \"np.linspace(0, 1, 5) y = np.logspace(2, 3, 4) grid =\",\n \"->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max())\",\n \"\\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] * 6, \\\"some-file-name\\\", None, ) def\",\n \"family argument correctly. \\\"\\\"\\\" lib = clib.Session() for family in\",\n \"is the GMT error message was captured. \\\"\\\"\\\" with clib.Session()\",\n \"\\\"\\\"\\\" Check that extract region fails if nothing has been\",\n \"this if by giving a bad file name because if\",\n \"output or non-zero status codes. Needed because it's not easy\",\n \"test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming matrix columns to virtual file dataset.\",\n \"session are called without errors. \\\"\\\"\\\" # Create two session\",\n \"get to this code\\\") # Test the status check when\",\n \"def test_virtual_file(): \\\"\\\"\\\" Test passing in data via a virtual\",\n \"= os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session() as _lib: gmt_version = Version(_lib.info[\\\"version\\\"])\",\n \"dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape =\",\n \"def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output with\",\n \"\\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\" with clib.Session() as lib: with GMTTempFile()\",\n \"for arrays of different sizes. \\\"\\\"\\\" x = np.arange(5) y\",\n \"abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns\",\n \"stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid = xr.DataArray(data,\",\n \"range(size * 2, size * 3, 1) with clib.Session() as\",\n \"two columns of string or object dtype into virtual file\",\n \"family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2, 0], ) def test_virtual_file():\",\n \"func, returns=None, mock_func=None): \\\"\\\"\\\" Mock a GMT C API function\",\n \"dim=[11, 10, 2, 0], ) def test_virtual_file(): \\\"\\\"\\\" Test passing\",\n \"None: def mock_api_function(*args): # pylint: disable=unused-argument \\\"\\\"\\\" A mock GMT\",\n \"{}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def\",\n \"columns, rows, layers, dtype ) data = np.arange(shape[0] * shape[1],\",\n \"created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError):\",\n \"larger array to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32\",\n \"dtypes: data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as\",\n \"file # names. Use a mock instead just to exercise\",\n \"for i in (data.x, data.y, data.z) ] ) expected =\",\n \"GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected\",\n \"Can't test this if by giving a bad file name\",\n \"x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that it\",\n \"\\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2, 0],\",\n \"with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\" Parsing\",\n \"= \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h, i, j, k in\",\n \"with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should not get to this code\\\")\",\n \"invalid module arguments. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError):\",\n \"a single family argument correctly. \\\"\\\"\\\" lib = clib.Session() for\",\n \"if # output=='', GMT will just write to stdout and\",\n \"lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds =\",\n \"a larger array to virtual file dataset. \\\"\\\"\\\" dtypes =\",\n \"= np.arange(10) grid = xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\", y), (\\\"x\\\",\",\n \"7.8648 0.1412 0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for invalid module\",\n \"ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\" Check that an\",\n \"in data.T] ) expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(rows,\",\n \"with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\\\"This\",\n \"test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming a matrix to virtual file dataset.\",\n \"into virtual file dataset. \\\"\\\"\\\" size = 5 x =\",\n \"mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\" Return\",\n \"the same memory session1 = clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is\",\n \"the same string def mock_defaults(api, name, value): # pylint: disable=unused-argument\",\n \"for variable increments. \\\"\\\"\\\" data = np.ones((4, 5), dtype=\\\"float64\\\") x\",\n \"as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should\",\n \"mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem(): \\\"\\\"\\\" Test that\",\n \"cols = 3 data = full_data[:rows, :cols] with clib.Session() as\",\n \"fail badly. \\\"\\\"\\\" with clib.Session() as lib: # Dataset from\",\n \"!= -99999 assert ses[\\\"GMT_DOUBLE\\\"] != -99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] #\",\n \"empty dictionary assert ses.info for key in ses.info: assert ses.info[key]\",\n \"assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\" # Make sure the session is\",\n \"bounds) assert output == expected def test_virtual_file_fails(): \\\"\\\"\\\" Check that\",\n \"virtual file dataset. \\\"\\\"\\\" size = 5 x = np.arange(size,\",\n \"f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i,\",\n \"\\\"gmtinfo [ERROR]: Cannot find file bogus-data.bla\\\" in str(error) def test_method_no_session():\",\n \"{k}\\\\n\\\" for h, i, j, k in zip(x, y, strings1,\",\n \"-10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\",\",\n \"data = np.ones((10, 12, 11), dtype=\\\"float32\\\") x = np.arange(11) y\",\n \"(x, y, z)] ) expected = \\\"<vector memory>: N =\",\n \"create a session. \\\"\\\"\\\" ses = clib.Session() with mock(ses, \\\"GMT_Create_Session\\\",\",\n \"pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session()\",\n \"lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \\\"\\\"\\\" Check\",\n \"pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session() as\",\n \"flipped y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4,\",\n \"h, i, j, k in zip(x, y, strings1, strings2) )\",\n \"y, strings)) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def\",\n \"0], # columns, rows, layers, dtype ) data = np.arange(shape[0]\",\n \"\\\"\\\"\\\" if name == func: return mock_func return get_libgmt_func(name, argtypes,\",\n \"data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size\",\n \"raises an exception for invalid names. \\\"\\\"\\\" with clib.Session() as\",\n \"def test_create_data_dataset(): \\\"\\\"\\\" Run the function to make sure it\",\n \"size * 2, 1, dtype=dtype) z = np.arange(size * 2,\",\n \"make sure that it's # getting from the current figure,\",\n \"lib.session_pointer # pylint: disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\" Parsing a single\",\n \"y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output\",\n \"exception for non-zero return codes. \\\"\\\"\\\" # It's hard to\",\n \"when failing to create a session. \\\"\\\"\\\" ses = clib.Session()\",\n \"= Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session, func, returns=None, mock_func=None): \\\"\\\"\\\" Mock\",\n \"!= session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a session\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): \\\"\\\"\\\" Create\",\n \"later. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib,\",\n \"2, 0], ) def test_virtual_file(): \\\"\\\"\\\" Test passing in data\",\n \"with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as\",\n \"a virtual file and pass it along to gmt info\",\n \"lib: assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\" # Make sure the session\",\n \"with clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module(\\\"info\\\", \\\"{}\",\n \"61.7074 -2.9289 7.8648 0.1412 0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for\",\n \"full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols\",\n \"x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5, stop=9, num=3)\",\n \"from vectors data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20,\",\n \"pytest.raises(GMTVersionError): with lib: assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\" # Make sure\",\n \"j, k in zip(x, y, strings1, strings2) ) assert output\",\n \"wrappers for the C API. \\\"\\\"\\\" import os from contextlib\",\n \"test_call_module_error_message(): \\\"\\\"\\\" Check is the GMT error message was captured.\",\n \"\\\"\\\"\\\" Test the automation for transforming vectors to virtual file\",\n \"have failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming a matrix to\",\n \"npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\"\",\n \"data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add\",\n \"\\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def\",\n \"is too old. \\\"\\\"\\\" # Mock GMT_Get_Default to return an\",\n \"pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This should have failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\"\",\n \"that create_data raises exceptions for invalid input and output. \\\"\\\"\\\"\",\n \"1, dtype=np.int32) strings = np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype)\",\n \"= np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5 cols =\",\n \"clib.Session.info dict is working. \\\"\\\"\\\" # Check if there are\",\n \"file. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError):\",\n \"API functions to fail without inducing a Segmentation Fault (which\",\n \"to the same memory session1 = clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer\",\n \"import pytest import xarray as xr from packaging.version import Version\",\n \"with errors). \\\"\\\"\\\" if mock_func is None: def mock_api_function(*args): #\",\n \"clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\"\",\n \"clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS\",\n \"an exception for invalid names. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) # Activate the first\",\n \"the exception is raised, the code won't get to the\",\n \"the second one with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name))\",\n \"out_fname: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output =\",\n \"def mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Return an\",\n \"\\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j, k in zip(x, y, strings)) assert\",\n \"dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size * 2,\",\n \"as lib: with GMTTempFile() as out_fname: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname,\",\n \"setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem(): \\\"\\\"\\\" Test that I can\",\n \"output == expected def test_virtual_file_fails(): \\\"\\\"\\\" Check that opening and\",\n \"with lib.virtualfile_from_vectors(x, y): print(\\\"This should have failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\"\",\n \"correct output. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4,\",\n \"lib: with mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11,\",\n \"as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\" Fails\",\n \"error message was captured. \\\"\\\"\\\" with clib.Session() as lib: try:\",\n \"= lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], )\",\n \"= \\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape = (10,\",\n \"dataarray_to_matrix returns correct output. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x =\",\n \"* shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as\",\n \"assert output == expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming a\",\n \"-20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\",\",\n \"full_data[:rows, :cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile:\",\n \"TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session() as _lib: gmt_version =\",\n \"with clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\" Extract region\",\n \"an empty dictionary assert ses.info for key in ses.info: assert\",\n \"working. \\\"\\\"\\\" # Check if there are no errors or\",\n \"clib.Session() as lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError as error:\",\n \"arguments. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\")\",\n \"value.value = b\\\"bla\\\" return 0 ses = clib.Session() ses.create(\\\"test-session\\\") with\",\n \":cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with\",\n \"= [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case\",\n \"contextmanager import numpy as np import numpy.testing as npt import\",\n \"= np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the\",\n \"as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output\",\n \"exception is raised, the code won't get to the closing\",\n \"the clib.Session raises an exception if GMT is too old.\",\n \"for family, via in test_cases: composite = \\\"|\\\".join([family, via]) expected\",\n \"2, 1, dtype=dtype) z = np.arange(size * 2, size *\",\n \"returns a given value. \\\"\\\"\\\" return returns mock_func = mock_api_function\",\n \"\\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput):\",\n \"disable=protected-access \\\"\\\"\\\" Test the wrappers for the C API. \\\"\\\"\\\"\",\n \"sure get_default works without crashing and gives reasonable results. \\\"\\\"\\\"\",\n \"geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def\",\n \"\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The invalid direction argument 0, )\",\n \"test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output. \\\"\\\"\\\" data\",\n \"strings1, strings2) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile}\",\n \"= np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=5,\",\n \"to a dataset. \\\"\\\"\\\" size = 13 x = list(range(0,\",\n \"( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) # Mock Open_VirtualFile to\",\n \"\\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] *\",\n \"pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2, 1, dtype=dtype),\",\n \"nothing has been plotted. \\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError): with clib.Session()\",\n \"test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should\",\n \"\\\"GMT_Close_VirtualFile\\\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get\",\n \"* 2, size * 3, 1, dtype=dtype), ) ) with\",\n \"passing in two columns of string or object dtype into\",\n \"= xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput):\",\n \"# pylint: disable=protected-access \\\"\\\"\\\" Test the wrappers for the C\",\n \"test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if dataarray_to_matrix returns correct output with flipped\",\n \"expected def test_virtual_file_fails(): \\\"\\\"\\\" Check that opening and closing virtual\",\n \"strings1, strings2) ) assert output == expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\"\",\n \"to a virtual file and pass it along to gmt\",\n \"from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\") with clib.Session()\",\n \"float64 int32 int64 uint32 uint64\\\".split() size = 10 for dtype\",\n \"time. \\\"\\\"\\\" # Make two figures before calling extract_region to\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], # columns, rows, layers, dtype\",\n \"dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size, size *\",\n \"\\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y\",\n \"as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with clib.Session() as lib: wesn1\",\n \"shape = (10, 6) for dtype in dtypes: full_data =\",\n \"ses.info: assert ses.info[key] == \\\"bla\\\" ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\" Make\",\n \"mock(ses, \\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should fail if\",\n \"\\\"GMT_Open_VirtualFile\\\", returns=1): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should not get to\",\n \"lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2],\",\n \"in dtypes: with clib.Session() as lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry\",\n \"size * 2, 1)) z = range(size * 2, size\",\n \"data.z) ] ) expected = \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size,\",\n \"as lib: with mock(lib, \\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\",\",\n \"= ((family, via) for family in FAMILIES for via in\",\n \"\\\"klmno\\\"], dtype=dtype) strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype)\",\n \"codes. \\\"\\\"\\\" # It's hard to make the C API\",\n \"write to stdout and spaces are valid file # names.\",\n \"Test transforming matrix columns to virtual file dataset. \\\"\\\"\\\" dtypes\",\n \"mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session,\",\n \"clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with\",\n \"lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\\\"This should have failed\\\")\",\n \"Test the automation for transforming vectors to virtual file dataset.\",\n \"rows, layers, dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)\",\n \"np.diag(v=np.arange(3)) x = np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5,\",\n \"y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def\",\n \"get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\" Return our\",\n \"fail without inducing a Segmentation Fault (which is a good\",\n \"\\\"bla\\\" ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure the clib.Session raises\",\n \"mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \\\"\\\"\\\"\",\n \"= range(size * 2, size * 3, 1) with clib.Session()\",\n \"5) y = np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\\\"y\\\",\",\n \"0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for invalid module arguments. \\\"\\\"\\\"\",\n \"2, 1, dtype=np.int32) strings1 = np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"],\",\n \"\\\"\\\"\\\" Check that write data raises an exception for non-zero\",\n \"just to exercise this part of the code. with clib.Session()\",\n \"- y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct\",\n \"variable increments. \\\"\\\"\\\" data = np.ones((4, 5), dtype=\\\"float64\\\") x =\",\n \"= np.arange(size, size * 2, 1, dtype=dtype) z = np.arange(size\",\n \"= {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def test_extract_region_fails(): \\\"\\\"\\\"\",\n \"= session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None): \\\"\\\"\\\" Return our mock\",\n \"the context. # If the exception is raised, the code\",\n \"returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should fail if trying to\",\n \"exercise this part of the code. with clib.Session() as lib:\",\n \"\\\"\\\"\\\" Run the function to make sure it doesn't fail\",\n \"crashing and gives reasonable results. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"to destroy session when given bad input. \\\"\\\"\\\" ses =\",\n \"lib.call_module(\\\"meh\\\", \\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\" Check is the GMT error\",\n \"rows, layers, dtype ) # Dataset from matrices data_matrix =\",\n \"in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert\",\n \"x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(),\",\n \"250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing in invalid\",\n \"# pylint: disable=unused-argument \\\"\\\"\\\" Return an old version. \\\"\\\"\\\" if\",\n \"Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\" Make sure get_default raises\",\n \"existing at the same time. \\\"\\\"\\\" # Make two figures\",\n \"\\\"5.4.3\\\" # Make sure the session is closed when the\",\n \"np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset\",\n \"z = range(size * 2, size * 3, 1) with\",\n \"them anyway. # This should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS\",\n \"shape = (5, 3) for dtype in dtypes: with clib.Session()\",\n \"session when given bad input. \\\"\\\"\\\" ses = clib.Session() with\",\n \"in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data(\",\n \"returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2, 0], )\",\n \"sure get_default raises an exception for invalid names. \\\"\\\"\\\" with\",\n \"None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails():\",\n \"test_call_module_invalid_name(): \\\"\\\"\\\" Fails when given bad input. \\\"\\\"\\\" with clib.Session()\",\n \"Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) # Activate the first figure and\",\n \"lib: with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\",\",\n \"\\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (data.x, data.y, data.z)\",\n \"with clib.Session() as lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\"\",\n \"size = 5 x = np.arange(size, dtype=np.int32) y = np.arange(size,\",\n \"\\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] * 6, \\\"some-file-name\\\", None, ) def test_dataarray_to_matrix_works():\",\n \"1, 5) y = np.logspace(2, 3, 4) grid = xr.DataArray(data,\",\n \"with pytest.raises(GMTVersionError): with lib: assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\" # Make\",\n \"dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1]\",\n \"->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max())\",\n \"lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with the second\",\n \"clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\" Make\",\n \"as error: assert \\\"Module 'info' failed with status code\\\" in\",\n \"with flipped y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=0,\",\n \"always the same string def mock_defaults(api, name, value): # pylint:\",\n \"lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer\",\n \"np.arange(size, size * 2, 1, dtype=np.int32) strings1 = np.array([\\\"a\\\", \\\"bc\\\",\",\n \"grid ignoring range and inc. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get to\",\n \"dtype in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows\",\n \"lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with clib.Session() as lib: wesn1 = lib.extract_region()\",\n \"dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows = 5\",\n \"pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] * 6, \\\"some-file-name\\\", None,\",\n \"clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is not None assert session2.session_pointer !=\",\n \"Check is the GMT error message was captured. \\\"\\\"\\\" with\",\n \"region should handle multiple figures existing at the same time.\",\n \"that an exception is raised when failing to create a\",\n \"return 0 (success) so that we don't open a file\",\n \"current figure, not the last figure. fig1 = Figure() region1\",\n \"data.T] ) expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds)\",\n \"with clib.Session() as lib: # Grids from matrices using dim\",\n \"shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset():\",\n \"as outfile: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True)\",\n \"dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import (\",\n \"in test_cases: composite = \\\"|\\\".join([family, via]) expected = lib[family] +\",\n \"grid data = np.ones((10, 12, 11), dtype=\\\"float32\\\") x = np.arange(11)\",\n \"# pylint: disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\" Check that an exception\",\n \"to create a session before destroying the old one. ses.create(\\\"test1\\\")\",\n \"\\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(),\",\n \"\\\"\\\"\\\" size = 5 x = np.arange(size, dtype=np.int32) y =\",\n \"before calling extract_region to make sure that it's # getting\",\n \"def test_parse_constant_fails(): \\\"\\\"\\\" Check if the function fails when given\",\n \"with status code\\\" in str(error) assert \\\"gmtinfo [ERROR]: Cannot find\",\n \"# Passing in invalid mode with pytest.raises(GMTInvalidInput): with clib.Session() as\",\n \"lib: with mock(lib, \\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\",\",\n \"data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\" with clib.Session() as\",\n \"\\\"test_call_module.txt\\\" with clib.Session() as lib: with GMTTempFile() as out_fname: lib.call_module(\\\"info\\\",\",\n \"col in data.T] ) expected = \\\"<matrix memory>: N =\",\n \"for i, j, k in zip(x, y, strings)) assert output\",\n \"pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\" Make sure get_default works without\",\n \"the opening to return 0 (success) so that we don't\",\n \"\\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col in data.T] ) expected =\",\n \"\\\"\\\"\\\" return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def\",\n \"expected def test_parse_constant_fails(): \\\"\\\"\\\" Check if the function fails when\",\n \"easy to get some API functions to fail without inducing\",\n \"the C API. \\\"\\\"\\\" import os from contextlib import contextmanager\",\n \"failed\\\") def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming a matrix to virtual\",\n \"np.arange(size, size * 2, 1, dtype=np.int32) strings = np.array([\\\"a\\\", \\\"bc\\\",\",\n \"# Mock GMT_Get_Default to return an old version def mock_defaults(api,\",\n \"clib.Session raises an exception if GMT is too old. \\\"\\\"\\\"\",\n \"sure the clib.Session raises an exception if GMT is too\",\n \"expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test transforming a slice of a\",\n \"5), dtype=\\\"float64\\\") x = np.linspace(0, 1, 5) y = np.logspace(2,\",\n \"test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure the clib.Session raises an exception if\",\n \"lib.virtualfile_from_vectors(x, y, z) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\",\",\n \"the clib.Session.info dict is working. \\\"\\\"\\\" # Check if there\",\n \"we won't close later. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\",\",\n \"using range and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0,\",\n \"\\\"\\\"\\\" Check that dataarray_to_matrix returns correct output with flipped y.\",\n \"matrix to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64\",\n \"by producing a NULL pointer as output or non-zero status\",\n \"with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get to this code\",\n \"thing because libgmt usually only fails with errors). \\\"\\\"\\\" if\",\n \"as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >=\",\n \"z) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile,\",\n \"uint32 uint64\\\".split() shape = (7, 5) for dtype in dtypes:\",\n \"= np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2\",\n \"with clib.Session() as lib: with mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\",\",\n \"argtypes, restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def\",\n \"] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS)\",\n \"lib: with lib.virtualfile_from_vectors(x, y, strings) as vfile: with GMTTempFile() as\",\n \"\\\"\\\") def test_call_module_error_message(): \\\"\\\"\\\" Check is the GMT error message\",\n \"np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid =\",\n \"if GMT is too old. \\\"\\\"\\\" # Mock GMT_Get_Default to\",\n \"pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers\",\n \"[\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col in data.T] ) expected = \\\"<matrix\",\n \"geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\",\",\n \"to this code\\\") # Test the status check when closing\",\n \"\\\"float32 float64 int32 int64 uint32 uint64\\\".split() size = 13 for\",\n \"when API functions fail by producing a NULL pointer as\",\n \"lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\" Make sure the\",\n \"\\\"\\\"\\\" ses = clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert ses[\\\"GMT_MODULE_CMD\\\"]\",\n \"Dataset from matrices data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10,\",\n \"and spaces are valid file # names. Use a mock\",\n \"->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j,\",\n \"for an empty dictionary assert ses.info for key in ses.info:\",\n \"clib.Session() as _lib: gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session, func,\",\n \"failing to create a session. \\\"\\\"\\\" ses = clib.Session() with\",\n \"all of the # properties. with clib.Session() as lib: assert\",\n \"lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def\",\n \") # Dataset from matrices data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\",\",\n \"transforming a slice of a larger array to virtual file\",\n \"only fails with errors). \\\"\\\"\\\" if mock_func is None: def\",\n \"return codes. \\\"\\\"\\\" vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None,\",\n \"with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer is\",\n \"== b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\" else: value.value = b\\\"bla\\\" return\",\n \"data raises an exception for non-zero return codes. \\\"\\\"\\\" #\",\n \"for col in data.T] ) expected = \\\"{}\\\\n\\\".format(bounds) assert output\",\n \"# Use in a different session to avoid any memory\",\n \"250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \\\"\\\"\\\" Check\",\n \"{}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass\",\n \"mock(session, func, returns=None, mock_func=None): \\\"\\\"\\\" Mock a GMT C API\",\n \"status check when entering the context. # If the exception\",\n \"for dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype),\",\n \"\\\"\\\"\\\" value.value = b\\\"bla\\\" return 0 ses = clib.Session() ses.create(\\\"test-session\\\")\",\n \"Check for an empty dictionary assert ses.info for key in\",\n \") expected = \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert\",\n \"function that always returns a given value. \\\"\\\"\\\" return returns\",\n \"disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\" Check that an exception is raised\",\n \"was captured. \\\"\\\"\\\" with clib.Session() as lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\")\",\n \"\\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split() size\",\n \"with clib.Session() as lib: # Dataset from vectors data_vector =\",\n \"4) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput):\",\n \"gives reasonable results. \\\"\\\"\\\" with clib.Session() as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\")\",\n \"pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\" Fail to destroy session when\",\n \"as lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError as error: assert\",\n \"\\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape = (7, 5)\",\n \"sure it doesn't fail badly. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile:\",\n \"clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with clib.Session() as lib:\",\n \"GMT API function that always returns a given value. \\\"\\\"\\\"\",\n \"clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as\",\n \"= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,\",\n \"outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for\",\n \"import numpy.testing as npt import pandas as pd import pytest\",\n \"family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0,\",\n \"parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def\",\n \"\\\"\\\"\\\" size = 13 x = list(range(0, size, 1)) y\",\n \"\\\"\\\"\\\" Check that it fails for variable increments. \\\"\\\"\\\" data\",\n \"as npt import pandas as pd import pytest import xarray\",\n \"lib: wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it\",\n \"pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\" Fails when given bad\",\n \"won't get to the closing of the # virtual file.\",\n \"with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, z) as vfile:\",\n \"# Add the dataset to a virtual file and pass\",\n \"* 2, 1, dtype=np.int32) strings1 = np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\",\",\n \"for dtype in dtypes: x = np.arange(size, dtype=dtype) y =\",\n \"shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_vectors(*data.T) as vfile:\",\n \"functions fail by producing a NULL pointer as output or\",\n \"not given valid modifiers but is using them anyway. #\",\n \"argument (separated by |) correctly. \\\"\\\"\\\" lib = clib.Session() test_cases\",\n \"from the current figure, not the last figure. fig1 =\",\n \"lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \\\"\\\"\\\" Run the\",\n \"for transforming vectors to virtual file dataset. \\\"\\\"\\\" dtypes =\",\n \"are called without errors. \\\"\\\"\\\" # Create two session and\",\n \"session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is not None assert session2.session_pointer != session1.session_pointer\",\n \"an old version. \\\"\\\"\\\" if name == b\\\"API_VERSION\\\": value.value =\",\n \"= \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col in data.T] ) expected\",\n \"the value buffer. \\\"\\\"\\\" value.value = b\\\"bla\\\" return 0 ses\",\n \"memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\",\",\n \"data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size * 2,\",\n \"\\\"\\\"\\\" Fail to destroy session when given bad input. \\\"\\\"\\\"\",\n \"dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()])\",\n \"desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1]\",\n \"\\\"{} -C ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join(\",\n \"np import numpy.testing as npt import pandas as pd import\",\n \"clib.Session() as lib: lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\" Extract region should\",\n \"lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\" Fails when\",\n \"= 3 data = full_data[:rows, :cols] with clib.Session() as lib:\",\n \"output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test\",\n \"* 2, 1, dtype=dtype) z = np.arange(size * 2, size\",\n \"sure they are not pointing to the same memory session1\",\n \"# Dataset from matrices data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"code either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing an invalid direction\",\n \"file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32\",\n \"= lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1, 0], #\",\n \"getting all of the # properties. with clib.Session() as lib:\",\n \"0.1412 0.9338\\\" def test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for invalid module arguments.\",\n \"# But this shouldn't. with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None\",\n \"f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h, i, j, k in zip(x, y,\",\n \"Fails when given bad input. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"as pd import pytest import xarray as xr from packaging.version\",\n \"in zip(x, y, strings1, strings2) ) assert output == expected\",\n \"get to this code either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing\",\n \"the code. with clib.Session() as lib: with mock(lib, \\\"GMT_Write_Data\\\", returns=1):\",\n \"invalid names. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\")\",\n \"z=np.arange(size * 2, size * 3, 1, dtype=dtype), ) )\",\n \"has been plotted. \\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as\",\n \"num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix, region,\",\n \"\\\"\\\"\\\" Parsing a single family argument correctly. \\\"\\\"\\\" lib =\",\n \"Test that I can get correct constants from the C\",\n \"with lib.open_virtual_file(*vfargs): print(\\\"This should have failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test\",\n \"x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(),\",\n \"np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5,\",\n \"# Make a 3D regular grid data = np.ones((10, 12,\",\n \"Segmentation # Fault. Can't test this if by giving a\",\n \"mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ): with pytest.raises(GMTCLibError):\",\n \"= \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (data.x, data.y,\",\n \"of the # virtual file. with clib.Session() as lib, mock(lib,\",\n \"Test passing an invalid direction argument. \\\"\\\"\\\" with clib.Session() as\",\n \"with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile()\",\n \"\\\"\\\"\\\" with clib.Session() as lib: try: lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") except GMTCLibError\",\n \"data pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError): with\",\n \"1, 0], ) def test_create_data_grid_range(): \\\"\\\"\\\" Create a grid specifying\",\n \"def test_virtualfile_from_matrix(): \\\"\\\"\\\" Test transforming a matrix to virtual file\",\n \"= \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output ==\",\n \"x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]])\",\n \"shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to a\",\n \"def test_call_module(): \\\"\\\"\\\" Run a command to see if call_module\",\n \"outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\"\",\n \"\\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check for an empty dictionary assert ses.info\",\n \"\\\"\\\"\\\" Make sure get_default raises an exception for invalid names.\",\n \"the automation for transforming vectors to virtual file dataset. \\\"\\\"\\\"\",\n \"(\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0,\",\n \"int64 uint32 uint64\\\".split() shape = (10, 6) for dtype in\",\n \"a dataset using pandas Series. \\\"\\\"\\\" dtypes = \\\"float32 float64\",\n \"as _lib: gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session, func, returns=None,\",\n \"session. \\\"\\\"\\\" ses = clib.Session() with mock(ses, \\\"GMT_Create_Session\\\", returns=None): with\",\n \"bad input. \\\"\\\"\\\" lib = clib.Session() test_cases = [ \\\"SOME_random_STRING\\\",\",\n \"and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", ranges=[150.0, 250.0, -20.0, 20.0],\",\n \"= ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The invalid direction argument\",\n \"dim=[shape[1], shape[0], 1, 0], # columns, rows, layers, dtype )\",\n \"\\\"\\\"\\\" A mock GMT API function that always returns a\",\n \"import pandas as pd import pytest import xarray as xr\",\n \"f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\"\",\n \"before destroying the old one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def\",\n \"columns to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64\",\n \"import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions import\",\n \"5) for dtype in dtypes: data = np.arange(shape[0] * shape[1],\",\n \"pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with mock(lib, \\\"GMT_Create_Data\\\",\",\n \"destroy a session twice ses = clib.Session() for __ in\",\n \"0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing\",\n \"returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module(): \\\"\\\"\\\" Run a\",\n \"\\\"\\\"\\\" Test passing in two columns of string or object\",\n \"with mock(ses, \\\"GMT_Create_Session\\\", returns=None): with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should fail\",\n \"that dataarray_to_matrix returns correct output. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x\",\n \"* 3, 1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,\",\n \"matrix=data) # Add the dataset to a virtual file and\",\n \"= clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert ses[\\\"GMT_MODULE_CMD\\\"] != -99999\",\n \"= \\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape = (7,\",\n \"test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the function fails for arrays of different\",\n \"* shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset, matrix=data) # Add the dataset to\",\n \"strings2) ) assert output == expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test\",\n \"in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data(\",\n \"lib. \\\"\\\"\\\" ses = clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] != -99999 assert\",\n \"to see if call_module works. \\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\")\",\n \"figure and extract the region from it # Use in\",\n \"Parsing a single family argument correctly. \\\"\\\"\\\" lib = clib.Session()\",\n \"out_fname = \\\"test_call_module.txt\\\" with clib.Session() as lib: with GMTTempFile() as\",\n \"wesn1 = lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with\",\n \"'bla' in the value buffer. \\\"\\\"\\\" value.value = b\\\"bla\\\" return\",\n \"should have failed\\\") def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the automation for\",\n \"abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that it fails\",\n \"\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=VIAS ) # But this shouldn't. with pytest.raises(GMTInvalidInput):\",\n \"lib: with lib.virtualfile_from_matrix(data) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\",\",\n \"pylint: disable=unused-argument \\\"\\\"\\\" Return an old version. \\\"\\\"\\\" if name\",\n \"Needed because it's not easy to get some API functions\",\n \"os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\" with clib.Session() as lib: with\",\n \"memory problems. with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig1._name)) with\",\n \"name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Return an old version.\",\n \"clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1\",\n \"int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert Version(lib.get_default(\\\"API_VERSION\\\")) >= Version(\\\"6.2.0\\\") def test_get_default_fails(): \\\"\\\"\\\"\",\n \"outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (x,\",\n \"(7, 5) for dtype in dtypes: data = np.arange(shape[0] *\",\n \"value buffer. \\\"\\\"\\\" value.value = b\\\"bla\\\" return 0 ses =\",\n \"size * 2, 1, dtype=np.int32) strings = np.array([\\\"a\\\", \\\"bc\\\", \\\"defg\\\",\",\n \"y = np.arange(size, size * 2, 1, dtype=np.int32) strings =\",\n \"test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the automation for transforming vectors to virtual\",\n \"destroy session are called without errors. \\\"\\\"\\\" # Create two\",\n \"exception is raised when failing to create a session. \\\"\\\"\\\"\",\n \"desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check\",\n \"# pylint: disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\" Test that create and\",\n \"Version from pygmt import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix\",\n \"def test_virtualfile_from_vectors(): \\\"\\\"\\\" Test the automation for transforming vectors to\",\n \"= \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\" dataset = lib.create_data( family=family, geometry=geometry,\",\n \"with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError):\",\n \"open a file that # we won't close later. with\",\n \"test_create_session_fails(): \\\"\\\"\\\" Check that an exception is raised when failing\",\n \"matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region,\",\n \"outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j, k in zip(x,\",\n \"inc=[0.1, 0.2], ) def test_create_data_fails(): \\\"\\\"\\\" Check that create_data raises\",\n \"= np.ones((10, 12, 11), dtype=\\\"float32\\\") x = np.arange(11) y =\",\n \"!= \\\"5.4.3\\\" # Make sure the session is closed when\",\n \"shape[0], 1, 0], # columns, rows, layers, dtype ) data\",\n \"check when entering the context. # If the exception is\",\n \"def test_parse_constant_composite(): \\\"\\\"\\\" Parsing a composite constant argument (separated by\",\n \"\\\"@#\\\", \\\"$\\\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,\",\n \"GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True)\",\n \"functions to fail without inducing a Segmentation Fault (which is\",\n \"\\\"\\\"\\\" Check that an exception is raised when failing to\",\n \"= (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs) as vfile: with\",\n \"\\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) # Mock Open_VirtualFile to test the\",\n \"npt import pandas as pd import pytest import xarray as\",\n \"uint32 uint64\\\".split() shape = (5, 3) for dtype in dtypes:\",\n \"lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip()\",\n \"API function that always returns a given value. \\\"\\\"\\\" return\",\n \"when closing the virtual file # Mock the opening to\",\n \"ses.info[key] == \\\"bla\\\" ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure the\",\n \"clib.Session() as lib: with pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\\\"This should\",\n \"for h, i, j, k in zip(x, y, strings1, strings2)\",\n \"lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} -C\",\n \"correct constants from the C lib. \\\"\\\"\\\" ses = clib.Session()\",\n \"data.T] ) expected = \\\"{}\\\\n\\\".format(bounds) assert output == expected def\",\n \"\\\"\\\"\\\" Pass vectors to a dataset using pandas Series. \\\"\\\"\\\"\",\n \"np.arange(size * 2, size * 3, 1, dtype=dtype) with clib.Session()\",\n \"dataset = lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1, 0],\",\n \"size * 2, 1, dtype=np.int32) strings1 = np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\",\",\n \"returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None,\",\n \"\\\"{} -C ->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert\",\n \"with pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"info vfargs = (family, geometry, \\\"GMT_IN|GMT_IS_REFERENCE\\\", dataset) with lib.open_virtual_file(*vfargs) as\",\n \"\\\"defg\\\", \\\"hijklmn\\\", \\\"opqrst\\\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,\",\n \"npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\"\",\n \"lib = clib.Session() for family in FAMILIES: parsed = lib._parse_constant(family,\",\n \"that exceptions are raised when API functions fail by producing\",\n \"5 x = np.arange(size, dtype=np.int32) y = np.arange(size, size *\",\n \"xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid)\",\n \"Dataset from vectors data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10,\",\n \"xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default():\",\n \"float64 int32 int64 uint32 uint64\\\".split() size = 13 for dtype\",\n \"[ERROR]: Cannot find file bogus-data.bla\\\" in str(error) def test_method_no_session(): \\\"\\\"\\\"\",\n \"clib.Session() as lib: assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\"))\",\n \"test_call_module(): \\\"\\\"\\\" Run a command to see if call_module works.\",\n \"size = 13 x = list(range(0, size, 1)) y =\",\n \"dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1]\",\n \"outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output = outfile.read(keep_tabs=True) expected = \\\"\\\".join(\",\n \"rows = 5 cols = 3 data = full_data[:rows, :cols]\",\n \"lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region()\",\n \"Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES,\",\n \"= np.arange(11) y = np.arange(12) z = np.arange(10) grid =\",\n \"C API function fail without causing a Segmentation # Fault.\",\n \"ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) # Passing in\",\n \"-C ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(),\",\n \"# pylint: disable=pointless-statement def test_parse_constant_single(): \\\"\\\"\\\" Parsing a single family\",\n \"x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\" Make sure get_default\",\n \"mock_func=None): \\\"\\\"\\\" Mock a GMT C API function to make\",\n \"raises an exception for non- zero return codes. \\\"\\\"\\\" vfargs\",\n \"using pandas Series. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64\",\n \"giving a bad file name because if # output=='', GMT\",\n \"pylint: disable=protected-access \\\"\\\"\\\" Test the wrappers for the C API.\",\n \"flipped x/y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0,\",\n \"test_create_data_grid_dim(): \\\"\\\"\\\" Create a grid ignoring range and inc. \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" Mock a GMT C API function to make it\",\n \"is not None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() #\",\n \"session is closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError):\",\n \"3, 1, dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x, y,\",\n \"( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile\",\n \"= np.arange(size, dtype=dtype) y = np.arange(size, size * 2, 1,\",\n \"output == \\\"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\\\" def test_call_module_invalid_arguments():\",\n \") with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as\",\n \"using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0],\",\n \"desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check\",\n \"Create and destroy a session twice ses = clib.Session() for\",\n \"dtypes: data = pd.DataFrame( data=dict( x=np.arange(size, dtype=dtype), y=np.arange(size, size *\",\n \"lib = clib.Session() test_cases = [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\",\",\n \"\\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype) with clib.Session() as lib: with lib.virtualfile_from_vectors(x,\",\n \"bounds = \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (data.x,\",\n \"= outfile.read(keep_tabs=True) expected = \\\"\\\".join(f\\\"{i}\\\\t{j}\\\\t{k}\\\\n\\\" for i, j, k in\",\n \"-150.0, 15.0, 25.0])) def test_write_data_fails(): \\\"\\\"\\\" Check that write data\",\n \"y), (\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data))\",\n \"lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): \\\"\\\"\\\" Parsing\",\n \"if dataarray_to_matrix returns correct output with flipped x. \\\"\\\"\\\" data\",\n \"outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds =\",\n \"passing an invalid direction argument. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"\\\"\\\"\\\" Check that opening and closing virtual files raises an\",\n \"in two columns of string or object dtype into virtual\",\n \"Figure() region1 = np.array([0, 10, -20, -10]) fig1.coast(region=region1, projection=\\\"M6i\\\", frame=True,\",\n \"region from it # Use in a different session to\",\n \"= xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def\",\n \"xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid)\",\n \"the C lib. \\\"\\\"\\\" ses = clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"] !=\",\n \"data_vector != data_matrix def test_create_data_grid_dim(): \\\"\\\"\\\" Create a grid ignoring\",\n \"also fail if not given valid modifiers but is using\",\n \"strings)) assert output == expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_two_string_or_object_columns(dtype):\",\n \"status codes. Needed because it's not easy to get some\",\n \"as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile: with GMTTempFile()\",\n \"dtype=\\\"float32\\\") x = np.arange(11) y = np.arange(12) z = np.arange(10)\",\n \"different session to avoid any memory problems. with clib.Session() as\",\n \"= \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(rows, bounds) assert output ==\",\n \"\\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\" Fails when given bad input. \\\"\\\"\\\"\",\n \"if there are no errors or segfaults from getting all\",\n \"errors or segfaults from getting all of the # properties.\",\n \"virtual file. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=1): with\",\n \"session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create and destroy a\",\n \"non-zero return codes. \\\"\\\"\\\" # It's hard to make the\",\n \"= clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is not None assert session2.session_pointer\",\n \"= clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer #\",\n \"clib.Session() as lib: with mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\",\",\n \"context. # If the exception is raised, the code won't\",\n \"sure that it's # getting from the current figure, not\",\n \"size, 1)) y = tuple(range(size, size * 2, 1)) z\",\n \"with a Dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64\",\n \"pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import FAMILIES, VIAS from pygmt.exceptions\",\n \"sure the session is closed when the exception is raised.\",\n \"stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid = xr.DataArray(data,\",\n \"dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\" Check that it fails for variable\",\n \"if trying to create a session before destroying the old\",\n \"Now try it with the second one with clib.Session() as\",\n \"packaging.version import Version from pygmt import Figure, clib from pygmt.clib.conversion\",\n \"VIAS from pygmt.exceptions import ( GMTCLibError, GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, )\",\n \"get correct constants from the C lib. \\\"\\\"\\\" ses =\",\n \"\\\"\\\"\\\" lib = clib.Session() test_cases = ((family, via) for family\",\n \"to make sure that it's # getting from the current\",\n \"= np.linspace(start=4, stop=0, num=3) y = np.linspace(start=5, stop=9, num=3) grid\",\n \"3 data = full_data[:rows, :cols] with clib.Session() as lib: with\",\n \"= (7, 5) for dtype in dtypes: data = np.arange(shape[0]\",\n \"\\\"GMT_IN|GMT_IS_REFERENCE\\\", None, ) # Mock Open_VirtualFile to test the status\",\n \"def test_destroy_session_fails(): \\\"\\\"\\\" Fail to destroy session when given bad\",\n \"data.y, data.z) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{}\",\n \"dtype=dtype) z = np.arange(size * 2, size * 3, 1,\",\n \"size * 2, 1, dtype=dtype), z=np.arange(size * 2, size *\",\n \"with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement def test_create_session_fails(): \\\"\\\"\\\" Check\",\n \"as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile: with\",\n \"assert lib.get_default(\\\"API_GRID_LAYOUT\\\") in [\\\"rows\\\", \\\"columns\\\"] assert int(lib.get_default(\\\"API_CORES\\\")) >= 1 assert\",\n \"in ses.info: assert ses.info[key] == \\\"bla\\\" ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\"\",\n \"ses.destroy() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy()\",\n \"Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as lib:\",\n \"mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name, argtypes=None, restype=None):\",\n \"in FAMILIES for via in VIAS) for family, via in\",\n \"as lib: vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The\",\n \"pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): print(\\\"Should not get to this code\\\") #\",\n \"parsed == expected def test_parse_constant_fails(): \\\"\\\"\\\" Check if the function\",\n \"(\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails(): \\\"\\\"\\\"\",\n \"xr from packaging.version import Version from pygmt import Figure, clib\",\n \"with flipped x/y. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4,\",\n \"not easy to get some API functions to fail without\",\n \"opening and closing virtual files raises an exception for non-\",\n \"\\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\", \\\"NOT_A_PROPER_FAMILY|GMT_VIA_MATRIX\\\", \\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case in test_cases:\",\n \"with lib.open_virtual_file(*vfargs): print(\\\"Should not get to this code\\\") # Test\",\n \"Mock a GMT C API function to make it always\",\n \"vectors to a dataset. \\\"\\\"\\\" size = 13 x =\",\n \"z = np.arange(10) grid = xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\", y),\",\n \"# If the exception is raised, the code won't get\",\n \"int64 uint32 uint64\\\".split() size = 13 for dtype in dtypes:\",\n \"pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass print(\\\"Shouldn't get to this code either\\\")\",\n \"when given bad input. \\\"\\\"\\\" with clib.Session() as lib: with\",\n \"test_call_module_invalid_arguments(): \\\"\\\"\\\" Fails for invalid module arguments. \\\"\\\"\\\" with clib.Session()\",\n \"y=np.arange(size, size * 2, 1, dtype=dtype), z=np.arange(size * 2, size\",\n \"test_destroy_session_fails(): \\\"\\\"\\\" Fail to destroy session when given bad input.\",\n \"as out_fname: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output\",\n \"to fail without inducing a Segmentation Fault (which is a\",\n \"= full_data[:rows, :cols] with clib.Session() as lib: with lib.virtualfile_from_matrix(data) as\",\n \"pylint: disable=unused-argument \\\"\\\"\\\" Put 'bla' in the value buffer. \\\"\\\"\\\"\",\n \"Grids from matrices using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10,\",\n \"with clib.Session() as lib: lib.call_module(\\\"figure\\\", \\\"{} -\\\".format(fig2._name)) with clib.Session() as\",\n \"version. \\\"\\\"\\\" if name == b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\" else:\",\n \"* 2, 1)) z = range(size * 2, size *\",\n \"ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check for an empty\",\n \"multiple figures existing at the same time. \\\"\\\"\\\" # Make\",\n \"for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) #\",\n \"test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES, valid_modifiers=VIAS) # Should also fail\",\n \"clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint:\",\n \"Mock Open_VirtualFile to test the status check when entering the\",\n \"ses.destroy() def test_fails_for_wrong_version(): \\\"\\\"\\\" Make sure the clib.Session raises an\",\n \"x = np.arange(5) y = np.arange(6) with clib.Session() as lib:\",\n \"is None: def mock_api_function(*args): # pylint: disable=unused-argument \\\"\\\"\\\" A mock\",\n \"names. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def\",\n \"that it's # getting from the current figure, not the\",\n \"dtype ) # Dataset from matrices data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\",\",\n \"for invalid module arguments. \\\"\\\"\\\" with clib.Session() as lib: with\",\n \"fails if nothing has been plotted. \\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError):\",\n \"0], ) def test_virtual_file(): \\\"\\\"\\\" Test passing in data via\",\n \"= b\\\"bla\\\" return 0 ses = clib.Session() ses.create(\\\"test-session\\\") with mock(ses,\",\n \"Parsing a composite constant argument (separated by |) correctly. \\\"\\\"\\\"\",\n \"= clib.Session() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check for\",\n \"same time. \\\"\\\"\\\" # Make two figures before calling extract_region\",\n \"lib[family] + lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed\",\n \"GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), \\\"data\\\")\",\n \"test_create_data_fails(): \\\"\\\"\\\" Check that create_data raises exceptions for invalid input\",\n \"an exception for non- zero return codes. \\\"\\\"\\\" vfargs =\",\n \"arrays of different sizes. \\\"\\\"\\\" x = np.arange(5) y =\",\n \"10, 2, 0], ) def test_virtual_file(): \\\"\\\"\\\" Test passing in\",\n \"lib.create_data( family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1, 0], # columns,\",\n \"npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,\",\n \"is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement\",\n \"fails for variable increments. \\\"\\\"\\\" data = np.ones((4, 5), dtype=\\\"float64\\\")\",\n \"assert output == \\\"11.5309 61.7074 -2.9289 7.8648 0.1412 0.9338\\\" def\",\n \"input. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"meh\\\", \\\"\\\")\",\n \"float64 int32 int64 uint32 uint64\\\".split() shape = (5, 3) for\",\n \"been plotted. \\\"\\\"\\\" Figure() with pytest.raises(GMTCLibError): with clib.Session() as lib:\",\n \"+ lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed ==\",\n \"pytest.raises(GMTInvalidInput): with clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_GRID\\\", geometry=\\\"Not_a_valid_geometry\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[0,\",\n \"def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing an invalid direction argument. \\\"\\\"\\\"\",\n \"output = outfile.read(keep_tabs=True) expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h,\",\n \"frame=True) # Activate the first figure and extract the region\",\n \"given value. Used to test that exceptions are raised when\",\n \") expected = \\\"{}\\\\n\\\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size():\",\n \") ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x, data.y, data.z)\",\n \"dim=[10, 20, 1, 0], # columns, rows, layers, dtype )\",\n \"exception for non- zero return codes. \\\"\\\"\\\" vfargs = (\",\n \"producing a NULL pointer as output or non-zero status codes.\",\n \"15.0, 25.0])) def test_write_data_fails(): \\\"\\\"\\\" Check that write data raises\",\n \"def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing in one column with string\",\n \"is created. lib = clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with\",\n \"\\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape\",\n \"input. \\\"\\\"\\\" lib = clib.Session() test_cases = [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\",\",\n \"with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name():\",\n \") def test_create_data_dataset(): \\\"\\\"\\\" Run the function to make sure\",\n \"output == expected def test_virtualfile_from_vectors_transpose(): \\\"\\\"\\\" Test transforming matrix columns\",\n \"fail by producing a NULL pointer as output or non-zero\",\n \"zip(x, y, strings1, strings2) ) assert output == expected def\",\n \"0.2], ) # If the data pointer returned is None\",\n \"\\\"\\\"\\\" Test passing an invalid direction argument. \\\"\\\"\\\" with clib.Session()\",\n \"Test that create and destroy session are called without errors.\",\n \"\\\"{} -\\\".format(fig2._name)) with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2,\",\n \"Should fail if trying to create a session before destroying\",\n \"25.0])) def test_write_data_fails(): \\\"\\\"\\\" Check that write data raises an\",\n \"name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Put 'bla' in the\",\n \"dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split()\",\n \"either\\\") def test_virtual_file_bad_direction(): \\\"\\\"\\\" Test passing an invalid direction argument.\",\n \"# Dataset from vectors data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"\\\"\\\"\\\" Create a grid specifying range and inc instead of\",\n \"= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc,\",\n \"clib.Session() with pytest.raises(GMTCLibNoSessionError): lib.call_module(\\\"gmtdefaults\\\", \\\"\\\") with pytest.raises(GMTCLibNoSessionError): lib.session_pointer # pylint:\",\n \"npt.assert_allclose(wesn2, np.array([-165.0, -150.0, 15.0, 25.0])) def test_write_data_fails(): \\\"\\\"\\\" Check that\",\n \"in dtypes: x = np.arange(size, dtype=dtype) y = np.arange(size, size\",\n \"Test passing in one column with string or object dtype\",\n \"b\\\"5.4.3\\\" else: value.value = b\\\"bla\\\" return 0 lib = clib.Session()\",\n \"exceptions are raised when API functions fail by producing a\",\n \"return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func def mock_get_libgmt_func(name,\",\n \"not pointing to the same memory session1 = clib.Session() session1.create(name=\\\"test_session1\\\")\",\n \"the wrappers for the C API. \\\"\\\"\\\" import os from\",\n \"the function fails when given bad input. \\\"\\\"\\\" lib =\",\n \") def test_dataarray_to_matrix_works(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output.\",\n \"a different session to avoid any memory problems. with clib.Session()\",\n \"properties. with clib.Session() as lib: assert lib.info # Mock GMT_Get_Default\",\n \"region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flipud(data)) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),\",\n \"size = 10 for dtype in dtypes: x = np.arange(size,\",\n \"for > 2 dims. \\\"\\\"\\\" # Make a 3D regular\",\n \"argument. \\\"\\\"\\\" with clib.Session() as lib: vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\",\",\n \"assert output == expected def test_extract_region_fails(): \\\"\\\"\\\" Check that extract\",\n \"y), (\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data,\",\n \"a given value. Used to test that exceptions are raised\",\n \"ses.destroy() ses.destroy() def test_call_module(): \\\"\\\"\\\" Run a command to see\",\n \"won't close later. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0),\",\n \"pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should fail if trying to create a\",\n \"vfile: with GMTTempFile() as outfile: lib.call_module(\\\"convert\\\", f\\\"{vfile} ->{outfile.name}\\\") output =\",\n \"as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(vfile,\",\n \"desired=data) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]),\",\n \"opening to return 0 (success) so that we don't open\",\n \"Test passing in data via a virtual file with a\",\n \"as lib: lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\" Extract region should handle\",\n \"= np.arange(5) y = np.arange(6) with clib.Session() as lib: with\",\n \"setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem(): \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def\",\n \"is raised when failing to create a session. \\\"\\\"\\\" ses\",\n \"layers, dtype ) data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) lib.put_matrix(dataset,\",\n \"old. \\\"\\\"\\\" # Mock GMT_Get_Default to return an old version\",\n \"float64 int32 int64 uint32 uint64\\\".split() shape = (7, 5) for\",\n \"to avoid any memory problems. with clib.Session() as lib: lib.call_module(\\\"figure\\\",\",\n \"# pylint: disable=unused-argument \\\"\\\"\\\" Put 'bla' in the value buffer.\",\n \"key in ses.info: assert ses.info[key] == \\\"bla\\\" ses.destroy() def test_fails_for_wrong_version():\",\n \"npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1]\",\n \"list(range(0, size, 1)) y = tuple(range(size, size * 2, 1))\",\n \"lib: assert lib.info # Mock GMT_Get_Default to return always the\",\n \"with lib: assert lib.info[\\\"version\\\"] != \\\"5.4.3\\\" # Make sure the\",\n \"API functions fail by producing a NULL pointer as output\",\n \"range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer\",\n \"np.linspace(start=0, stop=4, num=3) y = np.linspace(start=9, stop=5, num=3) grid =\",\n \"projection=\\\"M6i\\\", frame=True, land=\\\"black\\\") fig2 = Figure() fig2.basemap(region=\\\"US.HI+r5\\\", projection=\\\"M6i\\\", frame=True) #\",\n \"is closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError): assert\",\n \"np.ones((4, 5), dtype=\\\"float64\\\") x = np.linspace(0, 1, 5) y =\",\n \"for family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES) assert parsed\",\n \"columns of string or object dtype into virtual file dataset.\",\n \"data.y, data.z) ] ) expected = \\\"<vector memory>: N =\",\n \"test_cases: composite = \\\"|\\\".join([family, via]) expected = lib[family] + lib[via]\",\n \"Add the dataset to a virtual file and pass it\",\n \"2 dims. \\\"\\\"\\\" # Make a 3D regular grid data\",\n \"= outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i in\",\n \"# Mock GMT_Get_Default to return always the same string def\",\n \"= lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails():\",\n \"(10, 6) for dtype in dtypes: full_data = np.arange(shape[0] *\",\n \"Extract region should handle multiple figures existing at the same\",\n \"code. with clib.Session() as lib: with mock(lib, \\\"GMT_Write_Data\\\", returns=1): with\",\n \"{}\\\\t{}\\\\n\\\".format(size, bounds) assert output == expected def test_extract_region_fails(): \\\"\\\"\\\" Check\",\n \"numpy.testing as npt import pandas as pd import pytest import\",\n \"\\\"\\\"\\\" with clib.Session() as lib: # Dataset from vectors data_vector\",\n \"pass it along to gmt info vfargs = (family, geometry,\",\n \"= {}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\"\",\n \"= \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (x, y, z)]\",\n \"with clib.Session() as lib: wesn2 = lib.extract_region() npt.assert_allclose(wesn2, np.array([-165.0, -150.0,\",\n \"bounds) assert output == expected def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors\",\n \"0 ses = clib.Session() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): #\",\n \"codes. \\\"\\\"\\\" vfargs = ( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IN|GMT_IS_REFERENCE\\\", None, )\",\n \"np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib: with lib.virtualfile_from_matrix(data)\",\n \"Run the function to make sure it doesn't fail badly.\",\n \"valid_modifiers=None ) def test_create_data_dataset(): \\\"\\\"\\\" Run the function to make\",\n \"= lib.extract_region() npt.assert_allclose(wesn1, region1) # Now try it with the\",\n \"lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\" Fails when given bad input.\",\n \"def test_call_module_invalid_name(): \\\"\\\"\\\" Fails when given bad input. \\\"\\\"\\\" with\",\n \"clib.Session() as lib: lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1,\",\n \"0.2], ) def test_create_data_fails(): \\\"\\\"\\\" Check that create_data raises exceptions\",\n \"raises an exception for non-zero return codes. \\\"\\\"\\\" # It's\",\n \"value. \\\"\\\"\\\" return returns mock_func = mock_api_function get_libgmt_func = session.get_libgmt_func\",\n \"\\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\" with clib.Session()\",\n \"when given bad input. \\\"\\\"\\\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError):\",\n \"dtypes = \\\"float32 float64 int32 int64 uint32 uint64\\\".split() size =\",\n \"dtype=dtype), z=np.arange(size * 2, size * 3, 1, dtype=dtype), )\",\n \"mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Put 'bla' in\",\n \"because it's not easy to get some API functions to\",\n \"a NULL pointer as output or non-zero status codes. Needed\",\n \"with pytest.raises(GMTCLibError): ses.create(\\\"test-session-name\\\") # Should fail if trying to create\",\n \"desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[x[1] - x[0], y[1] -\",\n \"in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) rows =\",\n \"( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_IS_GRID\\\", # The invalid direction argument 0,\",\n \"\\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i),\",\n \"function fails when given bad input. \\\"\\\"\\\" lib = clib.Session()\",\n \"== expected def test_virtual_file_fails(): \\\"\\\"\\\" Check that opening and closing\",\n \"int64 uint32 uint64\\\".split() shape = (7, 5) for dtype in\",\n \"geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2, 0], ) def test_virtual_file(): \\\"\\\"\\\"\",\n \"with mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10,\",\n \"as outfile: lib.call_module(\\\"info\\\", \\\"{} ->{}\\\".format(vfile, outfile.name)) output = outfile.read(keep_tabs=True) bounds\",\n \"mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[11, 10, 2,\",\n \"the old one. ses.create(\\\"test1\\\") with pytest.raises(GMTCLibError): ses.create(\\\"test2\\\") def test_destroy_session_fails(): \\\"\\\"\\\"\",\n \"y), (\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.fliplr(data))\",\n \"Check that dataarray_to_matrix returns correct output with flipped y. \\\"\\\"\\\"\",\n \"\\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col in data.T] ) expected =\",\n \"the status check when entering the context. # If the\",\n \"mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1, 0], # columns, rows, layers, dtype\",\n \"3D regular grid data = np.ones((10, 12, 11), dtype=\\\"float32\\\") x\",\n \"Fails for invalid module arguments. \\\"\\\"\\\" with clib.Session() as lib:\",\n \"with flipped x. \\\"\\\"\\\" data = np.diag(v=np.arange(3)) x = np.linspace(start=4,\",\n \"outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [ \\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in\",\n \"= outfile.read(keep_tabs=True) expected = \\\"\\\".join( f\\\"{h}\\\\t{i}\\\\t{j} {k}\\\\n\\\" for h, i,\",\n \"size * 3, 1, dtype=dtype) with clib.Session() as lib: with\",\n \"in a session. \\\"\\\"\\\" # Create an instance of Session\",\n \"output. \\\"\\\"\\\" # Passing in invalid mode with pytest.raises(GMTInvalidInput): with\",\n \"virtual files raises an exception for non- zero return codes.\",\n \"session to avoid any memory problems. with clib.Session() as lib:\",\n \"npt.assert_allclose(wesn1, region1) # Now try it with the second one\",\n \"see if call_module works. \\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname\",\n \"that dataarray_to_matrix returns correct output with flipped y. \\\"\\\"\\\" data\",\n \"test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output with flipped\",\n \"i.max()) for i in (x, y, z)] ) expected =\",\n \"projection=\\\"M6i\\\", frame=True) # Activate the first figure and extract the\",\n \"memory>: N = {}\\\\t{}\\\\n\\\".format(rows, bounds) assert output == expected def\",\n \"None assert session2.session_pointer != session1.session_pointer session1.destroy() session2.destroy() # Create and\",\n \"__ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer # pylint: disable=pointless-statement ses.create(\\\"session1\\\")\",\n \"y), (\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data)\",\n \"Check that an exception is raised when failing to create\",\n \"valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): \\\"\\\"\\\" Check\",\n \"to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32 float64 int32\",\n \"of the # properties. with clib.Session() as lib: assert lib.info\",\n \"-C ->{}\\\".format(data_fname, out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output\",\n \"so that we don't open a file that # we\",\n \"ses = clib.Session() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): # Check\",\n \"= clib.Session() test_cases = ((family, via) for family in FAMILIES\",\n \"col.max()) for col in data.T] ) expected = \\\"{}\\\\n\\\".format(bounds) assert\",\n \"test_write_data_fails(): \\\"\\\"\\\" Check that write data raises an exception for\",\n \"close later. with clib.Session() as lib, mock(lib, \\\"GMT_Open_VirtualFile\\\", returns=0), mock(\",\n \"= outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(col.min(), col.max()) for col in\",\n \") expected = \\\"<matrix memory>: N = {}\\\\t{}\\\\n\\\".format(rows, bounds) assert\",\n \"= \\\"float32 float64 int32 int64 uint32 uint64\\\".split() size = 13\",\n \"np.linspace(start=4, stop=0, num=3) y = np.linspace(start=9, stop=5, num=3) grid =\",\n \"== expected @pytest.mark.parametrize(\\\"dtype\\\", [str, object]) def test_virtualfile_from_vectors_one_string_or_object_column(dtype): \\\"\\\"\\\" Test passing\",\n \"as lib: # Grids from matrices using range and int\",\n \"API function fail without causing a Segmentation # Fault. Can't\",\n \"test that exceptions are raised when API functions fail by\",\n \"the data pointer returned is None (NULL pointer) with pytest.raises(GMTCLibError):\",\n \"from matrices using dim lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20,\",\n \"\\\"\\\"\\\" Test that create and destroy session are called without\",\n \"uint64\\\".split() shape = (7, 5) for dtype in dtypes: data\",\n \"uint64\\\".split() size = 13 for dtype in dtypes: data =\",\n \"ses = clib.Session() for __ in range(2): with pytest.raises(GMTCLibNoSessionError): ses.session_pointer\",\n \"clib.Session() as lib: with lib.virtualfile_from_vectors(x, y, strings1, strings2) as vfile:\",\n \"== lib[family] def test_parse_constant_composite(): \\\"\\\"\\\" Parsing a composite constant argument\",\n \"if the function fails when given bad input. \\\"\\\"\\\" lib\",\n \"with pytest.raises(GMTCLibError): lib.call_module(\\\"info\\\", \\\"bogus-data.bla\\\") def test_call_module_invalid_name(): \\\"\\\"\\\" Fails when given\",\n \"y[0])]) def test_dataarray_to_matrix_negative_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct output\",\n \"argtypes=None, restype=None): \\\"\\\"\\\" Return our mock function. \\\"\\\"\\\" if name\",\n \"os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == \\\"11.5309 61.7074 -2.9289\",\n \"as lib: with mock(lib, \\\"GMT_Create_Data\\\", returns=None): lib.create_data( family=\\\"GMT_IS_DATASET\\\", geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\",\",\n \"geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0],\",\n \"code\\\") # Test the status check when closing the virtual\",\n \"pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\" Make sure the clib.Session.info dict\",\n \"layers, dtype ) # Dataset from matrices data_matrix = lib.create_data(\",\n \"family=family, geometry=geometry, mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[shape[1], shape[0], 1, 0], # columns, rows,\",\n \"test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing in two columns of string or\",\n \"x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])])\",\n \"= np.logspace(2, 3, 4) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\",\",\n \"6) for dtype in dtypes: full_data = np.arange(shape[0] * shape[1],\",\n \"def mock_defaults(api, name, value): # pylint: disable=unused-argument \\\"\\\"\\\" Put 'bla'\",\n \"1, dtype=dtype) z = np.arange(size * 2, size * 3,\",\n \"Mock the opening to return 0 (success) so that we\",\n \"'info' failed with status code\\\" in str(error) assert \\\"gmtinfo [ERROR]:\",\n \"mode=\\\"Not_a_valid_mode\\\", dim=[0, 0, 1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1,\",\n \"a file that # we won't close later. with clib.Session()\",\n \"they are not pointing to the same memory session1 =\",\n \"GMTCLibNoSessionError, GMTInvalidInput, GMTVersionError, ) from pygmt.helpers import GMTTempFile TEST_DATA_DIR =\",\n \"closing virtual files raises an exception for non- zero return\",\n \"the GMT error message was captured. \\\"\\\"\\\" with clib.Session() as\",\n \"bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(i.min(), i.max()) for i in (x, y,\",\n \"# Grids from matrices using range and int lib.create_data( family=\\\"GMT_IS_GRID|GMT_VIA_MATRIX\\\",\",\n \"errors). \\\"\\\"\\\" if mock_func is None: def mock_api_function(*args): # pylint:\",\n \"x = np.arange(11) y = np.arange(12) z = np.arange(10) grid\",\n \"lib: lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\" Extract region should handle multiple\",\n \"- x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails(): \\\"\\\"\\\" Check that\",\n \"\\\"float32 float64 int32 int64 uint32 uint64\\\".split() shape = (10, 6)\",\n \"raised when API functions fail by producing a NULL pointer\",\n \"get_default works without crashing and gives reasonable results. \\\"\\\"\\\" with\",\n \"in (data.x, data.y, data.z) ] ) expected = \\\"<vector memory>:\",\n \"are valid file # names. Use a mock instead just\",\n \"outfile.name)) output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for\",\n \"with mock(ses, \\\"GMT_Destroy_Session\\\", returns=1): with pytest.raises(GMTCLibError): ses.destroy() ses.destroy() def test_call_module():\",\n \"\\\"\\\"\\\" Test that I can get correct constants from the\",\n \"raised when failing to create a session. \\\"\\\"\\\" ses =\",\n \"closed when the exception is raised. with pytest.raises(GMTCLibNoSessionError): assert lib.session_pointer\",\n \"returns correct output with flipped y. \\\"\\\"\\\" data = np.diag(v=np.arange(3))\",\n \"\\\"GMT_WRITE_SET\\\", [1] * 6, \\\"some-file-name\\\", None, ) def test_dataarray_to_matrix_works(): \\\"\\\"\\\"\",\n \"a matrix to virtual file dataset. \\\"\\\"\\\" dtypes = \\\"float32\",\n \"at the same time. \\\"\\\"\\\" # Make two figures before\",\n \"an exception is raised when failing to create a session.\",\n \"def test_virtualfile_from_vectors_two_string_or_object_columns(dtype): \\\"\\\"\\\" Test passing in two columns of string\",\n \"for invalid names. \\\"\\\"\\\" with clib.Session() as lib: with pytest.raises(GMTCLibError):\",\n \"for i in (x, y, z)] ) expected = \\\"<vector\",\n \"lib: with GMTTempFile() as out_fname: lib.call_module(\\\"info\\\", \\\"{} -C ->{}\\\".format(data_fname, out_fname.name))\",\n \"\\\"with\\\" so no session is created. lib = clib.Session() with\",\n \"return always the same string def mock_defaults(api, name, value): #\",\n \"= clib.Session() for family in FAMILIES: parsed = lib._parse_constant(family, valid=FAMILIES)\",\n \"\\\"NOT_A_PROPER_FAMILY|ALSO_INVALID\\\", ] for test_case in test_cases: with pytest.raises(GMTInvalidInput): lib._parse_constant(test_case, valid=FAMILIES,\",\n \"\\\"\\\"\\\" x = np.arange(5) y = np.arange(6) with clib.Session() as\",\n \"# If the data pointer returned is None (NULL pointer)\",\n \"\\\"\\\"\\\" lib = clib.Session() test_cases = [ \\\"SOME_random_STRING\\\", \\\"GMT_IS_DATASET|GMT_VIA_MATRIX|GMT_VIA_VECTOR\\\", \\\"GMT_IS_DATASET|NOT_A_PROPER_VIA\\\",\",\n \"virtual file and pass it along to gmt info vfargs\",\n \"sizes. \\\"\\\"\\\" x = np.arange(5) y = np.arange(6) with clib.Session()\",\n \"y = np.arange(6) with clib.Session() as lib: with pytest.raises(GMTInvalidInput): with\",\n \"- x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if\",\n \"np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"], dtype=dtype) with clib.Session() as lib:\",\n \"{}\\\\t{}\\\\n\\\".format(shape[0], bounds) assert output == expected def test_virtualfile_from_matrix_slice(): \\\"\\\"\\\" Test\",\n \"should handle multiple figures existing at the same time. \\\"\\\"\\\"\",\n \"with pytest.raises(GMTInvalidInput): lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \\\"\\\"\\\"\",\n \"in data.T] ) expected = \\\"{}\\\\n\\\".format(bounds) assert output == expected\",\n \"range and inc instead of dim. \\\"\\\"\\\" with clib.Session() as\",\n \"session1.destroy() session2.destroy() # Create and destroy a session twice ses\",\n \"call_module works. \\\"\\\"\\\" data_fname = os.path.join(TEST_DATA_DIR, \\\"points.txt\\\") out_fname = \\\"test_call_module.txt\\\"\",\n \"\\\"\\\"\\\" Pass array-like vectors to a dataset. \\\"\\\"\\\" size =\",\n \"y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] - y[0])]) def test_dataarray_to_matrix_dims_fails():\",\n \"function to make it always return a given value. Used\",\n \"for the C API. \\\"\\\"\\\" import os from contextlib import\",\n \"mock_func is None: def mock_api_function(*args): # pylint: disable=unused-argument \\\"\\\"\\\" A\",\n \"13 for dtype in dtypes: data = pd.DataFrame( data=dict( x=np.arange(size,\",\n \"# It's hard to make the C API function fail\",\n \"if mock_func is None: def mock_api_function(*args): # pylint: disable=unused-argument \\\"\\\"\\\"\",\n \"for dtype in dtypes: full_data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)\",\n \"and pass it along to gmt info vfargs = (family,\",\n \"closing of the # virtual file. with clib.Session() as lib,\",\n \"return 0 ses = clib.Session() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Get_Default\\\", mock_func=mock_defaults):\",\n \"clib.Session() session1.create(name=\\\"test_session1\\\") assert session1.session_pointer is not None session2 = clib.Session()\",\n \"it # Use in a different session to avoid any\",\n \"= lib._parse_constant(family, valid=FAMILIES) assert parsed == lib[family] def test_parse_constant_composite(): \\\"\\\"\\\"\",\n \"for non-zero return codes. \\\"\\\"\\\" # It's hard to make\",\n \"\\\"\\\"\\\" Check is the GMT error message was captured. \\\"\\\"\\\"\",\n \"old version. \\\"\\\"\\\" if name == b\\\"API_VERSION\\\": value.value = b\\\"5.4.3\\\"\",\n \"\\\"\\\"\\\" Create a grid ignoring range and inc. \\\"\\\"\\\" with\",\n \"badly. \\\"\\\"\\\" with clib.Session() as lib: # Dataset from vectors\",\n \"# Passing in invalid geometry with pytest.raises(GMTInvalidInput): with clib.Session() as\",\n \"None (NULL pointer) with pytest.raises(GMTCLibError): with clib.Session() as lib: with\",\n \"1, 0], ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) #\",\n \"exceptions for invalid input and output. \\\"\\\"\\\" # Passing in\",\n \"valid_modifiers=VIAS) # Should also fail if not given valid modifiers\",\n \"GMT will just write to stdout and spaces are valid\",\n \"lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1] * 6, \\\"some-file-name\\\", None, )\",\n \"output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i\",\n \"1, dtype=dtype), z=np.arange(size * 2, size * 3, 1, dtype=dtype),\",\n \"out_fname.name)) assert os.path.exists(out_fname.name) output = out_fname.read().strip() assert output == \\\"11.5309\",\n \"= \\\"{}\\\\n\\\".format(bounds) assert output == expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test\",\n \"\\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2 = np.array([\\\"pqrst\\\", \\\"uvwx\\\", \\\"yz!\\\", \\\"@#\\\", \\\"$\\\"],\",\n \"def test_create_session_fails(): \\\"\\\"\\\" Check that an exception is raised when\",\n \"function fails for arrays of different sizes. \\\"\\\"\\\" x =\",\n \"clib.Session() with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert\",\n \"API function to make it always return a given value.\",\n \"code\\\" in str(error) assert \\\"gmtinfo [ERROR]: Cannot find file bogus-data.bla\\\"\",\n \"def test_virtualfile_from_vectors_pandas(): \\\"\\\"\\\" Pass vectors to a dataset using pandas\",\n \"# Make two figures before calling extract_region to make sure\",\n \"it fails for variable increments. \\\"\\\"\\\" data = np.ones((4, 5),\",\n \"data = np.diag(v=np.arange(3)) x = np.linspace(start=4, stop=0, num=3) y =\",\n \"from getting all of the # properties. with clib.Session() as\",\n \"lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\" dataset = lib.create_data(\",\n \"return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session, \\\"get_libgmt_func\\\", mock_get_libgmt_func) yield\",\n \"to create a session. \\\"\\\"\\\" ses = clib.Session() with mock(ses,\",\n \"yield setattr(session, \\\"get_libgmt_func\\\", get_libgmt_func) def test_getitem(): \\\"\\\"\\\" Test that I\",\n \"Create an instance of Session without \\\"with\\\" so no session\",\n \"fail if trying to create a session before destroying the\",\n \"lib[via] parsed = lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected\",\n \"expected def test_extract_region_fails(): \\\"\\\"\\\" Check that extract region fails if\",\n \"\\\"data\\\") with clib.Session() as _lib: gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager def\",\n \"clib.Session() as lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\" geometry = \\\"GMT_IS_POINT\\\" dataset\",\n \"shape[1], dtype=dtype).reshape(shape) rows = 5 cols = 3 data =\",\n \"first figure and extract the region from it # Use\",\n \"ranges=[150.0, 250.0, -20.0, 20.0], inc=[0.1, 0.2], ) def test_create_data_fails(): \\\"\\\"\\\"\",\n \"mock(lib, \\\"GMT_Write_Data\\\", returns=1): with pytest.raises(GMTCLibError): lib.write_data( \\\"GMT_IS_VECTOR\\\", \\\"GMT_IS_POINT\\\", \\\"GMT_WRITE_SET\\\", [1]\",\n \"mock( lib, \\\"GMT_Close_VirtualFile\\\", returns=1 ): with pytest.raises(GMTCLibError): with lib.open_virtual_file(*vfargs): pass\",\n \"from contextlib import contextmanager import numpy as np import numpy.testing\",\n \"NULL pointer as output or non-zero status codes. Needed because\",\n \"10 for dtype in dtypes: x = np.arange(size, dtype=dtype) y\",\n \"with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\" Test\",\n \"is not None session2 = clib.Session() session2.create(name=\\\"test_session2\\\") assert session2.session_pointer is\",\n \"for invalid input and output. \\\"\\\"\\\" # Passing in invalid\",\n \"pytest.raises(GMTInvalidInput): with lib.virtualfile_from_vectors(x, y): print(\\\"This should have failed\\\") def test_virtualfile_from_matrix():\",\n \"grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix, region, inc\",\n \"z), (\\\"y\\\", y), (\\\"x\\\", x)]) with pytest.raises(GMTInvalidInput): dataarray_to_matrix(grid) def test_dataarray_to_matrix_inc_fails():\",\n \"# columns, rows, layers, dtype ) data = np.arange(shape[0] *\",\n \"passing in one column with string or object dtype into\",\n \"ses[\\\"GMT_MODULE_CMD\\\"] != -99999 assert ses[\\\"GMT_PAD_DEFAULT\\\"] != -99999 assert ses[\\\"GMT_DOUBLE\\\"] !=\",\n \"= outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col in\",\n \"fails when given bad input. \\\"\\\"\\\" lib = clib.Session() test_cases\",\n \"bad input. \\\"\\\"\\\" ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\")\",\n \"data_matrix = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", geometry=\\\"GMT_IS_POINT\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0],\",\n \"name == func: return mock_func return get_libgmt_func(name, argtypes, restype) setattr(session,\",\n \"data = np.ones((4, 5), dtype=\\\"float64\\\") x = np.linspace(0, 1, 5)\",\n \"-99999 with pytest.raises(GMTCLibError): ses[\\\"A_WHOLE_LOT_OF_JUNK\\\"] # pylint: disable=pointless-statement def test_create_destroy_session(): \\\"\\\"\\\"\",\n \"] ) expected = \\\"<vector memory>: N = {}\\\\t{}\\\\n\\\".format(size, bounds)\",\n \"gmt_version = Version(_lib.info[\\\"version\\\"]) @contextmanager def mock(session, func, returns=None, mock_func=None): \\\"\\\"\\\"\",\n \"(\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region,\",\n \"lib.extract_region() def test_extract_region_two_figures(): \\\"\\\"\\\" Extract region should handle multiple figures\",\n \"assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError): ses.session_pointer #\",\n \"dtype=np.int32) strings1 = np.array([\\\"a\\\", \\\"bc\\\", \\\"def\\\", \\\"ghij\\\", \\\"klmno\\\"], dtype=dtype) strings2\",\n \"with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\" Make sure the clib.Session.info\",\n \"Put 'bla' in the value buffer. \\\"\\\"\\\" value.value = b\\\"bla\\\"\",\n \"desired=[x[1] - x[0], y[1] - y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check\",\n \"ses = clib.Session() with pytest.raises(GMTCLibNoSessionError): ses.destroy() ses.create(\\\"test-session\\\") with mock(ses, \\\"GMT_Destroy_Session\\\",\",\n \"with clib.Session() as lib: assert lib.info # Mock GMT_Get_Default to\",\n \"import Figure, clib from pygmt.clib.conversion import dataarray_to_matrix from pygmt.clib.session import\",\n \"from the C lib. \\\"\\\"\\\" ses = clib.Session() assert ses[\\\"GMT_SESSION_EXTERNAL\\\"]\",\n \"because if # output=='', GMT will just write to stdout\",\n \"outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col in data.T]\",\n \"with mock(lib, \\\"GMT_Get_Default\\\", mock_func=mock_defaults): with pytest.raises(GMTVersionError): with lib: assert lib.info[\\\"version\\\"]\",\n \"import os from contextlib import contextmanager import numpy as np\",\n \"dataarray_to_matrix(grid) def test_get_default(): \\\"\\\"\\\" Make sure get_default works without crashing\",\n \"If the data pointer returned is None (NULL pointer) with\",\n \"dtype in dtypes: with clib.Session() as lib: family = \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\"\",\n \"test_parse_constant_composite(): \\\"\\\"\\\" Parsing a composite constant argument (separated by |)\",\n \"- y[0])]) def test_dataarray_to_matrix_negative_x_and_y_increment(): \\\"\\\"\\\" Check that dataarray_to_matrix returns correct\",\n \"data via a virtual file with a Dataset. \\\"\\\"\\\" dtypes\",\n \"geometry=\\\"GMT_IS_SURFACE\\\", mode=\\\"GMT_CONTAINER_ONLY\\\", dim=[10, 20, 1, 0], ) def test_create_data_grid_range(): \\\"\\\"\\\"\",\n \"0.2], ) # Passing in invalid geometry with pytest.raises(GMTInvalidInput): with\",\n \"= list(range(0, size, 1)) y = tuple(range(size, size * 2,\",\n \"disable=pointless-statement ses.create(\\\"session1\\\") assert ses.session_pointer is not None ses.destroy() with pytest.raises(GMTCLibNoSessionError):\",\n \"string or object dtype into virtual file dataset. \\\"\\\"\\\" size\",\n \"output = outfile.read(keep_tabs=True) bounds = \\\"\\\\t\\\".join( [\\\"{:.0f}\\\\t{:.0f}\\\".format(col.min(), col.max()) for col\",\n \"test_parse_constant_fails(): \\\"\\\"\\\" Check if the function fails when given bad\",\n \"x = np.arange(size, dtype=np.int32) y = np.arange(size, size * 2,\",\n \"desired=[x.min(), x.max(), y.min(), y.max()]) npt.assert_allclose(actual=inc, desired=[abs(x[1] - x[0]), abs(y[1] -\",\n \"- y[0]]) def test_dataarray_to_matrix_negative_x_increment(): \\\"\\\"\\\" Check if dataarray_to_matrix returns correct\",\n \"np.arange(12) z = np.arange(10) grid = xr.DataArray(data, coords=[(\\\"z\\\", z), (\\\"y\\\",\",\n \"stop=5, num=3) grid = xr.DataArray(data, coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix,\",\n \"output == expected def test_virtualfile_from_vectors_diff_size(): \\\"\\\"\\\" Test the function fails\",\n \"# Mock Open_VirtualFile to test the status check when entering\",\n \"as lib: # Dataset from vectors data_vector = lib.create_data( family=\\\"GMT_IS_DATASET|GMT_VIA_VECTOR\\\",\",\n \"with lib.virtualfile_from_vectors(*data.T) as vfile: with GMTTempFile() as outfile: lib.call_module(\\\"info\\\", \\\"{}\",\n \"= dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=np.flip(data, axis=(0, 1))) npt.assert_allclose(actual=region, desired=[x.min(), x.max(), y.min(),\",\n \"x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix, desired=data) npt.assert_allclose(actual=region, desired=[x.min(),\",\n \"assert output == expected def test_virtualfile_from_vectors_arraylike(): \\\"\\\"\\\" Pass array-like vectors\",\n \"figure. fig1 = Figure() region1 = np.array([0, 10, -20, -10])\",\n \"this part of the code. with clib.Session() as lib: with\",\n \"\\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\", valid=FAMILIES, valid_modifiers=None ) def test_create_data_dataset(): \\\"\\\"\\\" Run the function\",\n \"data = np.arange(shape[0] * shape[1], dtype=dtype).reshape(shape) with clib.Session() as lib:\",\n \"the function to make sure it doesn't fail badly. \\\"\\\"\\\"\",\n \"12, 11), dtype=\\\"float32\\\") x = np.arange(11) y = np.arange(12) z\",\n \"with clib.Session() as lib: with pytest.raises(GMTCLibError): lib.get_default(\\\"NOT_A_VALID_NAME\\\") def test_info_dict(): \\\"\\\"\\\"\",\n \"a grid specifying range and inc instead of dim. \\\"\\\"\\\"\",\n \"is using them anyway. # This should work... lib._parse_constant( \\\"GMT_IS_DATASET|GMT_VIA_MATRIX\\\",\",\n \"make the C API function fail without causing a Segmentation\",\n \"Open_VirtualFile to test the status check when entering the context.\",\n \"coords=[(\\\"y\\\", y), (\\\"x\\\", x)]) matrix, region, inc = dataarray_to_matrix(grid) npt.assert_allclose(actual=matrix,\",\n \"argument 0, ) with pytest.raises(GMTInvalidInput): with lib.open_virtual_file(*vfargs): print(\\\"This should have\",\n \"1, dtype=dtype), ) ) with clib.Session() as lib: with lib.virtualfile_from_vectors(data.x,\",\n \"handle multiple figures existing at the same time. \\\"\\\"\\\" #\",\n \"[\\\"<{:.0f}/{:.0f}>\\\".format(min(i), max(i)) for i in (x, y, z)] ) expected\"\n]","isConversational":false}}},{"rowIdx":393,"cells":{"ngram":{"kind":"list like","value":["use these features, so I don't think its worth including","We don't use these features, so I don't think its","can always change it later. class ExceptionInfo: @property def value(self)","# This class actually has more functions than are specified","\"\"\"Type stubs for _pytest._code.\"\"\" # This class actually has more","stubs for _pytest._code.\"\"\" # This class actually has more functions","specified here. # We don't use these features, so I","are specified here. # We don't use these features, so","actually has more functions than are specified here. # We","including # them in our type stub. We can always","don't think its worth including # them in our type","# We don't use these features, so I don't think","_pytest._code.\"\"\" # This class actually has more functions than are","This class actually has more functions than are specified here.","# them in our type stub. We can always change","here. # We don't use these features, so I don't","in our type stub. We can always change it later.","its worth including # them in our type stub. We","has more functions than are specified here. # We don't","type stub. We can always change it later. class ExceptionInfo:","We can always change it later. class ExceptionInfo: @property def","so I don't think its worth including # them in","more functions than are specified here. # We don't use","our type stub. We can always change it later. class","it later. class ExceptionInfo: @property def value(self) -> Exception: ...","don't use these features, so I don't think its worth","features, so I don't think its worth including # them","than are specified here. # We don't use these features,","worth including # them in our type stub. We can","class actually has more functions than are specified here. #","for _pytest._code.\"\"\" # This class actually has more functions than","think its worth including # them in our type stub.","always change it later. class ExceptionInfo: @property def value(self) ->","these features, so I don't think its worth including #","change it later. class ExceptionInfo: @property def value(self) -> Exception:","I don't think its worth including # them in our","them in our type stub. We can always change it","<reponame>questioneer-ltd/scrut \"\"\"Type stubs for _pytest._code.\"\"\" # This class actually has","functions than are specified here. # We don't use these","stub. We can always change it later. class ExceptionInfo: @property"],"string":"[\n \"use these features, so I don't think its worth including\",\n \"We don't use these features, so I don't think its\",\n \"can always change it later. class ExceptionInfo: @property def value(self)\",\n \"# This class actually has more functions than are specified\",\n \"\\\"\\\"\\\"Type stubs for _pytest._code.\\\"\\\"\\\" # This class actually has more\",\n \"stubs for _pytest._code.\\\"\\\"\\\" # This class actually has more functions\",\n \"specified here. # We don't use these features, so I\",\n \"are specified here. # We don't use these features, so\",\n \"actually has more functions than are specified here. # We\",\n \"including # them in our type stub. We can always\",\n \"don't think its worth including # them in our type\",\n \"# We don't use these features, so I don't think\",\n \"_pytest._code.\\\"\\\"\\\" # This class actually has more functions than are\",\n \"This class actually has more functions than are specified here.\",\n \"# them in our type stub. We can always change\",\n \"here. # We don't use these features, so I don't\",\n \"in our type stub. We can always change it later.\",\n \"its worth including # them in our type stub. We\",\n \"has more functions than are specified here. # We don't\",\n \"type stub. We can always change it later. class ExceptionInfo:\",\n \"We can always change it later. class ExceptionInfo: @property def\",\n \"so I don't think its worth including # them in\",\n \"more functions than are specified here. # We don't use\",\n \"our type stub. We can always change it later. class\",\n \"it later. class ExceptionInfo: @property def value(self) -> Exception: ...\",\n \"don't use these features, so I don't think its worth\",\n \"features, so I don't think its worth including # them\",\n \"than are specified here. # We don't use these features,\",\n \"worth including # them in our type stub. We can\",\n \"class actually has more functions than are specified here. #\",\n \"for _pytest._code.\\\"\\\"\\\" # This class actually has more functions than\",\n \"think its worth including # them in our type stub.\",\n \"always change it later. class ExceptionInfo: @property def value(self) ->\",\n \"these features, so I don't think its worth including #\",\n \"change it later. class ExceptionInfo: @property def value(self) -> Exception:\",\n \"I don't think its worth including # them in our\",\n \"them in our type stub. We can always change it\",\n \"<reponame>questioneer-ltd/scrut \\\"\\\"\\\"Type stubs for _pytest._code.\\\"\\\"\\\" # This class actually has\",\n \"functions than are specified here. # We don't use these\",\n \"stub. We can always change it later. class ExceptionInfo: @property\"\n]","isConversational":false}}},{"rowIdx":394,"cells":{"ngram":{"kind":"list like","value":["prime number as not prime return primes # returns the","by a particular prime number prime_factors.append(prime) # add the prime","0: # checks if the number is divisible by a","prime numbers while n != 1: # keeps diving the","prime number else: break # if the number is not","# loops over all multiples of the prime number starting","not prime return primes # returns the list containing prime","numbers while n != 1: # keeps diving the number","1): # loops over all the numbers to check for","number prime_factors.append(prime) # add the prime factor in the list","prime_factors.append(prime) # add the prime factor in the list if","True # marks the multiple of the prime number as","in the list if it divides the number n /=","# marks the multiple of the prime number as not","number then the inner loop breaks and the number is","number sieve[j] = True # marks the multiple of the","as not prime for i in range(2, n + 1):","numbers within the reange of the number sieve = [False]","1 if n % prime == 0: # checks if","n + 1, i): # loops over all multiples of","certain prime number until the number is 1 if n","% prime == 0: # checks if the number is","= [] # stores the prime factorization of the number","it is a prime number for j in range(i **","the next prime number until the number becomes 1 return","2, n + 1, i): # loops over all multiples","1: # keeps diving the number by a certain prime","divides the number n /= prime # reducing the number","# returns the list containing prime numbers def get_factorization(n): prime_factors","number is not a prime number primes.append(i) # adds a","+ 1) # stores boolean values indicating whether a number","# returns the list containing the prime factorization of the","# stores boolean values indicating whether a number is prime","prime number primes.append(i) # adds a number into list if","prime return primes # returns the list containing prime numbers","** 2, n + 1, i): # loops over all","1, i): # loops over all multiples of the prime","1 as not prime for i in range(2, n +","multiples of the prime number starting from the sqaure of","the number by a certain prime number until the number","the number is 1 if n % prime == 0:","the prime number starting from the sqaure of the prime","loops over all multiples of the prime number starting from","0 and 1 as not prime for i in range(2,","sieve = [False] * (n + 1) # stores boolean","+ 1): # loops over all the numbers to check","the prime number as not prime return primes # returns","primes.append(i) # adds a number into list if it is","def get_factorization(n): prime_factors = [] # stores the prime factorization","if the number is not divisible by the paricular prime","sieve[j] = True # marks the multiple of the prime","for prime in get_primes(n): # looping over all the prime","reange of the number sieve = [False] * (n +","# loops over all the numbers to check for prime","number if __name__ == \"__main__\": n = int(input(\"Enter a number:","list containing prime numbers def get_factorization(n): prime_factors = [] #","number starting from the sqaure of the prime number sieve[j]","# keeps diving the number by a certain prime number","is a prime number for j in range(i ** 2,","break # if the number is not divisible by the","all the numbers to check for prime numbers if sieve[i]:","the inner loop breaks and the number is further divided","n /= prime # reducing the number after dividing it","further divided by the next prime number until the number","number until the number is 1 if n % prime","prime == 0: # checks if the number is divisible","# checks if the number is divisible by a particular","of the number for prime in get_primes(n): # looping over","number is prime or not sieve[0] = sieve[1] = True","# reducing the number after dividing it by the prime","prime_factors = [] # stores the prime factorization of the","divisible by the paricular prime number then the inner loop","the number becomes 1 return prime_factors # returns the list","within the reange of the number sieve = [False] *","= sieve[1] = True # marking 0 and 1 as","to check for prime numbers if sieve[i]: # checks whether","a number is not prime continue # skips the loop","the prime factorization of the number if __name__ == \"__main__\":","[] # stores the prime numbers within the reange of","it by the prime number else: break # if the","is further divided by the next prime number until the","sieve[1] = True # marking 0 and 1 as not","loop if the number is not a prime number primes.append(i)","the sqaure of the prime number sieve[j] = True #","return primes # returns the list containing prime numbers def","a particular prime number prime_factors.append(prime) # add the prime factor","if the number is divisible by a particular prime number","factor in the list if it divides the number n","until the number becomes 1 return prime_factors # returns the","range(i ** 2, n + 1, i): # loops over","the numbers to check for prime numbers if sieve[i]: #","get_primes(n): primes = [] # stores the prime numbers within","a prime number primes.append(i) # adds a number into list","a number into list if it is a prime number","prime number sieve[j] = True # marks the multiple of","it divides the number n /= prime # reducing the","i in range(2, n + 1): # loops over all","and the number is further divided by the next prime","is divisible by a particular prime number prime_factors.append(prime) # add","[] # stores the prime factorization of the number for","over all the prime numbers while n != 1: #","factorization of the number if __name__ == \"__main__\": n =","(n + 1) # stores boolean values indicating whether a","particular prime number prime_factors.append(prime) # add the prime factor in","prime # reducing the number after dividing it by the","the prime numbers while n != 1: # keeps diving","sieve[0] = sieve[1] = True # marking 0 and 1","prime factor in the list if it divides the number","range(2, n + 1): # loops over all the numbers","by the next prime number until the number becomes 1","# add the prime factor in the list if it","boolean values indicating whether a number is prime or not","the prime numbers within the reange of the number sieve","prime or not sieve[0] = sieve[1] = True # marking","not a prime number primes.append(i) # adds a number into","__name__ == \"__main__\": n = int(input(\"Enter a number: \")) print(get_factorization(n))","number becomes 1 return prime_factors # returns the list containing","the number is not divisible by the paricular prime number","the multiple of the prime number as not prime return","is not divisible by the paricular prime number then the","number n /= prime # reducing the number after dividing","over all multiples of the prime number starting from the","add the prime factor in the list if it divides","number after dividing it by the prime number else: break","number is not prime continue # skips the loop if","+ 1, i): # loops over all multiples of the","paricular prime number then the inner loop breaks and the","number is 1 if n % prime == 0: #","the number is further divided by the next prime number","prime number prime_factors.append(prime) # add the prime factor in the","multiple of the prime number as not prime return primes","the list containing the prime factorization of the number if","j in range(i ** 2, n + 1, i): #","number until the number becomes 1 return prime_factors # returns","= [False] * (n + 1) # stores boolean values","= [] # stores the prime numbers within the reange","adds a number into list if it is a prime","by the prime number else: break # if the number","primes = [] # stores the prime numbers within the","if sieve[i]: # checks whether a number is not prime","all multiples of the prime number starting from the sqaure","n != 1: # keeps diving the number by a","next prime number until the number becomes 1 return prime_factors","= True # marking 0 and 1 as not prime","prime number for j in range(i ** 2, n +","the number after dividing it by the prime number else:","indicating whether a number is prime or not sieve[0] =","for j in range(i ** 2, n + 1, i):","divided by the next prime number until the number becomes","!= 1: # keeps diving the number by a certain","checks if the number is divisible by a particular prime","loop breaks and the number is further divided by the","get_factorization(n): prime_factors = [] # stores the prime factorization of","list if it divides the number n /= prime #","containing the prime factorization of the number if __name__ ==","if it is a prime number for j in range(i","in range(i ** 2, n + 1, i): # loops","number as not prime return primes # returns the list","prime continue # skips the loop if the number is","primes # returns the list containing prime numbers def get_factorization(n):","def get_primes(n): primes = [] # stores the prime numbers","number is further divided by the next prime number until","in get_primes(n): # looping over all the prime numbers while","number is divisible by a particular prime number prime_factors.append(prime) #","number for prime in get_primes(n): # looping over all the","prime factorization of the number for prime in get_primes(n): #","* (n + 1) # stores boolean values indicating whether","n % prime == 0: # checks if the number","over all the numbers to check for prime numbers if","stores the prime factorization of the number for prime in","# stores the prime factorization of the number for prime","number for j in range(i ** 2, n + 1,","a certain prime number until the number is 1 if","the list containing prime numbers def get_factorization(n): prime_factors = []","until the number is 1 if n % prime ==","values indicating whether a number is prime or not sieve[0]","not sieve[0] = sieve[1] = True # marking 0 and","the prime number else: break # if the number is","breaks and the number is further divided by the next","list containing the prime factorization of the number if __name__","numbers def get_factorization(n): prime_factors = [] # stores the prime","# checks whether a number is not prime continue #","the number n /= prime # reducing the number after","i): # loops over all multiples of the prime number","marks the multiple of the prime number as not prime","looping over all the prime numbers while n != 1:","prime number until the number becomes 1 return prime_factors #","= True # marks the multiple of the prime number","whether a number is prime or not sieve[0] = sieve[1]","prime number then the inner loop breaks and the number","checks whether a number is not prime continue # skips","into list if it is a prime number for j","prime number starting from the sqaure of the prime number","get_primes(n): # looping over all the prime numbers while n","if __name__ == \"__main__\": n = int(input(\"Enter a number: \"))","not prime for i in range(2, n + 1): #","# if the number is not divisible by the paricular","a number is prime or not sieve[0] = sieve[1] =","numbers if sieve[i]: # checks whether a number is not","stores boolean values indicating whether a number is prime or","of the prime number sieve[j] = True # marks the","prime in get_primes(n): # looping over all the prime numbers","the reange of the number sieve = [False] * (n","factorization of the number for prime in get_primes(n): # looping","# stores the prime numbers within the reange of the","# looping over all the prime numbers while n !=","of the number if __name__ == \"__main__\": n = int(input(\"Enter","reducing the number after dividing it by the prime number","return prime_factors # returns the list containing the prime factorization","while n != 1: # keeps diving the number by","all the prime numbers while n != 1: # keeps","number primes.append(i) # adds a number into list if it","numbers to check for prime numbers if sieve[i]: # checks","list if it is a prime number for j in","number else: break # if the number is not divisible","prime numbers if sieve[i]: # checks whether a number is","# skips the loop if the number is not a","sqaure of the prime number sieve[j] = True # marks","the number for prime in get_primes(n): # looping over all","sieve[i]: # checks whether a number is not prime continue","prime numbers within the reange of the number sieve =","the loop if the number is not a prime number","containing prime numbers def get_factorization(n): prime_factors = [] # stores","and 1 as not prime for i in range(2, n","diving the number by a certain prime number until the","== 0: # checks if the number is divisible by","else: break # if the number is not divisible by","[False] * (n + 1) # stores boolean values indicating","divisible by a particular prime number prime_factors.append(prime) # add the","from the sqaure of the prime number sieve[j] = True","returns the list containing the prime factorization of the number","by the paricular prime number then the inner loop breaks","# marking 0 and 1 as not prime for i","continue # skips the loop if the number is not","prime_factors # returns the list containing the prime factorization of","prime factorization of the number if __name__ == \"__main__\": n","True # marking 0 and 1 as not prime for","marking 0 and 1 as not prime for i in","n + 1): # loops over all the numbers to","/= prime # reducing the number after dividing it by","dividing it by the prime number else: break # if","is prime or not sieve[0] = sieve[1] = True #","not prime continue # skips the loop if the number","number sieve = [False] * (n + 1) # stores","as not prime return primes # returns the list containing","is 1 if n % prime == 0: # checks","by a certain prime number until the number is 1","the paricular prime number then the inner loop breaks and","# adds a number into list if it is a","if n % prime == 0: # checks if the","inner loop breaks and the number is further divided by","becomes 1 return prime_factors # returns the list containing the","for prime numbers if sieve[i]: # checks whether a number","or not sieve[0] = sieve[1] = True # marking 0","in range(2, n + 1): # loops over all the","if it divides the number n /= prime # reducing","the number is divisible by a particular prime number prime_factors.append(prime)","whether a number is not prime continue # skips the","is not a prime number primes.append(i) # adds a number","stores the prime numbers within the reange of the number","skips the loop if the number is not a prime","the number sieve = [False] * (n + 1) #","for i in range(2, n + 1): # loops over","then the inner loop breaks and the number is further","1 return prime_factors # returns the list containing the prime","the prime factorization of the number for prime in get_primes(n):","the list if it divides the number n /= prime","a prime number for j in range(i ** 2, n","starting from the sqaure of the prime number sieve[j] =","returns the list containing prime numbers def get_factorization(n): prime_factors =","check for prime numbers if sieve[i]: # checks whether a","of the prime number as not prime return primes #","number into list if it is a prime number for","the number if __name__ == \"__main__\": n = int(input(\"Enter a","the prime factor in the list if it divides the","prime numbers def get_factorization(n): prime_factors = [] # stores the","not divisible by the paricular prime number then the inner","of the number sieve = [False] * (n + 1)","1) # stores boolean values indicating whether a number is","prime for i in range(2, n + 1): # loops","loops over all the numbers to check for prime numbers","after dividing it by the prime number else: break #","number by a certain prime number until the number is","number is not divisible by the paricular prime number then","is not prime continue # skips the loop if the","keeps diving the number by a certain prime number until","of the prime number starting from the sqaure of the","prime number until the number is 1 if n %","if the number is not a prime number primes.append(i) #","the number is not a prime number primes.append(i) # adds","the prime number sieve[j] = True # marks the multiple"],"string":"[\n \"prime number as not prime return primes # returns the\",\n \"by a particular prime number prime_factors.append(prime) # add the prime\",\n \"0: # checks if the number is divisible by a\",\n \"prime numbers while n != 1: # keeps diving the\",\n \"prime number else: break # if the number is not\",\n \"# loops over all multiples of the prime number starting\",\n \"not prime return primes # returns the list containing prime\",\n \"numbers while n != 1: # keeps diving the number\",\n \"1): # loops over all the numbers to check for\",\n \"number prime_factors.append(prime) # add the prime factor in the list\",\n \"prime_factors.append(prime) # add the prime factor in the list if\",\n \"True # marks the multiple of the prime number as\",\n \"in the list if it divides the number n /=\",\n \"# marks the multiple of the prime number as not\",\n \"number then the inner loop breaks and the number is\",\n \"number sieve[j] = True # marks the multiple of the\",\n \"as not prime for i in range(2, n + 1):\",\n \"numbers within the reange of the number sieve = [False]\",\n \"1 if n % prime == 0: # checks if\",\n \"n + 1, i): # loops over all multiples of\",\n \"certain prime number until the number is 1 if n\",\n \"% prime == 0: # checks if the number is\",\n \"= [] # stores the prime factorization of the number\",\n \"it is a prime number for j in range(i **\",\n \"the next prime number until the number becomes 1 return\",\n \"2, n + 1, i): # loops over all multiples\",\n \"1: # keeps diving the number by a certain prime\",\n \"divides the number n /= prime # reducing the number\",\n \"# returns the list containing prime numbers def get_factorization(n): prime_factors\",\n \"number is not a prime number primes.append(i) # adds a\",\n \"+ 1) # stores boolean values indicating whether a number\",\n \"# returns the list containing the prime factorization of the\",\n \"# stores boolean values indicating whether a number is prime\",\n \"prime number primes.append(i) # adds a number into list if\",\n \"prime return primes # returns the list containing prime numbers\",\n \"** 2, n + 1, i): # loops over all\",\n \"1, i): # loops over all multiples of the prime\",\n \"1 as not prime for i in range(2, n +\",\n \"multiples of the prime number starting from the sqaure of\",\n \"the number by a certain prime number until the number\",\n \"the number is 1 if n % prime == 0:\",\n \"the prime number starting from the sqaure of the prime\",\n \"loops over all multiples of the prime number starting from\",\n \"0 and 1 as not prime for i in range(2,\",\n \"sieve = [False] * (n + 1) # stores boolean\",\n \"+ 1): # loops over all the numbers to check\",\n \"the prime number as not prime return primes # returns\",\n \"primes.append(i) # adds a number into list if it is\",\n \"def get_factorization(n): prime_factors = [] # stores the prime factorization\",\n \"if the number is not divisible by the paricular prime\",\n \"sieve[j] = True # marks the multiple of the prime\",\n \"for prime in get_primes(n): # looping over all the prime\",\n \"reange of the number sieve = [False] * (n +\",\n \"# loops over all the numbers to check for prime\",\n \"number if __name__ == \\\"__main__\\\": n = int(input(\\\"Enter a number:\",\n \"list containing prime numbers def get_factorization(n): prime_factors = [] #\",\n \"number starting from the sqaure of the prime number sieve[j]\",\n \"# keeps diving the number by a certain prime number\",\n \"is a prime number for j in range(i ** 2,\",\n \"break # if the number is not divisible by the\",\n \"all the numbers to check for prime numbers if sieve[i]:\",\n \"the inner loop breaks and the number is further divided\",\n \"n /= prime # reducing the number after dividing it\",\n \"further divided by the next prime number until the number\",\n \"number until the number is 1 if n % prime\",\n \"prime == 0: # checks if the number is divisible\",\n \"# checks if the number is divisible by a particular\",\n \"of the number for prime in get_primes(n): # looping over\",\n \"number is prime or not sieve[0] = sieve[1] = True\",\n \"# reducing the number after dividing it by the prime\",\n \"prime_factors = [] # stores the prime factorization of the\",\n \"divisible by the paricular prime number then the inner loop\",\n \"the number becomes 1 return prime_factors # returns the list\",\n \"within the reange of the number sieve = [False] *\",\n \"= sieve[1] = True # marking 0 and 1 as\",\n \"to check for prime numbers if sieve[i]: # checks whether\",\n \"a number is not prime continue # skips the loop\",\n \"the prime factorization of the number if __name__ == \\\"__main__\\\":\",\n \"[] # stores the prime numbers within the reange of\",\n \"it by the prime number else: break # if the\",\n \"is further divided by the next prime number until the\",\n \"sieve[1] = True # marking 0 and 1 as not\",\n \"loop if the number is not a prime number primes.append(i)\",\n \"the sqaure of the prime number sieve[j] = True #\",\n \"return primes # returns the list containing prime numbers def\",\n \"a particular prime number prime_factors.append(prime) # add the prime factor\",\n \"if the number is divisible by a particular prime number\",\n \"factor in the list if it divides the number n\",\n \"until the number becomes 1 return prime_factors # returns the\",\n \"range(i ** 2, n + 1, i): # loops over\",\n \"the numbers to check for prime numbers if sieve[i]: #\",\n \"get_primes(n): primes = [] # stores the prime numbers within\",\n \"a prime number primes.append(i) # adds a number into list\",\n \"a number into list if it is a prime number\",\n \"prime number sieve[j] = True # marks the multiple of\",\n \"it divides the number n /= prime # reducing the\",\n \"i in range(2, n + 1): # loops over all\",\n \"and the number is further divided by the next prime\",\n \"is divisible by a particular prime number prime_factors.append(prime) # add\",\n \"[] # stores the prime factorization of the number for\",\n \"over all the prime numbers while n != 1: #\",\n \"factorization of the number if __name__ == \\\"__main__\\\": n =\",\n \"(n + 1) # stores boolean values indicating whether a\",\n \"particular prime number prime_factors.append(prime) # add the prime factor in\",\n \"prime # reducing the number after dividing it by the\",\n \"the prime numbers while n != 1: # keeps diving\",\n \"sieve[0] = sieve[1] = True # marking 0 and 1\",\n \"prime factor in the list if it divides the number\",\n \"range(2, n + 1): # loops over all the numbers\",\n \"by the next prime number until the number becomes 1\",\n \"# add the prime factor in the list if it\",\n \"boolean values indicating whether a number is prime or not\",\n \"the prime numbers within the reange of the number sieve\",\n \"prime or not sieve[0] = sieve[1] = True # marking\",\n \"not a prime number primes.append(i) # adds a number into\",\n \"__name__ == \\\"__main__\\\": n = int(input(\\\"Enter a number: \\\")) print(get_factorization(n))\",\n \"number becomes 1 return prime_factors # returns the list containing\",\n \"the number is not divisible by the paricular prime number\",\n \"the multiple of the prime number as not prime return\",\n \"is not divisible by the paricular prime number then the\",\n \"number n /= prime # reducing the number after dividing\",\n \"over all multiples of the prime number starting from the\",\n \"add the prime factor in the list if it divides\",\n \"number after dividing it by the prime number else: break\",\n \"number is not prime continue # skips the loop if\",\n \"+ 1, i): # loops over all multiples of the\",\n \"paricular prime number then the inner loop breaks and the\",\n \"number is 1 if n % prime == 0: #\",\n \"the number is further divided by the next prime number\",\n \"prime number prime_factors.append(prime) # add the prime factor in the\",\n \"multiple of the prime number as not prime return primes\",\n \"the list containing the prime factorization of the number if\",\n \"j in range(i ** 2, n + 1, i): #\",\n \"number until the number becomes 1 return prime_factors # returns\",\n \"= [False] * (n + 1) # stores boolean values\",\n \"= [] # stores the prime numbers within the reange\",\n \"adds a number into list if it is a prime\",\n \"by the prime number else: break # if the number\",\n \"primes = [] # stores the prime numbers within the\",\n \"if sieve[i]: # checks whether a number is not prime\",\n \"all multiples of the prime number starting from the sqaure\",\n \"n != 1: # keeps diving the number by a\",\n \"next prime number until the number becomes 1 return prime_factors\",\n \"= True # marking 0 and 1 as not prime\",\n \"prime number for j in range(i ** 2, n +\",\n \"the number after dividing it by the prime number else:\",\n \"indicating whether a number is prime or not sieve[0] =\",\n \"for j in range(i ** 2, n + 1, i):\",\n \"divided by the next prime number until the number becomes\",\n \"!= 1: # keeps diving the number by a certain\",\n \"checks if the number is divisible by a particular prime\",\n \"loop breaks and the number is further divided by the\",\n \"get_factorization(n): prime_factors = [] # stores the prime factorization of\",\n \"list if it divides the number n /= prime #\",\n \"containing the prime factorization of the number if __name__ ==\",\n \"if it is a prime number for j in range(i\",\n \"in range(i ** 2, n + 1, i): # loops\",\n \"number as not prime return primes # returns the list\",\n \"prime continue # skips the loop if the number is\",\n \"primes # returns the list containing prime numbers def get_factorization(n):\",\n \"def get_primes(n): primes = [] # stores the prime numbers\",\n \"number is further divided by the next prime number until\",\n \"in get_primes(n): # looping over all the prime numbers while\",\n \"number is divisible by a particular prime number prime_factors.append(prime) #\",\n \"number for prime in get_primes(n): # looping over all the\",\n \"prime factorization of the number for prime in get_primes(n): #\",\n \"* (n + 1) # stores boolean values indicating whether\",\n \"n % prime == 0: # checks if the number\",\n \"over all the numbers to check for prime numbers if\",\n \"stores the prime factorization of the number for prime in\",\n \"# stores the prime factorization of the number for prime\",\n \"number for j in range(i ** 2, n + 1,\",\n \"a certain prime number until the number is 1 if\",\n \"the list containing prime numbers def get_factorization(n): prime_factors = []\",\n \"until the number is 1 if n % prime ==\",\n \"values indicating whether a number is prime or not sieve[0]\",\n \"not sieve[0] = sieve[1] = True # marking 0 and\",\n \"the prime number else: break # if the number is\",\n \"breaks and the number is further divided by the next\",\n \"list containing the prime factorization of the number if __name__\",\n \"numbers def get_factorization(n): prime_factors = [] # stores the prime\",\n \"# checks whether a number is not prime continue #\",\n \"the number n /= prime # reducing the number after\",\n \"i): # loops over all multiples of the prime number\",\n \"marks the multiple of the prime number as not prime\",\n \"looping over all the prime numbers while n != 1:\",\n \"prime number until the number becomes 1 return prime_factors #\",\n \"= True # marks the multiple of the prime number\",\n \"whether a number is prime or not sieve[0] = sieve[1]\",\n \"prime number then the inner loop breaks and the number\",\n \"checks whether a number is not prime continue # skips\",\n \"into list if it is a prime number for j\",\n \"prime number starting from the sqaure of the prime number\",\n \"get_primes(n): # looping over all the prime numbers while n\",\n \"if __name__ == \\\"__main__\\\": n = int(input(\\\"Enter a number: \\\"))\",\n \"not prime for i in range(2, n + 1): #\",\n \"# if the number is not divisible by the paricular\",\n \"a number is prime or not sieve[0] = sieve[1] =\",\n \"numbers if sieve[i]: # checks whether a number is not\",\n \"stores boolean values indicating whether a number is prime or\",\n \"of the prime number sieve[j] = True # marks the\",\n \"prime in get_primes(n): # looping over all the prime numbers\",\n \"the reange of the number sieve = [False] * (n\",\n \"factorization of the number for prime in get_primes(n): # looping\",\n \"# stores the prime numbers within the reange of the\",\n \"# looping over all the prime numbers while n !=\",\n \"of the number if __name__ == \\\"__main__\\\": n = int(input(\\\"Enter\",\n \"reducing the number after dividing it by the prime number\",\n \"return prime_factors # returns the list containing the prime factorization\",\n \"while n != 1: # keeps diving the number by\",\n \"all the prime numbers while n != 1: # keeps\",\n \"number primes.append(i) # adds a number into list if it\",\n \"numbers to check for prime numbers if sieve[i]: # checks\",\n \"list if it is a prime number for j in\",\n \"number else: break # if the number is not divisible\",\n \"prime numbers if sieve[i]: # checks whether a number is\",\n \"# skips the loop if the number is not a\",\n \"sqaure of the prime number sieve[j] = True # marks\",\n \"the number for prime in get_primes(n): # looping over all\",\n \"sieve[i]: # checks whether a number is not prime continue\",\n \"prime numbers within the reange of the number sieve =\",\n \"the loop if the number is not a prime number\",\n \"containing prime numbers def get_factorization(n): prime_factors = [] # stores\",\n \"and 1 as not prime for i in range(2, n\",\n \"diving the number by a certain prime number until the\",\n \"== 0: # checks if the number is divisible by\",\n \"else: break # if the number is not divisible by\",\n \"[False] * (n + 1) # stores boolean values indicating\",\n \"divisible by a particular prime number prime_factors.append(prime) # add the\",\n \"from the sqaure of the prime number sieve[j] = True\",\n \"returns the list containing the prime factorization of the number\",\n \"by the paricular prime number then the inner loop breaks\",\n \"# marking 0 and 1 as not prime for i\",\n \"continue # skips the loop if the number is not\",\n \"prime_factors # returns the list containing the prime factorization of\",\n \"prime factorization of the number if __name__ == \\\"__main__\\\": n\",\n \"True # marking 0 and 1 as not prime for\",\n \"marking 0 and 1 as not prime for i in\",\n \"n + 1): # loops over all the numbers to\",\n \"/= prime # reducing the number after dividing it by\",\n \"dividing it by the prime number else: break # if\",\n \"is prime or not sieve[0] = sieve[1] = True #\",\n \"not prime continue # skips the loop if the number\",\n \"number sieve = [False] * (n + 1) # stores\",\n \"as not prime return primes # returns the list containing\",\n \"is 1 if n % prime == 0: # checks\",\n \"by a certain prime number until the number is 1\",\n \"the paricular prime number then the inner loop breaks and\",\n \"# adds a number into list if it is a\",\n \"if n % prime == 0: # checks if the\",\n \"inner loop breaks and the number is further divided by\",\n \"becomes 1 return prime_factors # returns the list containing the\",\n \"for prime numbers if sieve[i]: # checks whether a number\",\n \"or not sieve[0] = sieve[1] = True # marking 0\",\n \"in range(2, n + 1): # loops over all the\",\n \"if it divides the number n /= prime # reducing\",\n \"the number is divisible by a particular prime number prime_factors.append(prime)\",\n \"whether a number is not prime continue # skips the\",\n \"is not a prime number primes.append(i) # adds a number\",\n \"stores the prime numbers within the reange of the number\",\n \"skips the loop if the number is not a prime\",\n \"the number sieve = [False] * (n + 1) #\",\n \"for i in range(2, n + 1): # loops over\",\n \"then the inner loop breaks and the number is further\",\n \"1 return prime_factors # returns the list containing the prime\",\n \"the prime factorization of the number for prime in get_primes(n):\",\n \"the list if it divides the number n /= prime\",\n \"a prime number for j in range(i ** 2, n\",\n \"starting from the sqaure of the prime number sieve[j] =\",\n \"returns the list containing prime numbers def get_factorization(n): prime_factors =\",\n \"check for prime numbers if sieve[i]: # checks whether a\",\n \"of the prime number as not prime return primes #\",\n \"number into list if it is a prime number for\",\n \"the number if __name__ == \\\"__main__\\\": n = int(input(\\\"Enter a\",\n \"the prime factor in the list if it divides the\",\n \"prime numbers def get_factorization(n): prime_factors = [] # stores the\",\n \"not divisible by the paricular prime number then the inner\",\n \"of the number sieve = [False] * (n + 1)\",\n \"1) # stores boolean values indicating whether a number is\",\n \"prime for i in range(2, n + 1): # loops\",\n \"loops over all the numbers to check for prime numbers\",\n \"after dividing it by the prime number else: break #\",\n \"number by a certain prime number until the number is\",\n \"number is not divisible by the paricular prime number then\",\n \"is not prime continue # skips the loop if the\",\n \"keeps diving the number by a certain prime number until\",\n \"of the prime number starting from the sqaure of the\",\n \"prime number until the number is 1 if n %\",\n \"if the number is not a prime number primes.append(i) #\",\n \"the number is not a prime number primes.append(i) # adds\",\n \"the prime number sieve[j] = True # marks the multiple\"\n]","isConversational":false}}},{"rowIdx":395,"cells":{"ngram":{"kind":"list like","value":["def _extended_gcd(self, a: int, b: int) -> tuple[int, int, int]:","self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0 else self._range","array is saved in ``_cache``. \"\"\" return np.arange(self.start, self.stop, self.step,","(attr, formatted_value) \"\"\" attrs = self._get_data_as_items() if self.name is not","ops.rdivmod, ]: return op(self._int64index, other) step: Callable | None =","# First non-empty index had only one element if rng.start","- 1 if no_steps == -1: return np.nan elif (meth","of bounds for axis 0 with size {len(self)}\" ) from","from pandas._libs.lib import no_default from pandas._typing import Dtype from pandas.compat.numpy","in the index. Attributes ---------- start stop step Methods -------","This is the default index type used by DataFrame and","+ (second.start - first.start) * first.step // gcd * s","rng_indexes]) result = Int64Index(values) return result.rename(name) step = rng.start -","@cache_readonly def _data(self) -> np.ndarray: \"\"\" An int array that","self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name =","self, sort: bool = False, na_sentinel: int | None =","fall back return super()._difference(other, sort=sort) if overlap.step != first.step: #","def __getitem__(self, key): \"\"\" Conserve RangeIndex type for scalar and","self._range.step < 0 or len(self) <= 1 def __contains__(self, key:","method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs =","\"\"\" Form the union of two Index objects and sorts","0: return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if","+ step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None):","= ( \"RangeIndex.{} is deprecated and will be \" \"removed","empty range index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int:","in non_empty_indexes: rng = obj._range if start is None: #","= max(len(first_val_str), len(last_val_str)) return header + [f\"{x:<{max_length}}\" for x in","**kwargs) -> bool: return 0 not in self._range def any(self,","otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes","check whether intervals intersect # deals with in- and decreasing","def _minmax(self, meth: str): no_steps = len(self) - 1 if","1, -1, -1, dtype=np.intp) if not ascending: result = result[::-1]","self, other try: # apply if we have an override","RangeIndex, return # as a Float64Index if we have float-like","ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return","Parameters ---------- other : Any op : callable that accepts","TypeError, ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index, other)","the effort. return super()._difference(other, sort=sort) if overlap[0] == first.start: #","bool = False, dtype: Dtype | None = None, names=None,","(`...`), numpy.newaxis (`None`) \" \"and integer or boolean \" \"arrays","if name is no_default else name if values.dtype.kind == \"f\":","isinstance(other, RangeIndex) and self._range == other._range: # Both are immutable","method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method: str |","perform the binary op \"\"\" if isinstance(other, ABCTimedeltaIndex): # Defer","end_r = max(end_s, end_o) if step_o == step_s: if (","25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2, ) return self.stop @property","base pandas Index type. Int64Index : Index of int64 data.","abs(self.step) * no_steps def _extended_gcd(self, a: int, b: int) ->","have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if","other.step < 0 else other._range # check whether intervals intersect","if len(overlap) == 0: return self.rename(name=res_name) if len(overlap) == len(self):","is created only when needed. The constructed array is saved","def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def","return result @doc(Int64Index.copy) def copy( self, name: Hashable = None,","other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right","other stop = start + len(self) * step new_range =","return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range, name=None,","target_array - start valid = (locs % step == 0)","**kwargs, ) def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def","Parameters ---------- start : int (default: 0), range, or other","res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if self.step <","_union(self, other: Index, sort): \"\"\" Form the union of two","returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union","if possible Parameters ---------- other : Index or array-like sort","for x in rng_indexes]) result = Int64Index(values) return result.rename(name) step","@property def stop(self) -> int: \"\"\" The value of the","None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key)","first = self._range[::-1] if self.step < 0 else self._range overlap","right = other.difference(self) result = left.union(right) if result_name is not","Methods ------- from_range See Also -------- Index : The base","values, name: Hashable = no_default): name = self.name if name","< 0): new_index = new_index[::-1] if sort is None: new_index","FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def _minmax(self,","return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if not","extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right = self, other","import getsizeof from typing import ( TYPE_CHECKING, Any, Callable, Hashable,","import Dtype from pandas.compat.numpy import function as nv from pandas.util._decorators","< stop) locs[~valid] = -1 locs[valid] = locs[valid] / step","# Int64Index return super()._intersection(other, sort=sort) if not len(self) or not","(start_s + step_o >= start_o) and (end_s - step_o <=","warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2, ) return self.start @property def","return self.start return self.start + self.step * no_steps def min(self,","range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first","integer range. RangeIndex is a memory-saving special case of Int64Index","- end_o) <= step_s / 2) ): return type(self)(start_r, end_r","is a RangeIndex we may have more efficient options other","= cast(List[RangeIndex], indexes) start = step = next_ = None","\"\"\" Parameters ---------- other : Any op : callable that","this was not supplied). .. deprecated:: 0.25.0 Use ``start`` instead.","self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self, other, result_name:","\"\"\" return self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64)","system-level memory consumption Returns ------- bytes used Notes ----- Memory","if we have float-like descriptors if not all(is_integer(x) for x","- start_s) % step_s == 0 and (start_o + step_s","bool = True, *args, **kwargs) -> int: \"\"\"The minimum value","or not rstep: raise ValueError else: rstep = left.step with","deep: bool = False, dtype: Dtype | None = None,","RangeIndex) for x in indexes): return super()._concat(indexes, name) elif len(indexes)","np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64, # so","def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d),","\"parameter dtype is deprecated and will be removed in a","Hashable, List, cast, ) import warnings import numpy as np","def _intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex): #","if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method","return old_r, old_s, old_t def _union(self, other: Index, sort): \"\"\"","\"\"\" rng = self._range return [(\"start\", rng.start), (\"stop\", rng.stop), (\"step\",","not None: attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): #","return Int64Index @cache_readonly def _data(self) -> np.ndarray: \"\"\" An int","None def _format_with_header(self, header: list[str], na_rep: str = \"NaN\") ->","quotient * r old_s, s = s, old_s - quotient","step is not None: next_ = rng[-1] + step if","Immutable Index implementing a monotonic integer range. RangeIndex is a","@property def inferred_type(self) -> str: return \"integer\" # -------------------------------------------------------------------- #","second.step // gcd new_range = range(tmp_start, int_high, new_step) new_index =","-> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \"\"\"","len(self) * step new_range = range(start, stop, step or 1)","# calculate parameters for the RangeIndex describing the # intersection","other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self,","# In this case return an empty range index. return","KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index,","self._cached_int64index res._name = self._name return res def _get_data_as_items(self): \"\"\" return","IndexError( f\"index {key} is out of bounds for axis 0","other: object) -> bool: \"\"\" Determines if two Index objects","dtype: warnings.warn( \"parameter dtype is deprecated and will be removed","(meth == \"max\" and self.step < 0): return self.start return","IndexError as err: raise IndexError( f\"index {key} is out of","cast, ) import warnings import numpy as np from pandas._libs","data. \"\"\" _typ = \"rangeindex\" _engine_type = libindex.Int64Engine _dtype_validation_metadata =","(step_s % 2 == 0) and (abs(start_s - start_o) <=","uniques = self if sort and self.step < 0: codes","(``1`` if this was not supplied). \"\"\" # GH 25710","in a future \" \"version. Use the astype method instead.\",","Overriding parent method for the case of all RangeIndex instances.","NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True","// gcd * s new_step = first.step * second.step //","def _start(self) -> int: \"\"\" The value of the `start`","& (target_array < stop) locs[~valid] = -1 locs[valid] = locs[valid]","new_index def symmetric_difference(self, other, result_name: Hashable = None, sort=None): if","_dtype_validation_metadata = (is_signed_integer_dtype, \"signed integer\") _can_hold_na = False _range: range","None else 0 if stop is None: start, stop =","list[str]: if not len(self._range): return header first_val_str = str(self._range[0]) last_val_str","range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust index to","None = None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0]","not len(self) or not len(other): return self._simple_new(_empty_range) first = self._range[::-1]","stop value from \"next\" or alternatively # from the last","had 0 length, i.e. were empty. # In this case","self.start, self.stop, self.step else: # GH 28678: work on reversed","type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def copy(","------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \"\"\" ascending = kwargs.pop(\"ascending\",","if step_o == step_s: if ( (start_s - start_o) %","value from \"next\" or alternatively # from the last non-empty","= {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self)","pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range","only when needed. The constructed array is saved in ``_cache``.","are formatting thru the attributes return None def _format_with_header(self, header:","step sizes, could use # cheaper alternative gcd, s, _","all RangeIndex instances. When all members of \"indexes\" are of","for x in [rstart, rstop, rstep]): result = result.astype(\"float64\") return","s new_step = first.step * second.step // gcd new_range =","0.25.0 Returns ------- union : Index \"\"\" if isinstance(other, RangeIndex)","next_ return RangeIndex(start, stop, step).rename(name) # Here all \"indexes\" had","IndexError( \"only integers, slices (`:`), \" \"ellipsis (`...`), numpy.newaxis (`None`)","self._minmax(\"min\") def max(self, axis=None, skipna: bool = True, *args, **kwargs)","and will be \" \"removed in a future version. Use","data: range, name=None, dtype: Dtype | None = None )","usage does not include memory consumed by elements that are","*args, **kwargs) -> int: \"\"\"The maximum value of the RangeIndex\"\"\"","sort is None: start_s, step_s = self.start, self.step end_s =","is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or len(self) <=","codes = np.arange(len(self), dtype=np.intp) uniques = self if sort and","d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering","self._range.index(new_key) except ValueError as err: raise KeyError(key) from err raise","Returns ------- bytes used Notes ----- Memory usage does not","\"\"\" return self._range.stop @property def _stop(self) -> int: \"\"\" The","// r old_r, r = r, old_r - quotient *","class RangeIndex(NumericIndex): \"\"\" Immutable Index implementing a monotonic integer range.","step_s / 2, step_s / 2) elif step_o % step_s","GH 25710 return self._range.start @property def _start(self) -> int: \"\"\"","return self._range.start @property def _start(self) -> int: \"\"\" The value","= ensure_python_int(key) except TypeError: return False return key in self._range","copy: bool = False, name: Hashable = None, ) ->","base index if not is_integer(rstep) or not rstep: raise ValueError","== 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start =","< 0: start_s, step_s, end_s = end_s, -step_s, start_s if","+ abs(self.step) * no_steps def _extended_gcd(self, a: int, b: int)","tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self if","for x in self._range] # -------------------------------------------------------------------- _deprecation_message = ( \"RangeIndex.{}","isinstance(other, RangeIndex): return self._range == other._range return super().equals(other) # --------------------------------------------------------------------","step_o, end_o = end_o, -step_o, start_o if len(self) == 1","# apply if we have an override if step: with","= None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if","take( self, indices, axis: int = 0, allow_fill: bool =","= self._simple_new(new_range) # adjust index to limiting interval new_start =","construction \"\"\" return Int64Index @cache_readonly def _data(self) -> np.ndarray: \"\"\"","start is None: # This is set by the first","We won't end up with RangeIndex, so fall back return","= 0, allow_fill: bool = True, fill_value=None, **kwargs ) ->","= str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header + [f\"{x:<{max_length}}\"","and will be removed in a future \" \"version. Use","new_index def _min_fitting_element(self, lower_limit: int) -> int: \"\"\"Returns the smallest","quotient * t return old_r, old_s, old_t def _union(self, other:","!= next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for x","extract_range=True) attrs = self._get_attributes_dict() left, right = self, other try:","left.union(right) if result_name is not None: result = result.rename(result_name) return","Int64Index: # wrap _cached_int64index so we can be sure its","start(self) -> int: \"\"\" The value of the `start` parameter","locs[valid] = len(self) - 1 - locs[valid] return ensure_platform_int(locs) #","is None: start, stop = 0, start else: stop =","memory consumed by elements that are not components of the","(start_o - end_s) <= step_s ): return type(self)(start_r, end_r +","0 else self._range overlap = self.intersection(other) if overlap.step < 0:","= self.start // other step = self.step // other stop","com from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from","[rstart, rstop, rstep]): result = result.astype(\"float64\") return result except (ValueError,","= None, limit: int | None = None, tolerance=None, )","of my values Parameters ---------- deep : bool Introspect the","step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range,","-> list[str]: if not len(self._range): return header first_val_str = str(self._range[0])","- start valid = (locs % step == 0) &","is deprecated and will be removed in a future \"","Also -------- numpy.ndarray.argsort \"\"\" ascending = kwargs.pop(\"ascending\", True) # EA","start = step = next_ = None # Filter the","and (abs(start_s - start_o) <= step_s / 2) and (abs(end_s","return len(self._range) @property def size(self) -> int: return len(self) def","range. RangeIndex is a memory-saving special case of Int64Index limited","// gcd new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range)","== 0: raise ValueError(\"Step must not be zero\") rng =","and slice keys. \"\"\" if isinstance(key, slice): new_range = self._range[key]","axis=axis) def delete(self, loc) -> Int64Index: # type: ignore[override] return","memory consumption Returns ------- bytes used Notes ----- Memory usage","\"\"\" if not isinstance(data, range): raise TypeError( f\"{cls.__name__}(...) must be","+ b*y = gcd(x, y) Finds one particular solution for","// other step = self.step // other stop = start","elif step is None: # First non-empty index had only","\"max\" and self.step < 0): return self.start return self.start +","components of the array if deep=False See Also -------- numpy.ndarray.nbytes","value of the `stop` parameter. \"\"\" return self._range.stop @property def","step).rename(name) # Here all \"indexes\" had 0 length, i.e. were","\"\"\" return the class to use for construction \"\"\" return","dtype=np.intp) uniques = self if sort and self.step < 0:","return 0 not in self._range def any(self, *args, **kwargs) ->","Also -------- numpy.ndarray.nbytes \"\"\" return self.nbytes @property def dtype(self) ->","warnings import numpy as np from pandas._libs import index as","indexes): return super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0]","non_consecutive = (step != rng.step and len(rng) > 1) or","self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else: result =","check whether element sets intersect if (first.start - second.start) %","all \"indexes\" had 0 length, i.e. were empty. # In","created only when needed. The constructed array is saved in","int: \"\"\"The maximum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs)","+ step if non_empty_indexes: # Get the stop value from","r, old_r = b, a while r: quotient = old_r","= self.intersection(other) if overlap.step < 0: overlap = overlap[::-1] if","of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\"max\") def argsort(self,","range(start, stop, step or 1) return self._simple_new(new_range, name=self.name) if len(self)","if TYPE_CHECKING: from pandas import Index _empty_range = range(0) class","# TODO: if other is a RangeIndex we may have","len(last_val_str)) return header + [f\"{x:<{max_length}}\" for x in self._range] #","given, interpreted as \"stop\" instead. stop : int (default: 0)","int_high <= int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine","start, cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif","def _get_indexer( self, target: Index, method: str | None =","\"indexes\" had 0 length, i.e. were empty. # In this","(is_signed_integer_dtype, \"signed integer\") _can_hold_na = False _range: range # --------------------------------------------------------------------","any(self, *args, **kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def","list[str], na_rep: str = \"NaN\") -> list[str]: if not len(self._range):","self._range overlap = self.intersection(other) if overlap.step < 0: overlap =","from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common","in indexes): return super()._concat(indexes, name) elif len(indexes) == 1: return","params perform the binary op \"\"\" if isinstance(other, ABCTimedeltaIndex): #","symmetric_difference(self, other, result_name: Hashable = None, sort=None): if not isinstance(other,","0 else self._range second = other._range[::-1] if other.step < 0","| None = None, tolerance=None, ) -> np.ndarray: # ->","step_o = abs(self.start - other.start) elif len(self) == 1: step_s","might be able to get a RangeIndex back, # but","a sorted ``Int64Index`` if not. ``sort=False`` always returns an unsorted","0: raise ValueError(\"Step must not be zero\") rng = range(start,","are equal, shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other,","None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls)","= new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) -> int:","\"\"\" return if the index has unique values \"\"\" return","# Filter the empty indexes non_empty_indexes = [obj for obj","smaller than or equal to the limit\"\"\" no_steps = (upper_limit","super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other, op): \"\"\"","`step` parameter (``1`` if this was not supplied). \"\"\" #","Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: # wrap _cached_int64index","representable op # so return a base index if not","name: Hashable = None, deep: bool = False, dtype: Dtype","problem # performance hint: for identical step sizes, could use","rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for","self._extended_gcd(first.step, second.step) # check whether element sets intersect if (first.start","= True, *args, **kwargs) -> int: \"\"\"The maximum value of","int(key) try: return self._range.index(new_key) except ValueError as err: raise KeyError(key)","first.start: # The difference is everything after the intersection new_rng","super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step > 0:","_data(self) -> np.ndarray: \"\"\" An int array that for performance","or ( next_ is not None and rng.start != next_","1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step < 0","RangeIndex from a range object. Returns ------- RangeIndex \"\"\" if","of the RangeIndex \"\"\" return len(self._range) @property def size(self) ->","step_s, end_s = end_s, -step_s, start_s if other.step < 0:","-> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take( self,","( TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import warnings","is the default index type used by DataFrame and Series","RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range = values","limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step)","super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0] rng_indexes =","None: result = result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self,","does not include memory consumed by elements that are not","= [obj for obj in rng_indexes if len(obj)] for obj","self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( \"parameter","Return the number of bytes in the underlying data. \"\"\"","return self._simple_new(new_range, name=self.name) if len(self) == 1: start = self.start","= step(left.step, right) # we don't have a representable op","called with integers\") start = ensure_python_int(start) if start is not","return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other): if is_integer(other) and","from a range object. Returns ------- RangeIndex \"\"\" if not","name=self.name) @property def _int64index(self) -> Int64Index: # wrap _cached_int64index so","self.start @property def stop(self) -> int: \"\"\" The value of","dtype is deprecated and will be removed in a future","__iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable","Notes ----- Memory usage does not include memory consumed by","* s old_t, t = t, old_t - quotient *","rng = obj._range if start is None: # This is","if not isinstance(overlap, RangeIndex): # We won't end up with","len(other) == 1: step_o = step_s start_r = min(start_s, start_o)","2) elif step_o % step_s == 0: if ( (start_o","to Int64Index implementation return op(self._int64index, other) # TODO: Do attrs","+ self.step * (len(self) - 1) start_o, step_o = other.start,","<= step_s and (start_o - end_s) <= step_s ): return","are of type RangeIndex: result will be RangeIndex if possible,","monotonic ranges. Using RangeIndex may in some instances improve computing","\" \"removed in a future version. Use RangeIndex.{} \" \"instead\"","= result[::-1] return result def factorize( self, sort: bool =","self.stop, self.step else: # GH 28678: work on reversed range","+ step_o >= start_o) and (end_s - step_o <= end_o)","------- from_range See Also -------- Index : The base pandas","key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except ValueError as","sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\"start\", \"stop\", \"step\"] )","and sort is None: start_s, step_s = self.start, self.step end_s","indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]:",": int (default: 1) dtype : np.int64 Unused, accepted for","or boolean \" \"arrays are valid indices\" ) # fall","efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict()","if isinstance(other, RangeIndex) and self._range == other._range: # Both are","= type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def","optimized set operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other)","Hashable = None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values,","= end_o, -step_o, start_o if len(self) == 1 and len(other)","Index type. Int64Index : Index of int64 data. \"\"\" _typ","this was not supplied). \"\"\" # GH 25710 return self._range.start","non_empty_indexes: rng = obj._range if start is None: # This","1: step_s = step_o elif len(other) == 1: step_o =","name=name) @classmethod def _simple_new(cls, values: range, name: Hashable = None)","= left.union(right) if result_name is not None: result = result.rename(result_name)","sort : False or None, default None Whether to sort","len(other) == 1: step_s = step_o = abs(self.start - other.start)","!= 0: if len(self) == 0 or self.start % other","instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2,","@property def size(self) -> int: return len(self) def __getitem__(self, key):","step: Callable | None = None if op in [operator.mul,","---------- other : Index or array-like sort : False or","if dtype: warnings.warn( \"parameter dtype is deprecated and will be","r old_r, r = r, old_r - quotient * r","index type used by DataFrame and Series when no explicit","__future__ import annotations from datetime import timedelta import operator from","be removed in a future \" \"version. Use the astype","names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( \"parameter dtype","self.step * (len(self) - 1) start_o, step_o = other.start, other.step","start, stop, step = self.start, self.stop, self.step else: # GH","``start`` instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2, ) return","import numpy as np from pandas._libs import index as libindex","---------- start stop step Methods ------- from_range See Also --------","---------- start : int (default: 0), range, or other RangeIndex","import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, )","is not None: next_ = rng[-1] + step if non_empty_indexes:","except TypeError: return False return key in self._range @property def","\"\"\" Returns the indices that would sort the index and","if this was not supplied). \"\"\" # GH 25710 return","@cache_readonly def nbytes(self) -> int: \"\"\" Return the number of","type. Int64Index : Index of int64 data. \"\"\" _typ =","0 and other.step < 0) is not (new_index.step < 0):","reasons is created only when needed. The constructed array is","default index type used by DataFrame and Series when no","\"\"\"The maximum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return","a monotonic integer range. RangeIndex is a memory-saving special case","back, # but not worth the effort. return super()._difference(other, sort=sort)","non_empty_indexes: # Get the stop value from \"next\" or alternatively","(default: 0) step : int (default: 1) dtype : np.int64","return \"integer\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self,","other # -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) ->","= int(key) try: return self._range.index(new_key) except ValueError as err: raise","return self.step @cache_readonly def nbytes(self) -> int: \"\"\" Return the","return attrs def _format_data(self, name=None): # we are formatting thru","and its underlying data. Returns ------- np.ndarray[np.intp] See Also --------","else 0 if stop is None: start, stop = 0,","step=None, dtype: Dtype | None = None, copy: bool =","isinstance(other, RangeIndex) and sort is None: start_s, step_s = self.start,","step_s / 2) ): return type(self)(start_r, end_r + step_s /","* (len(other) - 1) if self.step < 0: start_s, step_s,","-> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self","return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name: Hashable","-> RangeIndex: \"\"\" Create RangeIndex from a range object. Returns","min(self, axis=None, skipna: bool = True, *args, **kwargs) -> int:","when needed. The constructed array is saved in ``_cache``. \"\"\"","or alternatively # from the last non-empty index stop =","self.step > 0: start, stop, step = self.start, self.stop, self.step","non-empty index stop = non_empty_indexes[-1].stop if next_ is None else","on timedelta64, # so we need to catch these explicitly","name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name =","stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def _minmax(self, meth:","if ( (start_s - start_o) % step_s == 0 and","- start non_consecutive = (step != rng.step and len(rng) >","pandas._libs import index as libindex from pandas._libs.lib import no_default from","start : int (default: 0), range, or other RangeIndex instance","other._range[::-1] if other.step < 0 else other._range # check whether","ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index, other) #","of all RangeIndex instances. When all members of \"indexes\" are","Conserve RangeIndex type for scalar and slice keys. \"\"\" if","return self._range == other._range return super().equals(other) # -------------------------------------------------------------------- # Set",") from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int,","We reversed this range: transform to original locs locs[valid] =","equal, shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op)","op : callable that accepts 2 params perform the binary","tmp_start = first.start + (second.start - first.start) * first.step //","tuple[int, int, int]: \"\"\" Extended Euclidean algorithms to solve Bezout's","delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array =","op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod,","return result.rename(name) step = rng.start - start non_consecutive = (step","= result.astype(\"float64\") return result except (ValueError, TypeError, ZeroDivisionError): # Defer","0: if ( (start_s - start_o) % step_o == 0","abs(self.step)) return self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit:","max(end_s, end_o) if step_o == step_s: if ( (start_s -","start_r = min(start_s, start_o) end_r = max(end_s, end_o) if step_o","not None: next_ = rng[-1] + step if non_empty_indexes: #","start + len(self) * step new_range = range(start, stop, step","end_o, -step_o, start_o if len(self) == 1 and len(other) ==","is_integer(rstep) or not rstep: raise ValueError else: rstep = left.step","and (start_o - end_s) <= step_s ): return type(self)(start_r, end_r","kwargs) return self._minmax(\"min\") def max(self, axis=None, skipna: bool = True,","case of Int64Index limited to representing monotonic ranges. Using RangeIndex","= b, a while r: quotient = old_r // r","self._range[::-1] if self.step < 0 else self._range overlap = self.intersection(other)","raise TypeError(\"RangeIndex(...) must be called with integers\") start = ensure_python_int(start)","< 0: start_o, step_o, end_o = end_o, -step_o, start_o if","homogeneity with other index types. copy : bool, default False","start_s) % step_s == 0 and (start_o + step_s >=","default False Unused, accepted for homogeneity with other index types.","list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self,","to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target)","-> tuple[int, int, int]: \"\"\" Extended Euclidean algorithms to solve","other.start + other.step * (len(other) - 1) if self.step <","rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, )","a future \" \"version. Use the astype method instead.\", FutureWarning,","ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic","self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- #","fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__)","err: raise IndexError( f\"index {key} is out of bounds for","rng.start if step is None and len(rng) > 1: step","or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return","np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1, -1, -1,","parameter (``1`` if this was not supplied). \"\"\" # GH","reverse = self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step","must be called with integers\") start = ensure_python_int(start) if start","optional Name to be stored in the index. Attributes ----------","rng.step elif step is None: # First non-empty index had","object, optional Name to be stored in the index. Attributes","for homogeneity with other index types. name : object, optional","Index: \"\"\" Overriding parent method for the case of all","return self._range.stop @property def _stop(self) -> int: \"\"\" The value","start_o) <= step_s / 2) and (abs(end_s - end_o) <=","// other new_range = range(start, start + 1, 1) return","= None ) -> RangeIndex: \"\"\" Create RangeIndex from a","first.step) elif overlap[-1] == first[-1]: # The difference is everything","1 if no_steps == -1: return np.nan elif (meth ==","decreasing ranges int_low = max(first.start, second.start) int_high = min(first.stop, second.stop)","instance If int and \"stop\" is not given, interpreted as","and \"stop\" is not given, interpreted as \"stop\" instead. stop",": Index \"\"\" if isinstance(other, RangeIndex) and sort is None:","Also -------- Index : The base pandas Index type. Int64Index","coercible to a \" f\"range, {repr(data)} was passed\" ) cls._validate_dtype(dtype)","integer or boolean \" \"arrays are valid indices\" ) #","we don't have a representable op # so return a","super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array -","end_o) ): return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other,","# -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) -> Index:","import operator from sys import getsizeof from typing import (","isinstance(overlap, RangeIndex): # We won't end up with RangeIndex, so","result.rename(name) step = rng.start - start non_consecutive = (step !=","return self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int)","-> bool: \"\"\" return if the index has unique values","element sets intersect if (first.start - second.start) % gcd: return","first.step) else: # The difference is not range-like return super()._difference(other,","memory-saving special case of Int64Index limited to representing monotonic ranges.","= locs[valid] / step if step != self.step: # We","if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op","not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step <","first[-1]: # The difference is everything before the intersection new_rng","nv.validate_argsort(args, kwargs) if self._range.step > 0: result = np.arange(len(self), dtype=np.intp)","unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union : Index","new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if","return super()._difference(other, sort=sort) if overlap[0] == first.start: # The difference","return self._simple_new(new_range, name=self.name) return self._int64index // other # -------------------------------------------------------------------- #","for the RangeIndex describing the # intersection disregarding the lower","int = 0, allow_fill: bool = True, fill_value=None, **kwargs )",") from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import","True, *args, **kwargs) -> int: \"\"\"The maximum value of the","new_index = new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps","Parameters ---------- other : Index or array-like sort : False","# wrap _cached_int64index so we can be sure its name","step_s: if ( (start_s - start_o) % step_s == 0","(start_s - end_o) <= step_s and (start_o - end_s) <=","axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return","* r old_s, s = s, old_s - quotient *","isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64,","name: Hashable) -> Index: \"\"\" Overriding parent method for the","step): raise TypeError(\"RangeIndex(...) must be called with integers\") start =","if not all(is_integer(x) for x in [rstart, rstop, rstep]): result","a \" f\"range, {repr(data)} was passed\" ) cls._validate_dtype(dtype) return cls._simple_new(data,","as err: raise KeyError(key) from err raise KeyError(key) return super().get_loc(key,","values: range, name: Hashable = None) -> RangeIndex: result =","elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return op(self._int64index,","s, _ = self._extended_gcd(first.step, second.step) # check whether element sets","= np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not ascending:","\"\"\" The value of the `step` parameter (``1`` if this","= None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index","1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats,","dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool:","-(-(lower_limit - self.start) // abs(self.step)) return self.start + abs(self.step) *","limit=limit ) if self.step > 0: start, stop, step =","---------- deep : bool Introspect the data deeply, interrogate `object`","self, target: Index, method: str | None = None, limit:","typing import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast, )","self._minmax(\"max\") def argsort(self, *args, **kwargs) -> np.ndarray: \"\"\" Returns the","float-like descriptors if not all(is_integer(x) for x in [rstart, rstop,","used Notes ----- Memory usage does not include memory consumed","None, copy: bool = False, name: Hashable = None, )","everything after the intersection new_rng = range(overlap[-1] + first.step, first.stop,","type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index = new_index[::-1]","sort is not None: return super().symmetric_difference(other, result_name, sort) left =","super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \"\"\" Fastpath","Unused, accepted for homogeneity with other index types. copy :","= s, old_s - quotient * s old_t, t =","don't have a representable op # so return a base","index types. copy : bool, default False Unused, accepted for","start_s) and (end_o - step_s <= end_s) ): return type(self)(start_r,","op): if isinstance(other, RangeIndex) and self._range == other._range: # Both","if we have an override if step: with np.errstate(all=\"ignore\"): rstep","== \"max\" and self.step < 0): return self.start return self.start","type(self)(start_r, end_r + step_s, step_s) if ( (step_s % 2","len(self) == 1 and len(other) == 1: step_s = step_o","astype method instead.\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return","new_range = range(start, start + 1, 1) return self._simple_new(new_range, name=self.name)","-> bool: return 0 not in self._range def any(self, *args,","list of tuples of start, stop, step \"\"\" rng =","= self._get_data_as_items() if self.name is not None: attrs.append((\"name\", ibase.default_pprint(self.name))) return",") import warnings import numpy as np from pandas._libs import","limit: int | None = None, tolerance=None, ) -> np.ndarray:","len(self) or not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if","is_integer evaluated True on timedelta64, # so we need to","(start_s - start_o) % step_o == 0 and (start_s +","not self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self, other,","return [(\"start\", rng.start), (\"stop\", rng.stop), (\"step\", rng.step)] def __reduce__(self): d","Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other,","return op(self._int64index, other) step: Callable | None = None if","function as nv from pandas.util._decorators import ( cache_readonly, doc, )","saved in ``_cache``. \"\"\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly","= self._cache return result @doc(Int64Index.copy) def copy( self, name: Hashable","removed in a future \" \"version. Use the astype method","step = next_ = None # Filter the empty indexes","= abs(self.start - other.start) elif len(self) == 1: step_s =","ranges int_low = max(first.start, second.start) int_high = min(first.stop, second.stop) if","TYPE_CHECKING: from pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex):","\" f\"range, {repr(data)} was passed\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name)","new_key = int(key) try: return self._range[new_key] except IndexError as err:","transform to original locs locs[valid] = len(self) - 1 -","if (first.start - second.start) % gcd: return self._simple_new(_empty_range) # calculate","other.difference(self) result = left.union(right) if result_name is not None: result","False return key in self._range @property def inferred_type(self) -> str:","elements that are not components of the array if deep=False","the `stop` parameter. \"\"\" return self._range.stop @property def _stop(self) ->","return header + [f\"{x:<{max_length}}\" for x in self._range] # --------------------------------------------------------------------","value of the `start` parameter (``0`` if this was not","range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] == first[-1]: #","in [rstart, rstop, rstep]): result = result.astype(\"float64\") return result except","work on reversed range for simplicity reverse = self._range[::-1] start,","max(len(first_val_str), len(last_val_str)) return header + [f\"{x:<{max_length}}\" for x in self._range]","the class to use for construction \"\"\" return Int64Index @cache_readonly","self._range[new_key] except IndexError as err: raise IndexError( f\"index {key} is","None, deep: bool = False, dtype: Dtype | None =","return a list of tuples of start, stop, step \"\"\"","== step_s: if ( (start_s - start_o) % step_s ==","the arguments if com.all_none(start, stop, step): raise TypeError(\"RangeIndex(...) must be","result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) ->","-------- numpy.ndarray.nbytes \"\"\" return self.nbytes @property def dtype(self) -> np.dtype:","\"instead\" ) @property def start(self) -> int: \"\"\" The value","end up with RangeIndex, so fall back return super()._difference(other, sort=sort)","import warnings import numpy as np from pandas._libs import index","no_steps == -1: return np.nan elif (meth == \"min\" and","in rng_indexes]) result = Int64Index(values) return result.rename(name) step = rng.start","): return type(self)(start_r, end_r + step_s / 2, step_s /","index if not is_integer(rstep) or not rstep: raise ValueError else:","operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step:","def _max_fitting_element(self, upper_limit: int) -> int: \"\"\"Returns the largest element","list[Index], name: Hashable) -> Index: \"\"\" Overriding parent method for","self._range[::-1] if self.step < 0 else self._range second = other._range[::-1]","Index of int64 data. \"\"\" _typ = \"rangeindex\" _engine_type =","old_t = 1, 0 r, old_r = b, a while","overlap[0], first.step) else: # The difference is not range-like return","FutureWarning, stacklevel=2, ) return self.stop @property def step(self) -> int:","> 0: start, stop, step = self.start, self.stop, self.step else:","other == 0 and self.step % other == 0: start","stop, step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): #","| None = None, names=None, ): name = self._validate_names(name=name, names=names,","0): new_index = new_index[::-1] if sort is None: new_index =","index and its underlying data. Returns ------- np.ndarray[np.intp] See Also","whether intervals intersect # deals with in- and decreasing ranges","key): \"\"\" Conserve RangeIndex type for scalar and slice keys.","len(overlap) == 0: return self.rename(name=res_name) if len(overlap) == len(self): return","RangeIndex) and self._range == other._range: # Both are immutable so","for axis 0 with size {len(self)}\" ) from err elif","s, t \"\"\" s, old_s = 0, 1 t, old_t","<= step_s ): return type(self)(start_r, end_r + step_s, step_s) if",": int (default: 0) step : int (default: 1) dtype","\"RangeIndex.{} is deprecated and will be \" \"removed in a","( (step_s % 2 == 0) and (abs(start_s - start_o)","import function as nv from pandas.util._decorators import ( cache_readonly, doc,","Create RangeIndex from a range object. Returns ------- RangeIndex \"\"\"","future version. Use RangeIndex.{} \" \"instead\" ) @property def start(self)","start_s, step_s = self.start, self.step end_s = self.start + self.step","numpy as np from pandas._libs import index as libindex from","Use ``stop`` instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"),","# cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step) #","set by the first non-empty index start = rng.start if","def __floordiv__(self, other): if is_integer(other) and other != 0: if","and self.step > 0) or (meth == \"max\" and self.step","@unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other): if is_integer(other) and other != 0:","bytes in the underlying data. \"\"\" rng = self._range return","step if step != self.step: # We reversed this range:","to the limit\"\"\" no_steps = -(-(lower_limit - self.start) // abs(self.step))","return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\"start\",","parameter (``0`` if this was not supplied). .. deprecated:: 0.25.0","The constructed array is saved in ``_cache``. \"\"\" return np.arange(self.start,","result._range = values result._name = name result._cache = {} result._reset_identity()","> 0: result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self)","other == 0: start = self.start // other step =","name=None): # we are formatting thru the attributes return None","super()._intersection(other, sort=sort) if not len(self) or not len(other): return self._simple_new(_empty_range)","Bezout's identity: a*x + b*y = gcd(x, y) Finds one","return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized set","return codes, uniques def equals(self, other: object) -> bool: \"\"\"","first.step, first.stop, first.step) elif overlap[-1] == first[-1]: # The difference","from __future__ import annotations from datetime import timedelta import operator","None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self),","ensure_python_int(start) if start is not None else 0 if stop","_can_hold_na = False _range: range # -------------------------------------------------------------------- # Constructors def","algorithms to solve Bezout's identity: a*x + b*y = gcd(x,","Int64Index implementation return op(self._int64index, other) # TODO: Do attrs get","its name matches self.name res = self._cached_int64index res._name = self._name","# we are formatting thru the attributes return None def","up with RangeIndex, so fall back return super()._difference(other, sort=sort) if","_stop(self) -> int: \"\"\" The value of the `stop` parameter.","op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390","result = np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not","self.step < 0: start_s, step_s, end_s = end_s, -step_s, start_s","{len(self)}\" ) from err elif is_scalar(key): raise IndexError( \"only integers,","sort=sort) if overlap[0] == first.start: # The difference is everything","return self.start @property def stop(self) -> int: \"\"\" The value","- first.start) * first.step // gcd * s new_step =","be stored in the index. Attributes ---------- start stop step","sort=False): if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort)","possible Parameters ---------- other : Index or array-like sort :","None, limit: int | None = None, tolerance=None, ) ->","return self._minmax(\"min\") def max(self, axis=None, skipna: bool = True, *args,","other.step end_o = other.start + other.step * (len(other) - 1)","- end_s) <= step_s ): return type(self)(start_r, end_r + step_s,","result will be RangeIndex if possible, Int64Index otherwise. E.g.: indexes","is_unique(self) -> bool: \"\"\" return if the index has unique","self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try:","stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data:","self.name is not None: attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs def _format_data(self,","uniques def equals(self, other: object) -> bool: \"\"\" Determines if","- second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters for","stop = start + len(self) * step new_range = range(start,","deprecated:: 0.25.0 Use ``start`` instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning,","= self._cached_int64index res._name = self._name return res def _get_data_as_items(self): \"\"\"","self.start + abs(self.step) * no_steps def _extended_gcd(self, a: int, b:",") new_index = new_index.astype(dtype) return new_index def _minmax(self, meth: str):","np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values) return result.rename(name)","would sort the index and its underlying data. Returns -------","if next_ is None else next_ return RangeIndex(start, stop, step).rename(name)","self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2, ) return self.stop @property def step(self)","rstep, **attrs) # for compat with numpy / Int64Index #","use for construction \"\"\" return Int64Index @cache_readonly def _data(self) ->","stop, step \"\"\" rng = self._range return [(\"start\", rng.start), (\"stop\",","for system-level memory consumption Returns ------- bytes used Notes -----","_min_fitting_element(self, lower_limit: int) -> int: \"\"\"Returns the smallest element greater","and (start_s - end_o) <= step_s and (start_o - end_s)","if step == 0: raise ValueError(\"Step must not be zero\")","if len(self) == 1: start = self.start // other new_range","validate the arguments if com.all_none(start, stop, step): raise TypeError(\"RangeIndex(...) must","from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index,","integers\") start = ensure_python_int(start) if start is not None else","upper_limit: int) -> int: \"\"\"Returns the largest element smaller than","( (start_s - start_o) % step_o == 0 and (start_s","range, name: Hashable = None) -> RangeIndex: result = object.__new__(cls)","keys. \"\"\" if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range,","case of all RangeIndex instances. When all members of \"indexes\"","See Also -------- numpy.ndarray.argsort \"\"\" ascending = kwargs.pop(\"ascending\", True) #","= Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if step","to solve Bezout's identity: a*x + b*y = gcd(x, y)","start_o if len(self) == 1 and len(other) == 1: step_s","def take( self, indices, axis: int = 0, allow_fill: bool","attrs def _format_data(self, name=None): # we are formatting thru the","return new_index def _minmax(self, meth: str): no_steps = len(self) -","0.25.0 Use ``stop`` instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\",","= min(start_s, start_o) end_r = max(end_s, end_o) if step_o ==","\"step\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self) ->","type: ignore[override] return self._int64index.delete(loc) def take( self, indices, axis: int","of type RangeIndex: result will be RangeIndex if possible, Int64Index","def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \"\"\" Fastpath for","solve intersection problem # performance hint: for identical step sizes,","Returns the indices that would sort the index and its","or array-like sort : False or None, default None Whether","1, 1) return self._simple_new(new_range, name=self.name) return self._int64index // other #","compat with numpy / Int64Index # even if we can","result except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation","= self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key)","old_s = 0, 1 t, old_t = 1, 0 r,","other index types. copy : bool, default False Unused, accepted","be able to get a RangeIndex back, # but not","or not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step","the RangeIndex \"\"\" return len(self._range) @property def size(self) -> int:","unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range = range(0)","Diophantine equation # solve intersection problem # performance hint: for","self.start) // abs(self.step) return self.start + abs(self.step) * no_steps def","* no_steps def _extended_gcd(self, a: int, b: int) -> tuple[int,","deep=False See Also -------- numpy.ndarray.nbytes \"\"\" return self.nbytes @property def","in [\"start\", \"stop\", \"step\"] ) def memory_usage(self, deep: bool =","\"\"\" s, old_s = 0, 1 t, old_t = 1,","return self._range[new_key] except IndexError as err: raise IndexError( f\"index {key}","raise ValueError else: rstep = left.step with np.errstate(all=\"ignore\"): rstart =","stop, step).rename(name) # Here all \"indexes\" had 0 length, i.e.","from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common","Index : The base pandas Index type. Int64Index : Index","self._range == other._range: # Both are immutable so if ._range","def all(self, *args, **kwargs) -> bool: return 0 not in","step_o = other.start, other.step end_o = other.start + other.step *","if len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex):","return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: # type:","-> int: \"\"\" return the length of the RangeIndex \"\"\"","int (default: 0) step : int (default: 1) dtype :","speed. This is the default index type used by DataFrame","is everything before the intersection new_rng = range(first.start, overlap[0], first.step)","new_rng = range(first.start, overlap[0], first.step) else: # The difference is","is None and tolerance is None: if is_integer(key) or (is_float(key)","if overlap.step != first.step: # In some cases we might","# Must be an np.ndarray; GH#22390 return op(self._int64index, other) if","ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as com from","def _format_attrs(self): \"\"\" Return a list of tuples of the","target, method=method, tolerance=tolerance, limit=limit ) if self.step > 0: start,","See Also -------- Index : The base pandas Index type.","the limit\"\"\" no_steps = (upper_limit - self.start) // abs(self.step) return","types. copy : bool, default False Unused, accepted for homogeneity","Operations def _intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex):","for obj in non_empty_indexes: rng = obj._range if start is","reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general","by elements that are not components of the array if","[(\"start\", rng.start), (\"stop\", rng.stop), (\"step\", rng.step)] def __reduce__(self): d =","from typing import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast,","+ [f\"{x:<{max_length}}\" for x in self._range] # -------------------------------------------------------------------- _deprecation_message =","return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1]","intersection disregarding the lower bounds tmp_start = first.start + (second.start","RangeIndex) and sort is None: start_s, step_s = self.start, self.step","old_r = b, a while r: quotient = old_r //","= 0, start else: stop = ensure_python_int(stop) step = ensure_python_int(step)","int array that for performance reasons is created only when","fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj:","return super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self, other:","index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible or","Reductions def all(self, *args, **kwargs) -> bool: return 0 not","== 0 and (start_s - end_o) <= step_s and (start_o","self.start return self.start + self.step * no_steps def min(self, axis=None,","import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer,","new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust","step_o % step_s == 0: if ( (start_o - start_s)","start + 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index //","\"NaN\") -> list[str]: if not len(self._range): return header first_val_str =","the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\"max\") def argsort(self, *args,","= self._extended_gcd(first.step, second.step) # check whether element sets intersect if","and len(other) == 1: step_s = step_o = abs(self.start -","= True, *args, **kwargs) -> int: \"\"\"The minimum value of","other : Index or array-like sort : False or None,","pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype,","= ensure_python_int(stop) step = ensure_python_int(step) if step is not None","this case return an empty range index. return RangeIndex(0, 0).rename(name)","has unique values \"\"\" return True @cache_readonly def is_monotonic_increasing(self) ->","# for compat with numpy / Int64Index # even if","self._rename(name=name) if dtype: warnings.warn( \"parameter dtype is deprecated and will","RangeIndex): return self._range == other._range return super().equals(other) # -------------------------------------------------------------------- #","end_r + step_s / 2, step_s / 2) elif step_o","def _int64index(self) -> Int64Index: # wrap _cached_int64index so we can","Use ``start`` instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2, )","self.step else: # GH 28678: work on reversed range for","self.start + self.step * no_steps def min(self, axis=None, skipna: bool","underlying data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \"\"\"","super().symmetric_difference(other, result_name, sort) left = self.difference(other) right = other.difference(self) result","non-empty index start = rng.start if step is None and","str): no_steps = len(self) - 1 if no_steps == -1:","result.astype(\"float64\") return result except (ValueError, TypeError, ZeroDivisionError): # Defer to","f\"range, {repr(data)} was passed\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod","sys import getsizeof from typing import ( TYPE_CHECKING, Any, Callable,","GH 25710 return self._range.step @property def _step(self) -> int: \"\"\"","reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated","instances improve computing speed. This is the default index type","{repr(data)} was passed\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def","all members of \"indexes\" are of type RangeIndex: result will","-> np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool: \"\"\"","bounds for axis 0 with size {len(self)}\" ) from err","1 t, old_t = 1, 0 r, old_r = b,","\"indexes\" are of type RangeIndex: result will be RangeIndex if","-> int: \"\"\" The value of the `start` parameter (``0``","nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\"max\") def argsort(self, *args, **kwargs) ->","RangeIndex instances. When all members of \"indexes\" are of type","None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method,","stop = ensure_python_int(stop) step = ensure_python_int(step) if step is not","name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype:","increasing ``RangeIndex`` if possible or a sorted ``Int64Index`` if not.","1: step = rng.step elif step is None: # First","The base pandas Index type. Int64Index : Index of int64","None and rng.start != next_ ) if non_consecutive: result =","stop = non_empty_indexes[-1].stop if next_ is None else next_ return","= (upper_limit - self.start) // abs(self.step) return self.start + abs(self.step)","= 0, 1 t, old_t = 1, 0 r, old_r","len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't","bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if","-1, dtype=np.intp) if not ascending: result = result[::-1] return result","returns a monotonically increasing ``RangeIndex`` if possible or a sorted","rng = range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def","r = r, old_r - quotient * r old_s, s","int: \"\"\" The value of the `step` parameter (``1`` if","(first.start - second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters","+ sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\"start\", \"stop\", \"step\"]","25710 return self._range.step @property def _step(self) -> int: \"\"\" The","# solve intersection problem # performance hint: for identical step","elif step_o % step_s == 0: if ( (start_o -","is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex","RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache","**attrs) # for compat with numpy / Int64Index # even","x, y: s, t Returns: gcd, s, t \"\"\" s,","result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy)","t Returns: gcd, s, t \"\"\" s, old_s = 0,","a RangeIndex back, # but not worth the effort. return","\"\"\" return a list of tuples of start, stop, step","= self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn(","- 1, -1, -1, dtype=np.intp) if not ascending: result =","other): if is_integer(other) and other != 0: if len(self) ==","`object` dtypes for system-level memory consumption Returns ------- bytes used","[ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return","= step = next_ = None # Filter the empty","bool = False) -> int: \"\"\" Memory usage of my","with size {len(self)}\" ) from err elif is_scalar(key): raise IndexError(","= self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other): if","else: rstep = left.step with np.errstate(all=\"ignore\"): rstart = op(left.start, right)","have float-like descriptors if not all(is_integer(x) for x in [rstart,","step_s <= end_s) ): return type(self)(start_r, end_r + step_s, step_s)","end_s = self.start + self.step * (len(self) - 1) start_o,","other, result_name: Hashable = None, sort=None): if not isinstance(other, RangeIndex)","RangeIndex(0, 0).rename(name) def __len__(self) -> int: \"\"\" return the length","is None: start_s, step_s = self.start, self.step end_s = self.start","name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other): if is_integer(other) and other !=",") # fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self:","overlap = overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if","np.nan elif (meth == \"min\" and self.step > 0) or","= start + len(self) * step new_range = range(start, stop,","bool: return 0 not in self._range def any(self, *args, **kwargs)","isinstance(values, range) result._range = values result._name = name result._cache =","sort is None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self,","<= 1 def __contains__(self, key: Any) -> bool: hash(key) try:","with object coercible to a \" f\"range, {repr(data)} was passed\"","slice) -> RangeIndex: \"\"\" Fastpath for __getitem__ when we know","1: step_o = step_s start_r = min(start_s, start_o) end_r =","(len(other) - 1) if self.step < 0: start_s, step_s, end_s","pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex): \"\"\" Immutable",">= start_s) and (end_o - step_s <= end_s) ): return","| None = None, limit: int | None = None,","difference is everything after the intersection new_rng = range(overlap[-1] +","* step new_range = range(start, stop, step or 1) return","is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core","_cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range == other._range:","if self.step > 0: start, stop, step = self.start, self.stop,","in the underlying data. \"\"\" rng = self._range return getsizeof(rng)","| None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes =","and (start_o + step_s >= start_s) and (end_o - step_s","calculate parameters for the RangeIndex describing the # intersection disregarding","EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result =","name: Hashable = None) -> RangeIndex: result = object.__new__(cls) assert","dtype: Dtype | None = None, names=None, ): name =","non_empty_indexes = [obj for obj in rng_indexes if len(obj)] for","np.ndarray: \"\"\" Returns the indices that would sort the index","if self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else: result","if overlap.step < 0: overlap = overlap[::-1] if len(overlap) ==","the union of two Index objects and sorts if possible","= ops.get_op_result_name(self, other) first = self._range[::-1] if self.step < 0","was not supplied). \"\"\" # GH 25710 return self._range.start @property","step or 1) return self._simple_new(new_range, name=self.name) if len(self) == 1:","Any) -> bool: hash(key) try: key = ensure_python_int(key) except TypeError:","from \"next\" or alternatively # from the last non-empty index","``Int64Index`` if not. ``sort=False`` always returns an unsorted ``Int64Index`` ..","other != 0: if len(self) == 0 or self.start %","is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self,","elif (meth == \"min\" and self.step > 0) or (meth","= len(self) - 1 - locs[valid] return ensure_platform_int(locs) # --------------------------------------------------------------------","self, indices, axis: int = 0, allow_fill: bool = True,","abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) -> int: \"\"\"Returns","- step_o <= end_o) ): return type(self)(start_r, end_r + step_o,","values = np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values)","return False return key in self._range @property def inferred_type(self) ->","_ = self._extended_gcd(first.step, second.step) # check whether element sets intersect","raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target:","@property def _stop(self) -> int: \"\"\" The value of the","(locs >= 0) & (target_array < stop) locs[~valid] = -1","\"\"\" Extended Euclidean algorithms to solve Bezout's identity: a*x +","0 and (start_s - end_o) <= step_s and (start_o -","Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6)","\"\"\" attrs = self._get_data_as_items() if self.name is not None: attrs.append((\"name\",","sort=None): # optimized set operation if we have another RangeIndex","super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method: str","implementing a monotonic integer range. RangeIndex is a memory-saving special","deep : bool Introspect the data deeply, interrogate `object` dtypes","self._range.step @property def _step(self) -> int: \"\"\" The value of","not include memory consumed by elements that are not components","range # -------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None,","# -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None,","# validate the arguments if com.all_none(start, stop, step): raise TypeError(\"RangeIndex(...)","bool = True, *args, **kwargs) -> int: \"\"\"The maximum value","return type(self)(start_r, end_r + step_s, step_s) elif step_s % step_o","name=res_name) if first is not self._range: new_index = new_index[::-1] return","RangeIndex: result will be RangeIndex if possible, Int64Index otherwise. E.g.:","old_r, old_s, old_t def _union(self, other: Index, sort): \"\"\" Form","step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized","isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name)","be an np.ndarray; GH#22390 return op(self._int64index, other) if op in","end_o) <= step_s / 2) ): return type(self)(start_r, end_r +","@property def step(self) -> int: \"\"\" The value of the","so we need to catch these explicitly return op(self._int64index, other)","from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer(","-------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range","a future version. Use RangeIndex.{} \" \"instead\" ) @property def","other.step < 0: start_o, step_o, end_o = end_o, -step_o, start_o","and sorts if possible Parameters ---------- other : Index or","* no_steps def _max_fitting_element(self, upper_limit: int) -> int: \"\"\"Returns the","difference is not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng,","= [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4,","if non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return","to original locs locs[valid] = len(self) - 1 - locs[valid]","sort) left = self.difference(other) right = other.difference(self) result = left.union(right)","-1: return np.nan elif (meth == \"min\" and self.step >","# Defer to Int64Index implementation return op(self._int64index, other) # TODO:","= str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return","we might be able to get a RangeIndex back, #","\"\"\" return True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step","( next_ is not None and rng.start != next_ )","values Parameters ---------- deep : bool Introspect the data deeply,","factorize( self, sort: bool = False, na_sentinel: int | None","use # cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step)","binary op \"\"\" if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex","descriptors if not all(is_integer(x) for x in [rstart, rstop, rstep]):","result = object.__new__(cls) assert isinstance(values, range) result._range = values result._name","the `start` parameter (``0`` if this was not supplied). ..","rng = self._range return [(\"start\", rng.start), (\"stop\", rng.stop), (\"step\", rng.step)]","value of the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop``","callable that accepts 2 params perform the binary op \"\"\"","= False) -> int: \"\"\" Memory usage of my values","/ 2) ): return type(self)(start_r, end_r + step_s / 2,","return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self)","Parameters ---------- deep : bool Introspect the data deeply, interrogate","second.start) int_high = min(first.stop, second.stop) if int_high <= int_low: return","self._range second = other._range[::-1] if other.step < 0 else other._range","new_index.step) new_index = self._simple_new(new_range) if (self.step < 0 and other.step","ValueError as err: raise KeyError(key) from err raise KeyError(key) return","= (is_signed_integer_dtype, \"signed integer\") _can_hold_na = False _range: range #","Index \"\"\" if isinstance(other, RangeIndex) and sort is None: start_s,","elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on","other try: # apply if we have an override if","nv.validate_min(args, kwargs) return self._minmax(\"min\") def max(self, axis=None, skipna: bool =","\"\"\" return Int64Index @cache_readonly def _data(self) -> np.ndarray: \"\"\" An","obj in rng_indexes if len(obj)] for obj in non_empty_indexes: rng","new_index = new_index[::-1] if sort is None: new_index = new_index.sort_values()","= self.start // other new_range = range(start, start + 1,","== -1: return np.nan elif (meth == \"min\" and self.step","pandas._libs.lib import no_default from pandas._typing import Dtype from pandas.compat.numpy import","self.start + self.step * (len(self) - 1) start_o, step_o =","- end_o) <= step_s and (start_o - end_s) <= step_s","inferred_type(self) -> str: return \"integer\" # -------------------------------------------------------------------- # Indexing Methods","return super()._difference(other, sort=sort) if overlap.step != first.step: # In some","_format_data(self, name=None): # we are formatting thru the attributes return","dtype: Dtype | None = None ) -> RangeIndex: \"\"\"","GH 25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2, ) return self.step","no explicit index is provided by the user. Parameters ----------","Introspect the data deeply, interrogate `object` dtypes for system-level memory","value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\"max\") def","its underlying data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort","the RangeIndex describing the # intersection disregarding the lower bounds","= \"NaN\") -> list[str]: if not len(self._range): return header first_val_str","(upper_limit - self.start) // abs(self.step) return self.start + abs(self.step) *","*args, **kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self,","op \"\"\" if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation","== 1: step_s = step_o = abs(self.start - other.start) elif","name is no_default else name if values.dtype.kind == \"f\": return","rstep = left.step with np.errstate(all=\"ignore\"): rstart = op(left.start, right) rstop","if no_steps == -1: return np.nan elif (meth == \"min\"","_format_attrs(self): \"\"\" Return a list of tuples of the (attr,","== 0 and self.step % other == 0: start =","the index. Attributes ---------- start stop step Methods ------- from_range","numpy.ndarray.nbytes \"\"\" return self.nbytes @property def dtype(self) -> np.dtype: return","result = type(self)(rstart, rstop, rstep, **attrs) # for compat with","x in self._range] # -------------------------------------------------------------------- _deprecation_message = ( \"RangeIndex.{} is","step_o == step_s: if ( (start_s - start_o) % step_s","-1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques","\"\"\" if not all(isinstance(x, RangeIndex) for x in indexes): return","= gcd(x, y) Finds one particular solution for x, y:","same elements. \"\"\" if isinstance(other, RangeIndex): return self._range == other._range","+ step_s / 2, step_s / 2) elif step_o %","def get_loc(self, key, method=None, tolerance=None): if method is None and","locs[valid] / step if step != self.step: # We reversed","Fastpath for __getitem__ when we know we have a slice.","- step_s <= end_s) ): return type(self)(start_r, end_r + step_s,","first is not self._range: new_index = new_index[::-1] return new_index def","first.step * second.step // gcd new_range = range(tmp_start, int_high, new_step)","False, na_sentinel: int | None = -1 ) -> tuple[np.ndarray,","index had only one element if rng.start == start: values","max(self, axis=None, skipna: bool = True, *args, **kwargs) -> int:","locs = target_array - start valid = (locs % step","deprecated and will be removed in a future \" \"version.","*args, **kwargs) -> np.ndarray: \"\"\" Returns the indices that would","See Also -------- numpy.ndarray.nbytes \"\"\" return self.nbytes @property def dtype(self)","result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]:","the index and its underlying data. Returns ------- np.ndarray[np.intp] See","Index _empty_range = range(0) class RangeIndex(NumericIndex): \"\"\" Immutable Index implementing","is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key) try: return","self if sort and self.step < 0: codes = codes[::-1]","and other.step < 0) is not (new_index.step < 0): new_index","if not is_integer(rstep) or not rstep: raise ValueError else: rstep","== \"f\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self:","-step_s, start_s if other.step < 0: start_o, step_o, end_o =","Returns: gcd, s, t \"\"\" s, old_s = 0, 1","or (is_float(key) and key.is_integer()): new_key = int(key) try: return self._range.index(new_key)","bool: return self._range.step > 0 or len(self) <= 1 @cache_readonly","and self._range == other._range: # Both are immutable so if","are immutable so if ._range attr. are equal, shortcut is","have an override if step: with np.errstate(all=\"ignore\"): rstep = step(left.step,","is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops","allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return list(self._range)","no_steps = (upper_limit - self.start) // abs(self.step) return self.start +","tolerance=tolerance) def _get_indexer( self, target: Index, method: str | None","with other index types. copy : bool, default False Unused,","name: Hashable = no_default): name = self.name if name is","representing monotonic ranges. Using RangeIndex may in some instances improve","def is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or len(self)","rng[-1] + step if non_empty_indexes: # Get the stop value","def is_monotonic_increasing(self) -> bool: return self._range.step > 0 or len(self)","False Unused, accepted for homogeneity with other index types. name","isinstance(data, range): raise TypeError( f\"{cls.__name__}(...) must be called with object","< 0 else self._range overlap = self.intersection(other) if overlap.step <","2 params perform the binary op \"\"\" if isinstance(other, ABCTimedeltaIndex):","equation # solve intersection problem # performance hint: for identical","[RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \"\"\" if not all(isinstance(x, RangeIndex)","-------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) -> bool: return","rng_indexes])) return result.rename(name) if step is not None: next_ =","that accepts 2 params perform the binary op \"\"\" if","= range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range(","*args, **kwargs) -> int: \"\"\"The minimum value of the RangeIndex\"\"\"","and other != 0: if len(self) == 0 or self.start","// other # -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs)","range: transform to original locs locs[valid] = len(self) - 1","= other.start + other.step * (len(other) - 1) if self.step","and decreasing ranges int_low = max(first.start, second.start) int_high = min(first.stop,","- self.start) // abs(self.step)) return self.start + abs(self.step) * no_steps","not None else 0 if stop is None: start, stop","\" \"instead\" ) @property def start(self) -> int: \"\"\" The","Hashable = no_default): name = self.name if name is no_default","if possible or a sorted ``Int64Index`` if not. ``sort=False`` always","( (start_s - start_o) % step_s == 0 and (start_s",") return self.start @property def stop(self) -> int: \"\"\" The","Method hint: linear Diophantine equation # solve intersection problem #","== 1: step_o = step_s start_r = min(start_s, start_o) end_r","= self, other try: # apply if we have an","result._name = name result._cache = {} result._reset_identity() return result #","RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return","The value of the `start` parameter (``0`` if this was","are valid indices\" ) # fall back to Int64Index return","_typ = \"rangeindex\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \"signed","if this was not supplied). .. deprecated:: 0.25.0 Use ``step``","RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self if sort","TODO: if other is a RangeIndex we may have more","deprecated:: 0.25.0 Use ``step`` instead. \"\"\" # GH 25710 warnings.warn(","gcd: return self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing",": np.int64 Unused, accepted for homogeneity with other index types.","(end_o - step_s <= end_s) ): return type(self)(start_r, end_r +","stacklevel=2, ) return self.step @cache_readonly def nbytes(self) -> int: \"\"\"","= self._rename(name=name) if dtype: warnings.warn( \"parameter dtype is deprecated and","ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable |","False, dtype: Dtype | None = None, names=None, ): name","an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union :","f\"index {key} is out of bounds for axis 0 with","The difference is everything after the intersection new_rng = range(overlap[-1]","other step = self.step // other stop = start +","def equals(self, other: object) -> bool: \"\"\" Determines if two","sort the index and its underlying data. Returns ------- np.ndarray[np.intp]","RangeIndex instance If int and \"stop\" is not given, interpreted","one particular solution for x, y: s, t Returns: gcd,","6)] -> Int64Index([0,1,2,4,5]) \"\"\" if not all(isinstance(x, RangeIndex) for x","return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering Methods","\"integer\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key,","Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex:","return result def factorize( self, sort: bool = False, na_sentinel:","self.start % other == 0 and self.step % other ==","step new_range = range(start, stop, step or 1) return self._simple_new(new_range,","\"\"\"Returns the smallest element greater than or equal to the","= ensure_python_int(start) if start is not None else 0 if","def delete(self, loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc)","= False, na_sentinel: int | None = -1 ) ->","from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default):","= range(first.start, overlap[0], first.step) else: # The difference is not","self._range.stop @property def _stop(self) -> int: \"\"\" The value of","\" \"arrays are valid indices\" ) # fall back to","step_s >= start_s) and (end_o - step_s <= end_s) ):","None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right =","not None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right","# Set Operations def _intersection(self, other: Index, sort=False): if not","new_index = self._simple_new(new_range) if (self.step < 0 and other.step <","_start(self) -> int: \"\"\" The value of the `start` parameter","return self._minmax(\"max\") def argsort(self, *args, **kwargs) -> np.ndarray: \"\"\" Returns","len(obj)] for obj in non_empty_indexes: rng = obj._range if start","False or None, default None Whether to sort resulting index.","DataFrame and Series when no explicit index is provided by","len(self) == 0 or self.start % other == 0 and","the largest element smaller than or equal to the limit\"\"\"","+ other.step * (len(other) - 1) if self.step < 0:","from the last non-empty index stop = non_empty_indexes[-1].stop if next_","right) # we don't have a representable op # so","cls, data: range, name=None, dtype: Dtype | None = None","end_r + step_s, step_s) if ( (step_s % 2 ==","isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented elif","compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result = np.arange(len(self),","explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an","step == 0: raise ValueError(\"Step must not be zero\") rng","for performance reasons is created only when needed. The constructed","future \" \"version. Use the astype method instead.\", FutureWarning, stacklevel=2,","% step_s == 0 and (start_s - end_o) <= step_s","to a \" f\"range, {repr(data)} was passed\" ) cls._validate_dtype(dtype) return","valid = (locs % step == 0) & (locs >=","# In some cases we might be able to get","is not given, interpreted as \"stop\" instead. stop : int","is out of bounds for axis 0 with size {len(self)}\"","def _format_with_header(self, header: list[str], na_rep: str = \"NaN\") -> list[str]:","name result._cache = {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly","return self._range.step > 0 or len(self) <= 1 @cache_readonly def","other: Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index return","no_steps = -(-(lower_limit - self.start) // abs(self.step)) return self.start +","return the length of the RangeIndex \"\"\" return len(self._range) @property","< 0: overlap = overlap[::-1] if len(overlap) == 0: return","tolerance=tolerance, limit=limit ) if self.step > 0: start, stop, step","# Reductions def all(self, *args, **kwargs) -> bool: return 0","Int64Index limited to representing monotonic ranges. Using RangeIndex may in","Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING:","raise IndexError( \"only integers, slices (`:`), \" \"ellipsis (`...`), numpy.newaxis","= (locs % step == 0) & (locs >= 0)","= rng.step elif step is None: # First non-empty index","values \"\"\" return True @cache_readonly def is_monotonic_increasing(self) -> bool: return","return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array","# as a Float64Index if we have float-like descriptors if","and self.step < 0): return self.start return self.start + self.step","next_ = rng[-1] + step if non_empty_indexes: # Get the","Rendering Methods def _format_attrs(self): \"\"\" Return a list of tuples","[f\"{x:<{max_length}}\" for x in self._range] # -------------------------------------------------------------------- _deprecation_message = (","self.start // other new_range = range(start, start + 1, 1)","so return a base index if not is_integer(rstep) or not","type(self)(rstart, rstop, rstep, **attrs) # for compat with numpy /","if other.step < 0: start_o, step_o, end_o = end_o, -step_o,","not isinstance(overlap, RangeIndex): # We won't end up with RangeIndex,","provided by the user. Parameters ---------- start : int (default:","of int64 data. \"\"\" _typ = \"rangeindex\" _engine_type = libindex.Int64Engine","-> int: \"\"\"The minimum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args,","if int_high <= int_low: return self._simple_new(_empty_range) # Method hint: linear","rng.start == start: values = np.concatenate([x._values for x in rng_indexes])","tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from","cls, start=None, stop=None, step=None, dtype: Dtype | None = None,","not in self._range def any(self, *args, **kwargs) -> bool: return","ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other,","operator from sys import getsizeof from typing import ( TYPE_CHECKING,","-> RangeIndex: \"\"\" Fastpath for __getitem__ when we know we","step_o = step_s start_r = min(start_s, start_o) end_r = max(end_s,","no_steps def _max_fitting_element(self, upper_limit: int) -> int: \"\"\"Returns the largest","None: start_s, step_s = self.start, self.step end_s = self.start +","object coercible to a \" f\"range, {repr(data)} was passed\" )","codes, uniques def equals(self, other: object) -> bool: \"\"\" Determines","2 == 0) and (abs(start_s - start_o) <= step_s /","= name result._cache = {} result._reset_identity() return result # --------------------------------------------------------------------","-> str: return \"integer\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc)","RangeIndex: \"\"\" Fastpath for __getitem__ when we know we have","bool, default False Unused, accepted for homogeneity with other index","index stop = non_empty_indexes[-1].stop if next_ is None else next_","obj._range if start is None: # This is set by","__getitem__ when we know we have a slice. \"\"\" res","performance reasons is created only when needed. The constructed array","def start(self) -> int: \"\"\" The value of the `start`","is not None else 1 if step == 0: raise","the `step` parameter (``1`` if this was not supplied). \"\"\"","return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method:","Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: #","int (default: 1) dtype : np.int64 Unused, accepted for homogeneity","step_s) if ( (step_s % 2 == 0) and (abs(start_s","= self.step // other stop = start + len(self) *","name=self.name) if len(self) == 1: start = self.start // other","type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def","self.start, self.step end_s = self.start + self.step * (len(self) -","When all members of \"indexes\" are of type RangeIndex: result","\"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2, ) return self.start @property","result.rename(name) if step is not None: next_ = rng[-1] +","def copy( self, name: Hashable = None, deep: bool =","Index or array-like sort : False or None, default None","\"\"\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) ->","start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) # validate the","step : int (default: 1) dtype : np.int64 Unused, accepted","method=method, tolerance=tolerance, limit=limit ) if self.step > 0: start, stop,","name) elif len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex],","None = None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]:","# RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range):","len(self) def __getitem__(self, key): \"\"\" Conserve RangeIndex type for scalar","self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex):","if sort and self.step < 0: codes = codes[::-1] uniques",") from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import","indices, axis: int = 0, allow_fill: bool = True, fill_value=None,","0 length, i.e. were empty. # In this case return","deprecated:: 0.25.0 Use ``stop`` instead. \"\"\" # GH 25710 warnings.warn(","end_o = other.start + other.step * (len(other) - 1) if","result = result.astype(\"float64\") return result except (ValueError, TypeError, ZeroDivisionError): #","first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str))","other.start) elif len(self) == 1: step_s = step_o elif len(other)","_get_data_as_items(self): \"\"\" return a list of tuples of start, stop,","RangeIndex: \"\"\" Create RangeIndex from a range object. Returns -------","= new_index[::-1] if sort is None: new_index = new_index.sort_values() return","rstart = op(left.start, right) rstop = op(left.stop, right) result =","Hashable = None, sort=None): if not isinstance(other, RangeIndex) or sort","step_s == 0 and (start_o + step_s >= start_s) and","return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) ->",": The base pandas Index type. Int64Index : Index of","result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1,","assert isinstance(values, range) result._range = values result._name = name result._cache","TypeError(\"RangeIndex(...) must be called with integers\") start = ensure_python_int(start) if","of start, stop, step \"\"\" rng = self._range return [(\"start\",","extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right = self,","names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name)","sort and self.step < 0: codes = codes[::-1] uniques =","abs(self.step) return self.start + abs(self.step) * no_steps def _extended_gcd(self, a:","we need to catch these explicitly return op(self._int64index, other) elif","start_s, step_s, end_s = end_s, -step_s, start_s if other.step <","# Method hint: linear Diophantine equation # solve intersection problem","int(key) try: return self._range[new_key] except IndexError as err: raise IndexError(","# from the last non-empty index stop = non_empty_indexes[-1].stop if","a: int, b: int) -> tuple[int, int, int]: \"\"\" Extended","locs[valid] = locs[valid] / step if step != self.step: #","`stop` parameter. \"\"\" return self._range.stop @property def _stop(self) -> int:","\"\"\" if isinstance(other, RangeIndex) and sort is None: start_s, step_s","cls._simple_new(start, name=name) # validate the arguments if com.all_none(start, stop, step):","= new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range)","**kwargs) -> np.ndarray: \"\"\" Returns the indices that would sort","-step_o, start_o if len(self) == 1 and len(other) == 1:","supplied). \"\"\" # GH 25710 return self._range.start @property def _start(self)","or (meth == \"max\" and self.step < 0): return self.start","% step == 0) & (locs >= 0) & (target_array","(abs(end_s - end_o) <= step_s / 2) ): return type(self)(start_r,","the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. \"\"\"","int: \"\"\"Returns the smallest element greater than or equal to","self._name return res def _get_data_as_items(self): \"\"\" return a list of",".. deprecated:: 0.25.0 Use ``stop`` instead. \"\"\" # GH 25710","to sort resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex``","import annotations from datetime import timedelta import operator from sys","min(start_s, start_o) end_r = max(end_s, end_o) if step_o == step_s:","@classmethod def _simple_new(cls, values: range, name: Hashable = None) ->","numpy / Int64Index # even if we can represent as","old_t, t = t, old_t - quotient * t return","if non_empty_indexes: # Get the stop value from \"next\" or","the `step` parameter (``1`` if this was not supplied). ..","/ 2) elif step_o % step_s == 0: if (","raise IndexError( f\"index {key} is out of bounds for axis","numpy.ndarray.argsort \"\"\" ascending = kwargs.pop(\"ascending\", True) # EA compat nv.validate_argsort(args,","parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. \"\"\" # GH","An int array that for performance reasons is created only","start, stop = 0, start else: stop = ensure_python_int(stop) step","TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333","`stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. \"\"\" #","return op(self._int64index, other) # TODO: Do attrs get handled reliably?","< 0 and other.step < 0) is not (new_index.step <","rng.start != next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for","== 0) and (abs(start_s - start_o) <= step_s / 2)","for obj in rng_indexes if len(obj)] for obj in non_empty_indexes:","the data deeply, interrogate `object` dtypes for system-level memory consumption","r: quotient = old_r // r old_r, r = r,","RangeIndex \"\"\" if not isinstance(data, range): raise TypeError( f\"{cls.__name__}(...) must","s, old_s - quotient * s old_t, t = t,","indices that would sort the index and its underlying data.","if stop is None: start, stop = 0, start else:","the astype method instead.\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype)","the intersection new_rng = range(first.start, overlap[0], first.step) else: # The","\"\"\" The value of the `stop` parameter. \"\"\" return self._range.stop","_minmax(self, meth: str): no_steps = len(self) - 1 if no_steps","other new_range = range(start, start + 1, 1) return self._simple_new(new_range,","None, sort=None): if not isinstance(other, RangeIndex) or sort is not","result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort)","data deeply, interrogate `object` dtypes for system-level memory consumption Returns","step = self.start, self.stop, self.step else: # GH 28678: work","Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if step is",">= 0) & (target_array < stop) locs[~valid] = -1 locs[valid]","op): \"\"\" Parameters ---------- other : Any op : callable","try: return self._range[new_key] except IndexError as err: raise IndexError( f\"index","return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right = other.difference(self)","tolerance is None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key","the last non-empty index stop = non_empty_indexes[-1].stop if next_ is","Both are immutable so if ._range attr. are equal, shortcut","step_s, step_s) elif step_s % step_o == 0: if (","are not components of the array if deep=False See Also","new_key = int(key) try: return self._range.index(new_key) except ValueError as err:","overlap[0] == first.start: # The difference is everything after the","thru the attributes return None def _format_with_header(self, header: list[str], na_rep:","err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self,","boolean \" \"arrays are valid indices\" ) # fall back","could use # cheaper alternative gcd, s, _ = self._extended_gcd(first.step,","import pandas.core.common as com from pandas.core.construction import extract_array import pandas.core.indexes.base","int: \"\"\" The value of the `start` parameter (``0`` if","return RangeIndex(0, 0).rename(name) def __len__(self) -> int: \"\"\" return the","elif isinstance(start, range): return cls._simple_new(start, name=name) # validate the arguments","= first.step * second.step // gcd new_range = range(tmp_start, int_high,","not be zero\") rng = range(start, stop, step) return cls._simple_new(rng,","a*x + b*y = gcd(x, y) Finds one particular solution","op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs) # for","[operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO: if","other : Any op : callable that accepts 2 params","of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\"min\") def max(self,","the user. Parameters ---------- start : int (default: 0), range,","if not isinstance(data, range): raise TypeError( f\"{cls.__name__}(...) must be called","\" \"ellipsis (`...`), numpy.newaxis (`None`) \" \"and integer or boolean","_shallow_copy(self, values, name: Hashable = no_default): name = self.name if","was not supplied). .. deprecated:: 0.25.0 Use ``step`` instead. \"\"\"","return self.stop @property def step(self) -> int: \"\"\" The value","\"\"\" return the length of the RangeIndex \"\"\" return len(self._range)","Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: #","Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name,","0 and (start_o + step_s >= start_s) and (end_o -","self.step < 0 else self._range overlap = self.intersection(other) if overlap.step","GH 28678: work on reversed range for simplicity reverse =","res = self._cached_int64index res._name = self._name return res def _get_data_as_items(self):","step(left.step, right) # we don't have a representable op #","self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't end up","not None and rng.start != next_ ) if non_consecutive: result","can represent as a RangeIndex, return # as a Float64Index","(``0`` if this was not supplied). .. deprecated:: 0.25.0 Use","Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method","copy : bool, default False Unused, accepted for homogeneity with","\"\"\" return len(self._range) @property def size(self) -> int: return len(self)","def _stop(self) -> int: \"\"\" The value of the `stop`","name=None, dtype: Dtype | None = None ) -> RangeIndex:","return self._range.index(new_key) except ValueError as err: raise KeyError(key) from err","= uniques[::-1] return codes, uniques def equals(self, other: object) ->","return super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0] rng_indexes","self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data,","cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start,","return a base index if not is_integer(rstep) or not rstep:","or equal to the limit\"\"\" no_steps = (upper_limit - self.start)","parameter (``0`` if this was not supplied). \"\"\" # GH","not (new_index.step < 0): new_index = new_index[::-1] if sort is","was not supplied). \"\"\" # GH 25710 return self._range.step @property","to get a RangeIndex back, # but not worth the","be called with integers\") start = ensure_python_int(start) if start is","_getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \"\"\" Fastpath for __getitem__","== 0 and (start_s + step_o >= start_o) and (end_s","we know we have a slice. \"\"\" res = self._range[slobj]","start = self.start // other new_range = range(start, start +","None: start, stop = 0, start else: stop = ensure_python_int(stop)","if is_integer(other) and other != 0: if len(self) == 0","self._simple_new(new_range) if (self.step < 0 and other.step < 0) is","+ len(self) * step new_range = range(start, stop, step or","left.step with np.errstate(all=\"ignore\"): rstart = op(left.start, right) rstop = op(left.stop,","d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None #","isinstance(start, range): return cls._simple_new(start, name=name) # validate the arguments if","step_s = step_o elif len(other) == 1: step_o = step_s","<= int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine equation","GH#19333 is_integer evaluated True on timedelta64, # so we need","step Methods ------- from_range See Also -------- Index : The","> 0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) ->","def symmetric_difference(self, other, result_name: Hashable = None, sort=None): if not","type[Int64Index]: \"\"\" return the class to use for construction \"\"\"","new_index = new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable","return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other,","pandas Index type. Int64Index : Index of int64 data. \"\"\"","RangeIndex, slobj: slice) -> RangeIndex: \"\"\" Fastpath for __getitem__ when","ensure_python_int(stop) step = ensure_python_int(step) if step is not None else","parameters for the RangeIndex describing the # intersection disregarding the","kwargs) return self._minmax(\"max\") def argsort(self, *args, **kwargs) -> np.ndarray: \"\"\"","(start_s - start_o) % step_s == 0 and (start_s -","are delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array","| None = None, copy: bool = False, name: Hashable","start = rng.start if step is None and len(rng) >","\"\"\" Determines if two Index objects contain the same elements.","Constructors def __new__( cls, start=None, stop=None, step=None, dtype: Dtype |","self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing the #","# GH 25710 return self._range.step @property def _step(self) -> int:","def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name:","step_o >= start_o) and (end_s - step_o <= end_o) ):","second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters for the","\"next\" or alternatively # from the last non-empty index stop","sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if self.step","result = result[::-1] return result def factorize( self, sort: bool","other.start, other.step end_o = other.start + other.step * (len(other) -","codes = codes[::-1] uniques = uniques[::-1] return codes, uniques def","None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index =","else other._range # check whether intervals intersect # deals with","the intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif","skipna: bool = True, *args, **kwargs) -> int: \"\"\"The maximum","(start_o + step_s >= start_s) and (end_o - step_s <=","will be RangeIndex if possible, Int64Index otherwise. E.g.: indexes =","else: # GH 28678: work on reversed range for simplicity","length, i.e. were empty. # In this case return an","header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str),","try: return self._range.index(new_key) except ValueError as err: raise KeyError(key) from","* s new_step = first.step * second.step // gcd new_range","% step_s == 0: if ( (start_o - start_s) %","doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import (","extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from","self._simple_new(new_range) # adjust index to limiting interval new_start = new_index._min_fitting_element(int_low)","this was not supplied). \"\"\" # GH 25710 return self._range.step","rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self),","% other == 0 and self.step % other == 0:","while r: quotient = old_r // r old_r, r =","method: str | None = None, limit: int | None","(type(self), d), None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self):","= False, name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype)","step_s / 2) elif step_o % step_s == 0: if","whether element sets intersect if (first.start - second.start) % gcd:","self.difference(other) right = other.difference(self) result = left.union(right) if result_name is","= result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index],","step_s % step_o == 0: if ( (start_s - start_o)","= self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step if","case return an empty range index. return RangeIndex(0, 0).rename(name) def","Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)):","KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def","0 else other._range # check whether intervals intersect # deals","attrs = self._get_data_as_items() if self.name is not None: attrs.append((\"name\", ibase.default_pprint(self.name)))","self._cache return result @doc(Int64Index.copy) def copy( self, name: Hashable =","0) and (abs(start_s - start_o) <= step_s / 2) and","is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import","(\"stop\", rng.stop), (\"step\", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items()))","objects and sorts if possible Parameters ---------- other : Index","end_o = end_o, -step_o, start_o if len(self) == 1 and","if self.name is not None: attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs def","super()._difference(other, sort=sort) if overlap.step != first.step: # In some cases","\"arrays are valid indices\" ) # fall back to Int64Index","warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def","0) step : int (default: 1) dtype : np.int64 Unused,","index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int: \"\"\" return","tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if","deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( \"parameter dtype is","(len(self) - 1) start_o, step_o = other.start, other.step end_o =","yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable =","self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized set operation","result = Int64Index(values) return result.rename(name) step = rng.start - start","-1 locs[valid] = locs[valid] / step if step != self.step:","return type(self)(start_r, end_r + step_s, step_s) if ( (step_s %","from sys import getsizeof from typing import ( TYPE_CHECKING, Any,","-------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) -> Index: \"\"\"","consumption Returns ------- bytes used Notes ----- Memory usage does","= overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if len(overlap)","parent method for the case of all RangeIndex instances. When","0 not in self._range def any(self, *args, **kwargs) -> bool:","FutureWarning, stacklevel=2, ) return self.start @property def stop(self) -> int:","int: \"\"\"The minimum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs)","@property def _int64index(self) -> Int64Index: # wrap _cached_int64index so we","Euclidean algorithms to solve Bezout's identity: a*x + b*y =","step = rng.step elif step is None: # First non-empty","self._range] # -------------------------------------------------------------------- _deprecation_message = ( \"RangeIndex.{} is deprecated and","= self._simple_new(new_range) if (self.step < 0 and other.step < 0)","-> Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill,","2) ): return type(self)(start_r, end_r + step_s / 2, step_s","attr. are equal, shortcut is possible return super()._cmp_method(self, op) return","nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\"min\") def max(self, axis=None, skipna: bool","get_loc(self, key, method=None, tolerance=None): if method is None and tolerance","self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self)","if other.step < 0 else other._range # check whether intervals","in a future version. Use RangeIndex.{} \" \"instead\" ) @property","type for scalar and slice keys. \"\"\" if isinstance(key, slice):","0, 1 t, old_t = 1, 0 r, old_r =","_empty_range = range(0) class RangeIndex(NumericIndex): \"\"\" Immutable Index implementing a","range index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int: \"\"\"","new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] ==","import timedelta import operator from sys import getsizeof from typing","explicit index is provided by the user. Parameters ---------- start","is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method return super()._get_indexer(target,","len(rng) > 1) or ( next_ is not None and","= self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # --------------------------------------------------------------------","not supplied). \"\"\" # GH 25710 return self._range.step @property def","RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex if","1) dtype : np.int64 Unused, accepted for homogeneity with other","= other.start, other.step end_o = other.start + other.step * (len(other)","if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self,","ignore[override] return self._int64index.delete(loc) def take( self, indices, axis: int =","np.arange(len(self), dtype=np.intp) uniques = self if sort and self.step <","all(self, *args, **kwargs) -> bool: return 0 not in self._range","locs[~valid] = -1 locs[valid] = locs[valid] / step if step","this was not supplied). .. deprecated:: 0.25.0 Use ``step`` instead.","# EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result","the index has unique values \"\"\" return True @cache_readonly def","result_name, sort) left = self.difference(other) right = other.difference(self) result =","end_s) ): return type(self)(start_r, end_r + step_s, step_s) elif step_s","\"\"\" Memory usage of my values Parameters ---------- deep :","before the intersection new_rng = range(first.start, overlap[0], first.step) else: #","+ first.step, first.stop, first.step) elif overlap[-1] == first[-1]: # The","if isinstance(other, RangeIndex) and sort is None: start_s, step_s =","len(rng) > 1: step = rng.step elif step is None:","kwargs.pop(\"ascending\", True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step >","first non-empty index start = rng.start if step is None","self.name res = self._cached_int64index res._name = self._name return res def","locs locs[valid] = len(self) - 1 - locs[valid] return ensure_platform_int(locs)","index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start,","stop=None, step=None, dtype: Dtype | None = None, copy: bool","= self.start, self.step end_s = self.start + self.step * (len(self)","performance hint: for identical step sizes, could use # cheaper","object.__new__(cls) assert isinstance(values, range) result._range = values result._name = name","_difference(self, other, sort=None): # optimized set operation if we have","t = t, old_t - quotient * t return old_r,","index has unique values \"\"\" return True @cache_readonly def is_monotonic_increasing(self)","be zero\") rng = range(start, stop, step) return cls._simple_new(rng, name=name)","rng.start - start non_consecutive = (step != rng.step and len(rng)","bool = False, na_sentinel: int | None = -1 )","_concat(self, indexes: list[Index], name: Hashable) -> Index: \"\"\" Overriding parent","data. \"\"\" rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng,","linear Diophantine equation # solve intersection problem # performance hint:","str: return \"integer\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def","self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) ->","overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if len(overlap) ==","the empty indexes non_empty_indexes = [obj for obj in rng_indexes","locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) ->","when no explicit index is provided by the user. Parameters","by the user. Parameters ---------- start : int (default: 0),","/ 2, step_s / 2) elif step_o % step_s ==","header: list[str], na_rep: str = \"NaN\") -> list[str]: if not","indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step = next_","step = self.step // other stop = start + len(self)","step_s = step_o = abs(self.start - other.start) elif len(self) ==","-> int: \"\"\" Return the number of bytes in the","were empty. # In this case return an empty range","getsizeof from typing import ( TYPE_CHECKING, Any, Callable, Hashable, List,","= non_empty_indexes[-1].stop if next_ is None else next_ return RangeIndex(start,","index is provided by the user. Parameters ---------- start :","_simple_new(cls, values: range, name: Hashable = None) -> RangeIndex: result","if com.all_none(start, stop, step): raise TypeError(\"RangeIndex(...) must be called with","if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit","monotonically increasing ``RangeIndex`` if possible or a sorted ``Int64Index`` if","int) -> int: \"\"\"Returns the largest element smaller than or","( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if","The difference is not range-like return super()._difference(other, sort=sort) new_index =","if not. ``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded::","for compat with numpy / Int64Index # even if we","if not isinstance(other, RangeIndex) or sort is not None: return","stop, step = self.start, self.stop, self.step else: # GH 28678:","= op # TODO: if other is a RangeIndex we","ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index,","reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to","of the `start` parameter (``0`` if this was not supplied).","-> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op):",".. versionadded:: 0.25.0 Returns ------- union : Index \"\"\" if","in self._range @property def inferred_type(self) -> str: return \"integer\" #","str = \"NaN\") -> list[str]: if not len(self._range): return header","not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not","\"stop\"), FutureWarning, stacklevel=2, ) return self.stop @property def step(self) ->","two Index objects and sorts if possible Parameters ---------- other","- start_o) % step_s == 0 and (start_s - end_o)","pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as","= maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex): return","sort=sort) def _difference(self, other, sort=None): # optimized set operation if","nv.validate_max(args, kwargs) return self._minmax(\"max\") def argsort(self, *args, **kwargs) -> np.ndarray:","0: start = self.start // other step = self.step //","int_low = max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high","0, allow_fill: bool = True, fill_value=None, **kwargs ) -> Int64Index:","the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\"min\") def max(self, axis=None,","solution for x, y: s, t Returns: gcd, s, t","np.errstate(all=\"ignore\"): rstart = op(left.start, right) rstop = op(left.stop, right) result","if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif","pandas._typing import Dtype from pandas.compat.numpy import function as nv from","(new_index.step < 0): new_index = new_index[::-1] if sort is None:","= \"rangeindex\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \"signed integer\")","rng_indexes = cast(List[RangeIndex], indexes) start = step = next_ =","attr_name in [\"start\", \"stop\", \"step\"] ) def memory_usage(self, deep: bool","ensure_python_int(step) if step is not None else 1 if step","r old_s, s = s, old_s - quotient * s","in- and decreasing ranges int_low = max(first.start, second.start) int_high =","if step is not None: next_ = rng[-1] + step","with np.errstate(all=\"ignore\"): rstep = step(left.step, right) # we don't have","-> np.ndarray: \"\"\" Returns the indices that would sort the","not None: result = result.rename(result_name) return result # -------------------------------------------------------------------- def","TypeError( f\"{cls.__name__}(...) must be called with object coercible to a","nbytes(self) -> int: \"\"\" Return the number of bytes in","a RangeIndex we may have more efficient options other =","Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value,","if overlap[0] == first.start: # The difference is everything after","# optimized set operation if we have another RangeIndex self._validate_sort_keyword(sort)","# -------------------------------------------------------------------- _deprecation_message = ( \"RangeIndex.{} is deprecated and will","or len(self) <= 1 def __contains__(self, key: Any) -> bool:","Dtype from pandas.compat.numpy import function as nv from pandas.util._decorators import","and rng.start != next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values","indices\" ) # fall back to Int64Index return super().__getitem__(key) def","int: \"\"\" Memory usage of my values Parameters ---------- deep","my values Parameters ---------- deep : bool Introspect the data","original locs locs[valid] = len(self) - 1 - locs[valid] return","minimum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\"min\")","return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't end","of \"indexes\" are of type RangeIndex: result will be RangeIndex","pandas.core import ops import pandas.core.common as com from pandas.core.construction import","timedelta import operator from sys import getsizeof from typing import","= self._range[::-1] if self.step < 0 else self._range overlap =","name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result","_extended_gcd(self, a: int, b: int) -> tuple[int, int, int]: \"\"\"","r, old_r - quotient * r old_s, s = s,","``stop`` instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning,","new_step = first.step * second.step // gcd new_range = range(tmp_start,","0.25.0 Use ``step`` instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_step\",","def _min_fitting_element(self, lower_limit: int) -> int: \"\"\"Returns the smallest element","return new_index def symmetric_difference(self, other, result_name: Hashable = None, sort=None):","with RangeIndex, so fall back return super()._difference(other, sort=sort) if overlap.step","self.name if name is no_default else name if values.dtype.kind ==","return self._int64index // other # -------------------------------------------------------------------- # Reductions def all(self,","elif overlap[-1] == first[-1]: # The difference is everything before","even if we can represent as a RangeIndex, return #","as a RangeIndex, return # as a Float64Index if we","intersect if (first.start - second.start) % gcd: return self._simple_new(_empty_range) #","step_o == 0: if ( (start_s - start_o) % step_o","instead. stop : int (default: 0) step : int (default:","array that for performance reasons is created only when needed.","that for performance reasons is created only when needed. The","and tolerance is None: if is_integer(key) or (is_float(key) and key.is_integer()):","data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \"\"\" ascending","<= step_s / 2) ): return type(self)(start_r, end_r + step_s",") -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit):","name=self._name) elif is_integer(key): new_key = int(key) try: return self._range[new_key] except","elif is_integer(key): new_key = int(key) try: return self._range[new_key] except IndexError","meth: str): no_steps = len(self) - 1 if no_steps ==","Using RangeIndex may in some instances improve computing speed. This","str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header","None: # This is set by the first non-empty index","# GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2, ) return","Filter the empty indexes non_empty_indexes = [obj for obj in","# Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if","0) is not (new_index.step < 0): new_index = new_index[::-1] if","Dtype | None = None, names=None, ): name = self._validate_names(name=name,","shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def","None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int)","= rng.start - start non_consecutive = (step != rng.step and","if ( (start_s - start_o) % step_o == 0 and","ops.rtruediv]: step = op # TODO: if other is a","if this was not supplied). .. deprecated:: 0.25.0 Use ``start``","// abs(self.step) return self.start + abs(self.step) * no_steps def _extended_gcd(self,","key: Any) -> bool: hash(key) try: key = ensure_python_int(key) except","end_s) <= step_s ): return type(self)(start_r, end_r + step_s, step_s)","that are not components of the array if deep=False See","None = None, limit: int | None = None, tolerance=None,","limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step","from_range See Also -------- Index : The base pandas Index","Index, sort): \"\"\" Form the union of two Index objects","so fall back return super()._difference(other, sort=sort) if overlap.step != first.step:","RangeIndex(start, stop, step).rename(name) # Here all \"indexes\" had 0 length,",") from err elif is_scalar(key): raise IndexError( \"only integers, slices","def _data(self) -> np.ndarray: \"\"\" An int array that for","@property def _step(self) -> int: \"\"\" The value of the","return self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing the","nv from pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions","s old_t, t = t, old_t - quotient * t","self.step end_s = self.start + self.step * (len(self) - 1)","def _format_data(self, name=None): # we are formatting thru the attributes","axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) ->","* second.step // gcd new_range = range(tmp_start, int_high, new_step) new_index","len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step","step_o <= end_o) ): return type(self)(start_r, end_r + step_o, step_o)","max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high <= int_low:","step = op # TODO: if other is a RangeIndex","op # so return a base index if not is_integer(rstep)","as a Float64Index if we have float-like descriptors if not","\"f\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex)","RangeIndex) or sort is not None: return super().symmetric_difference(other, result_name, sort)","= [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \"\"\" if not all(isinstance(x,","other) elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return","# GH 28678: work on reversed range for simplicity reverse","of the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead.","is None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key =","axis: int = 0, allow_fill: bool = True, fill_value=None, **kwargs","dtype=np.intp) if not ascending: result = result[::-1] return result def","f\"{cls.__name__}(...) must be called with object coercible to a \"","-1, -1, dtype=np.intp) if not ascending: result = result[::-1] return","def memory_usage(self, deep: bool = False) -> int: \"\"\" Memory","np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \"\"\" ascending = kwargs.pop(\"ascending\", True)","not all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes, name)","with np.errstate(all=\"ignore\"): rstart = op(left.start, right) rstop = op(left.stop, right)","= kwargs.pop(\"ascending\", True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step","= other.difference(self) result = left.union(right) if result_name is not None:","Methods def _format_attrs(self): \"\"\" Return a list of tuples of","0: overlap = overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name)","np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return","-> int: \"\"\"The maximum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args,","# -------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index, sort=False):","of the `stop` parameter. \"\"\" return self._range.stop @property def _stop(self)","@doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values,","method=None, tolerance=None): if method is None and tolerance is None:","@property def _start(self) -> int: \"\"\" The value of the","dtype=np.intp) else: result = np.arange(len(self) - 1, -1, -1, dtype=np.intp)","None else 1 if step == 0: raise ValueError(\"Step must","# We reversed this range: transform to original locs locs[valid]","start non_consecutive = (step != rng.step and len(rng) > 1)","deals with in- and decreasing ranges int_low = max(first.start, second.start)","for identical step sizes, could use # cheaper alternative gcd,","solve Bezout's identity: a*x + b*y = gcd(x, y) Finds","rstop, rstep]): result = result.astype(\"float64\") return result except (ValueError, TypeError,","other) step: Callable | None = None if op in","from datetime import timedelta import operator from sys import getsizeof","pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import","accepts 2 params perform the binary op \"\"\" if isinstance(other,","\"only integers, slices (`:`), \" \"ellipsis (`...`), numpy.newaxis (`None`) \"","start, stop, step \"\"\" rng = self._range return [(\"start\", rng.start),","\"\"\" Return a list of tuples of the (attr, formatted_value)","indexes: list[Index], name: Hashable) -> Index: \"\"\" Overriding parent method","simplicity reverse = self._range[::-1] start, stop, step = reverse.start, reverse.stop,","range, or other RangeIndex instance If int and \"stop\" is","uniques = uniques[::-1] return codes, uniques def equals(self, other: object)","ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other)","= max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high <=","\"rangeindex\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \"signed integer\") _can_hold_na","step is None: # First non-empty index had only one","(`:`), \" \"ellipsis (`...`), numpy.newaxis (`None`) \" \"and integer or","super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index,","stop step Methods ------- from_range See Also -------- Index :","FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self) -> int:","end_o) <= step_s and (start_o - end_s) <= step_s ):","step == 0) & (locs >= 0) & (target_array <","dtype: Dtype | None = None, copy: bool = False,","result = left.union(right) if result_name is not None: result =",": bool, default False Unused, accepted for homogeneity with other","the stop value from \"next\" or alternatively # from the","not given, interpreted as \"stop\" instead. stop : int (default:","Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method is","equal to the limit\"\"\" no_steps = -(-(lower_limit - self.start) //","self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default): name",") return self.stop @property def step(self) -> int: \"\"\" The","a representable op # so return a base index if","-------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \"\"\" Return a list","repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self,","-> int: return len(self) def __getitem__(self, key): \"\"\" Conserve RangeIndex","# Both are immutable so if ._range attr. are equal,","Hashable = None, deep: bool = False, dtype: Dtype |","np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance,","-> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method,",") -> Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take( indices, axis=axis,","formatting thru the attributes return None def _format_with_header(self, header: list[str],","return result except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index","return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) # validate","integers, slices (`:`), \" \"ellipsis (`...`), numpy.newaxis (`None`) \" \"and","self.step < 0: codes = codes[::-1] uniques = uniques[::-1] return","elif step_s % step_o == 0: if ( (start_s -","int and \"stop\" is not given, interpreted as \"stop\" instead.","return np.dtype(np.int64) @property def is_unique(self) -> bool: \"\"\" return if","None else next_ return RangeIndex(start, stop, step).rename(name) # Here all","back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice)","the first non-empty index start = rng.start if step is","intersection problem # performance hint: for identical step sizes, could","ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import","not components of the array if deep=False See Also --------","% step_o == 0 and (start_s + step_o >= start_o)","= first.start + (second.start - first.start) * first.step // gcd","method is None and tolerance is None: if is_integer(key) or","= self._name return res def _get_data_as_items(self): \"\"\" return a list","maximum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\"max\")","= 1, 0 r, old_r = b, a while r:","pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import","second.step) # check whether element sets intersect if (first.start -","maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name)","step \"\"\" rng = self._range return [(\"start\", rng.start), (\"stop\", rng.stop),","op(self._int64index, other) if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod,","the same elements. \"\"\" if isinstance(other, RangeIndex): return self._range ==","# The difference is not range-like return super()._difference(other, sort=sort) new_index","end_s = end_s, -step_s, start_s if other.step < 0: start_o,","rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar,","= left.step with np.errstate(all=\"ignore\"): rstart = op(left.start, right) rstop =","-> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range","b: int) -> tuple[int, int, int]: \"\"\" Extended Euclidean algorithms","range) result._range = values result._name = name result._cache = {}","range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step < 0","if start is not None else 0 if stop is","= range(0) class RangeIndex(NumericIndex): \"\"\" Immutable Index implementing a monotonic","def is_unique(self) -> bool: \"\"\" return if the index has","dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property","new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index =","if we can represent as a RangeIndex, return # as","% step_s == 0 and (start_o + step_s >= start_s)","// other stop = start + len(self) * step new_range","% 2 == 0) and (abs(start_s - start_o) <= step_s","else 1 if step == 0: raise ValueError(\"Step must not","None # Filter the empty indexes non_empty_indexes = [obj for","sorted ``Int64Index`` if not. ``sort=False`` always returns an unsorted ``Int64Index``","x in indexes): return super()._concat(indexes, name) elif len(indexes) == 1:","---------- other : Any op : callable that accepts 2","step != self.step: # We reversed this range: transform to","indexes non_empty_indexes = [obj for obj in rng_indexes if len(obj)]","used by DataFrame and Series when no explicit index is","/ step if step != self.step: # We reversed this","t, old_t - quotient * t return old_r, old_s, old_t","self._simple_new(new_range, name=self.name) return self._int64index // other # -------------------------------------------------------------------- # Reductions","return self._simple_new(_empty_range) # Method hint: linear Diophantine equation # solve","of bytes in the underlying data. \"\"\" rng = self._range","RangeIndex \"\"\" return len(self._range) @property def size(self) -> int: return","old_r - quotient * r old_s, s = s, old_s","else: # The difference is not range-like return super()._difference(other, sort=sort)","- quotient * s old_t, t = t, old_t -","self._range.step > 0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self)","checks/conversions/roundings are delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance)","be \" \"removed in a future version. Use RangeIndex.{} \"","cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name: Hashable =","\"stop\", \"step\"] ) def memory_usage(self, deep: bool = False) ->","size(self) -> int: return len(self) def __getitem__(self, key): \"\"\" Conserve","any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex)","Use the astype method instead.\", FutureWarning, stacklevel=2, ) new_index =","start valid = (locs % step == 0) & (locs","self.step < 0): return self.start return self.start + self.step *","constructed array is saved in ``_cache``. \"\"\" return np.arange(self.start, self.stop,","is_scalar(key): raise IndexError( \"only integers, slices (`:`), \" \"ellipsis (`...`),","-> int: \"\"\" The value of the `stop` parameter. ..","evaluated True on timedelta64, # so we need to catch","# -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and","obj in non_empty_indexes: rng = obj._range if start is None:","\"\"\"Returns the largest element smaller than or equal to the","RangeIndex may in some instances improve computing speed. This is","len(self._range): return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length","= None, copy: bool = False, name: Hashable = None,","the (attr, formatted_value) \"\"\" attrs = self._get_data_as_items() if self.name is","E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes =","+ step_s, step_s) elif step_s % step_o == 0: if","is None: # This is set by the first non-empty","`start` parameter (``0`` if this was not supplied). \"\"\" #","= self._range[::-1] if self.step < 0 else self._range second =","bool Introspect the data deeply, interrogate `object` dtypes for system-level","Determines if two Index objects contain the same elements. \"\"\"","result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \"\"\" return","range, name=None, dtype: Dtype | None = None ) ->","return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step >","return # as a Float64Index if we have float-like descriptors","Index, method: str | None = None, limit: int |","version. Use RangeIndex.{} \" \"instead\" ) @property def start(self) ->","bool: hash(key) try: key = ensure_python_int(key) except TypeError: return False","\"stop\" instead. stop : int (default: 0) step : int","object. Returns ------- RangeIndex \"\"\" if not isinstance(data, range): raise","+ 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index // other","0: start, stop, step = self.start, self.stop, self.step else: #","start_s if other.step < 0: start_o, step_o, end_o = end_o,","possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other,","target: Index, method: str | None = None, limit: int","if len(obj)] for obj in non_empty_indexes: rng = obj._range if","# checks/conversions/roundings are delegated to general method return super()._get_indexer(target, method=method,","instances. When all members of \"indexes\" are of type RangeIndex:","\"\"\" # GH 25710 return self._range.step @property def _step(self) ->","type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other): if is_integer(other) and other","is not None else 0 if stop is None: start,","slice keys. \"\"\" if isinstance(key, slice): new_range = self._range[key] return","not supplied). .. deprecated:: 0.25.0 Use ``step`` instead. \"\"\" #","maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from","return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an np.ndarray;","self._get_attributes_dict() left, right = self, other try: # apply if","valid indices\" ) # fall back to Int64Index return super().__getitem__(key)","len(self) - 1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def","or other RangeIndex instance If int and \"stop\" is not","than or equal to the limit\"\"\" no_steps = (upper_limit -","rstep = step(left.step, right) # we don't have a representable","int: \"\"\"Returns the largest element smaller than or equal to","25710 return self._range.start @property def _start(self) -> int: \"\"\" The","# Here all \"indexes\" had 0 length, i.e. were empty.","= rng.start if step is None and len(rng) > 1:","range(first.start, overlap[0], first.step) else: # The difference is not range-like","(default: 0), range, or other RangeIndex instance If int and","sort=sort) if overlap.step != first.step: # In some cases we","special case of Int64Index limited to representing monotonic ranges. Using","result_name is not None: result = result.rename(result_name) return result #","< 0 else self._range second = other._range[::-1] if other.step <","dtype : np.int64 Unused, accepted for homogeneity with other index","not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method return","# Rendering Methods def _format_attrs(self): \"\"\" Return a list of","resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible","0: if ( (start_o - start_s) % step_s == 0",") if non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes]))","that would sort the index and its underlying data. Returns","str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header + [f\"{x:<{max_length}}\" for","== 0: return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name)","RangeIndex): # We won't end up with RangeIndex, so fall","name if values.dtype.kind == \"f\": return Float64Index(values, name=name) return Int64Index._simple_new(values,","\"\"\" Fastpath for __getitem__ when we know we have a","old_r, r = r, old_r - quotient * r old_s,","from pandas.compat.numpy import function as nv from pandas.util._decorators import (","0: start_o, step_o, end_o = end_o, -step_o, start_o if len(self)","\" \"version. Use the astype method instead.\", FutureWarning, stacklevel=2, )","we can represent as a RangeIndex, return # as a","y) Finds one particular solution for x, y: s, t","= type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index =","stop, step or 1) return self._simple_new(new_range, name=self.name) if len(self) ==","alternative gcd, s, _ = self._extended_gcd(first.step, second.step) # check whether","apply if we have an override if step: with np.errstate(all=\"ignore\"):","by DataFrame and Series when no explicit index is provided","new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) -> int: \"\"\"Returns","ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we are formatting","int: \"\"\" The value of the `stop` parameter. \"\"\" return","operator.truediv, ops.rtruediv]: step = op # TODO: if other is","result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name:","members of \"indexes\" are of type RangeIndex: result will be","as np from pandas._libs import index as libindex from pandas._libs.lib","\"\"\" Conserve RangeIndex type for scalar and slice keys. \"\"\"","start = self.start // other step = self.step // other","If int and \"stop\" is not given, interpreted as \"stop\"","= no_default): name = self.name if name is no_default else","Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from","if (self.step < 0 and other.step < 0) is not","1) if self.step < 0: start_s, step_s, end_s = end_s,","bool = False, name: Hashable = None, ) -> RangeIndex:","Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \"\"\" ascending =","annotations from datetime import timedelta import operator from sys import","``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns","index types. name : object, optional Name to be stored","None and len(rng) > 1: step = rng.step elif step","some instances improve computing speed. This is the default index","1 and len(other) == 1: step_s = step_o = abs(self.start","import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import","return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable)","old_t - quotient * t return old_r, old_s, old_t def","stop = 0, start else: stop = ensure_python_int(stop) step =","object) -> bool: \"\"\" Determines if two Index objects contain","is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from","First non-empty index had only one element if rng.start ==","= new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps =","Set Operations def _intersection(self, other: Index, sort=False): if not isinstance(other,","first.start) * first.step // gcd * s new_step = first.step","Name to be stored in the index. Attributes ---------- start","step_o elif len(other) == 1: step_o = step_s start_r =","non-empty index had only one element if rng.start == start:","or self.start % other == 0 and self.step % other","int]: \"\"\" Extended Euclidean algorithms to solve Bezout's identity: a*x","indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3),","with rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs,","from_range( cls, data: range, name=None, dtype: Dtype | None =","is None and len(rng) > 1: step = rng.step elif","np.int64 Unused, accepted for homogeneity with other index types. copy","= r, old_r - quotient * r old_s, s =","not. ``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0","know we have a slice. \"\"\" res = self._range[slobj] return","index start = rng.start if step is None and len(rng)","raise ValueError(\"Step must not be zero\") rng = range(start, stop,","< 0) is not (new_index.step < 0): new_index = new_index[::-1]","a Float64Index if we have float-like descriptors if not all(is_integer(x)",": Any op : callable that accepts 2 params perform","index as libindex from pandas._libs.lib import no_default from pandas._typing import","new_index def _minmax(self, meth: str): no_steps = len(self) - 1","loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take(","ops.get_op_result_name(self, other) first = self._range[::-1] if self.step < 0 else","!= self.step: # We reversed this range: transform to original","def min(self, axis=None, skipna: bool = True, *args, **kwargs) ->","axis=None, skipna: bool = True, *args, **kwargs) -> int: \"\"\"The","new_index = type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index","== 0: if ( (start_s - start_o) % step_o ==","step_s start_r = min(start_s, start_o) end_r = max(end_s, end_o) if","= (step != rng.step and len(rng) > 1) or (","def from_range( cls, data: range, name=None, dtype: Dtype | None","array if deep=False See Also -------- numpy.ndarray.nbytes \"\"\" return self.nbytes","\"\"\" The value of the `stop` parameter. .. deprecated:: 0.25.0",": False or None, default None Whether to sort resulting","b*y = gcd(x, y) Finds one particular solution for x,","element greater than or equal to the limit\"\"\" no_steps =","with numpy / Int64Index # even if we can represent","* t return old_r, old_s, old_t def _union(self, other: Index,","def __new__( cls, start=None, stop=None, step=None, dtype: Dtype | None","= op(left.start, right) rstop = op(left.stop, right) result = type(self)(rstart,","first.stop, first.step) elif overlap[-1] == first[-1]: # The difference is","self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name)","will be \" \"removed in a future version. Use RangeIndex.{}","\"\"\" _typ = \"rangeindex\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype,","result_name: Hashable = None, sort=None): if not isinstance(other, RangeIndex) or","step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings","stop(self) -> int: \"\"\" The value of the `stop` parameter.","index. Attributes ---------- start stop step Methods ------- from_range See","other is a RangeIndex we may have more efficient options","limit\"\"\" no_steps = -(-(lower_limit - self.start) // abs(self.step)) return self.start","we may have more efficient options other = extract_array(other, extract_numpy=True,","1 if step == 0: raise ValueError(\"Step must not be","name=name) @classmethod def from_range( cls, data: range, name=None, dtype: Dtype","type(self)(start_r, end_r + step_s / 2, step_s / 2) elif","(timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64, #","RangeIndex(NumericIndex): \"\"\" Immutable Index implementing a monotonic integer range. RangeIndex","= self.difference(other) right = other.difference(self) result = left.union(right) if result_name","(\"step\", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index,","int) -> tuple[int, int, int]: \"\"\" Extended Euclidean algorithms to","``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union : Index \"\"\"","for x in indexes): return super()._concat(indexes, name) elif len(indexes) ==","next_ is None else next_ return RangeIndex(start, stop, step).rename(name) #","= self.name if name is no_default else name if values.dtype.kind","com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit )","and (end_o - step_s <= end_s) ): return type(self)(start_r, end_r","cast(List[RangeIndex], indexes) start = step = next_ = None #","range object. Returns ------- RangeIndex \"\"\" if not isinstance(data, range):","return result.rename(name) if step is not None: next_ = rng[-1]","{} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) ->","\"\"\" The value of the `start` parameter (``0`` if this","Int64Index(values) return result.rename(name) step = rng.start - start non_consecutive =","is None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit:","import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range =","right = self, other try: # apply if we have","if self.step < 0: start_s, step_s, end_s = end_s, -step_s,","-> np.ndarray: \"\"\" An int array that for performance reasons",") def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self):","len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start","next_ is not None and rng.start != next_ ) if","name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def copy( self,","-> bool: return self._range.step > 0 or len(self) <= 1","range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls,","return self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property","for attr_name in [\"start\", \"stop\", \"step\"] ) def memory_usage(self, deep:","= t, old_t - quotient * t return old_r, old_s,","(second.start - first.start) * first.step // gcd * s new_step","com.all_none(start, stop, step): raise TypeError(\"RangeIndex(...) must be called with integers\")","bool = True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\"Int64Index\",","if ._range attr. are equal, shortcut is possible return super()._cmp_method(self,","gcd new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) #","# fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex,","self.step @cache_readonly def nbytes(self) -> int: \"\"\" Return the number","( (start_o - start_s) % step_s == 0 and (start_o",": object, optional Name to be stored in the index.","= obj._range if start is None: # This is set","self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try: return self._range[new_key]","+ step_s >= start_s) and (end_o - step_s <= end_s)",": Index or array-like sort : False or None, default","if not len(self._range): return header first_val_str = str(self._range[0]) last_val_str =","pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float,","= values result._name = name result._cache = {} result._reset_identity() return","self._range return [(\"start\", rng.start), (\"stop\", rng.stop), (\"step\", rng.step)] def __reduce__(self):","# Constructors def __new__( cls, start=None, stop=None, step=None, dtype: Dtype","False) -> int: \"\"\" Memory usage of my values Parameters","Dtype | None = None ) -> RangeIndex: \"\"\" Create","None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \"\"\" Return","other._range # check whether intervals intersect # deals with in-","computing speed. This is the default index type used by","- 1) if self.step < 0: start_s, step_s, end_s =","this range: transform to original locs locs[valid] = len(self) -","bool: return self._range.step < 0 or len(self) <= 1 def","sorts if possible Parameters ---------- other : Index or array-like","versionadded:: 0.25.0 Returns ------- union : Index \"\"\" if isinstance(other,","# so return a base index if not is_integer(rstep) or","only one element if rng.start == start: values = np.concatenate([x._values","- start_o) % step_o == 0 and (start_s + step_o","import no_default from pandas._typing import Dtype from pandas.compat.numpy import function","0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool:","**kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other,","<= step_s / 2) and (abs(end_s - end_o) <= step_s","True, *args, **kwargs) -> int: \"\"\"The minimum value of the","reversed this range: transform to original locs locs[valid] = len(self)","= True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__):","= op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs) #","RangeIndex if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3,","in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]:","(ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index,","is not None and rng.start != next_ ) if non_consecutive:","no_steps def _extended_gcd(self, a: int, b: int) -> tuple[int, int,","self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def","slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key","user. Parameters ---------- start : int (default: 0), range, or","RangeIndex, so fall back return super()._difference(other, sort=sort) if overlap.step !=","len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0","start=None, stop=None, step=None, dtype: Dtype | None = None, copy:","super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is not","the underlying data. \"\"\" rng = self._range return getsizeof(rng) +","-> type[Int64Index]: \"\"\" return the class to use for construction","None: next_ = rng[-1] + step if non_empty_indexes: # Get","quotient = old_r // r old_r, r = r, old_r","name matches self.name res = self._cached_int64index res._name = self._name return",") -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques =","elements. \"\"\" if isinstance(other, RangeIndex): return self._range == other._range return","than or equal to the limit\"\"\" no_steps = -(-(lower_limit -","axis 0 with size {len(self)}\" ) from err elif is_scalar(key):","other) if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv,","& (locs >= 0) & (target_array < stop) locs[~valid] =","if step is not None else 1 if step ==","_constructor(self) -> type[Int64Index]: \"\"\" return the class to use for","| None = None if op in [operator.mul, ops.rmul, operator.truediv,","from pandas.core import ops import pandas.core.common as com from pandas.core.construction","None: attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we","stop is None: start, stop = 0, start else: stop","_get_indexer( self, target: Index, method: str | None = None,","@classmethod def from_range( cls, data: range, name=None, dtype: Dtype |","value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\"min\") def","if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)]","_format_with_header(self, header: list[str], na_rep: str = \"NaN\") -> list[str]: if","for the case of all RangeIndex instances. When all members","np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not ascending: result","True on timedelta64, # so we need to catch these","\"\"\" Create RangeIndex from a range object. Returns ------- RangeIndex","next_ = None # Filter the empty indexes non_empty_indexes =","memory_usage(self, deep: bool = False) -> int: \"\"\" Memory usage","a list of tuples of start, stop, step \"\"\" rng","for x, y: s, t Returns: gcd, s, t \"\"\"","get a RangeIndex back, # but not worth the effort.","non_empty_indexes[-1].stop if next_ is None else next_ return RangeIndex(start, stop,","if other is a RangeIndex we may have more efficient","libindex from pandas._libs.lib import no_default from pandas._typing import Dtype from","we have float-like descriptors if not all(is_integer(x) for x in","tolerance=tolerance) target_array = np.asarray(target) locs = target_array - start valid","if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name =","to be stored in the index. Attributes ---------- start stop","== \"min\" and self.step > 0) or (meth == \"max\"","won't end up with RangeIndex, so fall back return super()._difference(other,","be RangeIndex if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3),","as err: raise IndexError( f\"index {key} is out of bounds","= new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable =","if len(self) == 1 and len(other) == 1: step_s =","t, old_t = 1, 0 r, old_r = b, a","arguments if com.all_none(start, stop, step): raise TypeError(\"RangeIndex(...) must be called","def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield","_deprecation_message = ( \"RangeIndex.{} is deprecated and will be \"","result[::-1] return result def factorize( self, sort: bool = False,","Finds one particular solution for x, y: s, t Returns:","Here all \"indexes\" had 0 length, i.e. were empty. #","try: key = ensure_python_int(key) except TypeError: return False return key","- start_o) <= step_s / 2) and (abs(end_s - end_o)","(default: 1) dtype : np.int64 Unused, accepted for homogeneity with","right) rstop = op(left.stop, right) result = type(self)(rstart, rstop, rstep,","instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2,","parameter. \"\"\" return self._range.stop @property def _stop(self) -> int: \"\"\"","new_index[::-1] if sort is None: new_index = new_index.sort_values() return new_index","if step is None and len(rng) > 1: step =","not ascending: result = result[::-1] return result def factorize( self,","datetime import timedelta import operator from sys import getsizeof from","self._get_data_as_items() if self.name is not None: attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs","hint: linear Diophantine equation # solve intersection problem # performance","stored in the index. Attributes ---------- start stop step Methods","other: Index, sort): \"\"\" Form the union of two Index","is not None: result = result.rename(result_name) return result # --------------------------------------------------------------------","hint: for identical step sizes, could use # cheaper alternative","int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine equation #","self, name: Hashable = None, deep: bool = False, dtype:","Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range,","default None Whether to sort resulting index. ``sort=None`` returns a","lower bounds tmp_start = first.start + (second.start - first.start) *","\"\"\" ascending = kwargs.pop(\"ascending\", True) # EA compat nv.validate_argsort(args, kwargs)","1) or ( next_ is not None and rng.start !=","__floordiv__(self, other): if is_integer(other) and other != 0: if len(self)","= Int64Index(values) return result.rename(name) step = rng.start - start non_consecutive","None, default None Whether to sort resulting index. ``sort=None`` returns","attributes return None def _format_with_header(self, header: list[str], na_rep: str =","(meth == \"min\" and self.step > 0) or (meth ==","__reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None","int, int]: \"\"\" Extended Euclidean algorithms to solve Bezout's identity:","array-like sort : False or None, default None Whether to","so if ._range attr. are equal, shortcut is possible return","None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range","or a sorted ``Int64Index`` if not. ``sort=False`` always returns an","Memory usage does not include memory consumed by elements that",") -> RangeIndex: \"\"\" Create RangeIndex from a range object.","cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range, name=None, dtype:","------- bytes used Notes ----- Memory usage does not include","= rng[-1] + step if non_empty_indexes: # Get the stop","\"\"\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self,","-> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index:","key, method=None, tolerance=None): if method is None and tolerance is","def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache","1) start_o, step_o = other.start, other.step end_o = other.start +","\"\"\" if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return","__getitem__(self, key): \"\"\" Conserve RangeIndex type for scalar and slice",".. deprecated:: 0.25.0 Use ``start`` instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"),","t return old_r, old_s, old_t def _union(self, other: Index, sort):","RangeIndex back, # but not worth the effort. return super()._difference(other,","- self.start) // abs(self.step) return self.start + abs(self.step) * no_steps","RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result","the case of all RangeIndex instances. When all members of","= np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values) return","import index as libindex from pandas._libs.lib import no_default from pandas._typing","when we know we have a slice. \"\"\" res =","np.ndarray: \"\"\" An int array that for performance reasons is","Use ``step`` instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"),","first.step // gcd * s new_step = first.step * second.step","Memory usage of my values Parameters ---------- deep : bool","-> int: \"\"\" The value of the `stop` parameter. \"\"\"","of tuples of the (attr, formatted_value) \"\"\" attrs = self._get_data_as_items()","/ Int64Index # even if we can represent as a","Form the union of two Index objects and sorts if","stop : int (default: 0) step : int (default: 1)","passed\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values:","\"stop\" is not given, interpreted as \"stop\" instead. stop :","improve computing speed. This is the default index type used","= range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step <","and len(rng) > 1: step = rng.step elif step is","end_s, -step_s, start_s if other.step < 0: start_o, step_o, end_o","0.25.0 Use ``start`` instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2,","0: start_s, step_s, end_s = end_s, -step_s, start_s if other.step","= np.arange(len(self), dtype=np.intp) uniques = self if sort and self.step","@doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default): name =","old_s, s = s, old_s - quotient * s old_t,","rng.step and len(rng) > 1) or ( next_ is not","no_steps def min(self, axis=None, skipna: bool = True, *args, **kwargs)","== other._range: # Both are immutable so if ._range attr.","d), None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \"\"\"","size {len(self)}\" ) from err elif is_scalar(key): raise IndexError( \"only","uniques[::-1] return codes, uniques def equals(self, other: object) -> bool:","of tuples of start, stop, step \"\"\" rng = self._range","# adjust index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range","number of bytes in the underlying data. \"\"\" rng =","an np.ndarray; GH#22390 return op(self._int64index, other) if op in [","all(is_integer(x) for x in [rstart, rstop, rstep]): result = result.astype(\"float64\")","first.start + (second.start - first.start) * first.step // gcd *","import ( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from","= None # Filter the empty indexes non_empty_indexes = [obj","tolerance=None): if method is None and tolerance is None: if","( \"RangeIndex.{} is deprecated and will be \" \"removed in","def argsort(self, *args, **kwargs) -> np.ndarray: \"\"\" Returns the indices","operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index,","0): return self.start return self.start + self.step * no_steps def","if isinstance(other, RangeIndex): return self._range == other._range return super().equals(other) #","element if rng.start == start: values = np.concatenate([x._values for x","Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex:","int_high = min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range)","step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): #","( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from","return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def","identical step sizes, could use # cheaper alternative gcd, s,","always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns -------","\"version. Use the astype method instead.\", FutureWarning, stacklevel=2, ) new_index","step_s) elif step_s % step_o == 0: if ( (start_s","list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy)","with integers\") start = ensure_python_int(start) if start is not None","np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool: \"\"\" return","isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first","called with object coercible to a \" f\"range, {repr(data)} was","!= rng.step and len(rng) > 1) or ( next_ is","if not ascending: result = result[::-1] return result def factorize(","accepted for homogeneity with other index types. name : object,","ops import pandas.core.common as com from pandas.core.construction import extract_array import","t \"\"\" s, old_s = 0, 1 t, old_t =","1: start = self.start // other new_range = range(start, start","= -1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp)","and (start_s + step_o >= start_o) and (end_s - step_o","b, a while r: quotient = old_r // r old_r,","-------- numpy.ndarray.argsort \"\"\" ascending = kwargs.pop(\"ascending\", True) # EA compat","= self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name","err elif is_scalar(key): raise IndexError( \"only integers, slices (`:`), \"","implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer",".. deprecated:: 0.25.0 Use ``step`` instead. \"\"\" # GH 25710","25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly","return self.start + abs(self.step) * no_steps def _extended_gcd(self, a: int,","and self.step % other == 0: start = self.start //","return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \"\"\"","-> bool: hash(key) try: key = ensure_python_int(key) except TypeError: return","pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import","= False _range: range # -------------------------------------------------------------------- # Constructors def __new__(","op(left.start, right) rstop = op(left.stop, right) result = type(self)(rstart, rstop,","rstop = op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs)","instead.\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def","< 0: codes = codes[::-1] uniques = uniques[::-1] return codes,","Returns ------- union : Index \"\"\" if isinstance(other, RangeIndex) and","== first.start: # The difference is everything after the intersection","must be called with object coercible to a \" f\"range,","**kwargs) -> int: \"\"\"The minimum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis)","return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def","Must be an np.ndarray; GH#22390 return op(self._int64index, other) if op","): return type(self)(start_r, end_r + step_s, step_s) elif step_s %","for scalar and slice keys. \"\"\" if isinstance(key, slice): new_range","gcd, s, _ = self._extended_gcd(first.step, second.step) # check whether element","old_r // r old_r, r = r, old_r - quotient","_intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index","is_integer(key): new_key = int(key) try: return self._range[new_key] except IndexError as","elif len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes)","super()._cmp_method(other, op) def _arith_method(self, other, op): \"\"\" Parameters ---------- other","is not self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self,","return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length =","-> bool: return self._range.step < 0 or len(self) <= 1","6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5])","range): raise TypeError( f\"{cls.__name__}(...) must be called with object coercible","int: \"\"\" The value of the `stop` parameter. .. deprecated::","libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \"signed integer\") _can_hold_na = False _range:","try: # apply if we have an override if step:","- 1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self,","not rstep: raise ValueError else: rstep = left.step with np.errstate(all=\"ignore\"):","a slice. \"\"\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\")","formatted_value) \"\"\" attrs = self._get_data_as_items() if self.name is not None:","\"\"\" if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name)","not isinstance(data, range): raise TypeError( f\"{cls.__name__}(...) must be called with","= range(start, stop, step or 1) return self._simple_new(new_range, name=self.name) if","int_high, new_step) new_index = self._simple_new(new_range) # adjust index to limiting","@cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or","ensure_python_int(key) except TypeError: return False return key in self._range @property","= None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step","by the first non-empty index start = rng.start if step","if two Index objects contain the same elements. \"\"\" if","# so we need to catch these explicitly return op(self._int64index,","attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we are","None ) -> RangeIndex: \"\"\" Create RangeIndex from a range","def _arith_method(self, other, op): \"\"\" Parameters ---------- other : Any","self._range @property def inferred_type(self) -> str: return \"integer\" # --------------------------------------------------------------------","first.step: # In some cases we might be able to","np from pandas._libs import index as libindex from pandas._libs.lib import","-> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return","result._cache = self._cache return result @doc(Int64Index.copy) def copy( self, name:","sort=None): if not isinstance(other, RangeIndex) or sort is not None:","other, sort=None): # optimized set operation if we have another","contain the same elements. \"\"\" if isinstance(other, RangeIndex): return self._range","__len__(self) -> int: \"\"\" return the length of the RangeIndex","== other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations def","self.step // other stop = start + len(self) * step","sort: bool = False, na_sentinel: int | None = -1","na_rep: str = \"NaN\") -> list[str]: if not len(self._range): return","% gcd: return self._simple_new(_empty_range) # calculate parameters for the RangeIndex","the indices that would sort the index and its underlying","# even if we can represent as a RangeIndex, return","The value of the `stop` parameter. .. deprecated:: 0.25.0 Use","min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range) # Method","RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\"max\") def argsort(self, *args, **kwargs)","ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering Methods def","largest element smaller than or equal to the limit\"\"\" no_steps","= extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right =","type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self,","GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2, ) return self.stop","we have a slice. \"\"\" res = self._range[slobj] return type(self)._simple_new(res,","return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result =","may have more efficient options other = extract_array(other, extract_numpy=True, extract_range=True)","Int64Index : Index of int64 data. \"\"\" _typ = \"rangeindex\"","supplied). \"\"\" # GH 25710 return self._range.step @property def _step(self)","name=name) # validate the arguments if com.all_none(start, stop, step): raise","may in some instances improve computing speed. This is the","return cls._simple_new(start, name=name) # validate the arguments if com.all_none(start, stop,","# The difference is everything after the intersection new_rng =","implementation return op(self._int64index, other) # TODO: Do attrs get handled","name=self.name) return self._int64index // other # -------------------------------------------------------------------- # Reductions def","= self.start + self.step * (len(self) - 1) start_o, step_o","self.start // other step = self.step // other stop =","0, start else: stop = ensure_python_int(stop) step = ensure_python_int(step) if","range(start, start + 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index","a range object. Returns ------- RangeIndex \"\"\" if not isinstance(data,","= step_o = abs(self.start - other.start) elif len(self) == 1:","worth the effort. return super()._difference(other, sort=sort) if overlap[0] == first.start:","return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is","after the intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step)","== 1: start = self.start // other new_range = range(start,","isinstance(other, RangeIndex) or sort is not None: return super().symmetric_difference(other, result_name,","_engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \"signed integer\") _can_hold_na =","left, right = self, other try: # apply if we","# This is set by the first non-empty index start","``RangeIndex`` if possible or a sorted ``Int64Index`` if not. ``sort=False``","if deep=False See Also -------- numpy.ndarray.nbytes \"\"\" return self.nbytes @property","res def _get_data_as_items(self): \"\"\" return a list of tuples of","is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return op(self._int64index, other)","Int64Index([0,1,2,4,5]) \"\"\" if not all(isinstance(x, RangeIndex) for x in indexes):","# -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats,","argsort(self, *args, **kwargs) -> np.ndarray: \"\"\" Returns the indices that","for x in rng_indexes])) return result.rename(name) if step is not","have a slice. \"\"\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name)","no_default else name if values.dtype.kind == \"f\": return Float64Index(values, name=name)","gcd(x, y) Finds one particular solution for x, y: s,","def _simple_new(cls, values: range, name: Hashable = None) -> RangeIndex:","not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if","the # intersection disregarding the lower bounds tmp_start = first.start","= None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values, range)","\"\"\" Overriding parent method for the case of all RangeIndex","return super()._cmp_method(other, op) def _arith_method(self, other, op): \"\"\" Parameters ----------","`step` parameter (``1`` if this was not supplied). .. deprecated::","allow_fill: bool = True, fill_value=None, **kwargs ) -> Int64Index: with","@property def is_unique(self) -> bool: \"\"\" return if the index","bounds tmp_start = first.start + (second.start - first.start) * first.step","to the limit\"\"\" no_steps = (upper_limit - self.start) // abs(self.step)","from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype,","int, b: int) -> tuple[int, int, int]: \"\"\" Extended Euclidean","def step(self) -> int: \"\"\" The value of the `step`","== 1 and len(other) == 1: step_s = step_o =","len(self) == 1: step_s = step_o elif len(other) == 1:","can be sure its name matches self.name res = self._cached_int64index","np.dtype(np.int64) @property def is_unique(self) -> bool: \"\"\" return if the","self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other): if is_integer(other)","return len(self) def __getitem__(self, key): \"\"\" Conserve RangeIndex type for","for simplicity reverse = self._range[::-1] start, stop, step = reverse.start,","pandas.compat.numpy import function as nv from pandas.util._decorators import ( cache_readonly,","slice. \"\"\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def","``_cache``. \"\"\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self)","_arith_method(self, other, op): \"\"\" Parameters ---------- other : Any op","class to use for construction \"\"\" return Int64Index @cache_readonly def","# -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \"\"\" return the","hash(key) try: key = ensure_python_int(key) except TypeError: return False return","step is None and len(rng) > 1: step = rng.step","not len(self._range): return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1])","Index objects and sorts if possible Parameters ---------- other :","if the index has unique values \"\"\" return True @cache_readonly","__contains__(self, key: Any) -> bool: hash(key) try: key = ensure_python_int(key)","supplied). .. deprecated:: 0.25.0 Use ``start`` instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\",","intervals intersect # deals with in- and decreasing ranges int_low","other.step < 0) is not (new_index.step < 0): new_index =","Index implementing a monotonic integer range. RangeIndex is a memory-saving","= self if sort and self.step < 0: codes =","0 r, old_r = b, a while r: quotient =","0: if len(self) == 0 or self.start % other ==","= int(key) try: return self._range[new_key] except IndexError as err: raise","start is not None else 0 if stop is None:","Float64Index if we have float-like descriptors if not all(is_integer(x) for","difference is everything before the intersection new_rng = range(first.start, overlap[0],","- quotient * r old_s, s = s, old_s -","sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is not self._range:","1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step","self.stop @property def step(self) -> int: \"\"\" The value of","to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) ->","but not worth the effort. return super()._difference(other, sort=sort) if overlap[0]","method for the case of all RangeIndex instances. When all","def __contains__(self, key: Any) -> bool: hash(key) try: key =","list of tuples of the (attr, formatted_value) \"\"\" attrs =","int | None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes","res._name = self._name return res def _get_data_as_items(self): \"\"\" return a","return op(self._int64index, other) if op in [ operator.pow, ops.rpow, operator.mod,","= range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust index","-> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return","TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import warnings import","]: return op(self._int64index, other) step: Callable | None = None","= old_r // r old_r, r = r, old_r -","# intersection disregarding the lower bounds tmp_start = first.start +","*args, **kwargs) -> bool: return 0 not in self._range def","# Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta,","= None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start,","\"\"\" Immutable Index implementing a monotonic integer range. RangeIndex is","not supplied). .. deprecated:: 0.25.0 Use ``start`` instead. \"\"\" warnings.warn(","else self._range second = other._range[::-1] if other.step < 0 else","in some instances improve computing speed. This is the default","@property def start(self) -> int: \"\"\" The value of the","start, stop, step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target):","def _difference(self, other, sort=None): # optimized set operation if we","def any(self, *args, **kwargs) -> bool: return any(self._range) # --------------------------------------------------------------------",": int (default: 0), range, or other RangeIndex instance If","------- RangeIndex \"\"\" if not isinstance(data, range): raise TypeError( f\"{cls.__name__}(...)","from pandas._libs import index as libindex from pandas._libs.lib import no_default","element smaller than or equal to the limit\"\"\" no_steps =","def _constructor(self) -> type[Int64Index]: \"\"\" return the class to use","-------------------------------------------------------------------- _deprecation_message = ( \"RangeIndex.{} is deprecated and will be","and Series when no explicit index is provided by the","int: \"\"\" return the length of the RangeIndex \"\"\" return","-> bool: \"\"\" Determines if two Index objects contain the","-> int: \"\"\" Memory usage of my values Parameters ----------","* no_steps def min(self, axis=None, skipna: bool = True, *args,","= step_o elif len(other) == 1: step_o = step_s start_r","self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step if not","union of two Index objects and sorts if possible Parameters","step_s and (start_o - end_s) <= step_s ): return type(self)(start_r,","self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2, ) return self.start @property def stop(self)","TypeError: return False return key in self._range @property def inferred_type(self)","if ( (start_o - start_s) % step_s == 0 and","Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take( self, indices,","empty indexes non_empty_indexes = [obj for obj in rng_indexes if","not worth the effort. return super()._difference(other, sort=sort) if overlap[0] ==","import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, )","matches self.name res = self._cached_int64index res._name = self._name return res","return None def _format_with_header(self, header: list[str], na_rep: str = \"NaN\")","attr_name)) for attr_name in [\"start\", \"stop\", \"step\"] ) def memory_usage(self,","from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index","bool: \"\"\" return if the index has unique values \"\"\"","def _concat(self, indexes: list[Index], name: Hashable) -> Index: \"\"\" Overriding","Hashable) -> Index: \"\"\" Overriding parent method for the case","we are formatting thru the attributes return None def _format_with_header(self,","for __getitem__ when we know we have a slice. \"\"\"","empty. # In this case return an empty range index.","Returns ------- RangeIndex \"\"\" if not isinstance(data, range): raise TypeError(","The value of the `step` parameter (``1`` if this was","if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start,","able to get a RangeIndex back, # but not worth","@cache_readonly def _constructor(self) -> type[Int64Index]: \"\"\" return the class to","in rng_indexes])) return result.rename(name) if step is not None: next_","= False, dtype: Dtype | None = None, names=None, ):","= self._range return [(\"start\", rng.start), (\"stop\", rng.stop), (\"step\", rng.step)] def","# -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target,","2, step_s / 2) elif step_o % step_s == 0:","an empty range index. return RangeIndex(0, 0).rename(name) def __len__(self) ->","pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex,","else next_ return RangeIndex(start, stop, step).rename(name) # Here all \"indexes\"","is everything after the intersection new_rng = range(overlap[-1] + first.step,","def size(self) -> int: return len(self) def __getitem__(self, key): \"\"\"","return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \"\"\"","include memory consumed by elements that are not components of","(`None`) \" \"and integer or boolean \" \"arrays are valid","# GH#19333 is_integer evaluated True on timedelta64, # so we",": Index of int64 data. \"\"\" _typ = \"rangeindex\" _engine_type","List, cast, ) import warnings import numpy as np from","the array if deep=False See Also -------- numpy.ndarray.nbytes \"\"\" return","is_integer(other) and other != 0: if len(self) == 0 or","raise TypeError( f\"{cls.__name__}(...) must be called with object coercible to","start stop step Methods ------- from_range See Also -------- Index","op # TODO: if other is a RangeIndex we may","Unused, accepted for homogeneity with other index types. name :","length of the RangeIndex \"\"\" return len(self._range) @property def size(self)","# we don't have a representable op # so return","override if step: with np.errstate(all=\"ignore\"): rstep = step(left.step, right) #","Int64Index return super()._intersection(other, sort=sort) if not len(self) or not len(other):","# check whether element sets intersect if (first.start - second.start)","== first[-1]: # The difference is everything before the intersection","= range(start, start + 1, 1) return self._simple_new(new_range, name=self.name) return","step = rng.start - start non_consecutive = (step != rng.step","\"signed integer\") _can_hold_na = False _range: range # -------------------------------------------------------------------- #","err: raise KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method,","objects contain the same elements. \"\"\" if isinstance(other, RangeIndex): return","= max(end_s, end_o) if step_o == step_s: if ( (start_s","[\"start\", \"stop\", \"step\"] ) def memory_usage(self, deep: bool = False)","no_default): name = self.name if name is no_default else name","catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must","return RangeIndex(start, stop, step).rename(name) # Here all \"indexes\" had 0","range): return cls._simple_new(start, name=name) # validate the arguments if com.all_none(start,","- locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None)","return new_index def _min_fitting_element(self, lower_limit: int) -> int: \"\"\"Returns the","self.step % other == 0: start = self.start // other","return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other, op):","= -(-(lower_limit - self.start) // abs(self.step)) return self.start + abs(self.step)","other RangeIndex instance If int and \"stop\" is not given,","return self._range.step @property def _step(self) -> int: \"\"\" The value","getsizeof(getattr(rng, attr_name)) for attr_name in [\"start\", \"stop\", \"step\"] ) def","step_s ): return type(self)(start_r, end_r + step_s, step_s) if (","other, op): \"\"\" Parameters ---------- other : Any op :","we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other)","rstop, rstep, **attrs) # for compat with numpy / Int64Index","the limit\"\"\" no_steps = -(-(lower_limit - self.start) // abs(self.step)) return",") cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range,","== 1: step_s = step_o elif len(other) == 1: step_o","start_o, step_o = other.start, other.step end_o = other.start + other.step","== 0 or self.start % other == 0 and self.step","This is set by the first non-empty index start =","\"\"\" Return the number of bytes in the underlying data.","- 1) start_o, step_o = other.start, other.step end_o = other.start","-> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex","Use RangeIndex.{} \" \"instead\" ) @property def start(self) -> int:","self._range def any(self, *args, **kwargs) -> bool: return any(self._range) #","> 0) or (meth == \"max\" and self.step < 0):","= self.start, self.stop, self.step else: # GH 28678: work on","next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for x in","return the class to use for construction \"\"\" return Int64Index","with in- and decreasing ranges int_low = max(first.start, second.start) int_high","return self._int64index.delete(loc) def take( self, indices, axis: int = 0,","# -------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None, step=None,","indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \"\"\" if not","cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name:","# Get the stop value from \"next\" or alternatively #","is no_default else name if values.dtype.kind == \"f\": return Float64Index(values,","fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take(","not all(is_integer(x) for x in [rstart, rstop, rstep]): result =","bytes used Notes ----- Memory usage does not include memory","= min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range) #","def _get_data_as_items(self): \"\"\" return a list of tuples of start,","if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if","is set by the first non-empty index start = rng.start","# performance hint: for identical step sizes, could use #","key = ensure_python_int(key) except TypeError: return False return key in","step is not None else 1 if step == 0:","< 0 or len(self) <= 1 def __contains__(self, key: Any)","``step`` instead. \"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning,","or equal to the limit\"\"\" no_steps = -(-(lower_limit - self.start)","@cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step > 0 or","start: values = np.concatenate([x._values for x in rng_indexes]) result =","of the `step` parameter (``1`` if this was not supplied).","supplied). .. deprecated:: 0.25.0 Use ``step`` instead. \"\"\" # GH","int: \"\"\" Return the number of bytes in the underlying","if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod,","``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible or a","* first.step // gcd * s new_step = first.step *","import Index _empty_range = range(0) class RangeIndex(NumericIndex): \"\"\" Immutable Index","if step != self.step: # We reversed this range: transform","if self.step < 0 else self._range second = other._range[::-1] if","start_o) % step_o == 0 and (start_s + step_o >=","stop) locs[~valid] = -1 locs[valid] = locs[valid] / step if","-> int: \"\"\"Returns the largest element smaller than or equal","0) & (target_array < stop) locs[~valid] = -1 locs[valid] =","# check whether intervals intersect # deals with in- and",">= start_o) and (end_s - step_o <= end_o) ): return","import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name","another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not","is None else next_ return RangeIndex(start, stop, step).rename(name) # Here","None: # First non-empty index had only one element if","new_index = self._simple_new(new_range) # adjust index to limiting interval new_start","Callable, Hashable, List, cast, ) import warnings import numpy as","of Int64Index limited to representing monotonic ranges. Using RangeIndex may","len(self._range) @property def size(self) -> int: return len(self) def __getitem__(self,","if len(self) == 0 or self.start % other == 0","rstep]): result = result.astype(\"float64\") return result except (ValueError, TypeError, ZeroDivisionError):","tuples of the (attr, formatted_value) \"\"\" attrs = self._get_data_as_items() if","__new__( cls, start=None, stop=None, step=None, dtype: Dtype | None =","new_index = self._rename(name=name) if dtype: warnings.warn( \"parameter dtype is deprecated","slobj: slice) -> RangeIndex: \"\"\" Fastpath for __getitem__ when we","ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO: if other","== 0) & (locs >= 0) & (target_array < stop)","dtypes for system-level memory consumption Returns ------- bytes used Notes","not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other)","< 0 else other._range # check whether intervals intersect #","self._simple_new(new_range, name=self.name) if len(self) == 1: start = self.start //","cases we might be able to get a RangeIndex back,","new_range = range(start, stop, step or 1) return self._simple_new(new_range, name=self.name)","raise KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance)","- other.start) elif len(self) == 1: step_s = step_o elif","new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps = len(self)","len(self) == 1: start = self.start // other new_range =","else self._range overlap = self.intersection(other) if overlap.step < 0: overlap","general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs","step_s / 2) and (abs(end_s - end_o) <= step_s /","union : Index \"\"\" if isinstance(other, RangeIndex) and sort is","was not supplied). .. deprecated:: 0.25.0 Use ``start`` instead. \"\"\"","is_monotonic_increasing(self) -> bool: return self._range.step > 0 or len(self) <=","elif is_scalar(key): raise IndexError( \"only integers, slices (`:`), \" \"ellipsis","accepted for homogeneity with other index types. copy : bool,","for construction \"\"\" return Int64Index @cache_readonly def _data(self) -> np.ndarray:","as libindex from pandas._libs.lib import no_default from pandas._typing import Dtype","need to catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other):","Series when no explicit index is provided by the user.","(start_o - start_s) % step_s == 0 and (start_o +","-> Index: \"\"\" Overriding parent method for the case of","% step_o == 0: if ( (start_s - start_o) %","and len(rng) > 1) or ( next_ is not None","-> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index:","def inferred_type(self) -> str: return \"integer\" # -------------------------------------------------------------------- # Indexing","int (default: 0), range, or other RangeIndex instance If int","Dtype | None = None, copy: bool = False, name:","RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] ->","if method is None and tolerance is None: if is_integer(key)","in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO:","deeply, interrogate `object` dtypes for system-level memory consumption Returns -------","-> Int64Index([0,1,2,4,5]) \"\"\" if not all(isinstance(x, RangeIndex) for x in","overlap.step != first.step: # In some cases we might be","new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step","as nv from pandas.util._decorators import ( cache_readonly, doc, ) from","return np.nan elif (meth == \"min\" and self.step > 0)","if rng.start == start: values = np.concatenate([x._values for x in","Any op : callable that accepts 2 params perform the","pandas.core.common as com from pandas.core.construction import extract_array import pandas.core.indexes.base as","(is_float(key) and key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except","\" \"and integer or boolean \" \"arrays are valid indices\"","possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] ->","underlying data. \"\"\" rng = self._range return getsizeof(rng) + sum(","target_array = np.asarray(target) locs = target_array - start valid =","return True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step >","step_s == 0: if ( (start_o - start_s) % step_s","self.step > 0) or (meth == \"max\" and self.step <","-------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None):","intersection new_rng = range(first.start, overlap[0], first.step) else: # The difference","def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range ==","_range: range # -------------------------------------------------------------------- # Constructors def __new__( cls, start=None,","def __len__(self) -> int: \"\"\" return the length of the","intersect # deals with in- and decreasing ranges int_low =","return an empty range index. return RangeIndex(0, 0).rename(name) def __len__(self)","_max_fitting_element(self, upper_limit: int) -> int: \"\"\"Returns the largest element smaller","step_s, step_s) if ( (step_s % 2 == 0) and","result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if",") -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) #","y: s, t Returns: gcd, s, t \"\"\" s, old_s","op(self._int64index, other) step: Callable | None = None if op","back return super()._difference(other, sort=sort) if overlap.step != first.step: # In","0: codes = codes[::-1] uniques = uniques[::-1] return codes, uniques","(step != rng.step and len(rng) > 1) or ( next_","= len(self) - 1 if no_steps == -1: return np.nan","0 and (start_s + step_o >= start_o) and (end_s -","sort=sort) if not len(self) or not len(other): return self._simple_new(_empty_range) first","True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__): return","sizes, could use # cheaper alternative gcd, s, _ =","Extended Euclidean algorithms to solve Bezout's identity: a*x + b*y","1) return self._simple_new(new_range, name=self.name) if len(self) == 1: start =","a memory-saving special case of Int64Index limited to representing monotonic","tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance,","import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as com","not isinstance(other, RangeIndex) or sort is not None: return super().symmetric_difference(other,","None = None ) -> RangeIndex: \"\"\" Create RangeIndex from","2) and (abs(end_s - end_o) <= step_s / 2) ):","to use for construction \"\"\" return Int64Index @cache_readonly def _data(self)","homogeneity with other index types. name : object, optional Name","Index objects contain the same elements. \"\"\" if isinstance(other, RangeIndex):","RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \"\"\" if not all(isinstance(x, RangeIndex) for","be sure its name matches self.name res = self._cached_int64index res._name","be called with object coercible to a \" f\"range, {repr(data)}","> 1: step = rng.step elif step is None: #","None Whether to sort resulting index. ``sort=None`` returns a monotonically","from err elif is_scalar(key): raise IndexError( \"only integers, slices (`:`),","**kwargs) -> int: \"\"\"The maximum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis)","1, 0 r, old_r = b, a while r: quotient","divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable | None","values result._name = name result._cache = {} result._reset_identity() return result","\"\"\" rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name))","other.step * (len(other) - 1) if self.step < 0: start_s,","sure its name matches self.name res = self._cached_int64index res._name =","self.start) // abs(self.step)) return self.start + abs(self.step) * no_steps def","Whether to sort resulting index. ``sort=None`` returns a monotonically increasing","old_t def _union(self, other: Index, sort): \"\"\" Form the union","if self.step < 0 else self._range overlap = self.intersection(other) if","rng.start), (\"stop\", rng.stop), (\"step\", rng.step)] def __reduce__(self): d = self._get_attributes_dict()","<= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step <","sets intersect if (first.start - second.start) % gcd: return self._simple_new(_empty_range)","is not None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other)","type RangeIndex: result will be RangeIndex if possible, Int64Index otherwise.","one element if rng.start == start: values = np.concatenate([x._values for","have more efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs","= -1 locs[valid] = locs[valid] / step if step !=","[obj for obj in rng_indexes if len(obj)] for obj in","equal to the limit\"\"\" no_steps = (upper_limit - self.start) //","= other._range[::-1] if other.step < 0 else other._range # check","0 or self.start % other == 0 and self.step %","+ abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) -> int:","result @doc(Int64Index.copy) def copy( self, name: Hashable = None, deep:","return if the index has unique values \"\"\" return True","deep: bool = False) -> int: \"\"\" Memory usage of","stop, step): raise TypeError(\"RangeIndex(...) must be called with integers\") start","start_o) end_r = max(end_s, end_o) if step_o == step_s: if","\"min\" and self.step > 0) or (meth == \"max\" and","indexes) start = step = next_ = None # Filter","delete(self, loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def","or 1) return self._simple_new(new_range, name=self.name) if len(self) == 1: start","getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\"start\", \"stop\",","NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas","two Index objects contain the same elements. \"\"\" if isinstance(other,","= self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name","-------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None, step=None, dtype:","or sort is not None: return super().symmetric_difference(other, result_name, sort) left","RangeIndex type for scalar and slice keys. \"\"\" if isinstance(key,",") if self.step > 0: start, stop, step = self.start,","result = result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes:","< 0): return self.start return self.start + self.step * no_steps","some cases we might be able to get a RangeIndex","method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array - start","self.step: # We reversed this range: transform to original locs","\"\"\" if isinstance(other, RangeIndex): return self._range == other._range return super().equals(other)","= type(self)(rstart, rstop, rstep, **attrs) # for compat with numpy","0: result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) -","type(self)(start_r, end_r + step_s, step_s) elif step_s % step_o ==","we have an override if step: with np.errstate(all=\"ignore\"): rstep =","adjust index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range =","else name if values.dtype.kind == \"f\": return Float64Index(values, name=name) return","step: with np.errstate(all=\"ignore\"): rstep = step(left.step, right) # we don't","len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): #","immutable so if ._range attr. are equal, shortcut is possible","if first is not self._range: new_index = new_index[::-1] return new_index","int: return len(self) def __getitem__(self, key): \"\"\" Conserve RangeIndex type","len(self) <= 1 def __contains__(self, key: Any) -> bool: hash(key)","s, t Returns: gcd, s, t \"\"\" s, old_s =","start_o, step_o, end_o = end_o, -step_o, start_o if len(self) ==","= None, sort=None): if not isinstance(other, RangeIndex) or sort is","usage of my values Parameters ---------- deep : bool Introspect","bool: \"\"\" Determines if two Index objects contain the same","== 0: if ( (start_o - start_s) % step_s ==","RangeIndex.{} \" \"instead\" ) @property def start(self) -> int: \"\"\"","stacklevel=2, ) return self.start @property def stop(self) -> int: \"\"\"","-> Int64Index: # wrap _cached_int64index so we can be sure","in ``_cache``. \"\"\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def","no_default from pandas._typing import Dtype from pandas.compat.numpy import function as","interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index","return self.start + self.step * no_steps def min(self, axis=None, skipna:","copy( self, name: Hashable = None, deep: bool = False,","the number of bytes in the underlying data. \"\"\" rng","step_s == 0 and (start_s - end_o) <= step_s and","return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: # wrap","gcd, s, t \"\"\" s, old_s = 0, 1 t,","sort): \"\"\" Form the union of two Index objects and","cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start,","self.step < 0 else self._range second = other._range[::-1] if other.step","name = maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex):","in self._range] # -------------------------------------------------------------------- _deprecation_message = ( \"RangeIndex.{} is deprecated","had only one element if rng.start == start: values =","effort. return super()._difference(other, sort=sort) if overlap[0] == first.start: # The","of two Index objects and sorts if possible Parameters ----------","step_o == 0 and (start_s + step_o >= start_o) and","step if non_empty_indexes: # Get the stop value from \"next\"","_view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache =","): return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort)","._range attr. are equal, shortcut is possible return super()._cmp_method(self, op)","to representing monotonic ranges. Using RangeIndex may in some instances","( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common","RangeIndex is a memory-saving special case of Int64Index limited to","Attributes ---------- start stop step Methods ------- from_range See Also","rng_indexes if len(obj)] for obj in non_empty_indexes: rng = obj._range","= next_ = None # Filter the empty indexes non_empty_indexes",") return self.step @cache_readonly def nbytes(self) -> int: \"\"\" Return","sort resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if","0) & (locs >= 0) & (target_array < stop) locs[~valid]","is None: # First non-empty index had only one element","def _union(self, other: Index, sort): \"\"\" Form the union of","greater than or equal to the limit\"\"\" no_steps = -(-(lower_limit","def factorize( self, sort: bool = False, na_sentinel: int |","a base index if not is_integer(rstep) or not rstep: raise","1: step_s = step_o = abs(self.start - other.start) elif len(self)","= self._get_attributes_dict() left, right = self, other try: # apply","overlap = self.intersection(other) if overlap.step < 0: overlap = overlap[::-1]","everything before the intersection new_rng = range(first.start, overlap[0], first.step) else:","values.dtype.kind == \"f\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def","old_s - quotient * s old_t, t = t, old_t","other, op): if isinstance(other, RangeIndex) and self._range == other._range: #","op) return super()._cmp_method(other, op) def _arith_method(self, other, op): \"\"\" Parameters","an override if step: with np.errstate(all=\"ignore\"): rstep = step(left.step, right)","range for simplicity reverse = self._range[::-1] start, stop, step =","@doc(Int64Index.copy) def copy( self, name: Hashable = None, deep: bool","): return type(self)(start_r, end_r + step_s, step_s) if ( (step_s","integer\") _can_hold_na = False _range: range # -------------------------------------------------------------------- # Constructors","method instead.\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index","was passed\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls,","from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int,","0 and self.step % other == 0: start = self.start","a RangeIndex, return # as a Float64Index if we have","tuples of start, stop, step \"\"\" rng = self._range return","GH#22390 return op(self._int64index, other) if op in [ operator.pow, ops.rpow,","28678: work on reversed range for simplicity reverse = self._range[::-1]","| None = None ) -> RangeIndex: \"\"\" Create RangeIndex","cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import","rng.stop), (\"step\", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return","with other index types. name : object, optional Name to","numpy.newaxis (`None`) \" \"and integer or boolean \" \"arrays are","None and tolerance is None: if is_integer(key) or (is_float(key) and","types. name : object, optional Name to be stored in","Int64Index # even if we can represent as a RangeIndex,","wrap _cached_int64index so we can be sure its name matches","# -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) -> bool:","max_length = max(len(first_val_str), len(last_val_str)) return header + [f\"{x:<{max_length}}\" for x","start_o) % step_s == 0 and (start_s - end_o) <=","# GH 25710 return self._range.start @property def _start(self) -> int:","step(self) -> int: \"\"\" The value of the `step` parameter","self._int64index.delete(loc) def take( self, indices, axis: int = 0, allow_fill:","= libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \"signed integer\") _can_hold_na = False","non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name)","warnings.warn( \"parameter dtype is deprecated and will be removed in","repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc)","int64 data. \"\"\" _typ = \"rangeindex\" _engine_type = libindex.Int64Engine _dtype_validation_metadata","def _step(self) -> int: \"\"\" The value of the `step`","a list of tuples of the (attr, formatted_value) \"\"\" attrs","a while r: quotient = old_r // r old_r, r","header + [f\"{x:<{max_length}}\" for x in self._range] # -------------------------------------------------------------------- _deprecation_message","zero\") rng = range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod","(``0`` if this was not supplied). \"\"\" # GH 25710","return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try: return","particular solution for x, y: s, t Returns: gcd, s,","key in self._range @property def inferred_type(self) -> str: return \"integer\"","is provided by the user. Parameters ---------- start : int","to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): #","**kwargs ) -> Int64Index: with rewrite_exception(\"Int64Index\", type(self).__name__): return self._int64index.take( indices,","rstep: raise ValueError else: rstep = left.step with np.errstate(all=\"ignore\"): rstart","except ValueError as err: raise KeyError(key) from err raise KeyError(key)","old_s, old_t def _union(self, other: Index, sort): \"\"\" Form the","(end_s - step_o <= end_o) ): return type(self)(start_r, end_r +","super()._difference(other, sort=sort) if overlap[0] == first.start: # The difference is","will be removed in a future \" \"version. Use the","new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable = None,","-> RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range =","interpreted as \"stop\" instead. stop : int (default: 0) step","attrs = self._get_attributes_dict() left, right = self, other try: #","timedelta64, # so we need to catch these explicitly return","the smallest element greater than or equal to the limit\"\"\"","False _range: range # -------------------------------------------------------------------- # Constructors def __new__( cls,","# GH 25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2, ) return","\"\"\"The minimum value of the RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return","to limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop,","res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\"__floordiv__\") def __floordiv__(self, other):","overlap[-1] == first[-1]: # The difference is everything before the","start_o) and (end_s - step_o <= end_o) ): return type(self)(start_r,","= object.__new__(cls) assert isinstance(values, range) result._range = values result._name =","self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in","ranges. Using RangeIndex may in some instances improve computing speed.","np.asarray(target) locs = target_array - start valid = (locs %","Defer to Int64Index implementation return op(self._int64index, other) # TODO: Do","is not None: attrs.append((\"name\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None):","no_steps = len(self) - 1 if no_steps == -1: return","and (end_s - step_o <= end_o) ): return type(self)(start_r, end_r","possible or a sorted ``Int64Index`` if not. ``sort=False`` always returns","in rng_indexes if len(obj)] for obj in non_empty_indexes: rng =","elif len(self) == 1: step_s = step_o elif len(other) ==","% other == 0: start = self.start // other step","The value of the `stop` parameter. \"\"\" return self._range.stop @property","def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self)","abs(self.start - other.start) elif len(self) == 1: step_s = step_o","ValueError else: rstep = left.step with np.errstate(all=\"ignore\"): rstart = op(left.start,",": callable that accepts 2 params perform the binary op","have a representable op # so return a base index","needed. The constructed array is saved in ``_cache``. \"\"\" return","= step_s start_r = min(start_s, start_o) end_r = max(end_s, end_o)","-------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \"\"\" return the class","int) -> int: \"\"\"Returns the smallest element greater than or","x in [rstart, rstop, rstep]): result = result.astype(\"float64\") return result","the length of the RangeIndex \"\"\" return len(self._range) @property def","Return a list of tuples of the (attr, formatted_value) \"\"\"","monotonic integer range. RangeIndex is a memory-saving special case of","name = self.name if name is no_default else name if","_step(self) -> int: \"\"\" The value of the `step` parameter","the default index type used by DataFrame and Series when","not supplied). \"\"\" # GH 25710 return self._range.start @property def","return key in self._range @property def inferred_type(self) -> str: return","in self._range def any(self, *args, **kwargs) -> bool: return any(self._range)","(abs(start_s - start_o) <= step_s / 2) and (abs(end_s -","if sort is None: new_index = new_index.sort_values() return new_index def","self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return","\"start\"), FutureWarning, stacklevel=2, ) return self.start @property def stop(self) ->","instead. \"\"\" warnings.warn( self._deprecation_message.format(\"_start\", \"start\"), FutureWarning, stacklevel=2, ) return self.start","self.step * no_steps def min(self, axis=None, skipna: bool = True,","= np.asarray(target) locs = target_array - start valid = (locs","False, name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name","reversed range for simplicity reverse = self._range[::-1] start, stop, step","// abs(self.step)) return self.start + abs(self.step) * no_steps def _max_fitting_element(self,","quotient * s old_t, t = t, old_t - quotient","gcd * s new_step = first.step * second.step // gcd","super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if","x in rng_indexes])) return result.rename(name) if step is not None:","intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1]","we can be sure its name matches self.name res =","= None, deep: bool = False, dtype: Dtype | None","np.errstate(all=\"ignore\"): rstep = step(left.step, right) # we don't have a","* (len(self) - 1) start_o, step_o = other.start, other.step end_o","these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be","-------- Index : The base pandas Index type. Int64Index :","0), range, or other RangeIndex instance If int and \"stop\"","second.stop) if int_high <= int_low: return self._simple_new(_empty_range) # Method hint:","RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) #","if start is None: # This is set by the","second = other._range[::-1] if other.step < 0 else other._range #","def _shallow_copy(self, values, name: Hashable = no_default): name = self.name","_int64index(self) -> Int64Index: # wrap _cached_int64index so we can be","= ensure_python_int(step) if step is not None else 1 if","more efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs =","return self._range.step < 0 or len(self) <= 1 def __contains__(self,","@doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method is None","Int64Index @cache_readonly def _data(self) -> np.ndarray: \"\"\" An int array","scalar and slice keys. \"\"\" if isinstance(key, slice): new_range =","lower_limit: int) -> int: \"\"\"Returns the smallest element greater than","unique values \"\"\" return True @cache_readonly def is_monotonic_increasing(self) -> bool:","limit\"\"\" no_steps = (upper_limit - self.start) // abs(self.step) return self.start","is not (new_index.step < 0): new_index = new_index[::-1] if sort","new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key =","= end_s, -step_s, start_s if other.step < 0: start_o, step_o,","return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index:","Get the stop value from \"next\" or alternatively # from","s, old_s = 0, 1 t, old_t = 1, 0","out of bounds for axis 0 with size {len(self)}\" )","identity: a*x + b*y = gcd(x, y) Finds one particular","i.e. were empty. # In this case return an empty","stacklevel=2, ) return self.stop @property def step(self) -> int: \"\"\"","True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0:","-> int: \"\"\" The value of the `step` parameter (``1``","int | None = None, tolerance=None, ) -> np.ndarray: #","len(self) - 1 if no_steps == -1: return np.nan elif","kwargs) if self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else:","------- union : Index \"\"\" if isinstance(other, RangeIndex) and sort","other) first = self._range[::-1] if self.step < 0 else self._range","as \"stop\" instead. stop : int (default: 0) step :","None = None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp]","the `start` parameter (``0`` if this was not supplied). \"\"\"","\"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2, )","as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import (","from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base","0 or len(self) <= 1 def __contains__(self, key: Any) ->","----- Memory usage does not include memory consumed by elements","else: result = np.arange(len(self) - 1, -1, -1, dtype=np.intp) if","new_step) new_index = self._simple_new(new_range) # adjust index to limiting interval","a monotonically increasing ``RangeIndex`` if possible or a sorted ``Int64Index``","-------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis)","(locs % step == 0) & (locs >= 0) &","(self.step < 0 and other.step < 0) is not (new_index.step","\"\"\" # GH 25710 warnings.warn( self._deprecation_message.format(\"_step\", \"step\"), FutureWarning, stacklevel=2, )","RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first =","pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception","disregarding the lower bounds tmp_start = first.start + (second.start -","RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \"\"\" if","return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index:","value of the `step` parameter (``1`` if this was not","In this case return an empty range index. return RangeIndex(0,","other index types. name : object, optional Name to be","def max(self, axis=None, skipna: bool = True, *args, **kwargs) ->","the lower bounds tmp_start = first.start + (second.start - first.start)","# but not worth the effort. return super()._difference(other, sort=sort) if","if ( (step_s % 2 == 0) and (abs(start_s -","# type: ignore[override] return self._int64index.delete(loc) def take( self, indices, axis:","elif len(other) == 1: step_o = step_s start_r = min(start_s,","_cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) ->","if not all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes,","/ 2) and (abs(end_s - end_o) <= step_s / 2)","result def factorize( self, sort: bool = False, na_sentinel: int","type used by DataFrame and Series when no explicit index","== 0 and (start_o + step_s >= start_s) and (end_o","RangeIndex\"\"\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\"min\") def max(self, axis=None, skipna:","limited to representing monotonic ranges. Using RangeIndex may in some","-------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index, sort=False): if","@cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def","self._range == other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations","first = self._range[::-1] if self.step < 0 else self._range second","end_r + step_s, step_s) elif step_s % step_o == 0:","end_o) if step_o == step_s: if ( (start_s - start_o)","set operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other,","\"\"\" # GH 25710 return self._range.start @property def _start(self) ->","right) result = type(self)(rstart, rstop, rstep, **attrs) # for compat","0) or (meth == \"max\" and self.step < 0): return","-> int: \"\"\"Returns the smallest element greater than or equal","skipna: bool = True, *args, **kwargs) -> int: \"\"\"The minimum","== start: values = np.concatenate([x._values for x in rng_indexes]) result","name : object, optional Name to be stored in the",": bool Introspect the data deeply, interrogate `object` dtypes for","import ops import pandas.core.common as com from pandas.core.construction import extract_array","isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not len(self)","not None else 1 if step == 0: raise ValueError(\"Step","interrogate `object` dtypes for system-level memory consumption Returns ------- bytes","# The difference is everything before the intersection new_rng =","\"step\"] ) def memory_usage(self, deep: bool = False) -> int:","na_sentinel: int | None = -1 ) -> tuple[np.ndarray, RangeIndex]:","the binary op \"\"\" if isinstance(other, ABCTimedeltaIndex): # Defer to","ascending = kwargs.pop(\"ascending\", True) # EA compat nv.validate_argsort(args, kwargs) if","== len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We","self._int64index // other # -------------------------------------------------------------------- # Reductions def all(self, *args,","> 1) or ( next_ is not None and rng.start","operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name","ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable","0 with size {len(self)}\" ) from err elif is_scalar(key): raise","if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented","RangeIndex we may have more efficient options other = extract_array(other,","except IndexError as err: raise IndexError( f\"index {key} is out","new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step < 0 and","if is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key) try:","of the (attr, formatted_value) \"\"\" attrs = self._get_data_as_items() if self.name","all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes, name) elif","step = ensure_python_int(step) if step is not None else 1","is not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name)","for homogeneity with other index types. copy : bool, default","str | None = None, limit: int | None =","0).rename(name) def __len__(self) -> int: \"\"\" return the length of","self._simple_new(_empty_range) # Method hint: linear Diophantine equation # solve intersection","left = self.difference(other) right = other.difference(self) result = left.union(right) if","options other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left,","not is_integer(rstep) or not rstep: raise ValueError else: rstep =","0 if stop is None: start, stop = 0, start","<= end_s) ): return type(self)(start_r, end_r + step_s, step_s) elif","so we can be sure its name matches self.name res","<= end_o) ): return type(self)(start_r, end_r + step_o, step_o) return","except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation return","RangeIndex describing the # intersection disregarding the lower bounds tmp_start","the attributes return None def _format_with_header(self, header: list[str], na_rep: str","cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step) # check","and key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except ValueError","(target_array < stop) locs[~valid] = -1 locs[valid] = locs[valid] /",") def memory_usage(self, deep: bool = False) -> int: \"\"\"","end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other,","and self.step < 0: codes = codes[::-1] uniques = uniques[::-1]","== 0: start = self.start // other step = self.step","# deals with in- and decreasing ranges int_low = max(first.start,","op) def _arith_method(self, other, op): \"\"\" Parameters ---------- other :","@property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self)","\"removed in a future version. Use RangeIndex.{} \" \"instead\" )","from pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex): \"\"\"","1 def __contains__(self, key: Any) -> bool: hash(key) try: key","import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric","equals(self, other: object) -> bool: \"\"\" Determines if two Index","last non-empty index stop = non_empty_indexes[-1].stop if next_ is None","return type(self)(start_r, end_r + step_s / 2, step_s / 2)","as com from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase","start else: stop = ensure_python_int(stop) step = ensure_python_int(step) if step","= range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] == first[-1]:","return super()._intersection(other, sort=sort) if not len(self) or not len(other): return","smallest element greater than or equal to the limit\"\"\" no_steps","if not len(self) or not len(other): return self._simple_new(_empty_range) first =","ascending: result = result[::-1] return result def factorize( self, sort:","RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other,","alternatively # from the last non-empty index stop = non_empty_indexes[-1].stop","s = s, old_s - quotient * s old_t, t","return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated","step_s = self.start, self.step end_s = self.start + self.step *","other._range: # Both are immutable so if ._range attr. are","def nbytes(self) -> int: \"\"\" Return the number of bytes","[RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)]","op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op #","def stop(self) -> int: \"\"\" The value of the `stop`","{key} is out of bounds for axis 0 with size","RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not len(self) or","new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) ->","result._cache = {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def","codes[::-1] uniques = uniques[::-1] return codes, uniques def equals(self, other:","np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer(","): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if","and (abs(end_s - end_o) <= step_s / 2) ): return","warnings.warn( self._deprecation_message.format(\"_stop\", \"stop\"), FutureWarning, stacklevel=2, ) return self.stop @property def","Any, Callable, Hashable, List, cast, ) import warnings import numpy","of the array if deep=False See Also -------- numpy.ndarray.nbytes \"\"\"","\"\"\" An int array that for performance reasons is created","else: stop = ensure_python_int(stop) step = ensure_python_int(step) if step is","= target_array - start valid = (locs % step ==",") @property def start(self) -> int: \"\"\" The value of","self.intersection(other) if overlap.step < 0: overlap = overlap[::-1] if len(overlap)","(``1`` if this was not supplied). .. deprecated:: 0.25.0 Use","return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step =","overlap.step < 0: overlap = overlap[::-1] if len(overlap) == 0:","slices (`:`), \" \"ellipsis (`...`), numpy.newaxis (`None`) \" \"and integer","+ self.step * no_steps def min(self, axis=None, skipna: bool =","is saved in ``_cache``. \"\"\" return np.arange(self.start, self.stop, self.step, dtype=np.int64)","= codes[::-1] uniques = uniques[::-1] return codes, uniques def equals(self,","represent as a RangeIndex, return # as a Float64Index if","if result_name is not None: result = result.rename(result_name) return result","last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header +","ValueError(\"Step must not be zero\") rng = range(start, stop, step)","None = None, copy: bool = False, name: Hashable =","from pandas._typing import Dtype from pandas.compat.numpy import function as nv","x in rng_indexes]) result = Int64Index(values) return result.rename(name) step =","def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self) ->","if values.dtype.kind == \"f\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name)","range(0) class RangeIndex(NumericIndex): \"\"\" Immutable Index implementing a monotonic integer","Callable | None = None if op in [operator.mul, ops.rmul,","from pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions import","if step: with np.errstate(all=\"ignore\"): rstep = step(left.step, right) # we","In some cases we might be able to get a","np.ndarray; GH#22390 return op(self._int64index, other) if op in [ operator.pow,","self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) ->","must not be zero\") rng = range(start, stop, step) return","return self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0 else","import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer","is deprecated and will be \" \"removed in a future","# We won't end up with RangeIndex, so fall back","\"and integer or boolean \" \"arrays are valid indices\" )","consumed by elements that are not components of the array","isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key):","or None, default None Whether to sort resulting index. ``sort=None``","= np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1, -1,","\"ellipsis (`...`), numpy.newaxis (`None`) \" \"and integer or boolean \"","!= first.step: # In some cases we might be able","describing the # intersection disregarding the lower bounds tmp_start =","- quotient * t return old_r, old_s, old_t def _union(self,","deprecated and will be \" \"removed in a future version.","parameter (``1`` if this was not supplied). .. deprecated:: 0.25.0","self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: # type: ignore[override]","1) return self._simple_new(new_range, name=self.name) return self._int64index // other # --------------------------------------------------------------------","self._range.start @property def _start(self) -> int: \"\"\" The value of","is a memory-saving special case of Int64Index limited to representing","None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step =","+ step_s, step_s) if ( (step_s % 2 == 0)","self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap,","other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other,","_cached_int64index so we can be sure its name matches self.name","= reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are","The difference is everything before the intersection new_rng = range(first.start,","on reversed range for simplicity reverse = self._range[::-1] start, stop,","return res def _get_data_as_items(self): \"\"\" return a list of tuples","True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step > 0","start = ensure_python_int(start) if start is not None else 0","# -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \"\"\" Return a","`start` parameter (``0`` if this was not supplied). .. deprecated::","name=name) def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name)","to catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): #"],"string":"[\n \"def _extended_gcd(self, a: int, b: int) -> tuple[int, int, int]:\",\n \"self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0 else self._range\",\n \"array is saved in ``_cache``. \\\"\\\"\\\" return np.arange(self.start, self.stop, self.step,\",\n \"(attr, formatted_value) \\\"\\\"\\\" attrs = self._get_data_as_items() if self.name is not\",\n \"ops.rdivmod, ]: return op(self._int64index, other) step: Callable | None =\",\n \"# First non-empty index had only one element if rng.start\",\n \"- 1 if no_steps == -1: return np.nan elif (meth\",\n \"of bounds for axis 0 with size {len(self)}\\\" ) from\",\n \"from pandas._libs.lib import no_default from pandas._typing import Dtype from pandas.compat.numpy\",\n \"in the index. Attributes ---------- start stop step Methods -------\",\n \"This is the default index type used by DataFrame and\",\n \"+ (second.start - first.start) * first.step // gcd * s\",\n \"rng_indexes]) result = Int64Index(values) return result.rename(name) step = rng.start -\",\n \"@cache_readonly def _data(self) -> np.ndarray: \\\"\\\"\\\" An int array that\",\n \"self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name =\",\n \"self, sort: bool = False, na_sentinel: int | None =\",\n \"fall back return super()._difference(other, sort=sort) if overlap.step != first.step: #\",\n \"def __getitem__(self, key): \\\"\\\"\\\" Conserve RangeIndex type for scalar and\",\n \"self._range.step < 0 or len(self) <= 1 def __contains__(self, key:\",\n \"method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs =\",\n \"\\\"\\\"\\\" Form the union of two Index objects and sorts\",\n \"0: return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if\",\n \"+ step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None):\",\n \"= ( \\\"RangeIndex.{} is deprecated and will be \\\" \\\"removed\",\n \"empty range index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int:\",\n \"in non_empty_indexes: rng = obj._range if start is None: #\",\n \"= max(len(first_val_str), len(last_val_str)) return header + [f\\\"{x:<{max_length}}\\\" for x in\",\n \"**kwargs) -> bool: return 0 not in self._range def any(self,\",\n \"otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes\",\n \"check whether intervals intersect # deals with in- and decreasing\",\n \"def _minmax(self, meth: str): no_steps = len(self) - 1 if\",\n \"1, -1, -1, dtype=np.intp) if not ascending: result = result[::-1]\",\n \"self, other try: # apply if we have an override\",\n \"RangeIndex, return # as a Float64Index if we have float-like\",\n \"ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return\",\n \"Parameters ---------- other : Any op : callable that accepts\",\n \"TypeError, ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index, other)\",\n \"the effort. return super()._difference(other, sort=sort) if overlap[0] == first.start: #\",\n \"bool = False, dtype: Dtype | None = None, names=None,\",\n \"(`...`), numpy.newaxis (`None`) \\\" \\\"and integer or boolean \\\" \\\"arrays\",\n \"if name is no_default else name if values.dtype.kind == \\\"f\\\":\",\n \"isinstance(other, RangeIndex) and self._range == other._range: # Both are immutable\",\n \"method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method: str |\",\n \"perform the binary op \\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex): # Defer\",\n \"end_r = max(end_s, end_o) if step_o == step_s: if (\",\n \"25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2, ) return self.stop @property\",\n \"base pandas Index type. Int64Index : Index of int64 data.\",\n \"abs(self.step) * no_steps def _extended_gcd(self, a: int, b: int) ->\",\n \"have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if\",\n \"other.step < 0 else other._range # check whether intervals intersect\",\n \"if len(overlap) == 0: return self.rename(name=res_name) if len(overlap) == len(self):\",\n \"is created only when needed. The constructed array is saved\",\n \"def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def\",\n \"return result @doc(Int64Index.copy) def copy( self, name: Hashable = None,\",\n \"other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right\",\n \"other stop = start + len(self) * step new_range =\",\n \"return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range, name=None,\",\n \"target_array - start valid = (locs % step == 0)\",\n \"**kwargs, ) def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def\",\n \"Parameters ---------- start : int (default: 0), range, or other\",\n \"res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if self.step <\",\n \"_union(self, other: Index, sort): \\\"\\\"\\\" Form the union of two\",\n \"returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union\",\n \"if possible Parameters ---------- other : Index or array-like sort\",\n \"for x in rng_indexes]) result = Int64Index(values) return result.rename(name) step\",\n \"@property def stop(self) -> int: \\\"\\\"\\\" The value of the\",\n \"None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key)\",\n \"first = self._range[::-1] if self.step < 0 else self._range overlap\",\n \"right = other.difference(self) result = left.union(right) if result_name is not\",\n \"Methods ------- from_range See Also -------- Index : The base\",\n \"values, name: Hashable = no_default): name = self.name if name\",\n \"< 0): new_index = new_index[::-1] if sort is None: new_index\",\n \"FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def _minmax(self,\",\n \"return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if not\",\n \"extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right = self, other\",\n \"import getsizeof from typing import ( TYPE_CHECKING, Any, Callable, Hashable,\",\n \"import Dtype from pandas.compat.numpy import function as nv from pandas.util._decorators\",\n \"< stop) locs[~valid] = -1 locs[valid] = locs[valid] / step\",\n \"# Int64Index return super()._intersection(other, sort=sort) if not len(self) or not\",\n \"(start_s + step_o >= start_o) and (end_s - step_o <=\",\n \"warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2, ) return self.start @property def\",\n \"return self.start return self.start + self.step * no_steps def min(self,\",\n \"range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first\",\n \"integer range. RangeIndex is a memory-saving special case of Int64Index\",\n \"- end_o) <= step_s / 2) ): return type(self)(start_r, end_r\",\n \"is a RangeIndex we may have more efficient options other\",\n \"= cast(List[RangeIndex], indexes) start = step = next_ = None\",\n \"\\\"\\\"\\\" Parameters ---------- other : Any op : callable that\",\n \"this was not supplied). .. deprecated:: 0.25.0 Use ``start`` instead.\",\n \"self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self, other, result_name:\",\n \"\\\"\\\"\\\" return self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64)\",\n \"system-level memory consumption Returns ------- bytes used Notes ----- Memory\",\n \"if we have float-like descriptors if not all(is_integer(x) for x\",\n \"- start_s) % step_s == 0 and (start_o + step_s\",\n \"bool = True, *args, **kwargs) -> int: \\\"\\\"\\\"The minimum value\",\n \"or not rstep: raise ValueError else: rstep = left.step with\",\n \"deep: bool = False, dtype: Dtype | None = None,\",\n \"RangeIndex) for x in indexes): return super()._concat(indexes, name) elif len(indexes)\",\n \"np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64, # so\",\n \"def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d),\",\n \"\\\"parameter dtype is deprecated and will be removed in a\",\n \"Hashable, List, cast, ) import warnings import numpy as np\",\n \"def _intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex): #\",\n \"if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method\",\n \"return old_r, old_s, old_t def _union(self, other: Index, sort): \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" rng = self._range return [(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\",\",\n \"not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): #\",\n \"return Int64Index @cache_readonly def _data(self) -> np.ndarray: \\\"\\\"\\\" An int\",\n \"None def _format_with_header(self, header: list[str], na_rep: str = \\\"NaN\\\") ->\",\n \"quotient * r old_s, s = s, old_s - quotient\",\n \"step is not None: next_ = rng[-1] + step if\",\n \"Immutable Index implementing a monotonic integer range. RangeIndex is a\",\n \"@property def inferred_type(self) -> str: return \\\"integer\\\" # -------------------------------------------------------------------- #\",\n \"second.step // gcd new_range = range(tmp_start, int_high, new_step) new_index =\",\n \"-> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\"\",\n \"len(self) * step new_range = range(start, stop, step or 1)\",\n \"# calculate parameters for the RangeIndex describing the # intersection\",\n \"other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self,\",\n \"# In this case return an empty range index. return\",\n \"KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index,\",\n \"self._cached_int64index res._name = self._name return res def _get_data_as_items(self): \\\"\\\"\\\" return\",\n \"IndexError( f\\\"index {key} is out of bounds for axis 0\",\n \"other: object) -> bool: \\\"\\\"\\\" Determines if two Index objects\",\n \"dtype: warnings.warn( \\\"parameter dtype is deprecated and will be removed\",\n \"(meth == \\\"max\\\" and self.step < 0): return self.start return\",\n \"IndexError as err: raise IndexError( f\\\"index {key} is out of\",\n \"cast, ) import warnings import numpy as np from pandas._libs\",\n \"data. \\\"\\\"\\\" _typ = \\\"rangeindex\\\" _engine_type = libindex.Int64Engine _dtype_validation_metadata =\",\n \"(step_s % 2 == 0) and (abs(start_s - start_o) <=\",\n \"uniques = self if sort and self.step < 0: codes\",\n \"(``1`` if this was not supplied). \\\"\\\"\\\" # GH 25710\",\n \"in a future \\\" \\\"version. Use the astype method instead.\\\",\",\n \"Overriding parent method for the case of all RangeIndex instances.\",\n \"NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True\",\n \"// gcd * s new_step = first.step * second.step //\",\n \"def _start(self) -> int: \\\"\\\"\\\" The value of the `start`\",\n \"& (target_array < stop) locs[~valid] = -1 locs[valid] = locs[valid]\",\n \"new_index def symmetric_difference(self, other, result_name: Hashable = None, sort=None): if\",\n \"_dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na = False _range: range\",\n \"None else 0 if stop is None: start, stop =\",\n \"list[str]: if not len(self._range): return header first_val_str = str(self._range[0]) last_val_str\",\n \"range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust index to\",\n \"None = None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0]\",\n \"not len(self) or not len(other): return self._simple_new(_empty_range) first = self._range[::-1]\",\n \"stop value from \\\"next\\\" or alternatively # from the last\",\n \"had 0 length, i.e. were empty. # In this case\",\n \"self.start, self.stop, self.step else: # GH 28678: work on reversed\",\n \"type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def copy(\",\n \"------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\",\",\n \"if step_o == step_s: if ( (start_s - start_o) %\",\n \"value from \\\"next\\\" or alternatively # from the last non-empty\",\n \"= {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self)\",\n \"pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range\",\n \"only when needed. The constructed array is saved in ``_cache``.\",\n \"are formatting thru the attributes return None def _format_with_header(self, header:\",\n \"step sizes, could use # cheaper alternative gcd, s, _\",\n \"all RangeIndex instances. When all members of \\\"indexes\\\" are of\",\n \"for x in [rstart, rstop, rstep]): result = result.astype(\\\"float64\\\") return\",\n \"s new_step = first.step * second.step // gcd new_range =\",\n \"0.25.0 Returns ------- union : Index \\\"\\\"\\\" if isinstance(other, RangeIndex)\",\n \"next_ return RangeIndex(start, stop, step).rename(name) # Here all \\\"indexes\\\" had\",\n \"IndexError( \\\"only integers, slices (`:`), \\\" \\\"ellipsis (`...`), numpy.newaxis (`None`)\",\n \"self._minmax(\\\"min\\\") def max(self, axis=None, skipna: bool = True, *args, **kwargs)\",\n \"and will be \\\" \\\"removed in a future version. Use\",\n \"data: range, name=None, dtype: Dtype | None = None )\",\n \"usage does not include memory consumed by elements that are\",\n \"*args, **kwargs) -> int: \\\"\\\"\\\"The maximum value of the RangeIndex\\\"\\\"\\\"\",\n \"sort is None: start_s, step_s = self.start, self.step end_s =\",\n \"is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or len(self) <=\",\n \"codes = np.arange(len(self), dtype=np.intp) uniques = self if sort and\",\n \"d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering\",\n \"self._range.index(new_key) except ValueError as err: raise KeyError(key) from err raise\",\n \"Returns ------- bytes used Notes ----- Memory usage does not\",\n \"\\\"\\\"\\\" return self._range.stop @property def _stop(self) -> int: \\\"\\\"\\\" The\",\n \"// r old_r, r = r, old_r - quotient *\",\n \"class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index implementing a monotonic integer range.\",\n \"step_s / 2, step_s / 2) elif step_o % step_s\",\n \"GH 25710 return self._range.start @property def _start(self) -> int: \\\"\\\"\\\"\",\n \"return self._range.start @property def _start(self) -> int: \\\"\\\"\\\" The value\",\n \"= ensure_python_int(key) except TypeError: return False return key in self._range\",\n \"copy: bool = False, name: Hashable = None, ) ->\",\n \"base index if not is_integer(rstep) or not rstep: raise ValueError\",\n \"== 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start =\",\n \"< 0: start_s, step_s, end_s = end_s, -step_s, start_s if\",\n \"+ abs(self.step) * no_steps def _extended_gcd(self, a: int, b: int)\",\n \"tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self if\",\n \"for x in self._range] # -------------------------------------------------------------------- _deprecation_message = ( \\\"RangeIndex.{}\",\n \"isinstance(other, RangeIndex): return self._range == other._range return super().equals(other) # --------------------------------------------------------------------\",\n \"step_o, end_o = end_o, -step_o, start_o if len(self) == 1\",\n \"# apply if we have an override if step: with\",\n \"= None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if\",\n \"take( self, indices, axis: int = 0, allow_fill: bool =\",\n \"= self._simple_new(new_range) # adjust index to limiting interval new_start =\",\n \"construction \\\"\\\"\\\" return Int64Index @cache_readonly def _data(self) -> np.ndarray: \\\"\\\"\\\"\",\n \"start is None: # This is set by the first\",\n \"We won't end up with RangeIndex, so fall back return\",\n \"= 0, allow_fill: bool = True, fill_value=None, **kwargs ) ->\",\n \"= str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header + [f\\\"{x:<{max_length}}\\\"\",\n \"and will be removed in a future \\\" \\\"version. Use\",\n \"new_index def _min_fitting_element(self, lower_limit: int) -> int: \\\"\\\"\\\"Returns the smallest\",\n \"quotient * t return old_r, old_s, old_t def _union(self, other:\",\n \"!= next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for x\",\n \"extract_range=True) attrs = self._get_attributes_dict() left, right = self, other try:\",\n \"left.union(right) if result_name is not None: result = result.rename(result_name) return\",\n \"Int64Index: # wrap _cached_int64index so we can be sure its\",\n \"start(self) -> int: \\\"\\\"\\\" The value of the `start` parameter\",\n \"locs[valid] = len(self) - 1 - locs[valid] return ensure_platform_int(locs) #\",\n \"is None: start, stop = 0, start else: stop =\",\n \"memory consumed by elements that are not components of the\",\n \"(start_o - end_s) <= step_s ): return type(self)(start_r, end_r +\",\n \"0 else self._range overlap = self.intersection(other) if overlap.step < 0:\",\n \"= self.start // other step = self.step // other stop\",\n \"com from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from\",\n \"[rstart, rstop, rstep]): result = result.astype(\\\"float64\\\") return result except (ValueError,\",\n \"= None, limit: int | None = None, tolerance=None, )\",\n \"of my values Parameters ---------- deep : bool Introspect the\",\n \"step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range,\",\n \"-> list[str]: if not len(self._range): return header first_val_str = str(self._range[0])\",\n \"- start valid = (locs % step == 0) &\",\n \"is deprecated and will be removed in a future \\\"\",\n \"Also -------- numpy.ndarray.argsort \\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\", True) # EA\",\n \"start = step = next_ = None # Filter the\",\n \"and (abs(start_s - start_o) <= step_s / 2) and (abs(end_s\",\n \"return len(self._range) @property def size(self) -> int: return len(self) def\",\n \"range. RangeIndex is a memory-saving special case of Int64Index limited\",\n \"// gcd new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range)\",\n \"== 0: raise ValueError(\\\"Step must not be zero\\\") rng =\",\n \"and slice keys. \\\"\\\"\\\" if isinstance(key, slice): new_range = self._range[key]\",\n \"axis=axis) def delete(self, loc) -> Int64Index: # type: ignore[override] return\",\n \"memory consumption Returns ------- bytes used Notes ----- Memory usage\",\n \"\\\"\\\"\\\" if not isinstance(data, range): raise TypeError( f\\\"{cls.__name__}(...) must be\",\n \"+ b*y = gcd(x, y) Finds one particular solution for\",\n \"// other step = self.step // other stop = start\",\n \"elif step is None: # First non-empty index had only\",\n \"\\\"max\\\" and self.step < 0): return self.start return self.start +\",\n \"components of the array if deep=False See Also -------- numpy.ndarray.nbytes\",\n \"value of the `stop` parameter. \\\"\\\"\\\" return self._range.stop @property def\",\n \"step).rename(name) # Here all \\\"indexes\\\" had 0 length, i.e. were\",\n \"\\\"\\\"\\\" return the class to use for construction \\\"\\\"\\\" return\",\n \"dtype=np.intp) uniques = self if sort and self.step < 0:\",\n \"return 0 not in self._range def any(self, *args, **kwargs) ->\",\n \"Also -------- numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes @property def dtype(self) ->\",\n \"warnings import numpy as np from pandas._libs import index as\",\n \"indexes): return super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0]\",\n \"non_consecutive = (step != rng.step and len(rng) > 1) or\",\n \"self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else: result =\",\n \"check whether element sets intersect if (first.start - second.start) %\",\n \"all \\\"indexes\\\" had 0 length, i.e. were empty. # In\",\n \"created only when needed. The constructed array is saved in\",\n \"int: \\\"\\\"\\\"The maximum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs)\",\n \"+ step if non_empty_indexes: # Get the stop value from\",\n \"r, old_r = b, a while r: quotient = old_r\",\n \"= self.intersection(other) if overlap.step < 0: overlap = overlap[::-1] if\",\n \"of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\") def argsort(self,\",\n \"range(start, stop, step or 1) return self._simple_new(new_range, name=self.name) if len(self)\",\n \"if TYPE_CHECKING: from pandas import Index _empty_range = range(0) class\",\n \"# TODO: if other is a RangeIndex we may have\",\n \"len(last_val_str)) return header + [f\\\"{x:<{max_length}}\\\" for x in self._range] #\",\n \"given, interpreted as \\\"stop\\\" instead. stop : int (default: 0)\",\n \"int_high <= int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine\",\n \"start, cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif\",\n \"def _get_indexer( self, target: Index, method: str | None =\",\n \"\\\"indexes\\\" had 0 length, i.e. were empty. # In this\",\n \"(is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na = False _range: range # --------------------------------------------------------------------\",\n \"any(self, *args, **kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def\",\n \"list[str], na_rep: str = \\\"NaN\\\") -> list[str]: if not len(self._range):\",\n \"self._range overlap = self.intersection(other) if overlap.step < 0: overlap =\",\n \"from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common\",\n \"in indexes): return super()._concat(indexes, name) elif len(indexes) == 1: return\",\n \"params perform the binary op \\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex): #\",\n \"symmetric_difference(self, other, result_name: Hashable = None, sort=None): if not isinstance(other,\",\n \"0 else self._range second = other._range[::-1] if other.step < 0\",\n \"| None = None, tolerance=None, ) -> np.ndarray: # ->\",\n \"step_o = abs(self.start - other.start) elif len(self) == 1: step_s\",\n \"might be able to get a RangeIndex back, # but\",\n \"a sorted ``Int64Index`` if not. ``sort=False`` always returns an unsorted\",\n \"0: raise ValueError(\\\"Step must not be zero\\\") rng = range(start,\",\n \"are equal, shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other,\",\n \"None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls)\",\n \"= new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) -> int:\",\n \"\\\"\\\"\\\" return if the index has unique values \\\"\\\"\\\" return\",\n \"# Filter the empty indexes non_empty_indexes = [obj for obj\",\n \"smaller than or equal to the limit\\\"\\\"\\\" no_steps = (upper_limit\",\n \"super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other, op): \\\"\\\"\\\"\",\n \"`step` parameter (``1`` if this was not supplied). \\\"\\\"\\\" #\",\n \"Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: # wrap _cached_int64index\",\n \"representable op # so return a base index if not\",\n \"name: Hashable = None, deep: bool = False, dtype: Dtype\",\n \"problem # performance hint: for identical step sizes, could use\",\n \"rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for\",\n \"self._extended_gcd(first.step, second.step) # check whether element sets intersect if (first.start\",\n \"= True, *args, **kwargs) -> int: \\\"\\\"\\\"The maximum value of\",\n \"int(key) try: return self._range.index(new_key) except ValueError as err: raise KeyError(key)\",\n \"first.start: # The difference is everything after the intersection new_rng\",\n \"super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step > 0:\",\n \"_data(self) -> np.ndarray: \\\"\\\"\\\" An int array that for performance\",\n \"or ( next_ is not None and rng.start != next_\",\n \"1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step < 0\",\n \"RangeIndex from a range object. Returns ------- RangeIndex \\\"\\\"\\\" if\",\n \"of the RangeIndex \\\"\\\"\\\" return len(self._range) @property def size(self) ->\",\n \"step_s, end_s = end_s, -step_s, start_s if other.step < 0:\",\n \"-> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take( self,\",\n \"( TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import warnings\",\n \"is the default index type used by DataFrame and Series\",\n \"RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range = values\",\n \"limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step)\",\n \"super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0] rng_indexes =\",\n \"None: result = result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self,\",\n \"does not include memory consumed by elements that are not\",\n \"= [obj for obj in rng_indexes if len(obj)] for obj\",\n \"self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( \\\"parameter\",\n \"Return the number of bytes in the underlying data. \\\"\\\"\\\"\",\n \"return self._simple_new(new_range, name=self.name) if len(self) == 1: start = self.start\",\n \"= step(left.step, right) # we don't have a representable op\",\n \"called with integers\\\") start = ensure_python_int(start) if start is not\",\n \"return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other): if is_integer(other) and\",\n \"from a range object. Returns ------- RangeIndex \\\"\\\"\\\" if not\",\n \"name=self.name) @property def _int64index(self) -> Int64Index: # wrap _cached_int64index so\",\n \"self.start @property def stop(self) -> int: \\\"\\\"\\\" The value of\",\n \"dtype is deprecated and will be removed in a future\",\n \"__iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable\",\n \"Notes ----- Memory usage does not include memory consumed by\",\n \"* s old_t, t = t, old_t - quotient *\",\n \"rng = obj._range if start is None: # This is\",\n \"if not isinstance(overlap, RangeIndex): # We won't end up with\",\n \"len(other) == 1: step_o = step_s start_r = min(start_s, start_o)\",\n \"2) elif step_o % step_s == 0: if ( (start_o\",\n \"to Int64Index implementation return op(self._int64index, other) # TODO: Do attrs\",\n \"+ self.step * (len(self) - 1) start_o, step_o = other.start,\",\n \"<= step_s and (start_o - end_s) <= step_s ): return\",\n \"are of type RangeIndex: result will be RangeIndex if possible,\",\n \"monotonic ranges. Using RangeIndex may in some instances improve computing\",\n \"\\\" \\\"removed in a future version. Use RangeIndex.{} \\\" \\\"instead\\\"\",\n \"= result[::-1] return result def factorize( self, sort: bool =\",\n \"self.stop, self.step else: # GH 28678: work on reversed range\",\n \"+ step_o >= start_o) and (end_s - step_o <= end_o)\",\n \"------- from_range See Also -------- Index : The base pandas\",\n \"key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except ValueError as\",\n \"sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"] )\",\n \"and sort is None: start_s, step_s = self.start, self.step end_s\",\n \"indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]:\",\n \": int (default: 1) dtype : np.int64 Unused, accepted for\",\n \"or boolean \\\" \\\"arrays are valid indices\\\" ) # fall\",\n \"efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict()\",\n \"if isinstance(other, RangeIndex) and self._range == other._range: # Both are\",\n \"= type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def\",\n \"optimized set operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other)\",\n \"Hashable = None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values,\",\n \"= end_o, -step_o, start_o if len(self) == 1 and len(other)\",\n \"Index type. Int64Index : Index of int64 data. \\\"\\\"\\\" _typ\",\n \"this was not supplied). \\\"\\\"\\\" # GH 25710 return self._range.start\",\n \"non_empty_indexes: rng = obj._range if start is None: # This\",\n \"1: step_s = step_o elif len(other) == 1: step_o =\",\n \"name=name) @classmethod def _simple_new(cls, values: range, name: Hashable = None)\",\n \"= left.union(right) if result_name is not None: result = result.rename(result_name)\",\n \"sort : False or None, default None Whether to sort\",\n \"len(other) == 1: step_s = step_o = abs(self.start - other.start)\",\n \"!= 0: if len(self) == 0 or self.start % other\",\n \"instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2,\",\n \"@property def size(self) -> int: return len(self) def __getitem__(self, key):\",\n \"step: Callable | None = None if op in [operator.mul,\",\n \"---------- other : Index or array-like sort : False or\",\n \"if dtype: warnings.warn( \\\"parameter dtype is deprecated and will be\",\n \"r old_r, r = r, old_r - quotient * r\",\n \"index type used by DataFrame and Series when no explicit\",\n \"__future__ import annotations from datetime import timedelta import operator from\",\n \"be removed in a future \\\" \\\"version. Use the astype\",\n \"names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( \\\"parameter dtype\",\n \"self.step * (len(self) - 1) start_o, step_o = other.start, other.step\",\n \"start, stop, step = self.start, self.stop, self.step else: # GH\",\n \"``start`` instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2, ) return\",\n \"import numpy as np from pandas._libs import index as libindex\",\n \"---------- start stop step Methods ------- from_range See Also --------\",\n \"---------- start : int (default: 0), range, or other RangeIndex\",\n \"import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, )\",\n \"is not None: next_ = rng[-1] + step if non_empty_indexes:\",\n \"except TypeError: return False return key in self._range @property def\",\n \"\\\"\\\"\\\" Returns the indices that would sort the index and\",\n \"if this was not supplied). \\\"\\\"\\\" # GH 25710 return\",\n \"@cache_readonly def nbytes(self) -> int: \\\"\\\"\\\" Return the number of\",\n \"type. Int64Index : Index of int64 data. \\\"\\\"\\\" _typ =\",\n \"0 and other.step < 0) is not (new_index.step < 0):\",\n \"reasons is created only when needed. The constructed array is\",\n \"default index type used by DataFrame and Series when no\",\n \"\\\"\\\"\\\"The maximum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return\",\n \"a monotonic integer range. RangeIndex is a memory-saving special case\",\n \"back, # but not worth the effort. return super()._difference(other, sort=sort)\",\n \"non_empty_indexes: # Get the stop value from \\\"next\\\" or alternatively\",\n \"(default: 0) step : int (default: 1) dtype : np.int64\",\n \"return \\\"integer\\\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self,\",\n \"other # -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) ->\",\n \"= int(key) try: return self._range.index(new_key) except ValueError as err: raise\",\n \"return self.step @cache_readonly def nbytes(self) -> int: \\\"\\\"\\\" Return the\",\n \"return attrs def _format_data(self, name=None): # we are formatting thru\",\n \"and its underlying data. Returns ------- np.ndarray[np.intp] See Also --------\",\n \"else 0 if stop is None: start, stop = 0,\",\n \"step=None, dtype: Dtype | None = None, copy: bool =\",\n \"isinstance(other, RangeIndex) and sort is None: start_s, step_s = self.start,\",\n \"step_s / 2) ): return type(self)(start_r, end_r + step_s /\",\n \"* (len(other) - 1) if self.step < 0: start_s, step_s,\",\n \"-> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self\",\n \"return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name: Hashable\",\n \"-> RangeIndex: \\\"\\\"\\\" Create RangeIndex from a range object. Returns\",\n \"min(self, axis=None, skipna: bool = True, *args, **kwargs) -> int:\",\n \"when needed. The constructed array is saved in ``_cache``. \\\"\\\"\\\"\",\n \"or alternatively # from the last non-empty index stop =\",\n \"self.step > 0: start, stop, step = self.start, self.stop, self.step\",\n \"non-empty index stop = non_empty_indexes[-1].stop if next_ is None else\",\n \"on timedelta64, # so we need to catch these explicitly\",\n \"name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name =\",\n \"stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def _minmax(self, meth:\",\n \"if ( (start_s - start_o) % step_s == 0 and\",\n \"- start non_consecutive = (step != rng.step and len(rng) >\",\n \"pandas._libs import index as libindex from pandas._libs.lib import no_default from\",\n \"start : int (default: 0), range, or other RangeIndex instance\",\n \"other._range[::-1] if other.step < 0 else other._range # check whether\",\n \"ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index, other) #\",\n \"of all RangeIndex instances. When all members of \\\"indexes\\\" are\",\n \"Conserve RangeIndex type for scalar and slice keys. \\\"\\\"\\\" if\",\n \"return self._range == other._range return super().equals(other) # -------------------------------------------------------------------- # Set\",\n \") from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int,\",\n \"We reversed this range: transform to original locs locs[valid] =\",\n \"equal, shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op)\",\n \"op : callable that accepts 2 params perform the binary\",\n \"tmp_start = first.start + (second.start - first.start) * first.step //\",\n \"tuple[int, int, int]: \\\"\\\"\\\" Extended Euclidean algorithms to solve Bezout's\",\n \"delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array =\",\n \"op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod,\",\n \"return result.rename(name) step = rng.start - start non_consecutive = (step\",\n \"= result.astype(\\\"float64\\\") return result except (ValueError, TypeError, ZeroDivisionError): # Defer\",\n \"0: if ( (start_s - start_o) % step_o == 0\",\n \"abs(self.step)) return self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit:\",\n \"max(end_s, end_o) if step_o == step_s: if ( (start_s -\",\n \"start_r = min(start_s, start_o) end_r = max(end_s, end_o) if step_o\",\n \"not None: next_ = rng[-1] + step if non_empty_indexes: #\",\n \"start + len(self) * step new_range = range(start, stop, step\",\n \"end_o, -step_o, start_o if len(self) == 1 and len(other) ==\",\n \"is_integer(rstep) or not rstep: raise ValueError else: rstep = left.step\",\n \"and (start_o - end_s) <= step_s ): return type(self)(start_r, end_r\",\n \"kwargs) return self._minmax(\\\"min\\\") def max(self, axis=None, skipna: bool = True,\",\n \"case of Int64Index limited to representing monotonic ranges. Using RangeIndex\",\n \"= b, a while r: quotient = old_r // r\",\n \"self._range[::-1] if self.step < 0 else self._range overlap = self.intersection(other)\",\n \"raise TypeError(\\\"RangeIndex(...) must be called with integers\\\") start = ensure_python_int(start)\",\n \"< 0: start_o, step_o, end_o = end_o, -step_o, start_o if\",\n \"homogeneity with other index types. copy : bool, default False\",\n \"start_s) % step_s == 0 and (start_o + step_s >=\",\n \"default False Unused, accepted for homogeneity with other index types.\",\n \"list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self,\",\n \"to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target)\",\n \"-> tuple[int, int, int]: \\\"\\\"\\\" Extended Euclidean algorithms to solve\",\n \"other.start + other.step * (len(other) - 1) if self.step <\",\n \"rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, )\",\n \"a future \\\" \\\"version. Use the astype method instead.\\\", FutureWarning,\",\n \"ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic\",\n \"self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- #\",\n \"fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__)\",\n \"err: raise IndexError( f\\\"index {key} is out of bounds for\",\n \"rng.start if step is None and len(rng) > 1: step\",\n \"or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return\",\n \"np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1, -1, -1,\",\n \"parameter (``1`` if this was not supplied). \\\"\\\"\\\" # GH\",\n \"reverse = self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step\",\n \"must be called with integers\\\") start = ensure_python_int(start) if start\",\n \"optional Name to be stored in the index. Attributes ----------\",\n \"rng.step elif step is None: # First non-empty index had\",\n \"object, optional Name to be stored in the index. Attributes\",\n \"for homogeneity with other index types. name : object, optional\",\n \"Index: \\\"\\\"\\\" Overriding parent method for the case of all\",\n \"return self._range.stop @property def _stop(self) -> int: \\\"\\\"\\\" The value\",\n \"start_o) <= step_s / 2) and (abs(end_s - end_o) <=\",\n \"// other new_range = range(start, start + 1, 1) return\",\n \"= None ) -> RangeIndex: \\\"\\\"\\\" Create RangeIndex from a\",\n \"first.step) elif overlap[-1] == first[-1]: # The difference is everything\",\n \"1 if no_steps == -1: return np.nan elif (meth ==\",\n \"decreasing ranges int_low = max(first.start, second.start) int_high = min(first.stop, second.stop)\",\n \"instance If int and \\\"stop\\\" is not given, interpreted as\",\n \"and \\\"stop\\\" is not given, interpreted as \\\"stop\\\" instead. stop\",\n \": Index \\\"\\\"\\\" if isinstance(other, RangeIndex) and sort is None:\",\n \"Also -------- Index : The base pandas Index type. Int64Index\",\n \"coercible to a \\\" f\\\"range, {repr(data)} was passed\\\" ) cls._validate_dtype(dtype)\",\n \"integer or boolean \\\" \\\"arrays are valid indices\\\" ) #\",\n \"we don't have a representable op # so return a\",\n \"super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array -\",\n \"end_o) ): return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other,\",\n \"# -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) -> Index:\",\n \"import operator from sys import getsizeof from typing import (\",\n \"isinstance(overlap, RangeIndex): # We won't end up with RangeIndex, so\",\n \"result.rename(name) step = rng.start - start non_consecutive = (step !=\",\n \"return self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int)\",\n \"-> bool: \\\"\\\"\\\" return if the index has unique values\",\n \"element sets intersect if (first.start - second.start) % gcd: return\",\n \"first.step) else: # The difference is not range-like return super()._difference(other,\",\n \"memory-saving special case of Int64Index limited to representing monotonic ranges.\",\n \"= locs[valid] / step if step != self.step: # We\",\n \"if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op\",\n \"not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step <\",\n \"first[-1]: # The difference is everything before the intersection new_rng\",\n \"nv.validate_argsort(args, kwargs) if self._range.step > 0: result = np.arange(len(self), dtype=np.intp)\",\n \"unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union : Index\",\n \"new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if\",\n \"return super()._difference(other, sort=sort) if overlap[0] == first.start: # The difference\",\n \"return self._simple_new(new_range, name=self.name) return self._int64index // other # -------------------------------------------------------------------- #\",\n \"for the RangeIndex describing the # intersection disregarding the lower\",\n \"int = 0, allow_fill: bool = True, fill_value=None, **kwargs )\",\n \") from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import\",\n \"True, *args, **kwargs) -> int: \\\"\\\"\\\"The maximum value of the\",\n \"new_index = new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps\",\n \"Parameters ---------- other : Index or array-like sort : False\",\n \"# wrap _cached_int64index so we can be sure its name\",\n \"step_s: if ( (start_s - start_o) % step_s == 0\",\n \"(start_s - end_o) <= step_s and (start_o - end_s) <=\",\n \"axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return\",\n \"* r old_s, s = s, old_s - quotient *\",\n \"isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64,\",\n \"name: Hashable) -> Index: \\\"\\\"\\\" Overriding parent method for the\",\n \"step): raise TypeError(\\\"RangeIndex(...) must be called with integers\\\") start =\",\n \"if not all(is_integer(x) for x in [rstart, rstop, rstep]): result\",\n \"a \\\" f\\\"range, {repr(data)} was passed\\\" ) cls._validate_dtype(dtype) return cls._simple_new(data,\",\n \"as err: raise KeyError(key) from err raise KeyError(key) return super().get_loc(key,\",\n \"values: range, name: Hashable = None) -> RangeIndex: result =\",\n \"elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return op(self._int64index,\",\n \"s, _ = self._extended_gcd(first.step, second.step) # check whether element sets\",\n \"= np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not ascending:\",\n \"\\\"\\\"\\\" The value of the `step` parameter (``1`` if this\",\n \"= None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index\",\n \"1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats,\",\n \"dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool:\",\n \"-(-(lower_limit - self.start) // abs(self.step)) return self.start + abs(self.step) *\",\n \"limit=limit ) if self.step > 0: start, stop, step =\",\n \"---------- deep : bool Introspect the data deeply, interrogate `object`\",\n \"self, target: Index, method: str | None = None, limit:\",\n \"typing import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast, )\",\n \"self._minmax(\\\"max\\\") def argsort(self, *args, **kwargs) -> np.ndarray: \\\"\\\"\\\" Returns the\",\n \"float-like descriptors if not all(is_integer(x) for x in [rstart, rstop,\",\n \"used Notes ----- Memory usage does not include memory consumed\",\n \"None, copy: bool = False, name: Hashable = None, )\",\n \"everything after the intersection new_rng = range(overlap[-1] + first.step, first.stop,\",\n \"type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index = new_index[::-1]\",\n \"sort is not None: return super().symmetric_difference(other, result_name, sort) left =\",\n \"super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \\\"\\\"\\\" Fastpath\",\n \"Unused, accepted for homogeneity with other index types. copy :\",\n \"= s, old_s - quotient * s old_t, t =\",\n \"don't have a representable op # so return a base\",\n \"index types. copy : bool, default False Unused, accepted for\",\n \"start_s) and (end_o - step_s <= end_s) ): return type(self)(start_r,\",\n \"op): if isinstance(other, RangeIndex) and self._range == other._range: # Both\",\n \"if we have an override if step: with np.errstate(all=\\\"ignore\\\"): rstep\",\n \"== \\\"max\\\" and self.step < 0): return self.start return self.start\",\n \"type(self)(start_r, end_r + step_s, step_s) if ( (step_s % 2\",\n \"len(self) == 1 and len(other) == 1: step_s = step_o\",\n \"astype method instead.\\\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return\",\n \"new_range = range(start, start + 1, 1) return self._simple_new(new_range, name=self.name)\",\n \"-> bool: return 0 not in self._range def any(self, *args,\",\n \"list of tuples of start, stop, step \\\"\\\"\\\" rng =\",\n \"= self._get_data_as_items() if self.name is not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return\",\n \") import warnings import numpy as np from pandas._libs import\",\n \"limit: int | None = None, tolerance=None, ) -> np.ndarray:\",\n \"len(self) or not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if\",\n \"is_integer evaluated True on timedelta64, # so we need to\",\n \"(start_s - start_o) % step_o == 0 and (start_s +\",\n \"not self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self, other,\",\n \"return [(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)] def __reduce__(self): d\",\n \"Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other,\",\n \"return op(self._int64index, other) step: Callable | None = None if\",\n \"function as nv from pandas.util._decorators import ( cache_readonly, doc, )\",\n \"saved in ``_cache``. \\\"\\\"\\\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly\",\n \"= self._cache return result @doc(Int64Index.copy) def copy( self, name: Hashable\",\n \"removed in a future \\\" \\\"version. Use the astype method\",\n \"step = next_ = None # Filter the empty indexes\",\n \"= abs(self.start - other.start) elif len(self) == 1: step_s =\",\n \"ranges int_low = max(first.start, second.start) int_high = min(first.stop, second.stop) if\",\n \"TYPE_CHECKING: from pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex):\",\n \"\\\" f\\\"range, {repr(data)} was passed\\\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name)\",\n \"new_key = int(key) try: return self._range[new_key] except IndexError as err:\",\n \"transform to original locs locs[valid] = len(self) - 1 -\",\n \"if (first.start - second.start) % gcd: return self._simple_new(_empty_range) # calculate\",\n \"other.difference(self) result = left.union(right) if result_name is not None: result\",\n \"False return key in self._range @property def inferred_type(self) -> str:\",\n \"elements that are not components of the array if deep=False\",\n \"the `stop` parameter. \\\"\\\"\\\" return self._range.stop @property def _stop(self) ->\",\n \"return header + [f\\\"{x:<{max_length}}\\\" for x in self._range] # --------------------------------------------------------------------\",\n \"value of the `start` parameter (``0`` if this was not\",\n \"range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] == first[-1]: #\",\n \"in [rstart, rstop, rstep]): result = result.astype(\\\"float64\\\") return result except\",\n \"work on reversed range for simplicity reverse = self._range[::-1] start,\",\n \"max(len(first_val_str), len(last_val_str)) return header + [f\\\"{x:<{max_length}}\\\" for x in self._range]\",\n \"the class to use for construction \\\"\\\"\\\" return Int64Index @cache_readonly\",\n \"self._range[new_key] except IndexError as err: raise IndexError( f\\\"index {key} is\",\n \"None, deep: bool = False, dtype: Dtype | None =\",\n \"return a list of tuples of start, stop, step \\\"\\\"\\\"\",\n \"== step_s: if ( (start_s - start_o) % step_s ==\",\n \"the arguments if com.all_none(start, stop, step): raise TypeError(\\\"RangeIndex(...) must be\",\n \"result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) ->\",\n \"-------- numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes @property def dtype(self) -> np.dtype:\",\n \"\\\"instead\\\" ) @property def start(self) -> int: \\\"\\\"\\\" The value\",\n \"end up with RangeIndex, so fall back return super()._difference(other, sort=sort)\",\n \"import warnings import numpy as np from pandas._libs import index\",\n \"no_steps == -1: return np.nan elif (meth == \\\"min\\\" and\",\n \"in rng_indexes]) result = Int64Index(values) return result.rename(name) step = rng.start\",\n \"): return type(self)(start_r, end_r + step_s / 2, step_s /\",\n \"index if not is_integer(rstep) or not rstep: raise ValueError else:\",\n \"operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step:\",\n \"def _max_fitting_element(self, upper_limit: int) -> int: \\\"\\\"\\\"Returns the largest element\",\n \"list[Index], name: Hashable) -> Index: \\\"\\\"\\\" Overriding parent method for\",\n \"self._range[::-1] if self.step < 0 else self._range second = other._range[::-1]\",\n \"Index of int64 data. \\\"\\\"\\\" _typ = \\\"rangeindex\\\" _engine_type =\",\n \"old_t = 1, 0 r, old_r = b, a while\",\n \"overlap[0], first.step) else: # The difference is not range-like return\",\n \"FutureWarning, stacklevel=2, ) return self.stop @property def step(self) -> int:\",\n \"> 0: start, stop, step = self.start, self.stop, self.step else:\",\n \"other == 0 and self.step % other == 0: start\",\n \"stop, step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): #\",\n \"| None = None, names=None, ): name = self._validate_names(name=name, names=names,\",\n \"0): new_index = new_index[::-1] if sort is None: new_index =\",\n \"index and its underlying data. Returns ------- np.ndarray[np.intp] See Also\",\n \"whether intervals intersect # deals with in- and decreasing ranges\",\n \"key): \\\"\\\"\\\" Conserve RangeIndex type for scalar and slice keys.\",\n \"len(overlap) == 0: return self.rename(name=res_name) if len(overlap) == len(self): return\",\n \"RangeIndex) and self._range == other._range: # Both are immutable so\",\n \"for axis 0 with size {len(self)}\\\" ) from err elif\",\n \"s, t \\\"\\\"\\\" s, old_s = 0, 1 t, old_t\",\n \"<= step_s ): return type(self)(start_r, end_r + step_s, step_s) if\",\n \": int (default: 0) step : int (default: 1) dtype\",\n \"\\\"RangeIndex.{} is deprecated and will be \\\" \\\"removed in a\",\n \"( (step_s % 2 == 0) and (abs(start_s - start_o)\",\n \"import function as nv from pandas.util._decorators import ( cache_readonly, doc,\",\n \"Create RangeIndex from a range object. Returns ------- RangeIndex \\\"\\\"\\\"\",\n \"future version. Use RangeIndex.{} \\\" \\\"instead\\\" ) @property def start(self)\",\n \"start_s, step_s = self.start, self.step end_s = self.start + self.step\",\n \"numpy as np from pandas._libs import index as libindex from\",\n \"Use ``stop`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"),\",\n \"# cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step) #\",\n \"set by the first non-empty index start = rng.start if\",\n \"def __floordiv__(self, other): if is_integer(other) and other != 0: if\",\n \"and self.step > 0) or (meth == \\\"max\\\" and self.step\",\n \"@unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other): if is_integer(other) and other != 0:\",\n \"bytes in the underlying data. \\\"\\\"\\\" rng = self._range return\",\n \"step if step != self.step: # We reversed this range:\",\n \"to the limit\\\"\\\"\\\" no_steps = -(-(lower_limit - self.start) // abs(self.step))\",\n \"return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\\\"start\\\",\",\n \"parameter (``0`` if this was not supplied). .. deprecated:: 0.25.0\",\n \"The constructed array is saved in ``_cache``. \\\"\\\"\\\" return np.arange(self.start,\",\n \"result._range = values result._name = name result._cache = {} result._reset_identity()\",\n \"> 0: result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self)\",\n \"other == 0: start = self.start // other step =\",\n \"name=None): # we are formatting thru the attributes return None\",\n \"super()._intersection(other, sort=sort) if not len(self) or not len(other): return self._simple_new(_empty_range)\",\n \"Bezout's identity: a*x + b*y = gcd(x, y) Finds one\",\n \"return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized set\",\n \"return codes, uniques def equals(self, other: object) -> bool: \\\"\\\"\\\"\",\n \"first.step, first.stop, first.step) elif overlap[-1] == first[-1]: # The difference\",\n \"from __future__ import annotations from datetime import timedelta import operator\",\n \"None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self),\",\n \"ensure_python_int(start) if start is not None else 0 if stop\",\n \"_can_hold_na = False _range: range # -------------------------------------------------------------------- # Constructors def\",\n \"algorithms to solve Bezout's identity: a*x + b*y = gcd(x,\",\n \"Int64Index implementation return op(self._int64index, other) # TODO: Do attrs get\",\n \"its name matches self.name res = self._cached_int64index res._name = self._name\",\n \"# we are formatting thru the attributes return None def\",\n \"up with RangeIndex, so fall back return super()._difference(other, sort=sort) if\",\n \"_stop(self) -> int: \\\"\\\"\\\" The value of the `stop` parameter.\",\n \"op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390\",\n \"result = np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not\",\n \"self.step < 0: start_s, step_s, end_s = end_s, -step_s, start_s\",\n \"{len(self)}\\\" ) from err elif is_scalar(key): raise IndexError( \\\"only integers,\",\n \"sort=sort) if overlap[0] == first.start: # The difference is everything\",\n \"return self.start @property def stop(self) -> int: \\\"\\\"\\\" The value\",\n \"- first.start) * first.step // gcd * s new_step =\",\n \"be stored in the index. Attributes ---------- start stop step\",\n \"sort=False): if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort)\",\n \"possible Parameters ---------- other : Index or array-like sort :\",\n \"None, limit: int | None = None, tolerance=None, ) ->\",\n \"return self._minmax(\\\"min\\\") def max(self, axis=None, skipna: bool = True, *args,\",\n \"other.step end_o = other.start + other.step * (len(other) - 1)\",\n \"- end_s) <= step_s ): return type(self)(start_r, end_r + step_s,\",\n \"result will be RangeIndex if possible, Int64Index otherwise. E.g.: indexes\",\n \"is_unique(self) -> bool: \\\"\\\"\\\" return if the index has unique\",\n \"self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try:\",\n \"stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls, data:\",\n \"self.name is not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs def _format_data(self,\",\n \"uniques def equals(self, other: object) -> bool: \\\"\\\"\\\" Determines if\",\n \"- second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters for\",\n \"stop = start + len(self) * step new_range = range(start,\",\n \"deprecated:: 0.25.0 Use ``start`` instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning,\",\n \"= self._cached_int64index res._name = self._name return res def _get_data_as_items(self): \\\"\\\"\\\"\",\n \"self.start + abs(self.step) * no_steps def _extended_gcd(self, a: int, b:\",\n \") new_index = new_index.astype(dtype) return new_index def _minmax(self, meth: str):\",\n \"np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values) return result.rename(name)\",\n \"would sort the index and its underlying data. Returns -------\",\n \"if next_ is None else next_ return RangeIndex(start, stop, step).rename(name)\",\n \"self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2, ) return self.stop @property def step(self)\",\n \"rstep, **attrs) # for compat with numpy / Int64Index #\",\n \"use for construction \\\"\\\"\\\" return Int64Index @cache_readonly def _data(self) ->\",\n \"stop, step \\\"\\\"\\\" rng = self._range return [(\\\"start\\\", rng.start), (\\\"stop\\\",\",\n \"for system-level memory consumption Returns ------- bytes used Notes -----\",\n \"_min_fitting_element(self, lower_limit: int) -> int: \\\"\\\"\\\"Returns the smallest element greater\",\n \"and (start_s - end_o) <= step_s and (start_o - end_s)\",\n \"if step == 0: raise ValueError(\\\"Step must not be zero\\\")\",\n \"if len(self) == 1: start = self.start // other new_range\",\n \"validate the arguments if com.all_none(start, stop, step): raise TypeError(\\\"RangeIndex(...) must\",\n \"from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index,\",\n \"integers\\\") start = ensure_python_int(start) if start is not None else\",\n \"upper_limit: int) -> int: \\\"\\\"\\\"Returns the largest element smaller than\",\n \"( (start_s - start_o) % step_o == 0 and (start_s\",\n \"range, name: Hashable = None) -> RangeIndex: result = object.__new__(cls)\",\n \"keys. \\\"\\\"\\\" if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range,\",\n \"case of all RangeIndex instances. When all members of \\\"indexes\\\"\",\n \"See Also -------- numpy.ndarray.argsort \\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\", True) #\",\n \"= Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if step\",\n \"to solve Bezout's identity: a*x + b*y = gcd(x, y)\",\n \"start_o if len(self) == 1 and len(other) == 1: step_s\",\n \"def take( self, indices, axis: int = 0, allow_fill: bool\",\n \"attrs def _format_data(self, name=None): # we are formatting thru the\",\n \"return new_index def _minmax(self, meth: str): no_steps = len(self) -\",\n \"0.25.0 Use ``stop`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\",\",\n \"= min(start_s, start_o) end_r = max(end_s, end_o) if step_o ==\",\n \"\\\"step\\\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self) ->\",\n \"type: ignore[override] return self._int64index.delete(loc) def take( self, indices, axis: int\",\n \"of type RangeIndex: result will be RangeIndex if possible, Int64Index\",\n \"def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \\\"\\\"\\\" Fastpath for\",\n \"solve intersection problem # performance hint: for identical step sizes,\",\n \"Returns the indices that would sort the index and its\",\n \"or array-like sort : False or None, default None Whether\",\n \"1, 1) return self._simple_new(new_range, name=self.name) return self._int64index // other #\",\n \"compat with numpy / Int64Index # even if we can\",\n \"result except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation\",\n \"= self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key)\",\n \"old_s = 0, 1 t, old_t = 1, 0 r,\",\n \"other index types. copy : bool, default False Unused, accepted\",\n \"be able to get a RangeIndex back, # but not\",\n \"or not len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step\",\n \"the RangeIndex \\\"\\\"\\\" return len(self._range) @property def size(self) -> int:\",\n \"unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range = range(0)\",\n \"Diophantine equation # solve intersection problem # performance hint: for\",\n \"self.start) // abs(self.step) return self.start + abs(self.step) * no_steps def\",\n \"* no_steps def _extended_gcd(self, a: int, b: int) -> tuple[int,\",\n \"deep=False See Also -------- numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes @property def\",\n \"in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"] ) def memory_usage(self, deep: bool =\",\n \"\\\"\\\"\\\" s, old_s = 0, 1 t, old_t = 1,\",\n \"return self._range[new_key] except IndexError as err: raise IndexError( f\\\"index {key}\",\n \"raise ValueError else: rstep = left.step with np.errstate(all=\\\"ignore\\\"): rstart =\",\n \"stop, step).rename(name) # Here all \\\"indexes\\\" had 0 length, i.e.\",\n \"from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common\",\n \"Index : The base pandas Index type. Int64Index : Index\",\n \"self._range == other._range: # Both are immutable so if ._range\",\n \"def all(self, *args, **kwargs) -> bool: return 0 not in\",\n \"step_o = other.start, other.step end_o = other.start + other.step *\",\n \"if len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex):\",\n \"return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: # type:\",\n \"-> int: \\\"\\\"\\\" return the length of the RangeIndex \\\"\\\"\\\"\",\n \"int (default: 0) step : int (default: 1) dtype :\",\n \"speed. This is the default index type used by DataFrame\",\n \"is everything before the intersection new_rng = range(first.start, overlap[0], first.step)\",\n \"new_rng = range(first.start, overlap[0], first.step) else: # The difference is\",\n \"is None and tolerance is None: if is_integer(key) or (is_float(key)\",\n \"if overlap.step != first.step: # In some cases we might\",\n \"# Must be an np.ndarray; GH#22390 return op(self._int64index, other) if\",\n \"ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as com from\",\n \"def _format_attrs(self): \\\"\\\"\\\" Return a list of tuples of the\",\n \"target, method=method, tolerance=tolerance, limit=limit ) if self.step > 0: start,\",\n \"See Also -------- Index : The base pandas Index type.\",\n \"the limit\\\"\\\"\\\" no_steps = (upper_limit - self.start) // abs(self.step) return\",\n \"types. copy : bool, default False Unused, accepted for homogeneity\",\n \"Operations def _intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex):\",\n \"for obj in non_empty_indexes: rng = obj._range if start is\",\n \"reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general\",\n \"by elements that are not components of the array if\",\n \"[(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)] def __reduce__(self): d =\",\n \"from typing import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast,\",\n \"+ [f\\\"{x:<{max_length}}\\\" for x in self._range] # -------------------------------------------------------------------- _deprecation_message =\",\n \"return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1]\",\n \"intersection disregarding the lower bounds tmp_start = first.start + (second.start\",\n \"RangeIndex) and sort is None: start_s, step_s = self.start, self.step\",\n \"old_r = b, a while r: quotient = old_r //\",\n \"= 0, start else: stop = ensure_python_int(stop) step = ensure_python_int(step)\",\n \"int array that for performance reasons is created only when\",\n \"fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj:\",\n \"return super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self, other:\",\n \"index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible or\",\n \"Reductions def all(self, *args, **kwargs) -> bool: return 0 not\",\n \"== 0 and (start_s - end_o) <= step_s and (start_o\",\n \"self.start return self.start + self.step * no_steps def min(self, axis=None,\",\n \"import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer,\",\n \"new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust\",\n \"step_o % step_s == 0: if ( (start_o - start_s)\",\n \"start + 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index //\",\n \"\\\"NaN\\\") -> list[str]: if not len(self._range): return header first_val_str =\",\n \"the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\") def argsort(self, *args,\",\n \"= self._extended_gcd(first.step, second.step) # check whether element sets intersect if\",\n \"and len(other) == 1: step_s = step_o = abs(self.start -\",\n \"= True, *args, **kwargs) -> int: \\\"\\\"\\\"The minimum value of\",\n \"other : Index or array-like sort : False or None,\",\n \"pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype,\",\n \"= ensure_python_int(stop) step = ensure_python_int(step) if step is not None\",\n \"this case return an empty range index. return RangeIndex(0, 0).rename(name)\",\n \"has unique values \\\"\\\"\\\" return True @cache_readonly def is_monotonic_increasing(self) ->\",\n \"# for compat with numpy / Int64Index # even if\",\n \"self._rename(name=name) if dtype: warnings.warn( \\\"parameter dtype is deprecated and will\",\n \"RangeIndex): return self._range == other._range return super().equals(other) # -------------------------------------------------------------------- #\",\n \"end_r + step_s / 2, step_s / 2) elif step_o\",\n \"def _int64index(self) -> Int64Index: # wrap _cached_int64index so we can\",\n \"Use ``start`` instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2, )\",\n \"self.step else: # GH 28678: work on reversed range for\",\n \"self.start + self.step * no_steps def min(self, axis=None, skipna: bool\",\n \"underlying data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \\\"\\\"\\\"\",\n \"super().symmetric_difference(other, result_name, sort) left = self.difference(other) right = other.difference(self) result\",\n \"non-empty index start = rng.start if step is None and\",\n \"str): no_steps = len(self) - 1 if no_steps == -1:\",\n \"result.astype(\\\"float64\\\") return result except (ValueError, TypeError, ZeroDivisionError): # Defer to\",\n \"f\\\"range, {repr(data)} was passed\\\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod\",\n \"sys import getsizeof from typing import ( TYPE_CHECKING, Any, Callable,\",\n \"GH 25710 return self._range.step @property def _step(self) -> int: \\\"\\\"\\\"\",\n \"reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated\",\n \"instances improve computing speed. This is the default index type\",\n \"{repr(data)} was passed\\\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def\",\n \"all members of \\\"indexes\\\" are of type RangeIndex: result will\",\n \"-> np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool: \\\"\\\"\\\"\",\n \"bounds for axis 0 with size {len(self)}\\\" ) from err\",\n \"1 t, old_t = 1, 0 r, old_r = b,\",\n \"\\\"indexes\\\" are of type RangeIndex: result will be RangeIndex if\",\n \"-> int: \\\"\\\"\\\" The value of the `start` parameter (``0``\",\n \"nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\") def argsort(self, *args, **kwargs) ->\",\n \"RangeIndex instances. When all members of \\\"indexes\\\" are of type\",\n \"None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method,\",\n \"stop = ensure_python_int(stop) step = ensure_python_int(step) if step is not\",\n \"name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype:\",\n \"increasing ``RangeIndex`` if possible or a sorted ``Int64Index`` if not.\",\n \"1: step = rng.step elif step is None: # First\",\n \"The base pandas Index type. Int64Index : Index of int64\",\n \"None and rng.start != next_ ) if non_consecutive: result =\",\n \"stop = non_empty_indexes[-1].stop if next_ is None else next_ return\",\n \"= (upper_limit - self.start) // abs(self.step) return self.start + abs(self.step)\",\n \"= 0, 1 t, old_t = 1, 0 r, old_r\",\n \"len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't\",\n \"bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if\",\n \"-1, dtype=np.intp) if not ascending: result = result[::-1] return result\",\n \"returns a monotonically increasing ``RangeIndex`` if possible or a sorted\",\n \"rng = range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def\",\n \"r = r, old_r - quotient * r old_s, s\",\n \"int: \\\"\\\"\\\" The value of the `step` parameter (``1`` if\",\n \"(first.start - second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters\",\n \"+ sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"]\",\n \"25710 return self._range.step @property def _step(self) -> int: \\\"\\\"\\\" The\",\n \"# solve intersection problem # performance hint: for identical step\",\n \"elif step_o % step_s == 0: if ( (start_o -\",\n \"is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex\",\n \"RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache\",\n \"**attrs) # for compat with numpy / Int64Index # even\",\n \"x, y: s, t Returns: gcd, s, t \\\"\\\"\\\" s,\",\n \"result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result @doc(Int64Index.copy)\",\n \"t Returns: gcd, s, t \\\"\\\"\\\" s, old_s = 0,\",\n \"a RangeIndex back, # but not worth the effort. return\",\n \"\\\"\\\"\\\" return a list of tuples of start, stop, step\",\n \"= self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn(\",\n \"- 1, -1, -1, dtype=np.intp) if not ascending: result =\",\n \"other): if is_integer(other) and other != 0: if len(self) ==\",\n \"`object` dtypes for system-level memory consumption Returns ------- bytes used\",\n \"[ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return\",\n \"= step = next_ = None # Filter the empty\",\n \"bool = False) -> int: \\\"\\\"\\\" Memory usage of my\",\n \"with size {len(self)}\\\" ) from err elif is_scalar(key): raise IndexError(\",\n \"= self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other): if\",\n \"else: rstep = left.step with np.errstate(all=\\\"ignore\\\"): rstart = op(left.start, right)\",\n \"have float-like descriptors if not all(is_integer(x) for x in [rstart,\",\n \"step_s <= end_s) ): return type(self)(start_r, end_r + step_s, step_s)\",\n \"end_s = self.start + self.step * (len(self) - 1) start_o,\",\n \"other, result_name: Hashable = None, sort=None): if not isinstance(other, RangeIndex)\",\n \"RangeIndex(0, 0).rename(name) def __len__(self) -> int: \\\"\\\"\\\" return the length\",\n \"is None: start_s, step_s = self.start, self.step end_s = self.start\",\n \"name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other): if is_integer(other) and other !=\",\n \") # fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self:\",\n \"overlap = overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if\",\n \"np.nan elif (meth == \\\"min\\\" and self.step > 0) or\",\n \"= start + len(self) * step new_range = range(start, stop,\",\n \"bool: return 0 not in self._range def any(self, *args, **kwargs)\",\n \"isinstance(values, range) result._range = values result._name = name result._cache =\",\n \"sort is None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self,\",\n \"<= 1 def __contains__(self, key: Any) -> bool: hash(key) try:\",\n \"with object coercible to a \\\" f\\\"range, {repr(data)} was passed\\\"\",\n \"slice) -> RangeIndex: \\\"\\\"\\\" Fastpath for __getitem__ when we know\",\n \"1: step_o = step_s start_r = min(start_s, start_o) end_r =\",\n \"(len(other) - 1) if self.step < 0: start_s, step_s, end_s\",\n \"pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable\",\n \">= start_s) and (end_o - step_s <= end_s) ): return\",\n \"| None = None, limit: int | None = None,\",\n \"difference is everything after the intersection new_rng = range(overlap[-1] +\",\n \"* step new_range = range(start, stop, step or 1) return\",\n \"is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core\",\n \"_cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range == other._range:\",\n \"if self.step > 0: start, stop, step = self.start, self.stop,\",\n \"in the underlying data. \\\"\\\"\\\" rng = self._range return getsizeof(rng)\",\n \"| None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes =\",\n \"and (start_o + step_s >= start_s) and (end_o - step_s\",\n \"calculate parameters for the RangeIndex describing the # intersection disregarding\",\n \"EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result =\",\n \"name: Hashable = None) -> RangeIndex: result = object.__new__(cls) assert\",\n \"dtype: Dtype | None = None, names=None, ): name =\",\n \"non_empty_indexes = [obj for obj in rng_indexes if len(obj)] for\",\n \"np.ndarray: \\\"\\\"\\\" Returns the indices that would sort the index\",\n \"if self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else: result\",\n \"if overlap.step < 0: overlap = overlap[::-1] if len(overlap) ==\",\n \"the union of two Index objects and sorts if possible\",\n \"= ops.get_op_result_name(self, other) first = self._range[::-1] if self.step < 0\",\n \"was not supplied). \\\"\\\"\\\" # GH 25710 return self._range.start @property\",\n \"step or 1) return self._simple_new(new_range, name=self.name) if len(self) == 1:\",\n \"Any) -> bool: hash(key) try: key = ensure_python_int(key) except TypeError:\",\n \"from \\\"next\\\" or alternatively # from the last non-empty index\",\n \"``Int64Index`` if not. ``sort=False`` always returns an unsorted ``Int64Index`` ..\",\n \"other != 0: if len(self) == 0 or self.start %\",\n \"is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self,\",\n \"elif (meth == \\\"min\\\" and self.step > 0) or (meth\",\n \"= len(self) - 1 - locs[valid] return ensure_platform_int(locs) # --------------------------------------------------------------------\",\n \"self, indices, axis: int = 0, allow_fill: bool = True,\",\n \"abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) -> int: \\\"\\\"\\\"Returns\",\n \"- step_o <= end_o) ): return type(self)(start_r, end_r + step_o,\",\n \"values = np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values)\",\n \"return False return key in self._range @property def inferred_type(self) ->\",\n \"_ = self._extended_gcd(first.step, second.step) # check whether element sets intersect\",\n \"raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target:\",\n \"@property def _stop(self) -> int: \\\"\\\"\\\" The value of the\",\n \"(locs >= 0) & (target_array < stop) locs[~valid] = -1\",\n \"\\\"\\\"\\\" Extended Euclidean algorithms to solve Bezout's identity: a*x +\",\n \"0 and (start_s - end_o) <= step_s and (start_o -\",\n \"Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6)\",\n \"\\\"\\\"\\\" attrs = self._get_data_as_items() if self.name is not None: attrs.append((\\\"name\\\",\",\n \"sort=None): # optimized set operation if we have another RangeIndex\",\n \"super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method: str\",\n \"implementing a monotonic integer range. RangeIndex is a memory-saving special\",\n \"deep : bool Introspect the data deeply, interrogate `object` dtypes\",\n \"self._range.step @property def _step(self) -> int: \\\"\\\"\\\" The value of\",\n \"not include memory consumed by elements that are not components\",\n \"range # -------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None,\",\n \"# -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None,\",\n \"# validate the arguments if com.all_none(start, stop, step): raise TypeError(\\\"RangeIndex(...)\",\n \"bool = True, *args, **kwargs) -> int: \\\"\\\"\\\"The maximum value\",\n \"return type(self)(start_r, end_r + step_s, step_s) elif step_s % step_o\",\n \"name=res_name) if first is not self._range: new_index = new_index[::-1] return\",\n \"RangeIndex: result will be RangeIndex if possible, Int64Index otherwise. E.g.:\",\n \"old_r, old_s, old_t def _union(self, other: Index, sort): \\\"\\\"\\\" Form\",\n \"step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized\",\n \"isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name)\",\n \"be an np.ndarray; GH#22390 return op(self._int64index, other) if op in\",\n \"end_o) <= step_s / 2) ): return type(self)(start_r, end_r +\",\n \"@property def step(self) -> int: \\\"\\\"\\\" The value of the\",\n \"so we need to catch these explicitly return op(self._int64index, other)\",\n \"from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer(\",\n \"-------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range\",\n \"a future version. Use RangeIndex.{} \\\" \\\"instead\\\" ) @property def\",\n \"other.step < 0: start_o, step_o, end_o = end_o, -step_o, start_o\",\n \"and sorts if possible Parameters ---------- other : Index or\",\n \"* no_steps def _max_fitting_element(self, upper_limit: int) -> int: \\\"\\\"\\\"Returns the\",\n \"difference is not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng,\",\n \"= [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4,\",\n \"if non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return\",\n \"to original locs locs[valid] = len(self) - 1 - locs[valid]\",\n \"sort) left = self.difference(other) right = other.difference(self) result = left.union(right)\",\n \"-1: return np.nan elif (meth == \\\"min\\\" and self.step >\",\n \"# Defer to Int64Index implementation return op(self._int64index, other) # TODO:\",\n \"= str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return\",\n \"we might be able to get a RangeIndex back, #\",\n \"\\\"\\\"\\\" return True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step\",\n \"( next_ is not None and rng.start != next_ )\",\n \"values Parameters ---------- deep : bool Introspect the data deeply,\",\n \"factorize( self, sort: bool = False, na_sentinel: int | None\",\n \"use # cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step)\",\n \"binary op \\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex\",\n \"descriptors if not all(is_integer(x) for x in [rstart, rstop, rstep]):\",\n \"result = object.__new__(cls) assert isinstance(values, range) result._range = values result._name\",\n \"the `start` parameter (``0`` if this was not supplied). ..\",\n \"rng = self._range return [(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)]\",\n \"value of the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop``\",\n \"callable that accepts 2 params perform the binary op \\\"\\\"\\\"\",\n \"= False) -> int: \\\"\\\"\\\" Memory usage of my values\",\n \"/ 2) ): return type(self)(start_r, end_r + step_s / 2,\",\n \"return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self)\",\n \"Parameters ---------- deep : bool Introspect the data deeply, interrogate\",\n \"second.start) int_high = min(first.stop, second.stop) if int_high <= int_low: return\",\n \"self._range second = other._range[::-1] if other.step < 0 else other._range\",\n \"new_index.step) new_index = self._simple_new(new_range) if (self.step < 0 and other.step\",\n \"ValueError as err: raise KeyError(key) from err raise KeyError(key) return\",\n \"= (is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na = False _range: range #\",\n \"Index \\\"\\\"\\\" if isinstance(other, RangeIndex) and sort is None: start_s,\",\n \"elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on\",\n \"other try: # apply if we have an override if\",\n \"nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\") def max(self, axis=None, skipna: bool =\",\n \"\\\"\\\"\\\" return Int64Index @cache_readonly def _data(self) -> np.ndarray: \\\"\\\"\\\" An\",\n \"obj in rng_indexes if len(obj)] for obj in non_empty_indexes: rng\",\n \"new_index = new_index[::-1] if sort is None: new_index = new_index.sort_values()\",\n \"= self.start // other new_range = range(start, start + 1,\",\n \"== -1: return np.nan elif (meth == \\\"min\\\" and self.step\",\n \"pandas._libs.lib import no_default from pandas._typing import Dtype from pandas.compat.numpy import\",\n \"self.start + self.step * (len(self) - 1) start_o, step_o =\",\n \"- end_o) <= step_s and (start_o - end_s) <= step_s\",\n \"inferred_type(self) -> str: return \\\"integer\\\" # -------------------------------------------------------------------- # Indexing Methods\",\n \"return super()._difference(other, sort=sort) if overlap.step != first.step: # In some\",\n \"_format_data(self, name=None): # we are formatting thru the attributes return\",\n \"dtype: Dtype | None = None ) -> RangeIndex: \\\"\\\"\\\"\",\n \"GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2, ) return self.step\",\n \"no explicit index is provided by the user. Parameters ----------\",\n \"Introspect the data deeply, interrogate `object` dtypes for system-level memory\",\n \"value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\") def\",\n \"its underlying data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort\",\n \"the RangeIndex describing the # intersection disregarding the lower bounds\",\n \"= \\\"NaN\\\") -> list[str]: if not len(self._range): return header first_val_str\",\n \"(upper_limit - self.start) // abs(self.step) return self.start + abs(self.step) *\",\n \"*args, **kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self,\",\n \"op \\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation\",\n \"== 1: step_s = step_o = abs(self.start - other.start) elif\",\n \"name is no_default else name if values.dtype.kind == \\\"f\\\": return\",\n \"rstep = left.step with np.errstate(all=\\\"ignore\\\"): rstart = op(left.start, right) rstop\",\n \"if no_steps == -1: return np.nan elif (meth == \\\"min\\\"\",\n \"_format_attrs(self): \\\"\\\"\\\" Return a list of tuples of the (attr,\",\n \"== 0 and self.step % other == 0: start =\",\n \"the index. Attributes ---------- start stop step Methods ------- from_range\",\n \"numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes @property def dtype(self) -> np.dtype: return\",\n \"result = type(self)(rstart, rstop, rstep, **attrs) # for compat with\",\n \"x in self._range] # -------------------------------------------------------------------- _deprecation_message = ( \\\"RangeIndex.{} is\",\n \"step_o == step_s: if ( (start_s - start_o) % step_s\",\n \"-1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques\",\n \"\\\"\\\"\\\" if not all(isinstance(x, RangeIndex) for x in indexes): return\",\n \"= gcd(x, y) Finds one particular solution for x, y:\",\n \"same elements. \\\"\\\"\\\" if isinstance(other, RangeIndex): return self._range == other._range\",\n \"+ step_s / 2, step_s / 2) elif step_o %\",\n \"def get_loc(self, key, method=None, tolerance=None): if method is None and\",\n \"locs[valid] / step if step != self.step: # We reversed\",\n \"Fastpath for __getitem__ when we know we have a slice.\",\n \"- step_s <= end_s) ): return type(self)(start_r, end_r + step_s,\",\n \"first is not self._range: new_index = new_index[::-1] return new_index def\",\n \"first.step * second.step // gcd new_range = range(tmp_start, int_high, new_step)\",\n \"False, na_sentinel: int | None = -1 ) -> tuple[np.ndarray,\",\n \"index had only one element if rng.start == start: values\",\n \"max(self, axis=None, skipna: bool = True, *args, **kwargs) -> int:\",\n \"locs = target_array - start valid = (locs % step\",\n \"deprecated and will be removed in a future \\\" \\\"version.\",\n \"*args, **kwargs) -> np.ndarray: \\\"\\\"\\\" Returns the indices that would\",\n \"See Also -------- numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes @property def dtype(self)\",\n \"result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]:\",\n \"the index and its underlying data. Returns ------- np.ndarray[np.intp] See\",\n \"Index _empty_range = range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index implementing\",\n \"is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key) try: return\",\n \"self if sort and self.step < 0: codes = codes[::-1]\",\n \"and other.step < 0) is not (new_index.step < 0): new_index\",\n \"if not is_integer(rstep) or not rstep: raise ValueError else: rstep\",\n \"== \\\"f\\\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self:\",\n \"-step_s, start_s if other.step < 0: start_o, step_o, end_o =\",\n \"Returns: gcd, s, t \\\"\\\"\\\" s, old_s = 0, 1\",\n \"or (is_float(key) and key.is_integer()): new_key = int(key) try: return self._range.index(new_key)\",\n \"bool: return self._range.step > 0 or len(self) <= 1 @cache_readonly\",\n \"and self._range == other._range: # Both are immutable so if\",\n \"are immutable so if ._range attr. are equal, shortcut is\",\n \"have an override if step: with np.errstate(all=\\\"ignore\\\"): rstep = step(left.step,\",\n \"is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops\",\n \"allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) -> list[int]: return list(self._range)\",\n \"no_steps = (upper_limit - self.start) // abs(self.step) return self.start +\",\n \"tolerance=tolerance) def _get_indexer( self, target: Index, method: str | None\",\n \"with other index types. copy : bool, default False Unused,\",\n \"name: Hashable = no_default): name = self.name if name is\",\n \"representing monotonic ranges. Using RangeIndex may in some instances improve\",\n \"def is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or len(self)\",\n \"rng[-1] + step if non_empty_indexes: # Get the stop value\",\n \"def is_monotonic_increasing(self) -> bool: return self._range.step > 0 or len(self)\",\n \"False Unused, accepted for homogeneity with other index types. name\",\n \"isinstance(data, range): raise TypeError( f\\\"{cls.__name__}(...) must be called with object\",\n \"< 0 else self._range overlap = self.intersection(other) if overlap.step <\",\n \"2 params perform the binary op \\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex):\",\n \"equation # solve intersection problem # performance hint: for identical\",\n \"[RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not all(isinstance(x, RangeIndex)\",\n \"-------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) -> bool: return\",\n \"rng_indexes])) return result.rename(name) if step is not None: next_ =\",\n \"that accepts 2 params perform the binary op \\\"\\\"\\\" if\",\n \"= range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range(\",\n \"*args, **kwargs) -> int: \\\"\\\"\\\"The minimum value of the RangeIndex\\\"\\\"\\\"\",\n \"and other != 0: if len(self) == 0 or self.start\",\n \"// other # -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs)\",\n \"range: transform to original locs locs[valid] = len(self) - 1\",\n \"= other.start + other.step * (len(other) - 1) if self.step\",\n \"and decreasing ranges int_low = max(first.start, second.start) int_high = min(first.stop,\",\n \"- self.start) // abs(self.step)) return self.start + abs(self.step) * no_steps\",\n \"not None else 0 if stop is None: start, stop\",\n \"\\\" \\\"instead\\\" ) @property def start(self) -> int: \\\"\\\"\\\" The\",\n \"Hashable = no_default): name = self.name if name is no_default\",\n \"if possible or a sorted ``Int64Index`` if not. ``sort=False`` always\",\n \"( (start_s - start_o) % step_s == 0 and (start_s\",\n \") return self.start @property def stop(self) -> int: \\\"\\\"\\\" The\",\n \"Method hint: linear Diophantine equation # solve intersection problem #\",\n \"== 1: step_o = step_s start_r = min(start_s, start_o) end_r\",\n \"= self, other try: # apply if we have an\",\n \"result._name = name result._cache = {} result._reset_identity() return result #\",\n \"RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return\",\n \"The value of the `start` parameter (``0`` if this was\",\n \"are valid indices\\\" ) # fall back to Int64Index return\",\n \"_typ = \\\"rangeindex\\\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed\",\n \"if this was not supplied). .. deprecated:: 0.25.0 Use ``step``\",\n \"RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques = self if sort\",\n \"TODO: if other is a RangeIndex we may have more\",\n \"deprecated:: 0.25.0 Use ``step`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn(\",\n \"gcd: return self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing\",\n \": np.int64 Unused, accepted for homogeneity with other index types.\",\n \"(end_o - step_s <= end_s) ): return type(self)(start_r, end_r +\",\n \"stacklevel=2, ) return self.step @cache_readonly def nbytes(self) -> int: \\\"\\\"\\\"\",\n \"= self._rename(name=name) if dtype: warnings.warn( \\\"parameter dtype is deprecated and\",\n \"ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable |\",\n \"False, dtype: Dtype | None = None, names=None, ): name\",\n \"an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union :\",\n \"f\\\"index {key} is out of bounds for axis 0 with\",\n \"The difference is everything after the intersection new_rng = range(overlap[-1]\",\n \"other step = self.step // other stop = start +\",\n \"def equals(self, other: object) -> bool: \\\"\\\"\\\" Determines if two\",\n \"sort the index and its underlying data. Returns ------- np.ndarray[np.intp]\",\n \"RangeIndex instance If int and \\\"stop\\\" is not given, interpreted\",\n \"one particular solution for x, y: s, t Returns: gcd,\",\n \"6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not all(isinstance(x, RangeIndex) for x\",\n \"return ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering Methods\",\n \"\\\"integer\\\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key,\",\n \"Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex:\",\n \"return result def factorize( self, sort: bool = False, na_sentinel:\",\n \"self.start % other == 0 and self.step % other ==\",\n \"step new_range = range(start, stop, step or 1) return self._simple_new(new_range,\",\n \"\\\"\\\"\\\"Returns the smallest element greater than or equal to the\",\n \"= ensure_python_int(start) if start is not None else 0 if\",\n \"def delete(self, loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc)\",\n \"= False, na_sentinel: int | None = -1 ) ->\",\n \"from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default):\",\n \"= range(first.start, overlap[0], first.step) else: # The difference is not\",\n \"self._range.stop @property def _stop(self) -> int: \\\"\\\"\\\" The value of\",\n \"\\\" \\\"arrays are valid indices\\\" ) # fall back to\",\n \"step_s >= start_s) and (end_o - step_s <= end_s) ):\",\n \"None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right =\",\n \"not None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right\",\n \"# Set Operations def _intersection(self, other: Index, sort=False): if not\",\n \"new_index = self._simple_new(new_range) if (self.step < 0 and other.step <\",\n \"_start(self) -> int: \\\"\\\"\\\" The value of the `start` parameter\",\n \"return self._minmax(\\\"max\\\") def argsort(self, *args, **kwargs) -> np.ndarray: \\\"\\\"\\\" Returns\",\n \"len(obj)] for obj in non_empty_indexes: rng = obj._range if start\",\n \"False or None, default None Whether to sort resulting index.\",\n \"DataFrame and Series when no explicit index is provided by\",\n \"len(self) == 0 or self.start % other == 0 and\",\n \"the largest element smaller than or equal to the limit\\\"\\\"\\\"\",\n \"+ other.step * (len(other) - 1) if self.step < 0:\",\n \"from the last non-empty index stop = non_empty_indexes[-1].stop if next_\",\n \"right) # we don't have a representable op # so\",\n \"cls, data: range, name=None, dtype: Dtype | None = None\",\n \"end_r + step_s, step_s) if ( (step_s % 2 ==\",\n \"isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented elif\",\n \"compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result = np.arange(len(self),\",\n \"explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an\",\n \"step == 0: raise ValueError(\\\"Step must not be zero\\\") rng\",\n \"for performance reasons is created only when needed. The constructed\",\n \"future \\\" \\\"version. Use the astype method instead.\\\", FutureWarning, stacklevel=2,\",\n \"% step_s == 0 and (start_s - end_o) <= step_s\",\n \"to a \\\" f\\\"range, {repr(data)} was passed\\\" ) cls._validate_dtype(dtype) return\",\n \"valid = (locs % step == 0) & (locs >=\",\n \"# In some cases we might be able to get\",\n \"is not given, interpreted as \\\"stop\\\" instead. stop : int\",\n \"is out of bounds for axis 0 with size {len(self)}\\\"\",\n \"def _format_with_header(self, header: list[str], na_rep: str = \\\"NaN\\\") -> list[str]:\",\n \"name result._cache = {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly\",\n \"return self._range.step > 0 or len(self) <= 1 @cache_readonly def\",\n \"other: Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index return\",\n \"no_steps = -(-(lower_limit - self.start) // abs(self.step)) return self.start +\",\n \"return the length of the RangeIndex \\\"\\\"\\\" return len(self._range) @property\",\n \"< 0: overlap = overlap[::-1] if len(overlap) == 0: return\",\n \"tolerance=tolerance, limit=limit ) if self.step > 0: start, stop, step\",\n \"# Reductions def all(self, *args, **kwargs) -> bool: return 0\",\n \"Int64Index limited to representing monotonic ranges. Using RangeIndex may in\",\n \"Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING:\",\n \"raise IndexError( \\\"only integers, slices (`:`), \\\" \\\"ellipsis (`...`), numpy.newaxis\",\n \"= (locs % step == 0) & (locs >= 0)\",\n \"= rng.step elif step is None: # First non-empty index\",\n \"values \\\"\\\"\\\" return True @cache_readonly def is_monotonic_increasing(self) -> bool: return\",\n \"return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array\",\n \"# as a Float64Index if we have float-like descriptors if\",\n \"and self.step < 0): return self.start return self.start + self.step\",\n \"next_ = rng[-1] + step if non_empty_indexes: # Get the\",\n \"Rendering Methods def _format_attrs(self): \\\"\\\"\\\" Return a list of tuples\",\n \"[f\\\"{x:<{max_length}}\\\" for x in self._range] # -------------------------------------------------------------------- _deprecation_message = (\",\n \"self.start // other new_range = range(start, start + 1, 1)\",\n \"so return a base index if not is_integer(rstep) or not\",\n \"type(self)(rstart, rstop, rstep, **attrs) # for compat with numpy /\",\n \"if other.step < 0: start_o, step_o, end_o = end_o, -step_o,\",\n \"not isinstance(overlap, RangeIndex): # We won't end up with RangeIndex,\",\n \"provided by the user. Parameters ---------- start : int (default:\",\n \"of int64 data. \\\"\\\"\\\" _typ = \\\"rangeindex\\\" _engine_type = libindex.Int64Engine\",\n \"-> int: \\\"\\\"\\\"The minimum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args,\",\n \"if int_high <= int_low: return self._simple_new(_empty_range) # Method hint: linear\",\n \"rng.start == start: values = np.concatenate([x._values for x in rng_indexes])\",\n \"tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from\",\n \"cls, start=None, stop=None, step=None, dtype: Dtype | None = None,\",\n \"not in self._range def any(self, *args, **kwargs) -> bool: return\",\n \"ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other,\",\n \"operator from sys import getsizeof from typing import ( TYPE_CHECKING,\",\n \"-> RangeIndex: \\\"\\\"\\\" Fastpath for __getitem__ when we know we\",\n \"step_o = step_s start_r = min(start_s, start_o) end_r = max(end_s,\",\n \"no_steps def _max_fitting_element(self, upper_limit: int) -> int: \\\"\\\"\\\"Returns the largest\",\n \"None: start_s, step_s = self.start, self.step end_s = self.start +\",\n \"object coercible to a \\\" f\\\"range, {repr(data)} was passed\\\" )\",\n \"codes, uniques def equals(self, other: object) -> bool: \\\"\\\"\\\" Determines\",\n \"2 == 0) and (abs(start_s - start_o) <= step_s /\",\n \"= name result._cache = {} result._reset_identity() return result # --------------------------------------------------------------------\",\n \"-> str: return \\\"integer\\\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc)\",\n \"RangeIndex: \\\"\\\"\\\" Fastpath for __getitem__ when we know we have\",\n \"bool, default False Unused, accepted for homogeneity with other index\",\n \"index stop = non_empty_indexes[-1].stop if next_ is None else next_\",\n \"obj._range if start is None: # This is set by\",\n \"__getitem__ when we know we have a slice. \\\"\\\"\\\" res\",\n \"performance reasons is created only when needed. The constructed array\",\n \"def start(self) -> int: \\\"\\\"\\\" The value of the `start`\",\n \"is not None else 1 if step == 0: raise\",\n \"the `step` parameter (``1`` if this was not supplied). \\\"\\\"\\\"\",\n \"return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self, target: Index, method:\",\n \"Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: #\",\n \"int (default: 1) dtype : np.int64 Unused, accepted for homogeneity\",\n \"step_s) if ( (step_s % 2 == 0) and (abs(start_s\",\n \"= self.step // other stop = start + len(self) *\",\n \"name=self.name) if len(self) == 1: start = self.start // other\",\n \"type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def\",\n \"self.start, self.step end_s = self.start + self.step * (len(self) -\",\n \"When all members of \\\"indexes\\\" are of type RangeIndex: result\",\n \"\\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2, ) return self.start @property\",\n \"result.rename(name) if step is not None: next_ = rng[-1] +\",\n \"def copy( self, name: Hashable = None, deep: bool =\",\n \"Index or array-like sort : False or None, default None\",\n \"\\\"\\\"\\\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) ->\",\n \"start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) # validate the\",\n \"step : int (default: 1) dtype : np.int64 Unused, accepted\",\n \"method=method, tolerance=tolerance, limit=limit ) if self.step > 0: start, stop,\",\n \"name) elif len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex],\",\n \"None = None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]:\",\n \"# RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range):\",\n \"len(self) def __getitem__(self, key): \\\"\\\"\\\" Conserve RangeIndex type for scalar\",\n \"self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex):\",\n \"if sort and self.step < 0: codes = codes[::-1] uniques\",\n \") from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import\",\n \"indices, axis: int = 0, allow_fill: bool = True, fill_value=None,\",\n \"0 length, i.e. were empty. # In this case return\",\n \"deprecated:: 0.25.0 Use ``stop`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn(\",\n \"end_o = other.start + other.step * (len(other) - 1) if\",\n \"result = result.astype(\\\"float64\\\") return result except (ValueError, TypeError, ZeroDivisionError): #\",\n \"first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str))\",\n \"other.start) elif len(self) == 1: step_s = step_o elif len(other)\",\n \"_get_data_as_items(self): \\\"\\\"\\\" return a list of tuples of start, stop,\",\n \"RangeIndex: \\\"\\\"\\\" Create RangeIndex from a range object. Returns -------\",\n \"= new_index[::-1] if sort is None: new_index = new_index.sort_values() return\",\n \"rstart = op(left.start, right) rstop = op(left.stop, right) result =\",\n \"Hashable = None, sort=None): if not isinstance(other, RangeIndex) or sort\",\n \"step_s == 0 and (start_o + step_s >= start_s) and\",\n \"return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) ->\",\n \": The base pandas Index type. Int64Index : Index of\",\n \"result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1,\",\n \"assert isinstance(values, range) result._range = values result._name = name result._cache\",\n \"TypeError(\\\"RangeIndex(...) must be called with integers\\\") start = ensure_python_int(start) if\",\n \"of start, stop, step \\\"\\\"\\\" rng = self._range return [(\\\"start\\\",\",\n \"extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right = self,\",\n \"names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name)\",\n \"sort and self.step < 0: codes = codes[::-1] uniques =\",\n \"abs(self.step) return self.start + abs(self.step) * no_steps def _extended_gcd(self, a:\",\n \"we need to catch these explicitly return op(self._int64index, other) elif\",\n \"start_s, step_s, end_s = end_s, -step_s, start_s if other.step <\",\n \"# Method hint: linear Diophantine equation # solve intersection problem\",\n \"int(key) try: return self._range[new_key] except IndexError as err: raise IndexError(\",\n \"# from the last non-empty index stop = non_empty_indexes[-1].stop if\",\n \"a: int, b: int) -> tuple[int, int, int]: \\\"\\\"\\\" Extended\",\n \"locs[valid] = locs[valid] / step if step != self.step: #\",\n \"`stop` parameter. \\\"\\\"\\\" return self._range.stop @property def _stop(self) -> int:\",\n \"\\\"\\\"\\\" if isinstance(other, RangeIndex) and sort is None: start_s, step_s\",\n \"cls._simple_new(start, name=name) # validate the arguments if com.all_none(start, stop, step):\",\n \"= new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range)\",\n \"**kwargs) -> np.ndarray: \\\"\\\"\\\" Returns the indices that would sort\",\n \"-step_o, start_o if len(self) == 1 and len(other) == 1:\",\n \"supplied). \\\"\\\"\\\" # GH 25710 return self._range.start @property def _start(self)\",\n \"or (meth == \\\"max\\\" and self.step < 0): return self.start\",\n \"% step == 0) & (locs >= 0) & (target_array\",\n \"(abs(end_s - end_o) <= step_s / 2) ): return type(self)(start_r,\",\n \"the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. \\\"\\\"\\\"\",\n \"int: \\\"\\\"\\\"Returns the smallest element greater than or equal to\",\n \"self._name return res def _get_data_as_items(self): \\\"\\\"\\\" return a list of\",\n \".. deprecated:: 0.25.0 Use ``stop`` instead. \\\"\\\"\\\" # GH 25710\",\n \"to sort resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex``\",\n \"import annotations from datetime import timedelta import operator from sys\",\n \"min(start_s, start_o) end_r = max(end_s, end_o) if step_o == step_s:\",\n \"@classmethod def _simple_new(cls, values: range, name: Hashable = None) ->\",\n \"numpy / Int64Index # even if we can represent as\",\n \"old_t, t = t, old_t - quotient * t return\",\n \"if non_empty_indexes: # Get the stop value from \\\"next\\\" or\",\n \"the `step` parameter (``1`` if this was not supplied). ..\",\n \"/ 2) elif step_o % step_s == 0: if (\",\n \"raise IndexError( f\\\"index {key} is out of bounds for axis\",\n \"numpy.ndarray.argsort \\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\", True) # EA compat nv.validate_argsort(args,\",\n \"parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. \\\"\\\"\\\" # GH\",\n \"An int array that for performance reasons is created only\",\n \"start, stop = 0, start else: stop = ensure_python_int(stop) step\",\n \"TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333\",\n \"`stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead. \\\"\\\"\\\" #\",\n \"return op(self._int64index, other) # TODO: Do attrs get handled reliably?\",\n \"< 0 and other.step < 0) is not (new_index.step <\",\n \"rng.start != next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for\",\n \"== 0) and (abs(start_s - start_o) <= step_s / 2)\",\n \"for obj in rng_indexes if len(obj)] for obj in non_empty_indexes:\",\n \"the data deeply, interrogate `object` dtypes for system-level memory consumption\",\n \"r: quotient = old_r // r old_r, r = r,\",\n \"RangeIndex \\\"\\\"\\\" if not isinstance(data, range): raise TypeError( f\\\"{cls.__name__}(...) must\",\n \"s, old_s - quotient * s old_t, t = t,\",\n \"indices that would sort the index and its underlying data.\",\n \"if stop is None: start, stop = 0, start else:\",\n \"the astype method instead.\\\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype)\",\n \"the intersection new_rng = range(first.start, overlap[0], first.step) else: # The\",\n \"\\\"\\\"\\\" The value of the `stop` parameter. \\\"\\\"\\\" return self._range.stop\",\n \"_minmax(self, meth: str): no_steps = len(self) - 1 if no_steps\",\n \"other new_range = range(start, start + 1, 1) return self._simple_new(new_range,\",\n \"None, sort=None): if not isinstance(other, RangeIndex) or sort is not\",\n \"result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort)\",\n \"data deeply, interrogate `object` dtypes for system-level memory consumption Returns\",\n \"step = self.start, self.stop, self.step else: # GH 28678: work\",\n \"Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if step is\",\n \">= 0) & (target_array < stop) locs[~valid] = -1 locs[valid]\",\n \"op): \\\"\\\"\\\" Parameters ---------- other : Any op : callable\",\n \"try: return self._range[new_key] except IndexError as err: raise IndexError( f\\\"index\",\n \"return super().symmetric_difference(other, result_name, sort) left = self.difference(other) right = other.difference(self)\",\n \"tolerance is None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key\",\n \"the last non-empty index stop = non_empty_indexes[-1].stop if next_ is\",\n \"Both are immutable so if ._range attr. are equal, shortcut\",\n \"step_s, step_s) elif step_s % step_o == 0: if (\",\n \"are not components of the array if deep=False See Also\",\n \"new_key = int(key) try: return self._range.index(new_key) except ValueError as err:\",\n \"overlap[0] == first.start: # The difference is everything after the\",\n \"thru the attributes return None def _format_with_header(self, header: list[str], na_rep:\",\n \"err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def _get_indexer( self,\",\n \"boolean \\\" \\\"arrays are valid indices\\\" ) # fall back\",\n \"could use # cheaper alternative gcd, s, _ = self._extended_gcd(first.step,\",\n \"import pandas.core.common as com from pandas.core.construction import extract_array import pandas.core.indexes.base\",\n \"int: \\\"\\\"\\\" The value of the `start` parameter (``0`` if\",\n \"return RangeIndex(0, 0).rename(name) def __len__(self) -> int: \\\"\\\"\\\" return the\",\n \"elif isinstance(start, range): return cls._simple_new(start, name=name) # validate the arguments\",\n \"= first.step * second.step // gcd new_range = range(tmp_start, int_high,\",\n \"not be zero\\\") rng = range(start, stop, step) return cls._simple_new(rng,\",\n \"a*x + b*y = gcd(x, y) Finds one particular solution\",\n \"op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs) # for\",\n \"[operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO: if\",\n \"other : Any op : callable that accepts 2 params\",\n \"of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\") def max(self,\",\n \"the user. Parameters ---------- start : int (default: 0), range,\",\n \"if not isinstance(data, range): raise TypeError( f\\\"{cls.__name__}(...) must be called\",\n \"\\\" \\\"ellipsis (`...`), numpy.newaxis (`None`) \\\" \\\"and integer or boolean\",\n \"_shallow_copy(self, values, name: Hashable = no_default): name = self.name if\",\n \"was not supplied). .. deprecated:: 0.25.0 Use ``step`` instead. \\\"\\\"\\\"\",\n \"return self.stop @property def step(self) -> int: \\\"\\\"\\\" The value\",\n \"\\\"\\\"\\\" return the length of the RangeIndex \\\"\\\"\\\" return len(self._range)\",\n \"Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: #\",\n \"Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name,\",\n \"0 and (start_o + step_s >= start_s) and (end_o -\",\n \"self.step < 0 else self._range overlap = self.intersection(other) if overlap.step\",\n \"GH 28678: work on reversed range for simplicity reverse =\",\n \"res = self._cached_int64index res._name = self._name return res def _get_data_as_items(self):\",\n \"step(left.step, right) # we don't have a representable op #\",\n \"self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't end up\",\n \"not None and rng.start != next_ ) if non_consecutive: result\",\n \"can represent as a RangeIndex, return # as a Float64Index\",\n \"(``0`` if this was not supplied). .. deprecated:: 0.25.0 Use\",\n \"Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method\",\n \"copy : bool, default False Unused, accepted for homogeneity with\",\n \"\\\"\\\"\\\" return len(self._range) @property def size(self) -> int: return len(self)\",\n \"def _stop(self) -> int: \\\"\\\"\\\" The value of the `stop`\",\n \"name=None, dtype: Dtype | None = None ) -> RangeIndex:\",\n \"return self._range.index(new_key) except ValueError as err: raise KeyError(key) from err\",\n \"= uniques[::-1] return codes, uniques def equals(self, other: object) ->\",\n \"return super()._concat(indexes, name) elif len(indexes) == 1: return indexes[0] rng_indexes\",\n \"self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data,\",\n \"cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start,\",\n \"return a base index if not is_integer(rstep) or not rstep:\",\n \"or equal to the limit\\\"\\\"\\\" no_steps = (upper_limit - self.start)\",\n \"parameter (``0`` if this was not supplied). \\\"\\\"\\\" # GH\",\n \"not (new_index.step < 0): new_index = new_index[::-1] if sort is\",\n \"was not supplied). \\\"\\\"\\\" # GH 25710 return self._range.step @property\",\n \"to get a RangeIndex back, # but not worth the\",\n \"be called with integers\\\") start = ensure_python_int(start) if start is\",\n \"_getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \\\"\\\"\\\" Fastpath for __getitem__\",\n \"== 0 and (start_s + step_o >= start_o) and (end_s\",\n \"we know we have a slice. \\\"\\\"\\\" res = self._range[slobj]\",\n \"start = self.start // other new_range = range(start, start +\",\n \"None: start, stop = 0, start else: stop = ensure_python_int(stop)\",\n \"if is_integer(other) and other != 0: if len(self) == 0\",\n \"self._simple_new(new_range) if (self.step < 0 and other.step < 0) is\",\n \"+ len(self) * step new_range = range(start, stop, step or\",\n \"left.step with np.errstate(all=\\\"ignore\\\"): rstart = op(left.start, right) rstop = op(left.stop,\",\n \"d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None #\",\n \"isinstance(start, range): return cls._simple_new(start, name=name) # validate the arguments if\",\n \"step_s = step_o elif len(other) == 1: step_o = step_s\",\n \"<= int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine equation\",\n \"GH#19333 is_integer evaluated True on timedelta64, # so we need\",\n \"step Methods ------- from_range See Also -------- Index : The\",\n \"> 0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) ->\",\n \"def symmetric_difference(self, other, result_name: Hashable = None, sort=None): if not\",\n \"type[Int64Index]: \\\"\\\"\\\" return the class to use for construction \\\"\\\"\\\"\",\n \"new_index = new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable\",\n \"return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other,\",\n \"pandas Index type. Int64Index : Index of int64 data. \\\"\\\"\\\"\",\n \"RangeIndex, slobj: slice) -> RangeIndex: \\\"\\\"\\\" Fastpath for __getitem__ when\",\n \"ensure_python_int(stop) step = ensure_python_int(step) if step is not None else\",\n \"parameters for the RangeIndex describing the # intersection disregarding the\",\n \"kwargs) return self._minmax(\\\"max\\\") def argsort(self, *args, **kwargs) -> np.ndarray: \\\"\\\"\\\"\",\n \"(start_s - start_o) % step_s == 0 and (start_s -\",\n \"are delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array\",\n \"| None = None, copy: bool = False, name: Hashable\",\n \"start = rng.start if step is None and len(rng) >\",\n \"\\\"\\\"\\\" Determines if two Index objects contain the same elements.\",\n \"Constructors def __new__( cls, start=None, stop=None, step=None, dtype: Dtype |\",\n \"self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing the #\",\n \"# GH 25710 return self._range.step @property def _step(self) -> int:\",\n \"def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name:\",\n \"step_o >= start_o) and (end_s - step_o <= end_o) ):\",\n \"second.start) % gcd: return self._simple_new(_empty_range) # calculate parameters for the\",\n \"\\\"next\\\" or alternatively # from the last non-empty index stop\",\n \"sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if self.step\",\n \"result = result[::-1] return result def factorize( self, sort: bool\",\n \"other.start, other.step end_o = other.start + other.step * (len(other) -\",\n \"codes = codes[::-1] uniques = uniques[::-1] return codes, uniques def\",\n \"None, names=None, ): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index =\",\n \"else other._range # check whether intervals intersect # deals with\",\n \"the intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif\",\n \"skipna: bool = True, *args, **kwargs) -> int: \\\"\\\"\\\"The maximum\",\n \"(start_o + step_s >= start_s) and (end_o - step_s <=\",\n \"will be RangeIndex if possible, Int64Index otherwise. E.g.: indexes =\",\n \"else: # GH 28678: work on reversed range for simplicity\",\n \"length, i.e. were empty. # In this case return an\",\n \"header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str),\",\n \"try: return self._range.index(new_key) except ValueError as err: raise KeyError(key) from\",\n \"* s new_step = first.step * second.step // gcd new_range\",\n \"% step_s == 0: if ( (start_o - start_s) %\",\n \"doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import (\",\n \"extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from\",\n \"self._simple_new(new_range) # adjust index to limiting interval new_start = new_index._min_fitting_element(int_low)\",\n \"this was not supplied). \\\"\\\"\\\" # GH 25710 return self._range.step\",\n \"rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self),\",\n \"% other == 0 and self.step % other == 0:\",\n \"while r: quotient = old_r // r old_r, r =\",\n \"method: str | None = None, limit: int | None\",\n \"(type(self), d), None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self):\",\n \"= False, name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype)\",\n \"step_s / 2) elif step_o % step_s == 0: if\",\n \"whether element sets intersect if (first.start - second.start) % gcd:\",\n \"self.difference(other) right = other.difference(self) result = left.union(right) if result_name is\",\n \"= result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index],\",\n \"step_s % step_o == 0: if ( (start_s - start_o)\",\n \"= self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step if\",\n \"case return an empty range index. return RangeIndex(0, 0).rename(name) def\",\n \"Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)):\",\n \"KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance) def\",\n \"0 else other._range # check whether intervals intersect # deals\",\n \"attrs = self._get_data_as_items() if self.name is not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name)))\",\n \"self._cache return result @doc(Int64Index.copy) def copy( self, name: Hashable =\",\n \"0) and (abs(start_s - start_o) <= step_s / 2) and\",\n \"is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import\",\n \"(\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items()))\",\n \"objects and sorts if possible Parameters ---------- other : Index\",\n \"end_o = end_o, -step_o, start_o if len(self) == 1 and\",\n \"if self.name is not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs def\",\n \"super()._difference(other, sort=sort) if overlap.step != first.step: # In some cases\",\n \"\\\"arrays are valid indices\\\" ) # fall back to Int64Index\",\n \"warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def\",\n \"0) step : int (default: 1) dtype : np.int64 Unused,\",\n \"index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int: \\\"\\\"\\\" return\",\n \"tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if\",\n \"deep=deep)[0] new_index = self._rename(name=name) if dtype: warnings.warn( \\\"parameter dtype is\",\n \"(len(self) - 1) start_o, step_o = other.start, other.step end_o =\",\n \"yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable =\",\n \"self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): # optimized set operation\",\n \"result = Int64Index(values) return result.rename(name) step = rng.start - start\",\n \"-1 locs[valid] = locs[valid] / step if step != self.step:\",\n \"return type(self)(start_r, end_r + step_s, step_s) if ( (step_s %\",\n \"from sys import getsizeof from typing import ( TYPE_CHECKING, Any,\",\n \"-------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable) -> Index: \\\"\\\"\\\"\",\n \"consumption Returns ------- bytes used Notes ----- Memory usage does\",\n \"= overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if len(overlap)\",\n \"parent method for the case of all RangeIndex instances. When\",\n \"0 not in self._range def any(self, *args, **kwargs) -> bool:\",\n \"FutureWarning, stacklevel=2, ) return self.start @property def stop(self) -> int:\",\n \"int: \\\"\\\"\\\"The minimum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs)\",\n \"@property def _int64index(self) -> Int64Index: # wrap _cached_int64index so we\",\n \"Euclidean algorithms to solve Bezout's identity: a*x + b*y =\",\n \"step = rng.step elif step is None: # First non-empty\",\n \"self._range] # -------------------------------------------------------------------- _deprecation_message = ( \\\"RangeIndex.{} is deprecated and\",\n \"= self._simple_new(new_range) if (self.step < 0 and other.step < 0)\",\n \"-> Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill,\",\n \"2) ): return type(self)(start_r, end_r + step_s / 2, step_s\",\n \"attr. are equal, shortcut is possible return super()._cmp_method(self, op) return\",\n \"nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\") def max(self, axis=None, skipna: bool\",\n \"get_loc(self, key, method=None, tolerance=None): if method is None and tolerance\",\n \"self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self)\",\n \"if other.step < 0 else other._range # check whether intervals\",\n \"in a future version. Use RangeIndex.{} \\\" \\\"instead\\\" ) @property\",\n \"type for scalar and slice keys. \\\"\\\"\\\" if isinstance(key, slice):\",\n \"0, 1 t, old_t = 1, 0 r, old_r =\",\n \"_empty_range = range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index implementing a\",\n \"range index. return RangeIndex(0, 0).rename(name) def __len__(self) -> int: \\\"\\\"\\\"\",\n \"new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] ==\",\n \"import timedelta import operator from sys import getsizeof from typing\",\n \"explicit index is provided by the user. Parameters ---------- start\",\n \"is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method return super()._get_indexer(target,\",\n \"len(rng) > 1) or ( next_ is not None and\",\n \"= self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None # --------------------------------------------------------------------\",\n \"not supplied). \\\"\\\"\\\" # GH 25710 return self._range.step @property def\",\n \"RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex if\",\n \"1) dtype : np.int64 Unused, accepted for homogeneity with other\",\n \"= other.start, other.step end_o = other.start + other.step * (len(other)\",\n \"if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self,\",\n \"ignore[override] return self._int64index.delete(loc) def take( self, indices, axis: int =\",\n \"np.arange(len(self), dtype=np.intp) uniques = self if sort and self.step <\",\n \"all(self, *args, **kwargs) -> bool: return 0 not in self._range\",\n \"locs[~valid] = -1 locs[valid] = locs[valid] / step if step\",\n \"this was not supplied). .. deprecated:: 0.25.0 Use ``step`` instead.\",\n \"# EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0: result\",\n \"the index has unique values \\\"\\\"\\\" return True @cache_readonly def\",\n \"result_name, sort) left = self.difference(other) right = other.difference(self) result =\",\n \"end_s) ): return type(self)(start_r, end_r + step_s, step_s) elif step_s\",\n \"\\\"\\\"\\\" Memory usage of my values Parameters ---------- deep :\",\n \"before the intersection new_rng = range(first.start, overlap[0], first.step) else: #\",\n \"+ first.step, first.stop, first.step) elif overlap[-1] == first[-1]: # The\",\n \"if isinstance(other, RangeIndex) and sort is None: start_s, step_s =\",\n \"len(rng) > 1: step = rng.step elif step is None:\",\n \"kwargs.pop(\\\"ascending\\\", True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step >\",\n \"first non-empty index start = rng.start if step is None\",\n \"self.name res = self._cached_int64index res._name = self._name return res def\",\n \"locs locs[valid] = len(self) - 1 - locs[valid] return ensure_platform_int(locs)\",\n \"index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start,\",\n \"stop=None, step=None, dtype: Dtype | None = None, copy: bool\",\n \"= self.start, self.step end_s = self.start + self.step * (len(self)\",\n \"performance hint: for identical step sizes, could use # cheaper\",\n \"object.__new__(cls) assert isinstance(values, range) result._range = values result._name = name\",\n \"_difference(self, other, sort=None): # optimized set operation if we have\",\n \"t = t, old_t - quotient * t return old_r,\",\n \"index has unique values \\\"\\\"\\\" return True @cache_readonly def is_monotonic_increasing(self)\",\n \"be zero\\\") rng = range(start, stop, step) return cls._simple_new(rng, name=name)\",\n \"rng.start - start non_consecutive = (step != rng.step and len(rng)\",\n \"bool = False, na_sentinel: int | None = -1 )\",\n \"_concat(self, indexes: list[Index], name: Hashable) -> Index: \\\"\\\"\\\" Overriding parent\",\n \"data. \\\"\\\"\\\" rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng,\",\n \"linear Diophantine equation # solve intersection problem # performance hint:\",\n \"str: return \\\"integer\\\" # -------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def\",\n \"self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs, ) def tolist(self) ->\",\n \"overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name) if len(overlap) ==\",\n \"the empty indexes non_empty_indexes = [obj for obj in rng_indexes\",\n \"locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) ->\",\n \"when no explicit index is provided by the user. Parameters\",\n \"by the user. Parameters ---------- start : int (default: 0),\",\n \"/ 2, step_s / 2) elif step_o % step_s ==\",\n \"header: list[str], na_rep: str = \\\"NaN\\\") -> list[str]: if not\",\n \"indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step = next_\",\n \"step = self.step // other stop = start + len(self)\",\n \"step_s = step_o = abs(self.start - other.start) elif len(self) ==\",\n \"-> int: \\\"\\\"\\\" Return the number of bytes in the\",\n \"were empty. # In this case return an empty range\",\n \"getsizeof from typing import ( TYPE_CHECKING, Any, Callable, Hashable, List,\",\n \"= non_empty_indexes[-1].stop if next_ is None else next_ return RangeIndex(start,\",\n \"index is provided by the user. Parameters ---------- start :\",\n \"_simple_new(cls, values: range, name: Hashable = None) -> RangeIndex: result\",\n \"if com.all_none(start, stop, step): raise TypeError(\\\"RangeIndex(...) must be called with\",\n \"if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit\",\n \"monotonically increasing ``RangeIndex`` if possible or a sorted ``Int64Index`` if\",\n \"int) -> int: \\\"\\\"\\\"Returns the largest element smaller than or\",\n \"( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if\",\n \"The difference is not range-like return super()._difference(other, sort=sort) new_index =\",\n \"if not. ``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded::\",\n \"for compat with numpy / Int64Index # even if we\",\n \"if not isinstance(other, RangeIndex) or sort is not None: return\",\n \"stop, step = self.start, self.stop, self.step else: # GH 28678:\",\n \"= op # TODO: if other is a RangeIndex we\",\n \"ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index,\",\n \"reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to\",\n \"of the `start` parameter (``0`` if this was not supplied).\",\n \"-> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op):\",\n \".. versionadded:: 0.25.0 Returns ------- union : Index \\\"\\\"\\\" if\",\n \"in self._range @property def inferred_type(self) -> str: return \\\"integer\\\" #\",\n \"str = \\\"NaN\\\") -> list[str]: if not len(self._range): return header\",\n \"not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not\",\n \"\\\"stop\\\"), FutureWarning, stacklevel=2, ) return self.stop @property def step(self) ->\",\n \"two Index objects and sorts if possible Parameters ---------- other\",\n \"- start_o) % step_s == 0 and (start_s - end_o)\",\n \"pandas.core.dtypes.generic import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as\",\n \"= maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex): return\",\n \"sort=sort) def _difference(self, other, sort=None): # optimized set operation if\",\n \"nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\") def argsort(self, *args, **kwargs) -> np.ndarray:\",\n \"0: start = self.start // other step = self.step //\",\n \"int_low = max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high\",\n \"0, allow_fill: bool = True, fill_value=None, **kwargs ) -> Int64Index:\",\n \"the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\") def max(self, axis=None,\",\n \"solution for x, y: s, t Returns: gcd, s, t\",\n \"np.errstate(all=\\\"ignore\\\"): rstart = op(left.start, right) rstop = op(left.stop, right) result\",\n \"if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif\",\n \"pandas._typing import Dtype from pandas.compat.numpy import function as nv from\",\n \"(new_index.step < 0): new_index = new_index[::-1] if sort is None:\",\n \"= \\\"rangeindex\\\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed integer\\\")\",\n \"rng_indexes = cast(List[RangeIndex], indexes) start = step = next_ =\",\n \"attr_name in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"] ) def memory_usage(self, deep: bool\",\n \"ensure_python_int(step) if step is not None else 1 if step\",\n \"r old_s, s = s, old_s - quotient * s\",\n \"in- and decreasing ranges int_low = max(first.start, second.start) int_high =\",\n \"if step is not None: next_ = rng[-1] + step\",\n \"with np.errstate(all=\\\"ignore\\\"): rstep = step(left.step, right) # we don't have\",\n \"-> np.ndarray: \\\"\\\"\\\" Returns the indices that would sort the\",\n \"not None: result = result.rename(result_name) return result # -------------------------------------------------------------------- def\",\n \"TypeError( f\\\"{cls.__name__}(...) must be called with object coercible to a\",\n \"nbytes(self) -> int: \\\"\\\"\\\" Return the number of bytes in\",\n \"a RangeIndex we may have more efficient options other =\",\n \"Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value,\",\n \"if overlap[0] == first.start: # The difference is everything after\",\n \"# optimized set operation if we have another RangeIndex self._validate_sort_keyword(sort)\",\n \"# -------------------------------------------------------------------- _deprecation_message = ( \\\"RangeIndex.{} is deprecated and will\",\n \"or len(self) <= 1 def __contains__(self, key: Any) -> bool:\",\n \"Dtype from pandas.compat.numpy import function as nv from pandas.util._decorators import\",\n \"and rng.start != next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values\",\n \"indices\\\" ) # fall back to Int64Index return super().__getitem__(key) def\",\n \"int: \\\"\\\"\\\" Memory usage of my values Parameters ---------- deep\",\n \"my values Parameters ---------- deep : bool Introspect the data\",\n \"original locs locs[valid] = len(self) - 1 - locs[valid] return\",\n \"minimum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\")\",\n \"return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We won't end\",\n \"of \\\"indexes\\\" are of type RangeIndex: result will be RangeIndex\",\n \"pandas.core import ops import pandas.core.common as com from pandas.core.construction import\",\n \"timedelta import operator from sys import getsizeof from typing import\",\n \"= self._range[::-1] if self.step < 0 else self._range overlap =\",\n \"name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result\",\n \"_extended_gcd(self, a: int, b: int) -> tuple[int, int, int]: \\\"\\\"\\\"\",\n \"r, old_r - quotient * r old_s, s = s,\",\n \"``stop`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning,\",\n \"new_step = first.step * second.step // gcd new_range = range(tmp_start,\",\n \"0.25.0 Use ``step`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\",\",\n \"def _min_fitting_element(self, lower_limit: int) -> int: \\\"\\\"\\\"Returns the smallest element\",\n \"return new_index def symmetric_difference(self, other, result_name: Hashable = None, sort=None):\",\n \"with RangeIndex, so fall back return super()._difference(other, sort=sort) if overlap.step\",\n \"self.name if name is no_default else name if values.dtype.kind ==\",\n \"return self._int64index // other # -------------------------------------------------------------------- # Reductions def all(self,\",\n \"elif overlap[-1] == first[-1]: # The difference is everything before\",\n \"even if we can represent as a RangeIndex, return #\",\n \"as a RangeIndex, return # as a Float64Index if we\",\n \"intersect if (first.start - second.start) % gcd: return self._simple_new(_empty_range) #\",\n \"step_o == 0: if ( (start_s - start_o) % step_o\",\n \"instead. stop : int (default: 0) step : int (default:\",\n \"array that for performance reasons is created only when needed.\",\n \"that for performance reasons is created only when needed. The\",\n \"and tolerance is None: if is_integer(key) or (is_float(key) and key.is_integer()):\",\n \"data. Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \\\"\\\"\\\" ascending\",\n \"<= step_s / 2) ): return type(self)(start_r, end_r + step_s\",\n \") -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit):\",\n \"name=self._name) elif is_integer(key): new_key = int(key) try: return self._range[new_key] except\",\n \"elif is_integer(key): new_key = int(key) try: return self._range[new_key] except IndexError\",\n \"meth: str): no_steps = len(self) - 1 if no_steps ==\",\n \"Using RangeIndex may in some instances improve computing speed. This\",\n \"str(self._range[0]) last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header\",\n \"None: # This is set by the first non-empty index\",\n \"# GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2, ) return\",\n \"Filter the empty indexes non_empty_indexes = [obj for obj in\",\n \"# Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if\",\n \"0) is not (new_index.step < 0): new_index = new_index[::-1] if\",\n \"Dtype | None = None, names=None, ): name = self._validate_names(name=name,\",\n \"shortcut is possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def\",\n \"None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int)\",\n \"= rng.start - start non_consecutive = (step != rng.step and\",\n \"if ( (start_s - start_o) % step_o == 0 and\",\n \"ops.rtruediv]: step = op # TODO: if other is a\",\n \"if this was not supplied). .. deprecated:: 0.25.0 Use ``start``\",\n \"// abs(self.step) return self.start + abs(self.step) * no_steps def _extended_gcd(self,\",\n \"key: Any) -> bool: hash(key) try: key = ensure_python_int(key) except\",\n \"end_s) <= step_s ): return type(self)(start_r, end_r + step_s, step_s)\",\n \"that are not components of the array if deep=False See\",\n \"None = None, limit: int | None = None, tolerance=None,\",\n \"limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step\",\n \"from_range See Also -------- Index : The base pandas Index\",\n \"Index, sort): \\\"\\\"\\\" Form the union of two Index objects\",\n \"so fall back return super()._difference(other, sort=sort) if overlap.step != first.step:\",\n \"RangeIndex(start, stop, step).rename(name) # Here all \\\"indexes\\\" had 0 length,\",\n \") from err elif is_scalar(key): raise IndexError( \\\"only integers, slices\",\n \"def _data(self) -> np.ndarray: \\\"\\\"\\\" An int array that for\",\n \"@property def _step(self) -> int: \\\"\\\"\\\" The value of the\",\n \"return self._simple_new(_empty_range) # calculate parameters for the RangeIndex describing the\",\n \"nv from pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions\",\n \"s old_t, t = t, old_t - quotient * t\",\n \"self.step end_s = self.start + self.step * (len(self) - 1)\",\n \"def _format_data(self, name=None): # we are formatting thru the attributes\",\n \"axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) ->\",\n \"* second.step // gcd new_range = range(tmp_start, int_high, new_step) new_index\",\n \"len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step\",\n \"step_o <= end_o) ): return type(self)(start_r, end_r + step_o, step_o)\",\n \"max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high <= int_low:\",\n \"step = op # TODO: if other is a RangeIndex\",\n \"op # so return a base index if not is_integer(rstep)\",\n \"as a Float64Index if we have float-like descriptors if not\",\n \"\\\"f\\\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex)\",\n \"RangeIndex) or sort is not None: return super().symmetric_difference(other, result_name, sort)\",\n \"= [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not all(isinstance(x,\",\n \"other) elif is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return\",\n \"# GH 28678: work on reversed range for simplicity reverse\",\n \"of the `stop` parameter. .. deprecated:: 0.25.0 Use ``stop`` instead.\",\n \"is None: if is_integer(key) or (is_float(key) and key.is_integer()): new_key =\",\n \"axis: int = 0, allow_fill: bool = True, fill_value=None, **kwargs\",\n \"dtype=np.intp) if not ascending: result = result[::-1] return result def\",\n \"f\\\"{cls.__name__}(...) must be called with object coercible to a \\\"\",\n \"-1, -1, dtype=np.intp) if not ascending: result = result[::-1] return\",\n \"def memory_usage(self, deep: bool = False) -> int: \\\"\\\"\\\" Memory\",\n \"np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\", True)\",\n \"not all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes, name)\",\n \"with np.errstate(all=\\\"ignore\\\"): rstart = op(left.start, right) rstop = op(left.stop, right)\",\n \"= kwargs.pop(\\\"ascending\\\", True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step\",\n \"= other.difference(self) result = left.union(right) if result_name is not None:\",\n \"Methods def _format_attrs(self): \\\"\\\"\\\" Return a list of tuples of\",\n \"0: overlap = overlap[::-1] if len(overlap) == 0: return self.rename(name=res_name)\",\n \"np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return\",\n \"-> int: \\\"\\\"\\\"The maximum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args,\",\n \"# -------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index, sort=False):\",\n \"of the `stop` parameter. \\\"\\\"\\\" return self._range.stop @property def _stop(self)\",\n \"@doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values,\",\n \"method=None, tolerance=None): if method is None and tolerance is None:\",\n \"@property def _start(self) -> int: \\\"\\\"\\\" The value of the\",\n \"dtype=np.intp) else: result = np.arange(len(self) - 1, -1, -1, dtype=np.intp)\",\n \"None else 1 if step == 0: raise ValueError(\\\"Step must\",\n \"# We reversed this range: transform to original locs locs[valid]\",\n \"start non_consecutive = (step != rng.step and len(rng) > 1)\",\n \"deals with in- and decreasing ranges int_low = max(first.start, second.start)\",\n \"for identical step sizes, could use # cheaper alternative gcd,\",\n \"solve Bezout's identity: a*x + b*y = gcd(x, y) Finds\",\n \"rstop, rstep]): result = result.astype(\\\"float64\\\") return result except (ValueError, TypeError,\",\n \"other) step: Callable | None = None if op in\",\n \"from datetime import timedelta import operator from sys import getsizeof\",\n \"pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import\",\n \"accepts 2 params perform the binary op \\\"\\\"\\\" if isinstance(other,\",\n \"\\\"only integers, slices (`:`), \\\" \\\"ellipsis (`...`), numpy.newaxis (`None`) \\\"\",\n \"start, stop, step \\\"\\\"\\\" rng = self._range return [(\\\"start\\\", rng.start),\",\n \"\\\"\\\"\\\" Return a list of tuples of the (attr, formatted_value)\",\n \"indexes: list[Index], name: Hashable) -> Index: \\\"\\\"\\\" Overriding parent method\",\n \"simplicity reverse = self._range[::-1] start, stop, step = reverse.start, reverse.stop,\",\n \"range, or other RangeIndex instance If int and \\\"stop\\\" is\",\n \"uniques = uniques[::-1] return codes, uniques def equals(self, other: object)\",\n \"ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other)\",\n \"= max(first.start, second.start) int_high = min(first.stop, second.stop) if int_high <=\",\n \"\\\"rangeindex\\\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na\",\n \"step is None: # First non-empty index had only one\",\n \"(`:`), \\\" \\\"ellipsis (`...`), numpy.newaxis (`None`) \\\" \\\"and integer or\",\n \"super().equals(other) # -------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index,\",\n \"stop step Methods ------- from_range See Also -------- Index :\",\n \"FutureWarning, stacklevel=2, ) return self.step @cache_readonly def nbytes(self) -> int:\",\n \"end_o) <= step_s and (start_o - end_s) <= step_s ):\",\n \"step == 0) & (locs >= 0) & (target_array <\",\n \"dtype: Dtype | None = None, copy: bool = False,\",\n \"result = left.union(right) if result_name is not None: result =\",\n \": bool, default False Unused, accepted for homogeneity with other\",\n \"the stop value from \\\"next\\\" or alternatively # from the\",\n \"not given, interpreted as \\\"stop\\\" instead. stop : int (default:\",\n \"Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method is\",\n \"equal to the limit\\\"\\\"\\\" no_steps = -(-(lower_limit - self.start) //\",\n \"self._range @doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default): name\",\n \") return self.stop @property def step(self) -> int: \\\"\\\"\\\" The\",\n \"a representable op # so return a base index if\",\n \"-------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \\\"\\\"\\\" Return a list\",\n \"repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self,\",\n \"-> int: return len(self) def __getitem__(self, key): \\\"\\\"\\\" Conserve RangeIndex\",\n \"# Both are immutable so if ._range attr. are equal,\",\n \"Hashable = None, deep: bool = False, dtype: Dtype |\",\n \"np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance,\",\n \"-> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method,\",\n \") -> Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take( indices, axis=axis,\",\n \"formatting thru the attributes return None def _format_with_header(self, header: list[str],\",\n \"return result except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index\",\n \"return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) # validate\",\n \"integers, slices (`:`), \\\" \\\"ellipsis (`...`), numpy.newaxis (`None`) \\\" \\\"and\",\n \"self.step < 0: codes = codes[::-1] uniques = uniques[::-1] return\",\n \"elif step_s % step_o == 0: if ( (start_s -\",\n \"int and \\\"stop\\\" is not given, interpreted as \\\"stop\\\" instead.\",\n \"return np.dtype(np.int64) @property def is_unique(self) -> bool: \\\"\\\"\\\" return if\",\n \"None else next_ return RangeIndex(start, stop, step).rename(name) # Here all\",\n \"back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice)\",\n \"the first non-empty index start = rng.start if step is\",\n \"intersection problem # performance hint: for identical step sizes, could\",\n \"ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import\",\n \"not components of the array if deep=False See Also --------\",\n \"% step_o == 0 and (start_s + step_o >= start_o)\",\n \"= first.start + (second.start - first.start) * first.step // gcd\",\n \"method is None and tolerance is None: if is_integer(key) or\",\n \"= self._name return res def _get_data_as_items(self): \\\"\\\"\\\" return a list\",\n \"maximum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\")\",\n \"= 1, 0 r, old_r = b, a while r:\",\n \"pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import\",\n \"second.step) # check whether element sets intersect if (first.start -\",\n \"maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex): return start.copy(name=name)\",\n \"step \\\"\\\"\\\" rng = self._range return [(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop),\",\n \"op(self._int64index, other) if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod,\",\n \"the same elements. \\\"\\\"\\\" if isinstance(other, RangeIndex): return self._range ==\",\n \"# The difference is not range-like return super()._difference(other, sort=sort) new_index\",\n \"end_s = end_s, -step_s, start_s if other.step < 0: start_o,\",\n \"rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar,\",\n \"= left.step with np.errstate(all=\\\"ignore\\\"): rstart = op(left.start, right) rstop =\",\n \"-> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range\",\n \"b: int) -> tuple[int, int, int]: \\\"\\\"\\\" Extended Euclidean algorithms\",\n \"range) result._range = values result._name = name result._cache = {}\",\n \"range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step < 0\",\n \"if start is not None else 0 if stop is\",\n \"= range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index implementing a monotonic\",\n \"def is_unique(self) -> bool: \\\"\\\"\\\" return if the index has\",\n \"dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property\",\n \"new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index =\",\n \"if we can represent as a RangeIndex, return # as\",\n \"% step_s == 0 and (start_o + step_s >= start_s)\",\n \"// other stop = start + len(self) * step new_range\",\n \"% 2 == 0) and (abs(start_s - start_o) <= step_s\",\n \"else 1 if step == 0: raise ValueError(\\\"Step must not\",\n \"None # Filter the empty indexes non_empty_indexes = [obj for\",\n \"sorted ``Int64Index`` if not. ``sort=False`` always returns an unsorted ``Int64Index``\",\n \"x in indexes): return super()._concat(indexes, name) elif len(indexes) == 1:\",\n \"---------- other : Any op : callable that accepts 2\",\n \"step != self.step: # We reversed this range: transform to\",\n \"indexes non_empty_indexes = [obj for obj in rng_indexes if len(obj)]\",\n \"used by DataFrame and Series when no explicit index is\",\n \"/ step if step != self.step: # We reversed this\",\n \"t, old_t - quotient * t return old_r, old_s, old_t\",\n \"self._simple_new(new_range, name=self.name) return self._int64index // other # -------------------------------------------------------------------- # Reductions\",\n \"return self._simple_new(_empty_range) # Method hint: linear Diophantine equation # solve\",\n \"of bytes in the underlying data. \\\"\\\"\\\" rng = self._range\",\n \"RangeIndex \\\"\\\"\\\" return len(self._range) @property def size(self) -> int: return\",\n \"old_r - quotient * r old_s, s = s, old_s\",\n \"else: # The difference is not range-like return super()._difference(other, sort=sort)\",\n \"- quotient * s old_t, t = t, old_t -\",\n \"self._range.step > 0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self)\",\n \"checks/conversions/roundings are delegated to general method return super()._get_indexer(target, method=method, tolerance=tolerance)\",\n \"be \\\" \\\"removed in a future version. Use RangeIndex.{} \\\"\",\n \"cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name: Hashable =\",\n \"\\\"stop\\\", \\\"step\\\"] ) def memory_usage(self, deep: bool = False) ->\",\n \"size(self) -> int: return len(self) def __getitem__(self, key): \\\"\\\"\\\" Conserve\",\n \"any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex)\",\n \"Use the astype method instead.\\\", FutureWarning, stacklevel=2, ) new_index =\",\n \"start valid = (locs % step == 0) & (locs\",\n \"self.step < 0): return self.start return self.start + self.step *\",\n \"constructed array is saved in ``_cache``. \\\"\\\"\\\" return np.arange(self.start, self.stop,\",\n \"is_scalar(key): raise IndexError( \\\"only integers, slices (`:`), \\\" \\\"ellipsis (`...`),\",\n \"-> int: \\\"\\\"\\\" The value of the `stop` parameter. ..\",\n \"evaluated True on timedelta64, # so we need to catch\",\n \"# -------------------------------------------------------------------- def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and\",\n \"obj in non_empty_indexes: rng = obj._range if start is None:\",\n \"\\\"\\\"\\\"Returns the largest element smaller than or equal to the\",\n \"RangeIndex may in some instances improve computing speed. This is\",\n \"len(self._range): return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length\",\n \"= None, copy: bool = False, name: Hashable = None,\",\n \"the (attr, formatted_value) \\\"\\\"\\\" attrs = self._get_data_as_items() if self.name is\",\n \"E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes =\",\n \"+ step_s, step_s) elif step_s % step_o == 0: if\",\n \"is None: # This is set by the first non-empty\",\n \"`start` parameter (``0`` if this was not supplied). \\\"\\\"\\\" #\",\n \"= self._range[::-1] if self.step < 0 else self._range second =\",\n \"bool Introspect the data deeply, interrogate `object` dtypes for system-level\",\n \"Determines if two Index objects contain the same elements. \\\"\\\"\\\"\",\n \"result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \\\"\\\"\\\" return\",\n \"range, name=None, dtype: Dtype | None = None ) ->\",\n \"return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit ) if self.step >\",\n \"return # as a Float64Index if we have float-like descriptors\",\n \"Index, method: str | None = None, limit: int |\",\n \"version. Use RangeIndex.{} \\\" \\\"instead\\\" ) @property def start(self) ->\",\n \"bool: hash(key) try: key = ensure_python_int(key) except TypeError: return False\",\n \"\\\"stop\\\" instead. stop : int (default: 0) step : int\",\n \"object. Returns ------- RangeIndex \\\"\\\"\\\" if not isinstance(data, range): raise\",\n \"+ 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index // other\",\n \"0: start, stop, step = self.start, self.stop, self.step else: #\",\n \"start_s if other.step < 0: start_o, step_o, end_o = end_o,\",\n \"possible return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other,\",\n \"target: Index, method: str | None = None, limit: int\",\n \"if len(obj)] for obj in non_empty_indexes: rng = obj._range if\",\n \"# checks/conversions/roundings are delegated to general method return super()._get_indexer(target, method=method,\",\n \"instances. When all members of \\\"indexes\\\" are of type RangeIndex:\",\n \"\\\"\\\"\\\" # GH 25710 return self._range.step @property def _step(self) ->\",\n \"type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other): if is_integer(other) and other\",\n \"is not None else 0 if stop is None: start,\",\n \"slice keys. \\\"\\\"\\\" if isinstance(key, slice): new_range = self._range[key] return\",\n \"not supplied). .. deprecated:: 0.25.0 Use ``step`` instead. \\\"\\\"\\\" #\",\n \"maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, ) from\",\n \"return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be an np.ndarray;\",\n \"self._get_attributes_dict() left, right = self, other try: # apply if\",\n \"valid indices\\\" ) # fall back to Int64Index return super().__getitem__(key)\",\n \"len(self) - 1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def\",\n \"or other RangeIndex instance If int and \\\"stop\\\" is not\",\n \"than or equal to the limit\\\"\\\"\\\" no_steps = (upper_limit -\",\n \"rstep = step(left.step, right) # we don't have a representable\",\n \"int: \\\"\\\"\\\"Returns the largest element smaller than or equal to\",\n \"25710 return self._range.start @property def _start(self) -> int: \\\"\\\"\\\" The\",\n \"# Here all \\\"indexes\\\" had 0 length, i.e. were empty.\",\n \"= rng.start if step is None and len(rng) > 1:\",\n \"range(first.start, overlap[0], first.step) else: # The difference is not range-like\",\n \"(default: 0), range, or other RangeIndex instance If int and\",\n \"sort=sort) if overlap.step != first.step: # In some cases we\",\n \"special case of Int64Index limited to representing monotonic ranges. Using\",\n \"result_name is not None: result = result.rename(result_name) return result #\",\n \"< 0 else self._range second = other._range[::-1] if other.step <\",\n \"dtype : np.int64 Unused, accepted for homogeneity with other index\",\n \"not is_signed_integer_dtype(target): # checks/conversions/roundings are delegated to general method return\",\n \"# Rendering Methods def _format_attrs(self): \\\"\\\"\\\" Return a list of\",\n \"resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible\",\n \"0: if ( (start_o - start_s) % step_s == 0\",\n \") if non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes]))\",\n \"that would sort the index and its underlying data. Returns\",\n \"str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header + [f\\\"{x:<{max_length}}\\\" for\",\n \"== 0: return self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name)\",\n \"RangeIndex): # We won't end up with RangeIndex, so fall\",\n \"name if values.dtype.kind == \\\"f\\\": return Float64Index(values, name=name) return Int64Index._simple_new(values,\",\n \"\\\"\\\"\\\" Fastpath for __getitem__ when we know we have a\",\n \"old_r, r = r, old_r - quotient * r old_s,\",\n \"from pandas.compat.numpy import function as nv from pandas.util._decorators import (\",\n \"0: start_o, step_o, end_o = end_o, -step_o, start_o if len(self)\",\n \"\\\" \\\"version. Use the astype method instead.\\\", FutureWarning, stacklevel=2, )\",\n \"we can represent as a RangeIndex, return # as a\",\n \"y) Finds one particular solution for x, y: s, t\",\n \"= type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index =\",\n \"stop, step or 1) return self._simple_new(new_range, name=self.name) if len(self) ==\",\n \"alternative gcd, s, _ = self._extended_gcd(first.step, second.step) # check whether\",\n \"apply if we have an override if step: with np.errstate(all=\\\"ignore\\\"):\",\n \"by DataFrame and Series when no explicit index is provided\",\n \"new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) -> int: \\\"\\\"\\\"Returns\",\n \"ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we are formatting\",\n \"int: \\\"\\\"\\\" The value of the `stop` parameter. \\\"\\\"\\\" return\",\n \"operator.truediv, ops.rtruediv]: step = op # TODO: if other is\",\n \"result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name:\",\n \"members of \\\"indexes\\\" are of type RangeIndex: result will be\",\n \"as np from pandas._libs import index as libindex from pandas._libs.lib\",\n \"\\\"\\\"\\\" Conserve RangeIndex type for scalar and slice keys. \\\"\\\"\\\"\",\n \"start = self.start // other step = self.step // other\",\n \"If int and \\\"stop\\\" is not given, interpreted as \\\"stop\\\"\",\n \"= no_default): name = self.name if name is no_default else\",\n \"Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from\",\n \"if (self.step < 0 and other.step < 0) is not\",\n \"1) if self.step < 0: start_s, step_s, end_s = end_s,\",\n \"bool = False, name: Hashable = None, ) -> RangeIndex:\",\n \"Returns ------- np.ndarray[np.intp] See Also -------- numpy.ndarray.argsort \\\"\\\"\\\" ascending =\",\n \"annotations from datetime import timedelta import operator from sys import\",\n \"``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns\",\n \"index types. name : object, optional Name to be stored\",\n \"None and len(rng) > 1: step = rng.step elif step\",\n \"some instances improve computing speed. This is the default index\",\n \"1 and len(other) == 1: step_s = step_o = abs(self.start\",\n \"import ( TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import\",\n \"return result # -------------------------------------------------------------------- def _concat(self, indexes: list[Index], name: Hashable)\",\n \"old_t - quotient * t return old_r, old_s, old_t def\",\n \"stop = 0, start else: stop = ensure_python_int(stop) step =\",\n \"object) -> bool: \\\"\\\"\\\" Determines if two Index objects contain\",\n \"is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from pandas.core.dtypes.generic import ABCTimedeltaIndex from\",\n \"First non-empty index had only one element if rng.start ==\",\n \"= new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps =\",\n \"Set Operations def _intersection(self, other: Index, sort=False): if not isinstance(other,\",\n \"first.start) * first.step // gcd * s new_step = first.step\",\n \"Name to be stored in the index. Attributes ---------- start\",\n \"step_o elif len(other) == 1: step_o = step_s start_r =\",\n \"non-empty index had only one element if rng.start == start:\",\n \"or self.start % other == 0 and self.step % other\",\n \"int]: \\\"\\\"\\\" Extended Euclidean algorithms to solve Bezout's identity: a*x\",\n \"indexes = [RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3),\",\n \"with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take( indices, axis=axis, allow_fill=allow_fill, fill_value=fill_value, **kwargs,\",\n \"from_range( cls, data: range, name=None, dtype: Dtype | None =\",\n \"is None and len(rng) > 1: step = rng.step elif\",\n \"np.int64 Unused, accepted for homogeneity with other index types. copy\",\n \"= r, old_r - quotient * r old_s, s =\",\n \"not. ``sort=False`` always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0\",\n \"know we have a slice. \\\"\\\"\\\" res = self._range[slobj] return\",\n \"index start = rng.start if step is None and len(rng)\",\n \"raise ValueError(\\\"Step must not be zero\\\") rng = range(start, stop,\",\n \"< 0) is not (new_index.step < 0): new_index = new_index[::-1]\",\n \"a Float64Index if we have float-like descriptors if not all(is_integer(x)\",\n \": Any op : callable that accepts 2 params perform\",\n \"index as libindex from pandas._libs.lib import no_default from pandas._typing import\",\n \"new_index def _minmax(self, meth: str): no_steps = len(self) - 1\",\n \"loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take(\",\n \"ops.get_op_result_name(self, other) first = self._range[::-1] if self.step < 0 else\",\n \"!= self.step: # We reversed this range: transform to original\",\n \"def min(self, axis=None, skipna: bool = True, *args, **kwargs) ->\",\n \"axis=None, skipna: bool = True, *args, **kwargs) -> int: \\\"\\\"\\\"The\",\n \"new_index = type(self)._simple_new(new_rng, name=res_name) if first is not self._range: new_index\",\n \"== 0: if ( (start_s - start_o) % step_o ==\",\n \"step_s start_r = min(start_s, start_o) end_r = max(end_s, end_o) if\",\n \"= (step != rng.step and len(rng) > 1) or (\",\n \"def from_range( cls, data: range, name=None, dtype: Dtype | None\",\n \"array if deep=False See Also -------- numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes\",\n \"\\\"\\\"\\\" The value of the `stop` parameter. .. deprecated:: 0.25.0\",\n \": False or None, default None Whether to sort resulting\",\n \"b*y = gcd(x, y) Finds one particular solution for x,\",\n \"element greater than or equal to the limit\\\"\\\"\\\" no_steps =\",\n \"with numpy / Int64Index # even if we can represent\",\n \"* t return old_r, old_s, old_t def _union(self, other: Index,\",\n \"def __new__( cls, start=None, stop=None, step=None, dtype: Dtype | None\",\n \"= op(left.start, right) rstop = op(left.stop, right) result = type(self)(rstart,\",\n \"first.stop, first.step) elif overlap[-1] == first[-1]: # The difference is\",\n \"self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name)\",\n \"will be \\\" \\\"removed in a future version. Use RangeIndex.{}\",\n \"\\\"\\\"\\\" _typ = \\\"rangeindex\\\" _engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype,\",\n \"result_name: Hashable = None, sort=None): if not isinstance(other, RangeIndex) or\",\n \"step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings\",\n \"stop(self) -> int: \\\"\\\"\\\" The value of the `stop` parameter.\",\n \"index. Attributes ---------- start stop step Methods ------- from_range See\",\n \"other is a RangeIndex we may have more efficient options\",\n \"limit\\\"\\\"\\\" no_steps = -(-(lower_limit - self.start) // abs(self.step)) return self.start\",\n \"we may have more efficient options other = extract_array(other, extract_numpy=True,\",\n \"1 if step == 0: raise ValueError(\\\"Step must not be\",\n \"name=name) @classmethod def from_range( cls, data: range, name=None, dtype: Dtype\",\n \"type(self)(start_r, end_r + step_s / 2, step_s / 2) elif\",\n \"(timedelta, np.timedelta64)): # GH#19333 is_integer evaluated True on timedelta64, #\",\n \"RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index implementing a monotonic integer range. RangeIndex\",\n \"= self.difference(other) right = other.difference(self) result = left.union(right) if result_name\",\n \"(\\\"step\\\", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index,\",\n \"int) -> tuple[int, int, int]: \\\"\\\"\\\" Extended Euclidean algorithms to\",\n \"``Int64Index`` .. versionadded:: 0.25.0 Returns ------- union : Index \\\"\\\"\\\"\",\n \"for x in indexes): return super()._concat(indexes, name) elif len(indexes) ==\",\n \"next_ is None else next_ return RangeIndex(start, stop, step).rename(name) #\",\n \"= self.name if name is no_default else name if values.dtype.kind\",\n \"com.any_not_none(method, tolerance, limit): return super()._get_indexer( target, method=method, tolerance=tolerance, limit=limit )\",\n \"and (end_o - step_s <= end_s) ): return type(self)(start_r, end_r\",\n \"cast(List[RangeIndex], indexes) start = step = next_ = None #\",\n \"range object. Returns ------- RangeIndex \\\"\\\"\\\" if not isinstance(data, range):\",\n \"return result.rename(name) if step is not None: next_ = rng[-1]\",\n \"{} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) ->\",\n \"\\\"\\\"\\\" The value of the `start` parameter (``0`` if this\",\n \"Int64Index(values) return result.rename(name) step = rng.start - start non_consecutive =\",\n \"is None: new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit:\",\n \"import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index _empty_range =\",\n \"right = self, other try: # apply if we have\",\n \"if self.step < 0: start_s, step_s, end_s = end_s, -step_s,\",\n \"-> np.ndarray: \\\"\\\"\\\" An int array that for performance reasons\",\n \") def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self):\",\n \"len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start\",\n \"next_ is not None and rng.start != next_ ) if\",\n \"name=self._name) result._cache = self._cache return result @doc(Int64Index.copy) def copy( self,\",\n \"-> bool: return self._range.step > 0 or len(self) <= 1\",\n \"range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod def from_range( cls,\",\n \"return self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property\",\n \"for attr_name in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"] ) def memory_usage(self, deep:\",\n \"= t, old_t - quotient * t return old_r, old_s,\",\n \"(second.start - first.start) * first.step // gcd * s new_step\",\n \"com.all_none(start, stop, step): raise TypeError(\\\"RangeIndex(...) must be called with integers\\\")\",\n \"bool = True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\\\"Int64Index\\\",\",\n \"if ._range attr. are equal, shortcut is possible return super()._cmp_method(self,\",\n \"gcd new_range = range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) #\",\n \"# fall back to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex,\",\n \"self.step @cache_readonly def nbytes(self) -> int: \\\"\\\"\\\" Return the number\",\n \"( (start_o - start_s) % step_s == 0 and (start_o\",\n \": object, optional Name to be stored in the index.\",\n \"= obj._range if start is None: # This is set\",\n \"self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try: return self._range[new_key]\",\n \"+ step_s >= start_s) and (end_o - step_s <= end_s)\",\n \": Index or array-like sort : False or None, default\",\n \"if not len(self._range): return header first_val_str = str(self._range[0]) last_val_str =\",\n \"pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float,\",\n \"= values result._name = name result._cache = {} result._reset_identity() return\",\n \"self._range return [(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)] def __reduce__(self):\",\n \"# Constructors def __new__( cls, start=None, stop=None, step=None, dtype: Dtype\",\n \"False) -> int: \\\"\\\"\\\" Memory usage of my values Parameters\",\n \"Dtype | None = None ) -> RangeIndex: \\\"\\\"\\\" Create\",\n \"None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \\\"\\\"\\\" Return\",\n \"other._range # check whether intervals intersect # deals with in-\",\n \"computing speed. This is the default index type used by\",\n \"- 1) if self.step < 0: start_s, step_s, end_s =\",\n \"this range: transform to original locs locs[valid] = len(self) -\",\n \"bool: return self._range.step < 0 or len(self) <= 1 def\",\n \"sorts if possible Parameters ---------- other : Index or array-like\",\n \"versionadded:: 0.25.0 Returns ------- union : Index \\\"\\\"\\\" if isinstance(other,\",\n \"# so return a base index if not is_integer(rstep) or\",\n \"only one element if rng.start == start: values = np.concatenate([x._values\",\n \"- start_o) % step_o == 0 and (start_s + step_o\",\n \"import no_default from pandas._typing import Dtype from pandas.compat.numpy import function\",\n \"0 or len(self) <= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool:\",\n \"**kwargs) -> bool: return any(self._range) # -------------------------------------------------------------------- def _cmp_method(self, other,\",\n \"<= step_s / 2) and (abs(end_s - end_o) <= step_s\",\n \"True, *args, **kwargs) -> int: \\\"\\\"\\\"The minimum value of the\",\n \"reversed this range: transform to original locs locs[valid] = len(self)\",\n \"= True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__):\",\n \"= op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs) #\",\n \"RangeIndex if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3,\",\n \"in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]:\",\n \"(ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation return op(self._int64index,\",\n \"is not None and rng.start != next_ ) if non_consecutive:\",\n \"no_steps def _extended_gcd(self, a: int, b: int) -> tuple[int, int,\",\n \"self.nbytes @property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def\",\n \"slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key\",\n \"user. Parameters ---------- start : int (default: 0), range, or\",\n \"RangeIndex, so fall back return super()._difference(other, sort=sort) if overlap.step !=\",\n \"len(other): return self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0\",\n \"start=None, stop=None, step=None, dtype: Dtype | None = None, copy:\",\n \"super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is not\",\n \"the underlying data. \\\"\\\"\\\" rng = self._range return getsizeof(rng) +\",\n \"-> type[Int64Index]: \\\"\\\"\\\" return the class to use for construction\",\n \"None: next_ = rng[-1] + step if non_empty_indexes: # Get\",\n \"quotient = old_r // r old_r, r = r, old_r\",\n \"name matches self.name res = self._cached_int64index res._name = self._name return\",\n \") -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp) uniques =\",\n \"elements. \\\"\\\"\\\" if isinstance(other, RangeIndex): return self._range == other._range return\",\n \"than or equal to the limit\\\"\\\"\\\" no_steps = -(-(lower_limit -\",\n \"axis 0 with size {len(self)}\\\" ) from err elif is_scalar(key):\",\n \"other) if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv,\",\n \"& (locs >= 0) & (target_array < stop) locs[~valid] =\",\n \"if step is not None else 1 if step ==\",\n \"_constructor(self) -> type[Int64Index]: \\\"\\\"\\\" return the class to use for\",\n \"| None = None if op in [operator.mul, ops.rmul, operator.truediv,\",\n \"from pandas.core import ops import pandas.core.common as com from pandas.core.construction\",\n \"None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we\",\n \"stop is None: start, stop = 0, start else: stop\",\n \"_get_indexer( self, target: Index, method: str | None = None,\",\n \"@classmethod def from_range( cls, data: range, name=None, dtype: Dtype |\",\n \"value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\") def\",\n \"if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)]\",\n \"_format_with_header(self, header: list[str], na_rep: str = \\\"NaN\\\") -> list[str]: if\",\n \"for the case of all RangeIndex instances. When all members\",\n \"np.arange(len(self) - 1, -1, -1, dtype=np.intp) if not ascending: result\",\n \"True on timedelta64, # so we need to catch these\",\n \"\\\"\\\"\\\" Create RangeIndex from a range object. Returns ------- RangeIndex\",\n \"next_ = None # Filter the empty indexes non_empty_indexes =\",\n \"memory_usage(self, deep: bool = False) -> int: \\\"\\\"\\\" Memory usage\",\n \"a list of tuples of start, stop, step \\\"\\\"\\\" rng\",\n \"for x, y: s, t Returns: gcd, s, t \\\"\\\"\\\"\",\n \"get a RangeIndex back, # but not worth the effort.\",\n \"non_empty_indexes[-1].stop if next_ is None else next_ return RangeIndex(start, stop,\",\n \"if other is a RangeIndex we may have more efficient\",\n \"libindex from pandas._libs.lib import no_default from pandas._typing import Dtype from\",\n \"we have float-like descriptors if not all(is_integer(x) for x in\",\n \"tolerance=tolerance) target_array = np.asarray(target) locs = target_array - start valid\",\n \"if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name =\",\n \"to be stored in the index. Attributes ---------- start stop\",\n \"== \\\"min\\\" and self.step > 0) or (meth == \\\"max\\\"\",\n \"won't end up with RangeIndex, so fall back return super()._difference(other,\",\n \"be RangeIndex if possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3),\",\n \"as err: raise IndexError( f\\\"index {key} is out of bounds\",\n \"= new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable =\",\n \"if len(self) == 1 and len(other) == 1: step_s =\",\n \"t, old_t = 1, 0 r, old_r = b, a\",\n \"arguments if com.all_none(start, stop, step): raise TypeError(\\\"RangeIndex(...) must be called\",\n \"def tolist(self) -> list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield\",\n \"_deprecation_message = ( \\\"RangeIndex.{} is deprecated and will be \\\"\",\n \"result[::-1] return result def factorize( self, sort: bool = False,\",\n \"Finds one particular solution for x, y: s, t Returns:\",\n \"Here all \\\"indexes\\\" had 0 length, i.e. were empty. #\",\n \"try: key = ensure_python_int(key) except TypeError: return False return key\",\n \"- start_o) <= step_s / 2) and (abs(end_s - end_o)\",\n \"(default: 1) dtype : np.int64 Unused, accepted for homogeneity with\",\n \"right) rstop = op(left.stop, right) result = type(self)(rstart, rstop, rstep,\",\n \"instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2,\",\n \"parameter. \\\"\\\"\\\" return self._range.stop @property def _stop(self) -> int: \\\"\\\"\\\"\",\n \"new_index[::-1] if sort is None: new_index = new_index.sort_values() return new_index\",\n \"if step is None and len(rng) > 1: step =\",\n \"not ascending: result = result[::-1] return result def factorize( self,\",\n \"datetime import timedelta import operator from sys import getsizeof from\",\n \"self._get_data_as_items() if self.name is not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs\",\n \"hint: linear Diophantine equation # solve intersection problem # performance\",\n \"stored in the index. Attributes ---------- start stop step Methods\",\n \"other: Index, sort): \\\"\\\"\\\" Form the union of two Index\",\n \"is not None: result = result.rename(result_name) return result # --------------------------------------------------------------------\",\n \"hint: for identical step sizes, could use # cheaper alternative\",\n \"int_low: return self._simple_new(_empty_range) # Method hint: linear Diophantine equation #\",\n \"self, name: Hashable = None, deep: bool = False, dtype:\",\n \"Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range,\",\n \"default None Whether to sort resulting index. ``sort=None`` returns a\",\n \"lower bounds tmp_start = first.start + (second.start - first.start) *\",\n \"\\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\", True) # EA compat nv.validate_argsort(args, kwargs)\",\n \"1) or ( next_ is not None and rng.start !=\",\n \"__floordiv__(self, other): if is_integer(other) and other != 0: if len(self)\",\n \"= Int64Index(values) return result.rename(name) step = rng.start - start non_consecutive\",\n \"None, default None Whether to sort resulting index. ``sort=None`` returns\",\n \"attributes return None def _format_with_header(self, header: list[str], na_rep: str =\",\n \"(meth == \\\"min\\\" and self.step > 0) or (meth ==\",\n \"__reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return ibase._new_Index, (type(self), d), None\",\n \"int, int]: \\\"\\\"\\\" Extended Euclidean algorithms to solve Bezout's identity:\",\n \"array-like sort : False or None, default None Whether to\",\n \"so if ._range attr. are equal, shortcut is possible return\",\n \"None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range\",\n \"or a sorted ``Int64Index`` if not. ``sort=False`` always returns an\",\n \"Memory usage does not include memory consumed by elements that\",\n \") -> RangeIndex: \\\"\\\"\\\" Create RangeIndex from a range object.\",\n \"cls._simple_new(rng, name=name) @classmethod def from_range( cls, data: range, name=None, dtype:\",\n \"------- bytes used Notes ----- Memory usage does not include\",\n \"= rng[-1] + step if non_empty_indexes: # Get the stop\",\n \"\\\"\\\"\\\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self,\",\n \"-> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index:\",\n \"key, method=None, tolerance=None): if method is None and tolerance is\",\n \"def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache\",\n \"1) start_o, step_o = other.start, other.step end_o = other.start +\",\n \"\\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return\",\n \"__getitem__(self, key): \\\"\\\"\\\" Conserve RangeIndex type for scalar and slice\",\n \".. deprecated:: 0.25.0 Use ``start`` instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"),\",\n \"t return old_r, old_s, old_t def _union(self, other: Index, sort):\",\n \"RangeIndex back, # but not worth the effort. return super()._difference(other,\",\n \"- self.start) // abs(self.step) return self.start + abs(self.step) * no_steps\",\n \"RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return result\",\n \"the case of all RangeIndex instances. When all members of\",\n \"= np.concatenate([x._values for x in rng_indexes]) result = Int64Index(values) return\",\n \"import index as libindex from pandas._libs.lib import no_default from pandas._typing\",\n \"when we know we have a slice. \\\"\\\"\\\" res =\",\n \"np.ndarray: \\\"\\\"\\\" An int array that for performance reasons is\",\n \"Use ``step`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"),\",\n \"first.step // gcd * s new_step = first.step * second.step\",\n \"Memory usage of my values Parameters ---------- deep : bool\",\n \"-> int: \\\"\\\"\\\" The value of the `stop` parameter. \\\"\\\"\\\"\",\n \"of tuples of the (attr, formatted_value) \\\"\\\"\\\" attrs = self._get_data_as_items()\",\n \"/ Int64Index # even if we can represent as a\",\n \"Form the union of two Index objects and sorts if\",\n \"stop : int (default: 0) step : int (default: 1)\",\n \"passed\\\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values:\",\n \"\\\"stop\\\" is not given, interpreted as \\\"stop\\\" instead. stop :\",\n \"improve computing speed. This is the default index type used\",\n \"= range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step <\",\n \"and len(rng) > 1: step = rng.step elif step is\",\n \"end_s, -step_s, start_s if other.step < 0: start_o, step_o, end_o\",\n \"0.25.0 Use ``start`` instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2,\",\n \"0: start_s, step_s, end_s = end_s, -step_s, start_s if other.step\",\n \"= np.arange(len(self), dtype=np.intp) uniques = self if sort and self.step\",\n \"@doc(Int64Index._shallow_copy) def _shallow_copy(self, values, name: Hashable = no_default): name =\",\n \"old_s, s = s, old_s - quotient * s old_t,\",\n \"rng.step and len(rng) > 1) or ( next_ is not\",\n \"no_steps def min(self, axis=None, skipna: bool = True, *args, **kwargs)\",\n \"== other._range: # Both are immutable so if ._range attr.\",\n \"d), None # -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \\\"\\\"\\\"\",\n \"size {len(self)}\\\" ) from err elif is_scalar(key): raise IndexError( \\\"only\",\n \"uniques[::-1] return codes, uniques def equals(self, other: object) -> bool:\",\n \"of tuples of start, stop, step \\\"\\\"\\\" rng = self._range\",\n \"# adjust index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range\",\n \"number of bytes in the underlying data. \\\"\\\"\\\" rng =\",\n \"an np.ndarray; GH#22390 return op(self._int64index, other) if op in [\",\n \"all(is_integer(x) for x in [rstart, rstop, rstep]): result = result.astype(\\\"float64\\\")\",\n \"first.start + (second.start - first.start) * first.step // gcd *\",\n \"import ( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from\",\n \"= None # Filter the empty indexes non_empty_indexes = [obj\",\n \"tolerance=None): if method is None and tolerance is None: if\",\n \"( \\\"RangeIndex.{} is deprecated and will be \\\" \\\"removed in\",\n \"def argsort(self, *args, **kwargs) -> np.ndarray: \\\"\\\"\\\" Returns the indices\",\n \"operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index,\",\n \"0): return self.start return self.start + self.step * no_steps def\",\n \"if isinstance(other, RangeIndex): return self._range == other._range return super().equals(other) #\",\n \"element if rng.start == start: values = np.concatenate([x._values for x\",\n \"Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex:\",\n \"int_high = min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range)\",\n \"step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other, sort=None): #\",\n \"( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype, is_timedelta64_dtype, ) from\",\n \"return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy) def\",\n \"identical step sizes, could use # cheaper alternative gcd, s,\",\n \"always returns an unsorted ``Int64Index`` .. versionadded:: 0.25.0 Returns -------\",\n \"\\\"version. Use the astype method instead.\\\", FutureWarning, stacklevel=2, ) new_index\",\n \"step_s) elif step_s % step_o == 0: if ( (start_s\",\n \"list[int]: return list(self._range) @doc(Int64Index.__iter__) def __iter__(self): yield from self._range @doc(Int64Index._shallow_copy)\",\n \"with integers\\\") start = ensure_python_int(start) if start is not None\",\n \"np.dtype: return np.dtype(np.int64) @property def is_unique(self) -> bool: \\\"\\\"\\\" return\",\n \"isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first\",\n \"called with object coercible to a \\\" f\\\"range, {repr(data)} was\",\n \"!= rng.step and len(rng) > 1) or ( next_ is\",\n \"if not ascending: result = result[::-1] return result def factorize(\",\n \"accepted for homogeneity with other index types. name : object,\",\n \"ops import pandas.core.common as com from pandas.core.construction import extract_array import\",\n \"t \\\"\\\"\\\" s, old_s = 0, 1 t, old_t =\",\n \"1: start = self.start // other new_range = range(start, start\",\n \"= -1 ) -> tuple[np.ndarray, RangeIndex]: codes = np.arange(len(self), dtype=np.intp)\",\n \"and (start_s + step_o >= start_o) and (end_s - step_o\",\n \"b, a while r: quotient = old_r // r old_r,\",\n \"-------- numpy.ndarray.argsort \\\"\\\"\\\" ascending = kwargs.pop(\\\"ascending\\\", True) # EA compat\",\n \"= self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name\",\n \"err elif is_scalar(key): raise IndexError( \\\"only integers, slices (`:`), \\\"\",\n \"implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer\",\n \".. deprecated:: 0.25.0 Use ``step`` instead. \\\"\\\"\\\" # GH 25710\",\n \"25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2, ) return self.step @cache_readonly\",\n \"return self.start + abs(self.step) * no_steps def _extended_gcd(self, a: int,\",\n \"and self.step % other == 0: start = self.start //\",\n \"return result # -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \\\"\\\"\\\"\",\n \"-> bool: hash(key) try: key = ensure_python_int(key) except TypeError: return\",\n \"pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import\",\n \"= False _range: range # -------------------------------------------------------------------- # Constructors def __new__(\",\n \"op(left.start, right) rstop = op(left.stop, right) result = type(self)(rstart, rstop,\",\n \"rstop = op(left.stop, right) result = type(self)(rstart, rstop, rstep, **attrs)\",\n \"instead.\\\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index def\",\n \"< 0: codes = codes[::-1] uniques = uniques[::-1] return codes,\",\n \"Returns ------- union : Index \\\"\\\"\\\" if isinstance(other, RangeIndex) and\",\n \"== first.start: # The difference is everything after the intersection\",\n \"must be called with object coercible to a \\\" f\\\"range,\",\n \"**kwargs) -> int: \\\"\\\"\\\"The minimum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis)\",\n \"return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def\",\n \"Must be an np.ndarray; GH#22390 return op(self._int64index, other) if op\",\n \"): return type(self)(start_r, end_r + step_s, step_s) elif step_s %\",\n \"for scalar and slice keys. \\\"\\\"\\\" if isinstance(key, slice): new_range\",\n \"gcd, s, _ = self._extended_gcd(first.step, second.step) # check whether element\",\n \"old_r // r old_r, r = r, old_r - quotient\",\n \"_intersection(self, other: Index, sort=False): if not isinstance(other, RangeIndex): # Int64Index\",\n \"is_integer(key): new_key = int(key) try: return self._range[new_key] except IndexError as\",\n \"elif len(indexes) == 1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes)\",\n \"super()._cmp_method(other, op) def _arith_method(self, other, op): \\\"\\\"\\\" Parameters ---------- other\",\n \"is not self._range: new_index = new_index[::-1] return new_index def symmetric_difference(self,\",\n \"return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1]) max_length =\",\n \"-> bool: return self._range.step < 0 or len(self) <= 1\",\n \"6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5])\",\n \"range): raise TypeError( f\\\"{cls.__name__}(...) must be called with object coercible\",\n \"int: \\\"\\\"\\\" The value of the `stop` parameter. .. deprecated::\",\n \"libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na = False _range:\",\n \"try: # apply if we have an override if step:\",\n \"- 1 - locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self,\",\n \"not rstep: raise ValueError else: rstep = left.step with np.errstate(all=\\\"ignore\\\"):\",\n \"a slice. \\\"\\\"\\\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\")\",\n \"formatted_value) \\\"\\\"\\\" attrs = self._get_data_as_items() if self.name is not None:\",\n \"\\\"\\\"\\\" if isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name)\",\n \"not isinstance(data, range): raise TypeError( f\\\"{cls.__name__}(...) must be called with\",\n \"= range(start, stop, step or 1) return self._simple_new(new_range, name=self.name) if\",\n \"int_high, new_step) new_index = self._simple_new(new_range) # adjust index to limiting\",\n \"@cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step < 0 or\",\n \"ensure_python_int(key) except TypeError: return False return key in self._range @property\",\n \"= None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step\",\n \"by the first non-empty index start = rng.start if step\",\n \"if two Index objects contain the same elements. \\\"\\\"\\\" if\",\n \"# so we need to catch these explicitly return op(self._int64index,\",\n \"attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None): # we are\",\n \"None ) -> RangeIndex: \\\"\\\"\\\" Create RangeIndex from a range\",\n \"def _arith_method(self, other, op): \\\"\\\"\\\" Parameters ---------- other : Any\",\n \"self._range @property def inferred_type(self) -> str: return \\\"integer\\\" # --------------------------------------------------------------------\",\n \"first.step: # In some cases we might be able to\",\n \"np from pandas._libs import index as libindex from pandas._libs.lib import\",\n \"-> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache = self._cache return\",\n \"result._cache = self._cache return result @doc(Int64Index.copy) def copy( self, name:\",\n \"sort=None): if not isinstance(other, RangeIndex) or sort is not None:\",\n \"other, sort=None): # optimized set operation if we have another\",\n \"contain the same elements. \\\"\\\"\\\" if isinstance(other, RangeIndex): return self._range\",\n \"__len__(self) -> int: \\\"\\\"\\\" return the length of the RangeIndex\",\n \"== other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations def\",\n \"self.step // other stop = start + len(self) * step\",\n \"sort: bool = False, na_sentinel: int | None = -1\",\n \"na_rep: str = \\\"NaN\\\") -> list[str]: if not len(self._range): return\",\n \"% gcd: return self._simple_new(_empty_range) # calculate parameters for the RangeIndex\",\n \"the indices that would sort the index and its underlying\",\n \"# even if we can represent as a RangeIndex, return\",\n \"The value of the `stop` parameter. .. deprecated:: 0.25.0 Use\",\n \"min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range) # Method\",\n \"RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_max(args, kwargs) return self._minmax(\\\"max\\\") def argsort(self, *args, **kwargs)\",\n \"ibase._new_Index, (type(self), d), None # -------------------------------------------------------------------- # Rendering Methods def\",\n \"largest element smaller than or equal to the limit\\\"\\\"\\\" no_steps\",\n \"= extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left, right =\",\n \"type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self,\",\n \"GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2, ) return self.stop\",\n \"we have a slice. \\\"\\\"\\\" res = self._range[slobj] return type(self)._simple_new(res,\",\n \"return Int64Index._simple_new(values, name=name) def _view(self: RangeIndex) -> RangeIndex: result =\",\n \"may have more efficient options other = extract_array(other, extract_numpy=True, extract_range=True)\",\n \"Int64Index : Index of int64 data. \\\"\\\"\\\" _typ = \\\"rangeindex\\\"\",\n \"supplied). \\\"\\\"\\\" # GH 25710 return self._range.step @property def _step(self)\",\n \"name=name) # validate the arguments if com.all_none(start, stop, step): raise\",\n \"may in some instances improve computing speed. This is the\",\n \"return cls._simple_new(start, name=name) # validate the arguments if com.all_none(start, stop,\",\n \"# The difference is everything after the intersection new_rng =\",\n \"implementation return op(self._int64index, other) # TODO: Do attrs get handled\",\n \"name=self.name) return self._int64index // other # -------------------------------------------------------------------- # Reductions def\",\n \"= self.start + self.step * (len(self) - 1) start_o, step_o\",\n \"self.start // other step = self.step // other stop =\",\n \"0, start else: stop = ensure_python_int(stop) step = ensure_python_int(step) if\",\n \"range(start, start + 1, 1) return self._simple_new(new_range, name=self.name) return self._int64index\",\n \"a range object. Returns ------- RangeIndex \\\"\\\"\\\" if not isinstance(data,\",\n \"= step_o = abs(self.start - other.start) elif len(self) == 1:\",\n \"worth the effort. return super()._difference(other, sort=sort) if overlap[0] == first.start:\",\n \"return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is\",\n \"after the intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step)\",\n \"== 1: start = self.start // other new_range = range(start,\",\n \"isinstance(other, RangeIndex) or sort is not None: return super().symmetric_difference(other, result_name,\",\n \"_engine_type = libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na =\",\n \"left, right = self, other try: # apply if we\",\n \"# This is set by the first non-empty index start\",\n \"``RangeIndex`` if possible or a sorted ``Int64Index`` if not. ``sort=False``\",\n \"if deep=False See Also -------- numpy.ndarray.nbytes \\\"\\\"\\\" return self.nbytes @property\",\n \"res def _get_data_as_items(self): \\\"\\\"\\\" return a list of tuples of\",\n \"is_timedelta64_dtype(other): # Must be an np.ndarray; GH#22390 return op(self._int64index, other)\",\n \"Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not all(isinstance(x, RangeIndex) for x in indexes):\",\n \"# -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats,\",\n \"argsort(self, *args, **kwargs) -> np.ndarray: \\\"\\\"\\\" Returns the indices that\",\n \"for x in rng_indexes])) return result.rename(name) if step is not\",\n \"have a slice. \\\"\\\"\\\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name)\",\n \"no_default else name if values.dtype.kind == \\\"f\\\": return Float64Index(values, name=name)\",\n \"gcd(x, y) Finds one particular solution for x, y: s,\",\n \"def _simple_new(cls, values: range, name: Hashable = None) -> RangeIndex:\",\n \"not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if\",\n \"the # intersection disregarding the lower bounds tmp_start = first.start\",\n \"= None) -> RangeIndex: result = object.__new__(cls) assert isinstance(values, range)\",\n \"\\\"\\\"\\\" Overriding parent method for the case of all RangeIndex\",\n \"return super()._cmp_method(other, op) def _arith_method(self, other, op): \\\"\\\"\\\" Parameters ----------\",\n \"`step` parameter (``1`` if this was not supplied). .. deprecated::\",\n \"allow_fill: bool = True, fill_value=None, **kwargs ) -> Int64Index: with\",\n \"@property def is_unique(self) -> bool: \\\"\\\"\\\" return if the index\",\n \"bounds tmp_start = first.start + (second.start - first.start) * first.step\",\n \"to the limit\\\"\\\"\\\" no_steps = (upper_limit - self.start) // abs(self.step)\",\n \"from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int, is_float, is_integer, is_scalar, is_signed_integer_dtype,\",\n \"int, b: int) -> tuple[int, int, int]: \\\"\\\"\\\" Extended Euclidean\",\n \"def step(self) -> int: \\\"\\\"\\\" The value of the `step`\",\n \"== 1 and len(other) == 1: step_s = step_o =\",\n \"len(self) == 1: step_s = step_o elif len(other) == 1:\",\n \"can be sure its name matches self.name res = self._cached_int64index\",\n \"np.dtype(np.int64) @property def is_unique(self) -> bool: \\\"\\\"\\\" return if the\",\n \"self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other): if is_integer(other)\",\n \"return len(self) def __getitem__(self, key): \\\"\\\"\\\" Conserve RangeIndex type for\",\n \"for simplicity reverse = self._range[::-1] start, stop, step = reverse.start,\",\n \"pandas.compat.numpy import function as nv from pandas.util._decorators import ( cache_readonly,\",\n \"slice. \\\"\\\"\\\" res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def\",\n \"``_cache``. \\\"\\\"\\\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self)\",\n \"_arith_method(self, other, op): \\\"\\\"\\\" Parameters ---------- other : Any op\",\n \"class to use for construction \\\"\\\"\\\" return Int64Index @cache_readonly def\",\n \"# -------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \\\"\\\"\\\" return the\",\n \"hash(key) try: key = ensure_python_int(key) except TypeError: return False return\",\n \"step is None and len(rng) > 1: step = rng.step\",\n \"not len(self._range): return header first_val_str = str(self._range[0]) last_val_str = str(self._range[-1])\",\n \"Index objects and sorts if possible Parameters ---------- other :\",\n \"if the index has unique values \\\"\\\"\\\" return True @cache_readonly\",\n \"__contains__(self, key: Any) -> bool: hash(key) try: key = ensure_python_int(key)\",\n \"supplied). .. deprecated:: 0.25.0 Use ``start`` instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\",\",\n \"intervals intersect # deals with in- and decreasing ranges int_low\",\n \"other.step < 0) is not (new_index.step < 0): new_index =\",\n \"Index implementing a monotonic integer range. RangeIndex is a memory-saving\",\n \"= self if sort and self.step < 0: codes =\",\n \"0 r, old_r = b, a while r: quotient =\",\n \"0: if len(self) == 0 or self.start % other ==\",\n \"= int(key) try: return self._range[new_key] except IndexError as err: raise\",\n \"start is not None else 0 if stop is None:\",\n \"Float64Index if we have float-like descriptors if not all(is_integer(x) for\",\n \"difference is everything before the intersection new_rng = range(first.start, overlap[0],\",\n \"- quotient * r old_s, s = s, old_s -\",\n \"sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name) if first is not self._range:\",\n \"1: return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step\",\n \"self.stop @property def step(self) -> int: \\\"\\\"\\\" The value of\",\n \"to Int64Index return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) ->\",\n \"but not worth the effort. return super()._difference(other, sort=sort) if overlap[0]\",\n \"method for the case of all RangeIndex instances. When all\",\n \"def __contains__(self, key: Any) -> bool: hash(key) try: key =\",\n \"list of tuples of the (attr, formatted_value) \\\"\\\"\\\" attrs =\",\n \"int | None = -1 ) -> tuple[np.ndarray, RangeIndex]: codes\",\n \"res._name = self._name return res def _get_data_as_items(self): \\\"\\\"\\\" return a\",\n \"return op(self._int64index, other) if op in [ operator.pow, ops.rpow, operator.mod,\",\n \"= range(tmp_start, int_high, new_step) new_index = self._simple_new(new_range) # adjust index\",\n \"-> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return\",\n \"TYPE_CHECKING, Any, Callable, Hashable, List, cast, ) import warnings import\",\n \"]: return op(self._int64index, other) step: Callable | None = None\",\n \"= old_r // r old_r, r = r, old_r -\",\n \"# intersection disregarding the lower bounds tmp_start = first.start +\",\n \"*args, **kwargs) -> bool: return 0 not in self._range def\",\n \"# Defer to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta,\",\n \"= None, ) -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start,\",\n \"\\\"\\\"\\\" Immutable Index implementing a monotonic integer range. RangeIndex is\",\n \"not supplied). .. deprecated:: 0.25.0 Use ``start`` instead. \\\"\\\"\\\" warnings.warn(\",\n \"else self._range second = other._range[::-1] if other.step < 0 else\",\n \"in some instances improve computing speed. This is the default\",\n \"@property def start(self) -> int: \\\"\\\"\\\" The value of the\",\n \"start, stop, step = reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target):\",\n \"def _difference(self, other, sort=None): # optimized set operation if we\",\n \"def any(self, *args, **kwargs) -> bool: return any(self._range) # --------------------------------------------------------------------\",\n \": int (default: 0), range, or other RangeIndex instance If\",\n \"------- RangeIndex \\\"\\\"\\\" if not isinstance(data, range): raise TypeError( f\\\"{cls.__name__}(...)\",\n \"from pandas._libs import index as libindex from pandas._libs.lib import no_default\",\n \"element smaller than or equal to the limit\\\"\\\"\\\" no_steps =\",\n \"def _constructor(self) -> type[Int64Index]: \\\"\\\"\\\" return the class to use\",\n \"-------------------------------------------------------------------- _deprecation_message = ( \\\"RangeIndex.{} is deprecated and will be\",\n \"and Series when no explicit index is provided by the\",\n \"int: \\\"\\\"\\\" return the length of the RangeIndex \\\"\\\"\\\" return\",\n \"-> bool: \\\"\\\"\\\" Determines if two Index objects contain the\",\n \"-> int: \\\"\\\"\\\" Memory usage of my values Parameters ----------\",\n \"* no_steps def min(self, axis=None, skipna: bool = True, *args,\",\n \"= step_o elif len(other) == 1: step_o = step_s start_r\",\n \"self._range[::-1] start, stop, step = reverse.start, reverse.stop, reverse.step if not\",\n \"union of two Index objects and sorts if possible Parameters\",\n \"step_s and (start_o - end_s) <= step_s ): return type(self)(start_r,\",\n \"self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2, ) return self.start @property def stop(self)\",\n \"TypeError: return False return key in self._range @property def inferred_type(self)\",\n \"if ( (start_o - start_s) % step_s == 0 and\",\n \"Int64Index: # type: ignore[override] return self._int64index.delete(loc) def take( self, indices,\",\n \"empty indexes non_empty_indexes = [obj for obj in rng_indexes if\",\n \"not worth the effort. return super()._difference(other, sort=sort) if overlap[0] ==\",\n \"import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex, )\",\n \"matches self.name res = self._cached_int64index res._name = self._name return res\",\n \"return None def _format_with_header(self, header: list[str], na_rep: str = \\\"NaN\\\")\",\n \"attr_name)) for attr_name in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"] ) def memory_usage(self,\",\n \"from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas import Index\",\n \"bool: \\\"\\\"\\\" return if the index has unique values \\\"\\\"\\\"\",\n \"def _concat(self, indexes: list[Index], name: Hashable) -> Index: \\\"\\\"\\\" Overriding\",\n \"Hashable) -> Index: \\\"\\\"\\\" Overriding parent method for the case\",\n \"we are formatting thru the attributes return None def _format_with_header(self,\",\n \"for __getitem__ when we know we have a slice. \\\"\\\"\\\"\",\n \"empty. # In this case return an empty range index.\",\n \"Returns ------- RangeIndex \\\"\\\"\\\" if not isinstance(data, range): raise TypeError(\",\n \"The value of the `step` parameter (``1`` if this was\",\n \"if isinstance(start, RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start,\",\n \"able to get a RangeIndex back, # but not worth\",\n \"@cache_readonly def _constructor(self) -> type[Int64Index]: \\\"\\\"\\\" return the class to\",\n \"in rng_indexes])) return result.rename(name) if step is not None: next_\",\n \"= False, dtype: Dtype | None = None, names=None, ):\",\n \"= self._range return [(\\\"start\\\", rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)] def\",\n \"# -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer( target,\",\n \"2, step_s / 2) elif step_o % step_s == 0:\",\n \"an empty range index. return RangeIndex(0, 0).rename(name) def __len__(self) ->\",\n \"pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import ( Float64Index, Int64Index, NumericIndex,\",\n \"else next_ return RangeIndex(start, stop, step).rename(name) # Here all \\\"indexes\\\"\",\n \"is everything after the intersection new_rng = range(overlap[-1] + first.step,\",\n \"def size(self) -> int: return len(self) def __getitem__(self, key): \\\"\\\"\\\"\",\n \"return super().__getitem__(key) def _getitem_slice(self: RangeIndex, slobj: slice) -> RangeIndex: \\\"\\\"\\\"\",\n \"include memory consumed by elements that are not components of\",\n \"(`None`) \\\" \\\"and integer or boolean \\\" \\\"arrays are valid\",\n \"# GH#19333 is_integer evaluated True on timedelta64, # so we\",\n \": Index of int64 data. \\\"\\\"\\\" _typ = \\\"rangeindex\\\" _engine_type\",\n \"List, cast, ) import warnings import numpy as np from\",\n \"the array if deep=False See Also -------- numpy.ndarray.nbytes \\\"\\\"\\\" return\",\n \"is_integer(other) and other != 0: if len(self) == 0 or\",\n \"raise TypeError( f\\\"{cls.__name__}(...) must be called with object coercible to\",\n \"start stop step Methods ------- from_range See Also -------- Index\",\n \"op # TODO: if other is a RangeIndex we may\",\n \"Unused, accepted for homogeneity with other index types. name :\",\n \"length of the RangeIndex \\\"\\\"\\\" return len(self._range) @property def size(self)\",\n \"# we don't have a representable op # so return\",\n \"override if step: with np.errstate(all=\\\"ignore\\\"): rstep = step(left.step, right) #\",\n \"Int64Index return super()._intersection(other, sort=sort) if not len(self) or not len(other):\",\n \"# check whether element sets intersect if (first.start - second.start)\",\n \"== first[-1]: # The difference is everything before the intersection\",\n \"= range(start, start + 1, 1) return self._simple_new(new_range, name=self.name) return\",\n \"step = rng.start - start non_consecutive = (step != rng.step\",\n \"\\\"signed integer\\\") _can_hold_na = False _range: range # -------------------------------------------------------------------- #\",\n \"err: raise KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method,\",\n \"objects contain the same elements. \\\"\\\"\\\" if isinstance(other, RangeIndex): return\",\n \"= max(end_s, end_o) if step_o == step_s: if ( (start_s\",\n \"[\\\"start\\\", \\\"stop\\\", \\\"step\\\"] ) def memory_usage(self, deep: bool = False)\",\n \"no_default): name = self.name if name is no_default else name\",\n \"catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must\",\n \"return RangeIndex(start, stop, step).rename(name) # Here all \\\"indexes\\\" had 0\",\n \"range): return cls._simple_new(start, name=name) # validate the arguments if com.all_none(start,\",\n \"- locs[valid] return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None)\",\n \"return new_index def _min_fitting_element(self, lower_limit: int) -> int: \\\"\\\"\\\"Returns the\",\n \"self.step % other == 0: start = self.start // other\",\n \"return super()._cmp_method(self, op) return super()._cmp_method(other, op) def _arith_method(self, other, op):\",\n \"= -(-(lower_limit - self.start) // abs(self.step)) return self.start + abs(self.step)\",\n \"other RangeIndex instance If int and \\\"stop\\\" is not given,\",\n \"return self._range.step @property def _step(self) -> int: \\\"\\\"\\\" The value\",\n \"getsizeof(getattr(rng, attr_name)) for attr_name in [\\\"start\\\", \\\"stop\\\", \\\"step\\\"] ) def\",\n \"step_s ): return type(self)(start_r, end_r + step_s, step_s) if (\",\n \"other, op): \\\"\\\"\\\" Parameters ---------- other : Any op :\",\n \"we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other)\",\n \"rstop, rstep, **attrs) # for compat with numpy / Int64Index\",\n \"the limit\\\"\\\"\\\" no_steps = -(-(lower_limit - self.start) // abs(self.step)) return\",\n \") cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range,\",\n \"== 1: step_s = step_o elif len(other) == 1: step_o\",\n \"start_o, step_o = other.start, other.step end_o = other.start + other.step\",\n \"== 0 or self.start % other == 0 and self.step\",\n \"This is set by the first non-empty index start =\",\n \"\\\"\\\"\\\" Return the number of bytes in the underlying data.\",\n \"- 1) start_o, step_o = other.start, other.step end_o = other.start\",\n \"-> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex\",\n \"Use RangeIndex.{} \\\" \\\"instead\\\" ) @property def start(self) -> int:\",\n \"self._range def any(self, *args, **kwargs) -> bool: return any(self._range) #\",\n \"> 0) or (meth == \\\"max\\\" and self.step < 0):\",\n \"= self.start, self.stop, self.step else: # GH 28678: work on\",\n \"next_ ) if non_consecutive: result = Int64Index(np.concatenate([x._values for x in\",\n \"return the class to use for construction \\\"\\\"\\\" return Int64Index\",\n \"with in- and decreasing ranges int_low = max(first.start, second.start) int_high\",\n \"return self._int64index.delete(loc) def take( self, indices, axis: int = 0,\",\n \"# -------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None, step=None,\",\n \"indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not\",\n \"cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls, values: range, name:\",\n \"# Get the stop value from \\\"next\\\" or alternatively #\",\n \"is no_default else name if values.dtype.kind == \\\"f\\\": return Float64Index(values,\",\n \"fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take(\",\n \"not all(is_integer(x) for x in [rstart, rstop, rstep]): result =\",\n \"bytes used Notes ----- Memory usage does not include memory\",\n \"= min(first.stop, second.stop) if int_high <= int_low: return self._simple_new(_empty_range) #\",\n \"def _get_data_as_items(self): \\\"\\\"\\\" return a list of tuples of start,\",\n \"if not isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if\",\n \"is set by the first non-empty index start = rng.start\",\n \"# performance hint: for identical step sizes, could use #\",\n \"key = ensure_python_int(key) except TypeError: return False return key in\",\n \"step is not None else 1 if step == 0:\",\n \"< 0 or len(self) <= 1 def __contains__(self, key: Any)\",\n \"``step`` instead. \\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning,\",\n \"or equal to the limit\\\"\\\"\\\" no_steps = -(-(lower_limit - self.start)\",\n \"@cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step > 0 or\",\n \"start: values = np.concatenate([x._values for x in rng_indexes]) result =\",\n \"of the `step` parameter (``1`` if this was not supplied).\",\n \"supplied). .. deprecated:: 0.25.0 Use ``step`` instead. \\\"\\\"\\\" # GH\",\n \"int: \\\"\\\"\\\" Return the number of bytes in the underlying\",\n \"if op in [ operator.pow, ops.rpow, operator.mod, ops.rmod, ops.rfloordiv, divmod,\",\n \"``sort=None`` returns a monotonically increasing ``RangeIndex`` if possible or a\",\n \"* first.step // gcd * s new_step = first.step *\",\n \"import Index _empty_range = range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index\",\n \"if step != self.step: # We reversed this range: transform\",\n \"if self.step < 0 else self._range second = other._range[::-1] if\",\n \"start_o) % step_o == 0 and (start_s + step_o >=\",\n \"stop) locs[~valid] = -1 locs[valid] = locs[valid] / step if\",\n \"-> int: \\\"\\\"\\\"Returns the largest element smaller than or equal\",\n \"0) & (target_array < stop) locs[~valid] = -1 locs[valid] =\",\n \"# check whether intervals intersect # deals with in- and\",\n \">= start_o) and (end_s - step_o <= end_o) ): return\",\n \"import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name\",\n \"another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not\",\n \"is None else next_ return RangeIndex(start, stop, step).rename(name) # Here\",\n \"None: # First non-empty index had only one element if\",\n \"new_index = self._simple_new(new_range) # adjust index to limiting interval new_start\",\n \"Callable, Hashable, List, cast, ) import warnings import numpy as\",\n \"of Int64Index limited to representing monotonic ranges. Using RangeIndex may\",\n \"len(self._range) @property def size(self) -> int: return len(self) def __getitem__(self,\",\n \"if len(self) == 0 or self.start % other == 0\",\n \"rstep]): result = result.astype(\\\"float64\\\") return result except (ValueError, TypeError, ZeroDivisionError):\",\n \"tuples of the (attr, formatted_value) \\\"\\\"\\\" attrs = self._get_data_as_items() if\",\n \"__new__( cls, start=None, stop=None, step=None, dtype: Dtype | None =\",\n \"new_index = self._rename(name=name) if dtype: warnings.warn( \\\"parameter dtype is deprecated\",\n \"slobj: slice) -> RangeIndex: \\\"\\\"\\\" Fastpath for __getitem__ when we\",\n \"ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO: if other\",\n \"== 0) & (locs >= 0) & (target_array < stop)\",\n \"dtypes for system-level memory consumption Returns ------- bytes used Notes\",\n \"not isinstance(other, RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other)\",\n \"< 0 else other._range # check whether intervals intersect #\",\n \"self._simple_new(new_range, name=self.name) if len(self) == 1: start = self.start //\",\n \"cases we might be able to get a RangeIndex back,\",\n \"new_range = range(start, stop, step or 1) return self._simple_new(new_range, name=self.name)\",\n \"raise KeyError(key) from err raise KeyError(key) return super().get_loc(key, method=method, tolerance=tolerance)\",\n \"- other.start) elif len(self) == 1: step_s = step_o elif\",\n \"new_index.astype(dtype) return new_index def _minmax(self, meth: str): no_steps = len(self)\",\n \"len(self) == 1: start = self.start // other new_range =\",\n \"else self._range overlap = self.intersection(other) if overlap.step < 0: overlap\",\n \"general method return super()._get_indexer(target, method=method, tolerance=tolerance) target_array = np.asarray(target) locs\",\n \"step_s / 2) and (abs(end_s - end_o) <= step_s /\",\n \"union : Index \\\"\\\"\\\" if isinstance(other, RangeIndex) and sort is\",\n \"was not supplied). .. deprecated:: 0.25.0 Use ``start`` instead. \\\"\\\"\\\"\",\n \"is_monotonic_increasing(self) -> bool: return self._range.step > 0 or len(self) <=\",\n \"elif is_scalar(key): raise IndexError( \\\"only integers, slices (`:`), \\\" \\\"ellipsis\",\n \"accepted for homogeneity with other index types. copy : bool,\",\n \"for construction \\\"\\\"\\\" return Int64Index @cache_readonly def _data(self) -> np.ndarray:\",\n \"as libindex from pandas._libs.lib import no_default from pandas._typing import Dtype\",\n \"need to catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other):\",\n \"Series when no explicit index is provided by the user.\",\n \"(start_o - start_s) % step_s == 0 and (start_o +\",\n \"-> Index: \\\"\\\"\\\" Overriding parent method for the case of\",\n \"% step_o == 0: if ( (start_s - start_o) %\",\n \"and len(rng) > 1) or ( next_ is not None\",\n \"-> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index:\",\n \"def inferred_type(self) -> str: return \\\"integer\\\" # -------------------------------------------------------------------- # Indexing\",\n \"int (default: 0), range, or other RangeIndex instance If int\",\n \"Dtype | None = None, copy: bool = False, name:\",\n \"RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] ->\",\n \"if method is None and tolerance is None: if is_integer(key)\",\n \"in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op # TODO:\",\n \"deeply, interrogate `object` dtypes for system-level memory consumption Returns -------\",\n \"-> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not all(isinstance(x, RangeIndex) for x in\",\n \"overlap.step != first.step: # In some cases we might be\",\n \"new_range = range(new_start, new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step\",\n \"as nv from pandas.util._decorators import ( cache_readonly, doc, ) from\",\n \"return np.nan elif (meth == \\\"min\\\" and self.step > 0)\",\n \"if rng.start == start: values = np.concatenate([x._values for x in\",\n \"Any op : callable that accepts 2 params perform the\",\n \"pandas.core.common as com from pandas.core.construction import extract_array import pandas.core.indexes.base as\",\n \"(is_float(key) and key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except\",\n \"\\\" \\\"and integer or boolean \\\" \\\"arrays are valid indices\\\"\",\n \"possible, Int64Index otherwise. E.g.: indexes = [RangeIndex(3), RangeIndex(3, 6)] ->\",\n \"underlying data. \\\"\\\"\\\" rng = self._range return getsizeof(rng) + sum(\",\n \"target_array = np.asarray(target) locs = target_array - start valid =\",\n \"return True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step >\",\n \"step_s == 0: if ( (start_o - start_s) % step_s\",\n \"self.step > 0) or (meth == \\\"max\\\" and self.step <\",\n \"-------------------------------------------------------------------- # Indexing Methods @doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None):\",\n \"intersection new_rng = range(first.start, overlap[0], first.step) else: # The difference\",\n \"def _cmp_method(self, other, op): if isinstance(other, RangeIndex) and self._range ==\",\n \"_range: range # -------------------------------------------------------------------- # Constructors def __new__( cls, start=None,\",\n \"def __len__(self) -> int: \\\"\\\"\\\" return the length of the\",\n \"intersect # deals with in- and decreasing ranges int_low =\",\n \"return an empty range index. return RangeIndex(0, 0).rename(name) def __len__(self)\",\n \"_max_fitting_element(self, upper_limit: int) -> int: \\\"\\\"\\\"Returns the largest element smaller\",\n \"step_s, step_s) if ( (step_s % 2 == 0) and\",\n \"result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name) if\",\n \") -> RangeIndex: cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) #\",\n \"y: s, t Returns: gcd, s, t \\\"\\\"\\\" s, old_s\",\n \"op(self._int64index, other) step: Callable | None = None if op\",\n \"back return super()._difference(other, sort=sort) if overlap.step != first.step: # In\",\n \"0: codes = codes[::-1] uniques = uniques[::-1] return codes, uniques\",\n \"(step != rng.step and len(rng) > 1) or ( next_\",\n \"= len(self) - 1 if no_steps == -1: return np.nan\",\n \"0 and (start_s + step_o >= start_o) and (end_s -\",\n \"sort=sort) if not len(self) or not len(other): return self._simple_new(_empty_range) first\",\n \"True, fill_value=None, **kwargs ) -> Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return\",\n \"sizes, could use # cheaper alternative gcd, s, _ =\",\n \"Extended Euclidean algorithms to solve Bezout's identity: a*x + b*y\",\n \"1) return self._simple_new(new_range, name=self.name) if len(self) == 1: start =\",\n \"a memory-saving special case of Int64Index limited to representing monotonic\",\n \"tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance,\",\n \"import ABCTimedeltaIndex from pandas.core import ops import pandas.core.common as com\",\n \"not isinstance(other, RangeIndex) or sort is not None: return super().symmetric_difference(other,\",\n \"None = None ) -> RangeIndex: \\\"\\\"\\\" Create RangeIndex from\",\n \"2) and (abs(end_s - end_o) <= step_s / 2) ):\",\n \"to use for construction \\\"\\\"\\\" return Int64Index @cache_readonly def _data(self)\",\n \"homogeneity with other index types. name : object, optional Name\",\n \"Index objects contain the same elements. \\\"\\\"\\\" if isinstance(other, RangeIndex):\",\n \"RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if not all(isinstance(x, RangeIndex) for\",\n \"be sure its name matches self.name res = self._cached_int64index res._name\",\n \"be called with object coercible to a \\\" f\\\"range, {repr(data)}\",\n \"> 1: step = rng.step elif step is None: #\",\n \"None Whether to sort resulting index. ``sort=None`` returns a monotonically\",\n \"from err elif is_scalar(key): raise IndexError( \\\"only integers, slices (`:`),\",\n \"**kwargs) -> int: \\\"\\\"\\\"The maximum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis)\",\n \"1, 0 r, old_r = b, a while r: quotient\",\n \"divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable | None\",\n \"values result._name = name result._cache = {} result._reset_identity() return result\",\n \"\\\"\\\"\\\" rng = self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name))\",\n \"other.step * (len(other) - 1) if self.step < 0: start_s,\",\n \"sure its name matches self.name res = self._cached_int64index res._name =\",\n \"self.start) // abs(self.step)) return self.start + abs(self.step) * no_steps def\",\n \"Whether to sort resulting index. ``sort=None`` returns a monotonically increasing\",\n \"old_t def _union(self, other: Index, sort): \\\"\\\"\\\" Form the union\",\n \"if self.step < 0 else self._range overlap = self.intersection(other) if\",\n \"rng.start), (\\\"stop\\\", rng.stop), (\\\"step\\\", rng.step)] def __reduce__(self): d = self._get_attributes_dict()\",\n \"<= 1 @cache_readonly def is_monotonic_decreasing(self) -> bool: return self._range.step <\",\n \"sets intersect if (first.start - second.start) % gcd: return self._simple_new(_empty_range)\",\n \"is not None: return super().symmetric_difference(other, result_name, sort) left = self.difference(other)\",\n \"type RangeIndex: result will be RangeIndex if possible, Int64Index otherwise.\",\n \"one element if rng.start == start: values = np.concatenate([x._values for\",\n \"have more efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs\",\n \"= -1 locs[valid] = locs[valid] / step if step !=\",\n \"[obj for obj in rng_indexes if len(obj)] for obj in\",\n \"equal to the limit\\\"\\\"\\\" no_steps = (upper_limit - self.start) //\",\n \"= other._range[::-1] if other.step < 0 else other._range # check\",\n \"0 or self.start % other == 0 and self.step %\",\n \"+ abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) -> int:\",\n \"result @doc(Int64Index.copy) def copy( self, name: Hashable = None, deep:\",\n \"return if the index has unique values \\\"\\\"\\\" return True\",\n \"deep: bool = False) -> int: \\\"\\\"\\\" Memory usage of\",\n \"stop, step): raise TypeError(\\\"RangeIndex(...) must be called with integers\\\") start\",\n \"start_o) end_r = max(end_s, end_o) if step_o == step_s: if\",\n \"\\\"min\\\" and self.step > 0) or (meth == \\\"max\\\" and\",\n \"indexes) start = step = next_ = None # Filter\",\n \"delete(self, loc) -> Int64Index: # type: ignore[override] return self._int64index.delete(loc) def\",\n \"or 1) return self._simple_new(new_range, name=self.name) if len(self) == 1: start\",\n \"getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in [\\\"start\\\", \\\"stop\\\",\",\n \"NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer if TYPE_CHECKING: from pandas\",\n \"two Index objects contain the same elements. \\\"\\\"\\\" if isinstance(other,\",\n \"= self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name\",\n \"-------------------------------------------------------------------- # Constructors def __new__( cls, start=None, stop=None, step=None, dtype:\",\n \"or sort is not None: return super().symmetric_difference(other, result_name, sort) left\",\n \"RangeIndex type for scalar and slice keys. \\\"\\\"\\\" if isinstance(key,\",\n \") if self.step > 0: start, stop, step = self.start,\",\n \"result = result.rename(result_name) return result # -------------------------------------------------------------------- def _concat(self, indexes:\",\n \"< 0): return self.start return self.start + self.step * no_steps\",\n \"some cases we might be able to get a RangeIndex\",\n \"method=method, tolerance=tolerance) target_array = np.asarray(target) locs = target_array - start\",\n \"self.step: # We reversed this range: transform to original locs\",\n \"\\\"\\\"\\\" if isinstance(other, RangeIndex): return self._range == other._range return super().equals(other)\",\n \"= type(self)(rstart, rstop, rstep, **attrs) # for compat with numpy\",\n \"0: result = np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) -\",\n \"type(self)(start_r, end_r + step_s, step_s) elif step_s % step_o ==\",\n \"we have an override if step: with np.errstate(all=\\\"ignore\\\"): rstep =\",\n \"adjust index to limiting interval new_start = new_index._min_fitting_element(int_low) new_range =\",\n \"else name if values.dtype.kind == \\\"f\\\": return Float64Index(values, name=name) return\",\n \"step: with np.errstate(all=\\\"ignore\\\"): rstep = step(left.step, right) # we don't\",\n \"len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): #\",\n \"immutable so if ._range attr. are equal, shortcut is possible\",\n \"if first is not self._range: new_index = new_index[::-1] return new_index\",\n \"int: return len(self) def __getitem__(self, key): \\\"\\\"\\\" Conserve RangeIndex type\",\n \"len(self) <= 1 def __contains__(self, key: Any) -> bool: hash(key)\",\n \"s, t Returns: gcd, s, t \\\"\\\"\\\" s, old_s =\",\n \"start_o, step_o, end_o = end_o, -step_o, start_o if len(self) ==\",\n \"= None, sort=None): if not isinstance(other, RangeIndex) or sort is\",\n \"usage of my values Parameters ---------- deep : bool Introspect\",\n \"bool: \\\"\\\"\\\" Determines if two Index objects contain the same\",\n \"== 0: if ( (start_o - start_s) % step_s ==\",\n \"RangeIndex.{} \\\" \\\"instead\\\" ) @property def start(self) -> int: \\\"\\\"\\\"\",\n \"stacklevel=2, ) return self.start @property def stop(self) -> int: \\\"\\\"\\\"\",\n \"-> Int64Index: # wrap _cached_int64index so we can be sure\",\n \"in ``_cache``. \\\"\\\"\\\" return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def\",\n \"no_default from pandas._typing import Dtype from pandas.compat.numpy import function as\",\n \"interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop, new_index.step) new_index\",\n \"return self.start + self.step * no_steps def min(self, axis=None, skipna:\",\n \"copy( self, name: Hashable = None, deep: bool = False,\",\n \"the number of bytes in the underlying data. \\\"\\\"\\\" rng\",\n \"step_s == 0 and (start_s - end_o) <= step_s and\",\n \"return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) -> Int64Index: # wrap\",\n \"gcd, s, t \\\"\\\"\\\" s, old_s = 0, 1 t,\",\n \"sort): \\\"\\\"\\\" Form the union of two Index objects and\",\n \"cls._validate_dtype(dtype) name = maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start,\",\n \"self.step < 0 else self._range second = other._range[::-1] if other.step\",\n \"name = maybe_extract_name(name, start, cls) # RangeIndex if isinstance(start, RangeIndex):\",\n \"in self._range] # -------------------------------------------------------------------- _deprecation_message = ( \\\"RangeIndex.{} is deprecated\",\n \"had only one element if rng.start == start: values =\",\n \"effort. return super()._difference(other, sort=sort) if overlap[0] == first.start: # The\",\n \"of two Index objects and sorts if possible Parameters ----------\",\n \"step_o == 0 and (start_s + step_o >= start_o) and\",\n \"step if non_empty_indexes: # Get the stop value from \\\"next\\\"\",\n \"_view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name) result._cache =\",\n \"): return type(self)(start_r, end_r + step_o, step_o) return self._int64index._union(other, sort=sort)\",\n \"._range attr. are equal, shortcut is possible return super()._cmp_method(self, op)\",\n \"to representing monotonic ranges. Using RangeIndex may in some instances\",\n \"( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common\",\n \"RangeIndex is a memory-saving special case of Int64Index limited to\",\n \"Attributes ---------- start stop step Methods ------- from_range See Also\",\n \"rng_indexes if len(obj)] for obj in non_empty_indexes: rng = obj._range\",\n \"= next_ = None # Filter the empty indexes non_empty_indexes\",\n \") return self.step @cache_readonly def nbytes(self) -> int: \\\"\\\"\\\" Return\",\n \"sort resulting index. ``sort=None`` returns a monotonically increasing ``RangeIndex`` if\",\n \"0) & (locs >= 0) & (target_array < stop) locs[~valid]\",\n \"is None: # First non-empty index had only one element\",\n \"def _union(self, other: Index, sort): \\\"\\\"\\\" Form the union of\",\n \"greater than or equal to the limit\\\"\\\"\\\" no_steps = -(-(lower_limit\",\n \"def factorize( self, sort: bool = False, na_sentinel: int |\",\n \"a base index if not is_integer(rstep) or not rstep: raise\",\n \"1: step_s = step_o = abs(self.start - other.start) elif len(self)\",\n \"= self._get_attributes_dict() left, right = self, other try: # apply\",\n \"overlap = self.intersection(other) if overlap.step < 0: overlap = overlap[::-1]\",\n \"everything before the intersection new_rng = range(first.start, overlap[0], first.step) else:\",\n \"values.dtype.kind == \\\"f\\\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name) def\",\n \"old_s - quotient * s old_t, t = t, old_t\",\n \"other, op): if isinstance(other, RangeIndex) and self._range == other._range: #\",\n \"op) return super()._cmp_method(other, op) def _arith_method(self, other, op): \\\"\\\"\\\" Parameters\",\n \"an override if step: with np.errstate(all=\\\"ignore\\\"): rstep = step(left.step, right)\",\n \"range for simplicity reverse = self._range[::-1] start, stop, step =\",\n \"@doc(Int64Index.copy) def copy( self, name: Hashable = None, deep: bool\",\n \"): return type(self)(start_r, end_r + step_s, step_s) if ( (step_s\",\n \"integer\\\") _can_hold_na = False _range: range # -------------------------------------------------------------------- # Constructors\",\n \"method instead.\\\", FutureWarning, stacklevel=2, ) new_index = new_index.astype(dtype) return new_index\",\n \"was passed\\\" ) cls._validate_dtype(dtype) return cls._simple_new(data, name=name) @classmethod def _simple_new(cls,\",\n \"from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import ( ensure_platform_int, ensure_python_int,\",\n \"0 and self.step % other == 0: start = self.start\",\n \"a RangeIndex, return # as a Float64Index if we have\",\n \"tuples of start, stop, step \\\"\\\"\\\" rng = self._range return\",\n \"GH#22390 return op(self._int64index, other) if op in [ operator.pow, ops.rpow,\",\n \"28678: work on reversed range for simplicity reverse = self._range[::-1]\",\n \"| None = None ) -> RangeIndex: \\\"\\\"\\\" Create RangeIndex\",\n \"cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception from pandas.core.dtypes.common import\",\n \"rng.stop), (\\\"step\\\", rng.step)] def __reduce__(self): d = self._get_attributes_dict() d.update(dict(self._get_data_as_items())) return\",\n \"with other index types. name : object, optional Name to\",\n \"numpy.newaxis (`None`) \\\" \\\"and integer or boolean \\\" \\\"arrays are\",\n \"None and tolerance is None: if is_integer(key) or (is_float(key) and\",\n \"types. name : object, optional Name to be stored in\",\n \"Int64Index # even if we can represent as a RangeIndex,\",\n \"wrap _cached_int64index so we can be sure its name matches\",\n \"# -------------------------------------------------------------------- # Reductions def all(self, *args, **kwargs) -> bool:\",\n \"max_length = max(len(first_val_str), len(last_val_str)) return header + [f\\\"{x:<{max_length}}\\\" for x\",\n \"start_o) % step_s == 0 and (start_s - end_o) <=\",\n \"# GH 25710 return self._range.start @property def _start(self) -> int:\",\n \"step(self) -> int: \\\"\\\"\\\" The value of the `step` parameter\",\n \"self._int64index.delete(loc) def take( self, indices, axis: int = 0, allow_fill:\",\n \"= libindex.Int64Engine _dtype_validation_metadata = (is_signed_integer_dtype, \\\"signed integer\\\") _can_hold_na = False\",\n \"non_consecutive: result = Int64Index(np.concatenate([x._values for x in rng_indexes])) return result.rename(name)\",\n \"warnings.warn( \\\"parameter dtype is deprecated and will be removed in\",\n \"repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis) def delete(self, loc)\",\n \"int64 data. \\\"\\\"\\\" _typ = \\\"rangeindex\\\" _engine_type = libindex.Int64Engine _dtype_validation_metadata\",\n \"def _step(self) -> int: \\\"\\\"\\\" The value of the `step`\",\n \"a list of tuples of the (attr, formatted_value) \\\"\\\"\\\" attrs\",\n \"a while r: quotient = old_r // r old_r, r\",\n \"header + [f\\\"{x:<{max_length}}\\\" for x in self._range] # -------------------------------------------------------------------- _deprecation_message\",\n \"zero\\\") rng = range(start, stop, step) return cls._simple_new(rng, name=name) @classmethod\",\n \"(``0`` if this was not supplied). \\\"\\\"\\\" # GH 25710\",\n \"return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key = int(key) try: return\",\n \"particular solution for x, y: s, t Returns: gcd, s,\",\n \"key in self._range @property def inferred_type(self) -> str: return \\\"integer\\\"\",\n \"is provided by the user. Parameters ---------- start : int\",\n \"to TimedeltaIndex implementation return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): #\",\n \"**kwargs ) -> Int64Index: with rewrite_exception(\\\"Int64Index\\\", type(self).__name__): return self._int64index.take( indices,\",\n \"rstep: raise ValueError else: rstep = left.step with np.errstate(all=\\\"ignore\\\"): rstart\",\n \"except ValueError as err: raise KeyError(key) from err raise KeyError(key)\",\n \"old_s, old_t def _union(self, other: Index, sort): \\\"\\\"\\\" Form the\",\n \"(end_s - step_o <= end_o) ): return type(self)(start_r, end_r +\",\n \"super()._difference(other, sort=sort) if overlap[0] == first.start: # The difference is\",\n \"will be removed in a future \\\" \\\"version. Use the\",\n \"new_index[::-1] return new_index def symmetric_difference(self, other, result_name: Hashable = None,\",\n \"-> RangeIndex: result = object.__new__(cls) assert isinstance(values, range) result._range =\",\n \"interpreted as \\\"stop\\\" instead. stop : int (default: 0) step\",\n \"attrs = self._get_attributes_dict() left, right = self, other try: #\",\n \"timedelta64, # so we need to catch these explicitly return\",\n \"the smallest element greater than or equal to the limit\\\"\\\"\\\"\",\n \"False _range: range # -------------------------------------------------------------------- # Constructors def __new__( cls,\",\n \"# GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2, ) return\",\n \"\\\"\\\"\\\"The minimum value of the RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return\",\n \"to limiting interval new_start = new_index._min_fitting_element(int_low) new_range = range(new_start, new_index.stop,\",\n \"res = self._range[slobj] return type(self)._simple_new(res, name=self._name) @unpack_zerodim_and_defer(\\\"__floordiv__\\\") def __floordiv__(self, other):\",\n \"overlap[-1] == first[-1]: # The difference is everything before the\",\n \"start_o) and (end_s - step_o <= end_o) ): return type(self)(start_r,\",\n \"= object.__new__(cls) assert isinstance(values, range) result._range = values result._name =\",\n \"self._range return getsizeof(rng) + sum( getsizeof(getattr(rng, attr_name)) for attr_name in\",\n \"ranges. Using RangeIndex may in some instances improve computing speed.\",\n \"np.asarray(target) locs = target_array - start valid = (locs %\",\n \"Defer to Int64Index implementation return op(self._int64index, other) # TODO: Do\",\n \"is not None: attrs.append((\\\"name\\\", ibase.default_pprint(self.name))) return attrs def _format_data(self, name=None):\",\n \"no_steps = len(self) - 1 if no_steps == -1: return\",\n \"and (end_s - step_o <= end_o) ): return type(self)(start_r, end_r\",\n \"possible or a sorted ``Int64Index`` if not. ``sort=False`` always returns\",\n \"in rng_indexes if len(obj)] for obj in non_empty_indexes: rng =\",\n \"elif len(self) == 1: step_s = step_o elif len(other) ==\",\n \"% other == 0: start = self.start // other step\",\n \"The value of the `stop` parameter. \\\"\\\"\\\" return self._range.stop @property\",\n \"def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self)\",\n \"abs(self.start - other.start) elif len(self) == 1: step_s = step_o\",\n \"ValueError else: rstep = left.step with np.errstate(all=\\\"ignore\\\"): rstart = op(left.start,\",\n \": callable that accepts 2 params perform the binary op\",\n \"have a representable op # so return a base index\",\n \"needed. The constructed array is saved in ``_cache``. \\\"\\\"\\\" return\",\n \"= step_s start_r = min(start_s, start_o) end_r = max(end_s, end_o)\",\n \"-------------------------------------------------------------------- @cache_readonly def _constructor(self) -> type[Int64Index]: \\\"\\\"\\\" return the class\",\n \"int) -> int: \\\"\\\"\\\"Returns the smallest element greater than or\",\n \"x in [rstart, rstop, rstep]): result = result.astype(\\\"float64\\\") return result\",\n \"the length of the RangeIndex \\\"\\\"\\\" return len(self._range) @property def\",\n \"Return a list of tuples of the (attr, formatted_value) \\\"\\\"\\\"\",\n \"monotonic integer range. RangeIndex is a memory-saving special case of\",\n \"name = self.name if name is no_default else name if\",\n \"_step(self) -> int: \\\"\\\"\\\" The value of the `step` parameter\",\n \"the default index type used by DataFrame and Series when\",\n \"not supplied). \\\"\\\"\\\" # GH 25710 return self._range.start @property def\",\n \"return key in self._range @property def inferred_type(self) -> str: return\",\n \"in self._range def any(self, *args, **kwargs) -> bool: return any(self._range)\",\n \"(abs(start_s - start_o) <= step_s / 2) and (abs(end_s -\",\n \"if sort is None: new_index = new_index.sort_values() return new_index def\",\n \"self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return\",\n \"\\\"start\\\"), FutureWarning, stacklevel=2, ) return self.start @property def stop(self) ->\",\n \"instead. \\\"\\\"\\\" warnings.warn( self._deprecation_message.format(\\\"_start\\\", \\\"start\\\"), FutureWarning, stacklevel=2, ) return self.start\",\n \"self.step * no_steps def min(self, axis=None, skipna: bool = True,\",\n \"= np.asarray(target) locs = target_array - start valid = (locs\",\n \"False, name: Hashable = None, ) -> RangeIndex: cls._validate_dtype(dtype) name\",\n \"reversed range for simplicity reverse = self._range[::-1] start, stop, step\",\n \"// abs(self.step)) return self.start + abs(self.step) * no_steps def _max_fitting_element(self,\",\n \"quotient * s old_t, t = t, old_t - quotient\",\n \"gcd * s new_step = first.step * second.step // gcd\",\n \"super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first = self._range[::-1] if\",\n \"x in rng_indexes])) return result.rename(name) if step is not None:\",\n \"intersection new_rng = range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1]\",\n \"we can be sure its name matches self.name res =\",\n \"= None, deep: bool = False, dtype: Dtype | None\",\n \"np.errstate(all=\\\"ignore\\\"): rstep = step(left.step, right) # we don't have a\",\n \"* (len(self) - 1) start_o, step_o = other.start, other.step end_o\",\n \"these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): # Must be\",\n \"-------- Index : The base pandas Index type. Int64Index :\",\n \"0), range, or other RangeIndex instance If int and \\\"stop\\\"\",\n \"second.stop) if int_high <= int_low: return self._simple_new(_empty_range) # Method hint:\",\n \"RangeIndex): return start.copy(name=name) elif isinstance(start, range): return cls._simple_new(start, name=name) #\",\n \"if start is None: # This is set by the\",\n \"second = other._range[::-1] if other.step < 0 else other._range #\",\n \"def _shallow_copy(self, values, name: Hashable = no_default): name = self.name\",\n \"_int64index(self) -> Int64Index: # wrap _cached_int64index so we can be\",\n \"= ensure_python_int(step) if step is not None else 1 if\",\n \"more efficient options other = extract_array(other, extract_numpy=True, extract_range=True) attrs =\",\n \"return self._range.step < 0 or len(self) <= 1 def __contains__(self,\",\n \"@doc(Int64Index.get_loc) def get_loc(self, key, method=None, tolerance=None): if method is None\",\n \"Int64Index @cache_readonly def _data(self) -> np.ndarray: \\\"\\\"\\\" An int array\",\n \"scalar and slice keys. \\\"\\\"\\\" if isinstance(key, slice): new_range =\",\n \"lower_limit: int) -> int: \\\"\\\"\\\"Returns the smallest element greater than\",\n \"unique values \\\"\\\"\\\" return True @cache_readonly def is_monotonic_increasing(self) -> bool:\",\n \"limit\\\"\\\"\\\" no_steps = (upper_limit - self.start) // abs(self.step) return self.start\",\n \"is not (new_index.step < 0): new_index = new_index[::-1] if sort\",\n \"new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key): new_key =\",\n \"= end_s, -step_s, start_s if other.step < 0: start_o, step_o,\",\n \"return np.arange(self.start, self.stop, self.step, dtype=np.int64) @cache_readonly def _cached_int64index(self) -> Int64Index:\",\n \"Get the stop value from \\\"next\\\" or alternatively # from\",\n \"s, old_s = 0, 1 t, old_t = 1, 0\",\n \"out of bounds for axis 0 with size {len(self)}\\\" )\",\n \"identity: a*x + b*y = gcd(x, y) Finds one particular\",\n \"i.e. were empty. # In this case return an empty\",\n \"stacklevel=2, ) return self.stop @property def step(self) -> int: \\\"\\\"\\\"\",\n \"True) # EA compat nv.validate_argsort(args, kwargs) if self._range.step > 0:\",\n \"-> int: \\\"\\\"\\\" The value of the `step` parameter (``1``\",\n \"int | None = None, tolerance=None, ) -> np.ndarray: #\",\n \"len(self) - 1 if no_steps == -1: return np.nan elif\",\n \"kwargs) if self._range.step > 0: result = np.arange(len(self), dtype=np.intp) else:\",\n \"------- union : Index \\\"\\\"\\\" if isinstance(other, RangeIndex) and sort\",\n \"other) first = self._range[::-1] if self.step < 0 else self._range\",\n \"as \\\"stop\\\" instead. stop : int (default: 0) step :\",\n \"None = None, tolerance=None, ) -> np.ndarray: # -> np.ndarray[np.intp]\",\n \"the `start` parameter (``0`` if this was not supplied). \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2, )\",\n \"as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric import (\",\n \"from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase from pandas.core.indexes.base\",\n \"0 or len(self) <= 1 def __contains__(self, key: Any) ->\",\n \"----- Memory usage does not include memory consumed by elements\",\n \"else: result = np.arange(len(self) - 1, -1, -1, dtype=np.intp) if\",\n \"new_step) new_index = self._simple_new(new_range) # adjust index to limiting interval\",\n \"a monotonically increasing ``RangeIndex`` if possible or a sorted ``Int64Index``\",\n \"-------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index: return self._int64index.repeat(repeats, axis=axis)\",\n \"(locs % step == 0) & (locs >= 0) &\",\n \"(self.step < 0 and other.step < 0) is not (new_index.step\",\n \"\\\"\\\"\\\" # GH 25710 warnings.warn( self._deprecation_message.format(\\\"_step\\\", \\\"step\\\"), FutureWarning, stacklevel=2, )\",\n \"RangeIndex): return super()._difference(other, sort=sort) res_name = ops.get_op_result_name(self, other) first =\",\n \"pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions import rewrite_exception\",\n \"disregarding the lower bounds tmp_start = first.start + (second.start -\",\n \"RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)] -> Int64Index([0,1,2,4,5]) \\\"\\\"\\\" if\",\n \"return ensure_platform_int(locs) # -------------------------------------------------------------------- def repeat(self, repeats, axis=None) -> Int64Index:\",\n \"value of the `step` parameter (``1`` if this was not\",\n \"In this case return an empty range index. return RangeIndex(0,\",\n \"other index types. name : object, optional Name to be\",\n \"def max(self, axis=None, skipna: bool = True, *args, **kwargs) ->\",\n \"the lower bounds tmp_start = first.start + (second.start - first.start)\",\n \"# but not worth the effort. return super()._difference(other, sort=sort) if\",\n \"if ( (step_s % 2 == 0) and (abs(start_s -\",\n \"# type: ignore[override] return self._int64index.delete(loc) def take( self, indices, axis:\",\n \"elif len(other) == 1: step_o = step_s start_r = min(start_s,\",\n \"_cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def _int64index(self) ->\",\n \"if not all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes,\",\n \"/ 2) and (abs(end_s - end_o) <= step_s / 2)\",\n \"result def factorize( self, sort: bool = False, na_sentinel: int\",\n \"type used by DataFrame and Series when no explicit index\",\n \"== 0 and (start_o + step_s >= start_s) and (end_o\",\n \"RangeIndex\\\"\\\"\\\" nv.validate_minmax_axis(axis) nv.validate_min(args, kwargs) return self._minmax(\\\"min\\\") def max(self, axis=None, skipna:\",\n \"limited to representing monotonic ranges. Using RangeIndex may in some\",\n \"-------------------------------------------------------------------- # Set Operations def _intersection(self, other: Index, sort=False): if\",\n \"@cache_readonly def _cached_int64index(self) -> Int64Index: return Int64Index._simple_new(self._data, name=self.name) @property def\",\n \"self._range == other._range return super().equals(other) # -------------------------------------------------------------------- # Set Operations\",\n \"first = self._range[::-1] if self.step < 0 else self._range second\",\n \"end_r + step_s, step_s) elif step_s % step_o == 0:\",\n \"end_o) if step_o == step_s: if ( (start_s - start_o)\",\n \"set operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other,\",\n \"\\\"\\\"\\\" # GH 25710 return self._range.start @property def _start(self) ->\",\n \"right) result = type(self)(rstart, rstop, rstep, **attrs) # for compat\",\n \"0) or (meth == \\\"max\\\" and self.step < 0): return\",\n \"-> int: \\\"\\\"\\\"Returns the smallest element greater than or equal\",\n \"skipna: bool = True, *args, **kwargs) -> int: \\\"\\\"\\\"The minimum\",\n \"== start: values = np.concatenate([x._values for x in rng_indexes]) result\",\n \"name : object, optional Name to be stored in the\",\n \": bool Introspect the data deeply, interrogate `object` dtypes for\",\n \"import ops import pandas.core.common as com from pandas.core.construction import extract_array\",\n \"isinstance(other, RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not len(self)\",\n \"not None else 1 if step == 0: raise ValueError(\\\"Step\",\n \"interrogate `object` dtypes for system-level memory consumption Returns ------- bytes\",\n \"# The difference is everything before the intersection new_rng =\",\n \"\\\"step\\\"] ) def memory_usage(self, deep: bool = False) -> int:\",\n \"na_sentinel: int | None = -1 ) -> tuple[np.ndarray, RangeIndex]:\",\n \"the binary op \\\"\\\"\\\" if isinstance(other, ABCTimedeltaIndex): # Defer to\",\n \"ascending = kwargs.pop(\\\"ascending\\\", True) # EA compat nv.validate_argsort(args, kwargs) if\",\n \"== len(self): return self[:0].rename(res_name) if not isinstance(overlap, RangeIndex): # We\",\n \"self._int64index // other # -------------------------------------------------------------------- # Reductions def all(self, *args,\",\n \"> 1) or ( next_ is not None and rng.start\",\n \"operation if we have another RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name\",\n \"ops.rmod, ops.rfloordiv, divmod, ops.rdivmod, ]: return op(self._int64index, other) step: Callable\",\n \"0 with size {len(self)}\\\" ) from err elif is_scalar(key): raise\",\n \"if isinstance(other, ABCTimedeltaIndex): # Defer to TimedeltaIndex implementation return NotImplemented\",\n \"RangeIndex we may have more efficient options other = extract_array(other,\",\n \"except IndexError as err: raise IndexError( f\\\"index {key} is out\",\n \"new_index.stop, new_index.step) new_index = self._simple_new(new_range) if (self.step < 0 and\",\n \"if is_integer(key) or (is_float(key) and key.is_integer()): new_key = int(key) try:\",\n \"of the (attr, formatted_value) \\\"\\\"\\\" attrs = self._get_data_as_items() if self.name\",\n \"all(isinstance(x, RangeIndex) for x in indexes): return super()._concat(indexes, name) elif\",\n \"step = ensure_python_int(step) if step is not None else 1\",\n \"is not range-like return super()._difference(other, sort=sort) new_index = type(self)._simple_new(new_rng, name=res_name)\",\n \"for homogeneity with other index types. copy : bool, default\",\n \"str | None = None, limit: int | None =\",\n \"0).rename(name) def __len__(self) -> int: \\\"\\\"\\\" return the length of\",\n \"self._simple_new(_empty_range) # Method hint: linear Diophantine equation # solve intersection\",\n \"left = self.difference(other) right = other.difference(self) result = left.union(right) if\",\n \"options other = extract_array(other, extract_numpy=True, extract_range=True) attrs = self._get_attributes_dict() left,\",\n \"not is_integer(rstep) or not rstep: raise ValueError else: rstep =\",\n \"0 if stop is None: start, stop = 0, start\",\n \"<= end_s) ): return type(self)(start_r, end_r + step_s, step_s) elif\",\n \"so we can be sure its name matches self.name res\",\n \"<= end_o) ): return type(self)(start_r, end_r + step_o, step_o) return\",\n \"except (ValueError, TypeError, ZeroDivisionError): # Defer to Int64Index implementation return\",\n \"RangeIndex describing the # intersection disregarding the lower bounds tmp_start\",\n \"the attributes return None def _format_with_header(self, header: list[str], na_rep: str\",\n \"cheaper alternative gcd, s, _ = self._extended_gcd(first.step, second.step) # check\",\n \"and key.is_integer()): new_key = int(key) try: return self._range.index(new_key) except ValueError\",\n \"(target_array < stop) locs[~valid] = -1 locs[valid] = locs[valid] /\",\n \") def memory_usage(self, deep: bool = False) -> int: \\\"\\\"\\\"\",\n \"end_r + step_o, step_o) return self._int64index._union(other, sort=sort) def _difference(self, other,\",\n \"and self.step < 0: codes = codes[::-1] uniques = uniques[::-1]\",\n \"== 0: start = self.start // other step = self.step\",\n \"# deals with in- and decreasing ranges int_low = max(first.start,\",\n \"op) def _arith_method(self, other, op): \\\"\\\"\\\" Parameters ---------- other :\",\n \"@property def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self)\",\n \"\\\"removed in a future version. Use RangeIndex.{} \\\" \\\"instead\\\" )\",\n \"from pandas import Index _empty_range = range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\"\",\n \"1 def __contains__(self, key: Any) -> bool: hash(key) try: key\",\n \"import pandas.core.indexes.base as ibase from pandas.core.indexes.base import maybe_extract_name from pandas.core.indexes.numeric\",\n \"equals(self, other: object) -> bool: \\\"\\\"\\\" Determines if two Index\",\n \"last non-empty index stop = non_empty_indexes[-1].stop if next_ is None\",\n \"return type(self)(start_r, end_r + step_s / 2, step_s / 2)\",\n \"as com from pandas.core.construction import extract_array import pandas.core.indexes.base as ibase\",\n \"start else: stop = ensure_python_int(stop) step = ensure_python_int(step) if step\",\n \"= range(overlap[-1] + first.step, first.stop, first.step) elif overlap[-1] == first[-1]:\",\n \"return super()._intersection(other, sort=sort) if not len(self) or not len(other): return\",\n \"smallest element greater than or equal to the limit\\\"\\\"\\\" no_steps\",\n \"if not len(self) or not len(other): return self._simple_new(_empty_range) first =\",\n \"ascending: result = result[::-1] return result def factorize( self, sort:\",\n \"RangeIndex self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not isinstance(other,\",\n \"alternatively # from the last non-empty index stop = non_empty_indexes[-1].stop\",\n \"s = s, old_s - quotient * s old_t, t\",\n \"return NotImplemented elif isinstance(other, (timedelta, np.timedelta64)): # GH#19333 is_integer evaluated\",\n \"step_s = self.start, self.step end_s = self.start + self.step *\",\n \"other._range: # Both are immutable so if ._range attr. are\",\n \"def nbytes(self) -> int: \\\"\\\"\\\" Return the number of bytes\",\n \"[RangeIndex(3), RangeIndex(3, 6)] -> RangeIndex(6) indexes = [RangeIndex(3), RangeIndex(4, 6)]\",\n \"op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step = op #\",\n \"def stop(self) -> int: \\\"\\\"\\\" The value of the `stop`\",\n \"{key} is out of bounds for axis 0 with size\",\n \"RangeIndex): # Int64Index return super()._intersection(other, sort=sort) if not len(self) or\",\n \"new_index = new_index.sort_values() return new_index def _min_fitting_element(self, lower_limit: int) ->\",\n \"result._cache = {} result._reset_identity() return result # -------------------------------------------------------------------- @cache_readonly def\",\n \"codes[::-1] uniques = uniques[::-1] return codes, uniques def equals(self, other:\",\n \"np.ndarray: # -> np.ndarray[np.intp] if com.any_not_none(method, tolerance, limit): return super()._get_indexer(\",\n \"): name = self._validate_names(name=name, names=names, deep=deep)[0] new_index = self._rename(name=name) if\",\n \"and (abs(end_s - end_o) <= step_s / 2) ): return\",\n \"warnings.warn( self._deprecation_message.format(\\\"_stop\\\", \\\"stop\\\"), FutureWarning, stacklevel=2, ) return self.stop @property def\",\n \"Any, Callable, Hashable, List, cast, ) import warnings import numpy\",\n \"of the array if deep=False See Also -------- numpy.ndarray.nbytes \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" An int array that for performance reasons is created\",\n \"else: stop = ensure_python_int(stop) step = ensure_python_int(step) if step is\",\n \"= target_array - start valid = (locs % step ==\",\n \") @property def start(self) -> int: \\\"\\\"\\\" The value of\",\n \"self.intersection(other) if overlap.step < 0: overlap = overlap[::-1] if len(overlap)\",\n \"(``1`` if this was not supplied). .. deprecated:: 0.25.0 Use\",\n \"return indexes[0] rng_indexes = cast(List[RangeIndex], indexes) start = step =\",\n \"overlap.step < 0: overlap = overlap[::-1] if len(overlap) == 0:\",\n \"slices (`:`), \\\" \\\"ellipsis (`...`), numpy.newaxis (`None`) \\\" \\\"and integer\",\n \"+ self.step * no_steps def min(self, axis=None, skipna: bool =\",\n \"is saved in ``_cache``. \\\"\\\"\\\" return np.arange(self.start, self.stop, self.step, dtype=np.int64)\",\n \"= codes[::-1] uniques = uniques[::-1] return codes, uniques def equals(self,\",\n \"represent as a RangeIndex, return # as a Float64Index if\",\n \"if result_name is not None: result = result.rename(result_name) return result\",\n \"last_val_str = str(self._range[-1]) max_length = max(len(first_val_str), len(last_val_str)) return header +\",\n \"ValueError(\\\"Step must not be zero\\\") rng = range(start, stop, step)\",\n \"None = None, copy: bool = False, name: Hashable =\",\n \"from pandas._typing import Dtype from pandas.compat.numpy import function as nv\",\n \"x in rng_indexes]) result = Int64Index(values) return result.rename(name) step =\",\n \"def dtype(self) -> np.dtype: return np.dtype(np.int64) @property def is_unique(self) ->\",\n \"if values.dtype.kind == \\\"f\\\": return Float64Index(values, name=name) return Int64Index._simple_new(values, name=name)\",\n \"range(0) class RangeIndex(NumericIndex): \\\"\\\"\\\" Immutable Index implementing a monotonic integer\",\n \"Callable | None = None if op in [operator.mul, ops.rmul,\",\n \"from pandas.util._decorators import ( cache_readonly, doc, ) from pandas.util._exceptions import\",\n \"if step: with np.errstate(all=\\\"ignore\\\"): rstep = step(left.step, right) # we\",\n \"In some cases we might be able to get a\",\n \"np.ndarray; GH#22390 return op(self._int64index, other) if op in [ operator.pow,\",\n \"self.start + abs(self.step) * no_steps def _max_fitting_element(self, upper_limit: int) ->\",\n \"must not be zero\\\") rng = range(start, stop, step) return\",\n \"return self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0 else\",\n \"import ( Float64Index, Int64Index, NumericIndex, ) from pandas.core.ops.common import unpack_zerodim_and_defer\",\n \"is deprecated and will be \\\" \\\"removed in a future\",\n \"# We won't end up with RangeIndex, so fall back\",\n \"\\\"and integer or boolean \\\" \\\"arrays are valid indices\\\" )\",\n \"consumed by elements that are not components of the array\",\n \"isinstance(key, slice): new_range = self._range[key] return self._simple_new(new_range, name=self._name) elif is_integer(key):\",\n \"or None, default None Whether to sort resulting index. ``sort=None``\",\n \"= np.arange(len(self), dtype=np.intp) else: result = np.arange(len(self) - 1, -1,\",\n \"\\\"ellipsis (`...`), numpy.newaxis (`None`) \\\" \\\"and integer or boolean \\\"\",\n \"!= first.step: # In some cases we might be able\",\n \"describing the # intersection disregarding the lower bounds tmp_start =\",\n \"- quotient * t return old_r, old_s, old_t def _union(self,\",\n \"deprecated and will be \\\" \\\"removed in a future version.\",\n \"parameter (``1`` if this was not supplied). .. deprecated:: 0.25.0\",\n \"self._int64index.repeat(repeats, axis=axis) def delete(self, loc) -> Int64Index: # type: ignore[override]\",\n \"1) return self._simple_new(new_range, name=self.name) return self._int64index // other # --------------------------------------------------------------------\",\n \"self._range.start @property def _start(self) -> int: \\\"\\\"\\\" The value of\",\n \"is a memory-saving special case of Int64Index limited to representing\",\n \"None if op in [operator.mul, ops.rmul, operator.truediv, ops.rtruediv]: step =\",\n \"+ step_s, step_s) if ( (step_s % 2 == 0)\",\n \"self.rename(name=res_name) if len(overlap) == len(self): return self[:0].rename(res_name) if not isinstance(overlap,\",\n \"other, result_name = self._convert_can_do_setop(other) if not isinstance(other, RangeIndex): return super()._difference(other,\",\n \"_cached_int64index so we can be sure its name matches self.name\",\n \"= reverse.start, reverse.stop, reverse.step if not is_signed_integer_dtype(target): # checks/conversions/roundings are\",\n \"The difference is everything before the intersection new_rng = range(first.start,\",\n \"on reversed range for simplicity reverse = self._range[::-1] start, stop,\",\n \"return res def _get_data_as_items(self): \\\"\\\"\\\" return a list of tuples\",\n \"True @cache_readonly def is_monotonic_increasing(self) -> bool: return self._range.step > 0\",\n \"start = ensure_python_int(start) if start is not None else 0\",\n \"# -------------------------------------------------------------------- # Rendering Methods def _format_attrs(self): \\\"\\\"\\\" Return a\",\n \"`start` parameter (``0`` if this was not supplied). .. deprecated::\",\n \"name=name) def _view(self: RangeIndex) -> RangeIndex: result = type(self)._simple_new(self._range, name=self._name)\",\n \"to catch these explicitly return op(self._int64index, other) elif is_timedelta64_dtype(other): #\"\n]","isConversational":false}}},{"rowIdx":396,"cells":{"ngram":{"kind":"list like","value":["forward(self, x): out = self.l1(x) out = self.relu(out) out =","self.relu(out) out = self.l4(out) # no activation and no softmax","out = self.relu(out) out = self.l4(out) # no activation and","out = self.l2(out) out = self.relu(out) out = self.l3(out) out","nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes)","self.relu = nn.ReLU() def forward(self, x): out = self.l1(x) out","= self.relu(out) out = self.l2(out) out = self.relu(out) out =","as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet,","out = self.l1(x) out = self.relu(out) out = self.l2(out) out","self.l4(out) # no activation and no softmax at the end","no activation and no softmax at the end return out","NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 =","= self.relu(out) out = self.l3(out) out = self.relu(out) out =","self.l3(out) out = self.relu(out) out = self.l4(out) # no activation","= nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size,","self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x):","x): out = self.l1(x) out = self.relu(out) out = self.l2(out)","hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4","self.l1(x) out = self.relu(out) out = self.l2(out) out = self.relu(out)","out = self.relu(out) out = self.l2(out) out = self.relu(out) out","self.l2(out) out = self.relu(out) out = self.l3(out) out = self.relu(out)","nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def","out = self.relu(out) out = self.l3(out) out = self.relu(out) out","class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1","torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes):","def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size,","= self.relu(out) out = self.l4(out) # no activation and no","num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size,","__init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size)","= nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU()","self.relu(out) out = self.l2(out) out = self.relu(out) out = self.l3(out)","def forward(self, x): out = self.l1(x) out = self.relu(out) out","torch import torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size,","nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__()","super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size)","= nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x): out","import torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size,","num_classes) self.relu = nn.ReLU() def forward(self, x): out = self.l1(x)","= nn.ReLU() def forward(self, x): out = self.l1(x) out =","input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2","= self.l4(out) # no activation and no softmax at the","nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size)","out = self.l3(out) out = self.relu(out) out = self.l4(out) #","nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x): out =","import torch import torch.nn as nn class NeuralNet(nn.Module): def __init__(self,","self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3","= nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size,","out = self.l4(out) # no activation and no softmax at","# no activation and no softmax at the end return","= self.l3(out) out = self.relu(out) out = self.l4(out) # no","= self.l2(out) out = self.relu(out) out = self.l3(out) out =","hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu","hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self,","nn.ReLU() def forward(self, x): out = self.l1(x) out = self.relu(out)","self.relu(out) out = self.l3(out) out = self.relu(out) out = self.l4(out)","hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 =","self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 =","self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu =","= self.l1(x) out = self.relu(out) out = self.l2(out) out =","self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 ="],"string":"[\n \"forward(self, x): out = self.l1(x) out = self.relu(out) out =\",\n \"self.relu(out) out = self.l4(out) # no activation and no softmax\",\n \"out = self.relu(out) out = self.l4(out) # no activation and\",\n \"out = self.l2(out) out = self.relu(out) out = self.l3(out) out\",\n \"nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes)\",\n \"self.relu = nn.ReLU() def forward(self, x): out = self.l1(x) out\",\n \"= self.relu(out) out = self.l2(out) out = self.relu(out) out =\",\n \"as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet,\",\n \"out = self.l1(x) out = self.relu(out) out = self.l2(out) out\",\n \"self.l4(out) # no activation and no softmax at the end\",\n \"no activation and no softmax at the end return out\",\n \"NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 =\",\n \"= self.relu(out) out = self.l3(out) out = self.relu(out) out =\",\n \"self.l3(out) out = self.relu(out) out = self.l4(out) # no activation\",\n \"= nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size,\",\n \"self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x):\",\n \"x): out = self.l1(x) out = self.relu(out) out = self.l2(out)\",\n \"hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4\",\n \"self.l1(x) out = self.relu(out) out = self.l2(out) out = self.relu(out)\",\n \"out = self.relu(out) out = self.l2(out) out = self.relu(out) out\",\n \"self.l2(out) out = self.relu(out) out = self.l3(out) out = self.relu(out)\",\n \"nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def\",\n \"out = self.relu(out) out = self.l3(out) out = self.relu(out) out\",\n \"class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1\",\n \"torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes):\",\n \"def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size,\",\n \"= self.relu(out) out = self.l4(out) # no activation and no\",\n \"num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size,\",\n \"__init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size)\",\n \"= nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU()\",\n \"self.relu(out) out = self.l2(out) out = self.relu(out) out = self.l3(out)\",\n \"def forward(self, x): out = self.l1(x) out = self.relu(out) out\",\n \"torch import torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size,\",\n \"nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size, num_classes): super(NeuralNet, self).__init__()\",\n \"super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size)\",\n \"= nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x): out\",\n \"import torch.nn as nn class NeuralNet(nn.Module): def __init__(self, input_size, hidden_size,\",\n \"num_classes) self.relu = nn.ReLU() def forward(self, x): out = self.l1(x)\",\n \"= nn.ReLU() def forward(self, x): out = self.l1(x) out =\",\n \"input_size, hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2\",\n \"= self.l4(out) # no activation and no softmax at the\",\n \"nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size)\",\n \"out = self.l3(out) out = self.relu(out) out = self.l4(out) #\",\n \"nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self, x): out =\",\n \"import torch import torch.nn as nn class NeuralNet(nn.Module): def __init__(self,\",\n \"self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3\",\n \"= nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size,\",\n \"out = self.l4(out) # no activation and no softmax at\",\n \"# no activation and no softmax at the end return\",\n \"= self.l3(out) out = self.relu(out) out = self.l4(out) # no\",\n \"= self.l2(out) out = self.relu(out) out = self.l3(out) out =\",\n \"hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu\",\n \"hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu = nn.ReLU() def forward(self,\",\n \"nn.ReLU() def forward(self, x): out = self.l1(x) out = self.relu(out)\",\n \"self.relu(out) out = self.l3(out) out = self.relu(out) out = self.l4(out)\",\n \"hidden_size, num_classes): super(NeuralNet, self).__init__() self.l1 = nn.Linear(input_size, hidden_size) self.l2 =\",\n \"self.l1 = nn.Linear(input_size, hidden_size) self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 =\",\n \"self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 = nn.Linear(hidden_size, num_classes) self.relu =\",\n \"= self.l1(x) out = self.relu(out) out = self.l2(out) out =\",\n \"self.l2 = nn.Linear(hidden_size, hidden_size) self.l3 = nn.Linear(hidden_size, hidden_size) self.l4 =\"\n]","isConversational":false}}},{"rowIdx":397,"cells":{"ngram":{"kind":"list like","value":["file named ``config.json`` placed in the ``utils`` directory. References ----------","name. The name of the ``log_file`` is a combination of","os import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import","<NAME>, 2013 (WFC3 QL Version) Use --- To log the","Dependencies ------------ The user must have a configuration file named","The name of the module being logged. production_mode : bool","open(setup_file_name) as setup: for line in setup: if line[0:8] ==","if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function()","module in module_list] # Log common module version information for","to working dir. Returns ------- log_file : str The full","func(*a, **kw) t2_cpu = time.clock() t2_time = time.time() # Log","line[12:-2] module_list = module_required.split(',') # Clean up the module list","@log_fail def my_main_function(): pass if __name__ == '__main__': module =","to decorate. Returns ------- wrapped : func The wrapped function.","is a combination of the name of the module being","being logged and the current datetime. Parameters ---------- module :","output should be written to the production environment. path :","= [module.replace('\"', '').replace(\"'\", '').replace(' ', '') for module in module_list]","where the log file will be written to. \"\"\" timestamp","time.time() func(*a, **kw) t2_cpu = time.clock() t2_time = time.time() #","production_mode: log_file = os.path.join(log_path, module, filename) else: log_file = os.path.join(path,","@wraps(func) def wrapped(*a, **kw): # Log environment information logging.info('User: '","list of required modules settings = get_config() setup_file_name = settings['setup_file']","user must have a configuration file named ``config.json`` placed in","the output should be written to the production environment. path","References ---------- This code is adopted and updated from python","combination of the name of the module being logged and","the name of the module being logged and the current","= time.time() func(*a, **kw) t2_cpu = time.clock() t2_time = time.time()","- <NAME>, 2013 (WFC3 QL Version) Use --- To log","module in module_list: try: mod = importlib.import_module(module) logging.info(module + '","Log files are written to the ``logs/`` directory in the","be written to the production environement. path : str Where","list module_list = [module.replace('\"', '').replace(\"'\", '').replace(' ', '') for module","= [] if user != admin_account and module not in","time it t1_cpu = time.clock() t1_time = time.time() func(*a, **kw)","in the ``utils`` directory. References ---------- This code is adopted","---------- func : func The function to decorate. Returns -------","import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail",":: import os import logging from jwql.logging.logging_functions import configure_logging from","def wrapped(*a, **kw): # Log environment information logging.info('User: ' +","time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60)","**kw) t2_cpu = time.clock() t2_time = time.time() # Log execution","``utils`` directory. References ---------- This code is adopted and updated","logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def","'')) logging.info('Python Executable Path: ' + sys.executable) # Read in","'').replace(' ', '') for module in module_list] module_list = [module.split('=')[0]","build list of required modules settings = get_config() setup_file_name =","to where the log file will be written to. \"\"\"","if production_mode: log_file = os.path.join(log_path, module, filename) else: log_file =","t1_cpu = time.clock() t1_time = time.time() func(*a, **kw) t2_cpu =","as err: logging.warning(err) # Call the function and time it","pwd import socket import sys import time import traceback from","module name. The name of the ``log_file`` is a combination","a combination of the name of the module being logged","datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings =","to log the execution of modules. Log files are written","= time.time() # Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu","by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- -","# Determine log file location if production_mode: log_file = make_log_file(module)","name of the module being logged. production_mode : bool Whether","format. Parameters ---------- module : str The name of the","timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name","module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file","from functools import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils","and system information. Future packages we want to track can","# Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System: '","functions for the ``jwql`` automation platform. This module provides decorators","t2_cpu = time.clock() t2_time = time.time() # Log execution time","log if user-supplied path; default to working dir. \"\"\" #","= get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules =","module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user","hours_time, remainder_time = divmod(t2_time - t1_time, 60 * 60) minutes_time,","' Path: ' + mod.__path__[0]) except ImportError as err: logging.warning(err)","= time.clock() t1_time = time.time() func(*a, **kw) t2_cpu = time.clock()","logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu,","environement. path : str Where to write the log if","if user != admin_account and module not in exempt_modules and","'') configure_logging(module) my_main_function() Dependencies ------------ The user must have a","# Call the function and time it t1_cpu = time.clock()","admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if","2013 (WFC3 QL Version) Use --- To log the execution","``logging_functions.py`` written by Alex Viana, 2013 for the WFC3 Quicklook","import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = ''","the ``jwql`` automation platform. This module provides decorators to log","time.clock() t2_time = time.time() # Log execution time hours_cpu, remainder_cpu","global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode","want to track can be added or removed as necessary.","Executable Path: ' + sys.executable) # Read in setup.py file","name based on the module name. The name of the","= settings['setup_file'] with open(setup_file_name) as setup: for line in setup:","line[0:8] == \"REQUIRES\": module_required = line[12:-2] module_list = module_required.split(',') #","on the module name. The name of the ``log_file`` is","the function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED')","permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file)","current datetime. Parameters ---------- module : str The name of","wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists","of the module being logged. production_mode : bool Whether or","import os import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions","LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode #","exempt_modules and production_mode: module = os.path.join('dev', module) if production_mode: log_file","e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>, 2013","from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC","+ ' Version: ' + mod.__version__) logging.info(module + ' Path:","a configuration file named ``config.json`` placed in the ``utils`` directory.","provides decorators to log the execution of modules. Log files","function. \"\"\" @wraps(func) def wrapped(*a, **kw): # Log environment information","log_info(func): \"\"\"Decorator to log useful system information. This function can","log file location if production_mode: log_file = make_log_file(module) else: log_file","else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL","configure_logging(module) my_main_function() Dependencies ------------ The user must have a configuration","platform. \"\"\" import datetime import getpass import importlib import logging","%p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \"\"\"Create the log","working dir. \"\"\" # Determine log file location if production_mode:","Call the function and time it t1_cpu = time.clock() t1_time","logging.info(module + ' Path: ' + mod.__path__[0]) except ImportError as","datetime import getpass import importlib import logging import os import","decorators to log the execution of modules. Log files are","os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return","import log_fail @log_info @log_fail def my_main_function(): pass if __name__ ==","divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time,","importlib import logging import os import pwd import socket import","system information. This function can be used as a decorator","The wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw): # Log","settings['setup_file'] with open(setup_file_name) as setup: for line in setup: if","= divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time, 60","file with a standard logging format. Parameters ---------- module :","storage area, named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log``","if production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False,","the output should be written to the production environement. path","= make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC","logged. production_mode : bool Whether or not the output should","module provides decorators to log the execution of modules. Log","jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass if __name__","can be used as a decorator to log user environment","def log_info(func): \"\"\"Decorator to log useful system information. This function","production environment. path : str Where to write the log","Authors ------- - <NAME> 2018 - <NAME>, 2013 (WFC3 QL","2018 - <NAME>, 2013 (WFC3 QL Version) Use --- To","socket import sys import time import traceback from functools import","datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \"\"\"Create","func The wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw): try:","log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global","import socket import sys import time import traceback from functools","remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu","PRODUCTION_BOOL = production_mode # Create the log file and set","'{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account =","log file with a standard logging format. Parameters ---------- module","Read in setup.py file to build list of required modules","import datetime import getpass import importlib import logging import os","Log common module version information for module in module_list: try:","60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time:","module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME>","return wrapped def log_fail(func): \"\"\"Decorator to log crashes in the","modules settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as","in setup: if line[0:8] == \"REQUIRES\": module_required = line[12:-2] module_list","and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 -","= divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time =","# Create the log file and set the permissions logging.basicConfig(filename=log_file,","function. \"\"\" @wraps(func) def wrapped(*a, **kw): try: # Run the","# Log common module version information for module in module_list:","a standard logging format. Parameters ---------- module : str The","This function can be used as a decorator to log","my_main_function(): pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '')",": bool Whether or not the output should be written","if user-supplied path; default to working dir. Returns ------- log_file","files are written to the ``logs/`` directory in the ``jwql``","def configure_logging(module, production_mode=True, path='./'): \"\"\"Configure the log file with a","file location if production_mode: log_file = make_log_file(module) else: log_file =","import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def","must have a configuration file named ``config.json`` placed in the","and the current datetime. Parameters ---------- module : str The","the execution of a module, use: :: import os import","' + sys.executable) # Read in setup.py file to build","os import pwd import socket import sys import time import","to track can be added or removed as necessary. Parameters","in module_list] module_list = [module.split('=')[0] for module in module_list] #","func The wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw): #","try: mod = importlib.import_module(module) logging.info(module + ' Version: ' +","directory in the ``jwql`` central storage area, named by module","information. This function can be used as a decorator to","be written to the production environment. path : str Where","module : str The name of the module being logged.","production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path)","This code is adopted and updated from python routine ``logging_functions.py``","log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s',","= datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings","production_mode=True, path='./'): \"\"\"Create the log file name based on the","use: :: import os import logging from jwql.logging.logging_functions import configure_logging","user-supplied path; default to working dir. \"\"\" # Determine log","+ mod.__path__[0]) except ImportError as err: logging.warning(err) # Call the","module being logged. production_mode : bool Whether or not the","+ sys.version.replace('\\n', '')) logging.info('Python Executable Path: ' + sys.executable) #","the function and time it t1_cpu = time.clock() t1_time =","def make_log_file(module, production_mode=True, path='./'): \"\"\"Create the log file name based","setup: if line[0:8] == \"REQUIRES\": module_required = line[12:-2] module_list =","' + mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0])","ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \"\"\"Decorator to log useful system","from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass if","or removed as necessary. Parameters ---------- func : func The","function to decorate. Returns ------- wrapped : func The wrapped","import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info","%(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True,","line in setup: if line[0:8] == \"REQUIRES\": module_required = line[12:-2]","Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu))","def my_main_function(): pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py',","os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \"\"\"Decorator to log","setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for line in","+ sys.executable) # Read in setup.py file to build list","+ socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\n', '')) logging.info('Python Executable","area, named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors","divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu,","!= admin_account and module not in exempt_modules and production_mode: module","to the ``logs/`` directory in the ``jwql`` central storage area,","the execution of modules. Log files are written to the","and updated from python routine ``logging_functions.py`` written by Alex Viana,","in exempt_modules and production_mode: module = os.path.join('dev', module) if production_mode:",": func The wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw):","--- To log the execution of a module, use: ::","sys import time import traceback from functools import wraps from","information for module in module_list: try: mod = importlib.import_module(module) logging.info(module","dir. \"\"\" # Determine log file location if production_mode: log_file","module_list = module_required.split(',') # Clean up the module list module_list","logging.info(module + ' Version: ' + mod.__version__) logging.info(module + '","= '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): \"\"\"Configure","full path to where the log file will be written","and production_mode: module = os.path.join('dev', module) if production_mode: log_file =","QL Version) Use --- To log the execution of a","for the WFC3 Quicklook automation platform. \"\"\" import datetime import","output should be written to the production environement. path :","the log file with a standard logging format. Parameters ----------","or not the output should be written to the production","level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \"\"\"Create the log file","in setup.py file to build list of required modules settings","+ mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0]) except","60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real","of a module, use: :: import os import logging from","make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file","modules. Log files are written to the ``logs/`` directory in","``jwql`` central storage area, named by module name and timestamp,","the ``jwql`` central storage area, named by module name and","module_list: try: mod = importlib.import_module(module) logging.info(module + ' Version: '","**kw): # Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System:","str Where to write the log if user-supplied path; default","will be written to. \"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename =","module) if production_mode: log_file = os.path.join(log_path, module, filename) else: log_file","configure_logging(module, production_mode=True, path='./'): \"\"\"Configure the log file with a standard","{0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return","named ``config.json`` placed in the ``utils`` directory. References ---------- This","= importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__) logging.info(module","the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO)","Use --- To log the execution of a module, use:","' Version: ' + mod.__version__) logging.info(module + ' Path: '","for the ``jwql`` automation platform. This module provides decorators to","Alex Viana, 2013 for the WFC3 Quicklook automation platform. \"\"\"","Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System: ' +","have a configuration file named ``config.json`` placed in the ``utils``","should be written to the production environement. path : str",": str Where to write the log if user-supplied path;","pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path = settings['log_dir']","<NAME> 2018 - <NAME>, 2013 (WFC3 QL Version) Use ---","the log if user-supplied path; default to working dir. \"\"\"","log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC","path; default to working dir. Returns ------- log_file : str","Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \"\"\"Decorator to","file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y","the module being logged and the current datetime. Parameters ----------","The name of the ``log_file`` is a combination of the","version information for module in module_list: try: mod = importlib.import_module(module)","decorated code. Parameters ---------- func : func The function to","logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\n', ''))","\"\"\"Create the log file name based on the module name.","written to. \"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp)","= get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for","= [module.split('=')[0] for module in module_list] # Log common module","__name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies","' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\n', '')) logging.info('Python","= os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \"\"\"Decorator to","This module provides decorators to log the execution of modules.","module version information for module in module_list: try: mod =","set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p',","\"\"\"Decorator to log useful system information. This function can be","for module in module_list: try: mod = importlib.import_module(module) logging.info(module +","filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def","not the output should be written to the production environment.","\"\"\" Logging functions for the ``jwql`` automation platform. This module","time.time() # Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu -","(WFC3 QL Version) Use --- To log the execution of","and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S","logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version:","in the decorated code. Parameters ---------- func : func The","' + mod.__path__[0]) except ImportError as err: logging.warning(err) # Call","return log_file def log_info(func): \"\"\"Decorator to log useful system information.","as setup: for line in setup: if line[0:8] == \"REQUIRES\":","execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 *","{0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \"\"\"Decorator to log","def log_fail(func): \"\"\"Decorator to log crashes in the decorated code.","automation platform. \"\"\" import datetime import getpass import importlib import","central storage area, named by module name and timestamp, e.g.","* 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time:","configuration file named ``config.json`` placed in the ``utils`` directory. References","'__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The","log file will be written to. \"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M')","make_log_file(module, production_mode=True, path='./'): \"\"\"Create the log file name based on","------- log_file : str The full path to where the","path; default to working dir. \"\"\" # Determine log file","\"\"\"Configure the log file with a standard logging format. Parameters","time import traceback from functools import wraps from jwql.utils.permissions import","Create the log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s","log useful system information. This function can be used as","are written to the ``logs/`` directory in the ``jwql`` central","importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__) logging.info(module +","directory. References ---------- This code is adopted and updated from","wrapped(*a, **kw): # Log environment information logging.info('User: ' + getpass.getuser())","The user must have a configuration file named ``config.json`` placed","in module_list: try: mod = importlib.import_module(module) logging.info(module + ' Version:","my_main_function() Dependencies ------------ The user must have a configuration file","\"\"\"Decorator to log crashes in the decorated code. Parameters ----------","platform. This module provides decorators to log the execution of","file name based on the module name. The name of","datetime. Parameters ---------- module : str The name of the","decorate. Returns ------- wrapped : func The wrapped function. \"\"\"","', '') for module in module_list] module_list = [module.split('=')[0] for","\"\"\" @wraps(func) def wrapped(*a, **kw): # Log environment information logging.info('User:","func : func The function to decorate. Returns ------- wrapped","ImportError as err: logging.warning(err) # Call the function and time","production environement. path : str Where to write the log","to log crashes in the decorated code. Parameters ---------- func","name of the module being logged and the current datetime.","= module_required.split(',') # Clean up the module list module_list =","module, use: :: import os import logging from jwql.logging.logging_functions import","divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time, 60 *","set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \"\"\"Create the log file name","log_file = os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename)","from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL =","logging.info('Python Executable Path: ' + sys.executable) # Read in setup.py","logging.info('Python Version: ' + sys.version.replace('\\n', '')) logging.info('Python Executable Path: '","Version: ' + sys.version.replace('\\n', '')) logging.info('Python Executable Path: ' +","written to the ``logs/`` directory in the ``jwql`` central storage","getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\n',","@log_info @log_fail def my_main_function(): pass if __name__ == '__main__': module","logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from","execution of modules. Log files are written to the ``logs/``","divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU","file will be written to. \"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename","seconds_cpu)) return wrapped def log_fail(func): \"\"\"Decorator to log crashes in","Future packages we want to track can be added or","minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time,","file to build list of required modules settings = get_config()","t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed","[] if user != admin_account and module not in exempt_modules","sys.version.replace('\\n', '')) logging.info('Python Executable Path: ' + sys.executable) # Read","60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time","= settings['log_dir'] exempt_modules = [] if user != admin_account and","logged and the current datetime. Parameters ---------- module : str","\"\"\" import datetime import getpass import importlib import logging import","= production_mode # Create the log file and set the","get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules = []","func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED') return wrapped","in module_list] # Log common module version information for module","t2_time = time.time() # Log execution time hours_cpu, remainder_cpu =","time.clock() t1_time = time.time() func(*a, **kw) t2_cpu = time.clock() t2_time","t1_time = time.time() func(*a, **kw) t2_cpu = time.clock() t2_time =","production_mode : bool Whether or not the output should be","useful system information. This function can be used as a","Parameters ---------- func : func The function to decorate. Returns","== '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------","log_file PRODUCTION_BOOL = production_mode # Create the log file and","module_list = [module.replace('\"', '').replace(\"'\", '').replace(' ', '') for module in","minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped","timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>,","log user environment and system information. Future packages we want","jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import","Determine log file location if production_mode: log_file = make_log_file(module) else:","import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function():","to the production environement. path : str Where to write","Version: ' + mod.__version__) logging.info(module + ' Path: ' +","function can be used as a decorator to log user","environment information logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname())","working dir. Returns ------- log_file : str The full path","system information. Future packages we want to track can be","PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): \"\"\"Configure the log","To log the execution of a module, use: :: import","\"REQUIRES\": module_required = line[12:-2] module_list = module_required.split(',') # Clean up","name of the ``log_file`` is a combination of the name","# Clean up the module list module_list = [module.replace('\"', '').replace(\"'\",","logging.warning(err) # Call the function and time it t1_cpu =","admin_account and module not in exempt_modules and production_mode: module =","of the module being logged and the current datetime. Parameters","necessary. Parameters ---------- func : func The function to decorate.","---------- module : str The name of the module being","the production environment. path : str Where to write the","traceback from functools import wraps from jwql.utils.permissions import set_permissions from","str The name of the module being logged. production_mode :","user-supplied path; default to working dir. Returns ------- log_file :","settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if user !=","``logs/`` directory in the ``jwql`` central storage area, named by","production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL","socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\n', '')) logging.info('Python Executable Path:","seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time,","getpass import importlib import logging import os import pwd import","Parameters ---------- module : str The name of the module","being logged. production_mode : bool Whether or not the output","Path: ' + mod.__path__[0]) except ImportError as err: logging.warning(err) #","it t1_cpu = time.clock() t1_time = time.time() func(*a, **kw) t2_cpu","seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time))","crashes in the decorated code. Parameters ---------- func : func","can be added or removed as necessary. Parameters ---------- func","get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for line","for module in module_list] module_list = [module.split('=')[0] for module in","python routine ``logging_functions.py`` written by Alex Viana, 2013 for the","written to the production environement. path : str Where to","removed as necessary. Parameters ---------- func : func The function","try: # Run the function func(*a, **kw) logging.info('Completed Successfully') except","= os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file))","``jwql`` automation platform. This module provides decorators to log the","the log file name based on the module name. The","in the ``jwql`` central storage area, named by module name","routine ``logging_functions.py`` written by Alex Viana, 2013 for the WFC3","str The full path to where the log file will","decorator to log user environment and system information. Future packages","log if user-supplied path; default to working dir. Returns -------","+ getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' +","log crashes in the decorated code. Parameters ---------- func :","get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module,","if line[0:8] == \"REQUIRES\": module_required = line[12:-2] module_list = module_required.split(',')","the production environement. path : str Where to write the","log_fail(func): \"\"\"Decorator to log crashes in the decorated code. Parameters","is adopted and updated from python routine ``logging_functions.py`` written by","a module, use: :: import os import logging from jwql.logging.logging_functions","for line in setup: if line[0:8] == \"REQUIRES\": module_required =","if user-supplied path; default to working dir. \"\"\" # Determine","import getpass import importlib import logging import os import pwd","code is adopted and updated from python routine ``logging_functions.py`` written","the module list module_list = [module.replace('\"', '').replace(\"'\", '').replace(' ', '')","the decorated code. Parameters ---------- func : func The function","Where to write the log if user-supplied path; default to","added or removed as necessary. Parameters ---------- func : func","functools import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import","placed in the ``utils`` directory. References ---------- This code is","[module.split('=')[0] for module in module_list] # Log common module version","* 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time =","Version) Use --- To log the execution of a module,","Returns ------- log_file : str The full path to where","The function to decorate. Returns ------- wrapped : func The","filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \"\"\"Decorator to log useful","seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def","production_mode=True, path='./'): \"\"\"Configure the log file with a standard logging","= settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if user","module in module_list] module_list = [module.split('=')[0] for module in module_list]","of modules. Log files are written to the ``logs/`` directory","function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED') return","minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time -","%(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'):","from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail","# Read in setup.py file to build list of required","Quicklook automation platform. \"\"\" import datetime import getpass import importlib","wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw): # Log environment","jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = ''","The full path to where the log file will be","path : str Where to write the log if user-supplied","execution of a module, use: :: import os import logging","+ ' Path: ' + mod.__path__[0]) except ImportError as err:","common module version information for module in module_list: try: mod","a decorator to log user environment and system information. Future","module_list] module_list = [module.split('=')[0] for module in module_list] # Log","logging import os import pwd import socket import sys import","os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module, filename) else:","CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \"\"\"Decorator","and time it t1_cpu = time.clock() t1_time = time.time() func(*a,","we want to track can be added or removed as","settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup:","log_fail @log_info @log_fail def my_main_function(): pass if __name__ == '__main__':","The wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw): try: #","set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL","automation platform. This module provides decorators to log the execution","60) hours_time, remainder_time = divmod(t2_time - t1_time, 60 * 60)","= '' def configure_logging(module, production_mode=True, path='./'): \"\"\"Configure the log file","named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors -------","jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC =","= divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed","module = os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module,","import traceback from functools import wraps from jwql.utils.permissions import set_permissions","production_mode # Create the log file and set the permissions","for module in module_list] # Log common module version information","to. \"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user","the module name. The name of the ``log_file`` is a","the WFC3 Quicklook automation platform. \"\"\" import datetime import getpass","path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL =","log_file : str The full path to where the log","wrapped function. \"\"\" @wraps(func) def wrapped(*a, **kw): try: # Run","import sys import time import traceback from functools import wraps","by Alex Viana, 2013 for the WFC3 Quicklook automation platform.","settings = get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules","standard logging format. Parameters ---------- module : str The name","PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create the","the module being logged. production_mode : bool Whether or not","= line[12:-2] module_list = module_required.split(',') # Clean up the module","**kw): try: # Run the function func(*a, **kw) logging.info('Completed Successfully')","of the ``log_file`` is a combination of the name of","' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: '","minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \"\"\"Decorator to log crashes","global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create","Clean up the module list module_list = [module.replace('\"', '').replace(\"'\", '').replace('","remainder_time = divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time","dir. Returns ------- log_file : str The full path to","------------ The user must have a configuration file named ``config.json``","the ``log_file`` is a combination of the name of the","import time import traceback from functools import wraps from jwql.utils.permissions","path to where the log file will be written to.","as a decorator to log user environment and system information.","used as a decorator to log user environment and system","------- wrapped : func The wrapped function. \"\"\" @wraps(func) def","import importlib import logging import os import pwd import socket","= log_file PRODUCTION_BOOL = production_mode # Create the log file","err: logging.warning(err) # Call the function and time it t1_cpu","production_mode: module = os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path,","---------- This code is adopted and updated from python routine","user environment and system information. Future packages we want to","not in exempt_modules and production_mode: module = os.path.join('dev', module) if","the log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s:","function and time it t1_cpu = time.clock() t1_time = time.time()","\"\"\" @wraps(func) def wrapped(*a, **kw): try: # Run the function","[module.replace('\"', '').replace(\"'\", '').replace(' ', '') for module in module_list] module_list","from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions","t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time,","to write the log if user-supplied path; default to working","configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info","'' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): \"\"\"Configure the","the log file will be written to. \"\"\" timestamp =",": func The function to decorate. Returns ------- wrapped :","logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func):","user != admin_account and module not in exempt_modules and production_mode:","os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user must have","import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config,","= time.clock() t2_time = time.time() # Log execution time hours_cpu,","# Run the function func(*a, **kw) logging.info('Completed Successfully') except Exception:","module being logged and the current datetime. Parameters ---------- module","log the execution of modules. Log files are written to","Viana, 2013 for the WFC3 Quicklook automation platform. \"\"\" import","bool Whether or not the output should be written to","based on the module name. The name of the ``log_file``","= divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu =","mod = importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__)","module_required.split(',') # Clean up the module list module_list = [module.replace('\"',","2013 for the WFC3 Quicklook automation platform. \"\"\" import datetime","'').replace(\"'\", '').replace(' ', '') for module in module_list] module_list =","``config.json`` placed in the ``utils`` directory. References ---------- This code","updated from python routine ``logging_functions.py`` written by Alex Viana, 2013",": str The name of the module being logged. production_mode","wrapped(*a, **kw): try: # Run the function func(*a, **kw) logging.info('Completed","user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path","from python routine ``logging_functions.py`` written by Alex Viana, 2013 for","LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'):","as necessary. Parameters ---------- func : func The function to","to log useful system information. This function can be used","log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \"\"\"Decorator","the current datetime. Parameters ---------- module : str The name","module list module_list = [module.replace('\"', '').replace(\"'\", '').replace(' ', '') for","be written to. \"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module,","log file name based on the module name. The name","path='./'): \"\"\"Configure the log file with a standard logging format.","mod.__path__[0]) except ImportError as err: logging.warning(err) # Call the function","import logging import os import pwd import socket import sys","= make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC =","== \"REQUIRES\": module_required = line[12:-2] module_list = module_required.split(',') # Clean","Logging functions for the ``jwql`` automation platform. This module provides","the log if user-supplied path; default to working dir. Returns","log the execution of a module, use: :: import os","pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module)","packages we want to track can be added or removed","timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account']","log_file def log_info(func): \"\"\"Decorator to log useful system information. This","'' def configure_logging(module, production_mode=True, path='./'): \"\"\"Configure the log file with","with a standard logging format. Parameters ---------- module : str","of the name of the module being logged and the","Returns ------- wrapped : func The wrapped function. \"\"\" @wraps(func)","'') for module in module_list] module_list = [module.split('=')[0] for module","up the module list module_list = [module.replace('\"', '').replace(\"'\", '').replace(' ',","default to working dir. \"\"\" # Determine log file location","the ``logs/`` directory in the ``jwql`` central storage area, named","should be written to the production environment. path : str","mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0]) except ImportError","Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60","' + sys.version.replace('\\n', '')) logging.info('Python Executable Path: ' + sys.executable)","= os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user must","WFC3 Quicklook automation platform. \"\"\" import datetime import getpass import","sys.executable) # Read in setup.py file to build list of","``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>, 2013 (WFC3","module_list] # Log common module version information for module in","location if production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module,","information. Future packages we want to track can be added","and module not in exempt_modules and production_mode: module = os.path.join('dev',","filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config()","format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module,","Whether or not the output should be written to the","default to working dir. Returns ------- log_file : str The","jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def","logging format. Parameters ---------- module : str The name of","write the log if user-supplied path; default to working dir.","------- - <NAME> 2018 - <NAME>, 2013 (WFC3 QL Version)","- <NAME> 2018 - <NAME>, 2013 (WFC3 QL Version) Use","wrapped : func The wrapped function. \"\"\" @wraps(func) def wrapped(*a,","to the production environment. path : str Where to write","LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create the log","written by Alex Viana, 2013 for the WFC3 Quicklook automation","environment. path : str Where to write the log if","import pwd import socket import sys import time import traceback","\"\"\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user =","- t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60)","be used as a decorator to log user environment and","be added or removed as necessary. Parameters ---------- func :","Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu,","# Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu,","60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time,","required modules settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name)","@wraps(func) def wrapped(*a, **kw): try: # Run the function func(*a,","not the output should be written to the production environement.","= os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module, filename)","information logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python","make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global","log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass","hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu,","Path: ' + sys.executable) # Read in setup.py file to","track can be added or removed as necessary. Parameters ----------","adopted and updated from python routine ``logging_functions.py`` written by Alex","else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func):","exempt_modules = [] if user != admin_account and module not","%H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \"\"\"Create the","of required modules settings = get_config() setup_file_name = settings['setup_file'] with","except ImportError as err: logging.warning(err) # Call the function and","- t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60)","Run the function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc())","60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time","settings['log_dir'] exempt_modules = [] if user != admin_account and module","\"\"\" # Determine log file location if production_mode: log_file =","the ``utils`` directory. References ---------- This code is adopted and","written to the production environment. path : str Where to","to log user environment and system information. Future packages we","with open(setup_file_name) as setup: for line in setup: if line[0:8]","module_required = line[12:-2] module_list = module_required.split(',') # Clean up the","def wrapped(*a, **kw): try: # Run the function func(*a, **kw)","wrapped def log_fail(func): \"\"\"Decorator to log crashes in the decorated","path='./'): \"\"\"Create the log file name based on the module","``log_file`` is a combination of the name of the module","setup: for line in setup: if line[0:8] == \"REQUIRES\": module_required",": str The full path to where the log file","module not in exempt_modules and production_mode: module = os.path.join('dev', module)","to build list of required modules settings = get_config() setup_file_name","log_path = settings['log_dir'] exempt_modules = [] if user != admin_account","to working dir. \"\"\" # Determine log file location if","ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True,","name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018","module_list = [module.split('=')[0] for module in module_list] # Log common","= '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account","setup.py file to build list of required modules settings =","= pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path =","func The function to decorate. Returns ------- wrapped : func","environment and system information. Future packages we want to track","import os import pwd import socket import sys import time","code. Parameters ---------- func : func The function to decorate."],"string":"[\n \"file named ``config.json`` placed in the ``utils`` directory. References ----------\",\n \"name. The name of the ``log_file`` is a combination of\",\n \"os import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import\",\n \"<NAME>, 2013 (WFC3 QL Version) Use --- To log the\",\n \"Dependencies ------------ The user must have a configuration file named\",\n \"The name of the module being logged. production_mode : bool\",\n \"open(setup_file_name) as setup: for line in setup: if line[0:8] ==\",\n \"if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function()\",\n \"module in module_list] # Log common module version information for\",\n \"to working dir. Returns ------- log_file : str The full\",\n \"func(*a, **kw) t2_cpu = time.clock() t2_time = time.time() # Log\",\n \"line[12:-2] module_list = module_required.split(',') # Clean up the module list\",\n \"@log_fail def my_main_function(): pass if __name__ == '__main__': module =\",\n \"to decorate. Returns ------- wrapped : func The wrapped function.\",\n \"is a combination of the name of the module being\",\n \"being logged and the current datetime. Parameters ---------- module :\",\n \"output should be written to the production environment. path :\",\n \"= [module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ', '') for module in module_list]\",\n \"where the log file will be written to. \\\"\\\"\\\" timestamp\",\n \"time.time() func(*a, **kw) t2_cpu = time.clock() t2_time = time.time() #\",\n \"production_mode: log_file = os.path.join(log_path, module, filename) else: log_file = os.path.join(path,\",\n \"@wraps(func) def wrapped(*a, **kw): # Log environment information logging.info('User: '\",\n \"list of required modules settings = get_config() setup_file_name = settings['setup_file']\",\n \"user must have a configuration file named ``config.json`` placed in\",\n \"the output should be written to the production environment. path\",\n \"References ---------- This code is adopted and updated from python\",\n \"combination of the name of the module being logged and\",\n \"the name of the module being logged and the current\",\n \"= time.time() func(*a, **kw) t2_cpu = time.clock() t2_time = time.time()\",\n \"- <NAME>, 2013 (WFC3 QL Version) Use --- To log\",\n \"module in module_list: try: mod = importlib.import_module(module) logging.info(module + '\",\n \"Log files are written to the ``logs/`` directory in the\",\n \"be written to the production environement. path : str Where\",\n \"list module_list = [module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ', '') for module\",\n \"= [] if user != admin_account and module not in\",\n \"time it t1_cpu = time.clock() t1_time = time.time() func(*a, **kw)\",\n \"in the ``utils`` directory. References ---------- This code is adopted\",\n \"---------- func : func The function to decorate. Returns -------\",\n \"import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail\",\n \":: import os import logging from jwql.logging.logging_functions import configure_logging from\",\n \"def wrapped(*a, **kw): # Log environment information logging.info('User: ' +\",\n \"time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60)\",\n \"**kw) t2_cpu = time.clock() t2_time = time.time() # Log execution\",\n \"``utils`` directory. References ---------- This code is adopted and updated\",\n \"logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def\",\n \"'')) logging.info('Python Executable Path: ' + sys.executable) # Read in\",\n \"'').replace(' ', '') for module in module_list] module_list = [module.split('=')[0]\",\n \"build list of required modules settings = get_config() setup_file_name =\",\n \"to where the log file will be written to. \\\"\\\"\\\"\",\n \"if production_mode: log_file = os.path.join(log_path, module, filename) else: log_file =\",\n \"t1_cpu = time.clock() t1_time = time.time() func(*a, **kw) t2_cpu =\",\n \"as err: logging.warning(err) # Call the function and time it\",\n \"pwd import socket import sys import time import traceback from\",\n \"module name. The name of the ``log_file`` is a combination\",\n \"a combination of the name of the module being logged\",\n \"datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings =\",\n \"to log the execution of modules. Log files are written\",\n \"= time.time() # Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu\",\n \"by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- -\",\n \"# Determine log file location if production_mode: log_file = make_log_file(module)\",\n \"name of the module being logged. production_mode : bool Whether\",\n \"format. Parameters ---------- module : str The name of the\",\n \"timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name\",\n \"module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file\",\n \"from functools import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils\",\n \"and system information. Future packages we want to track can\",\n \"# Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System: '\",\n \"functions for the ``jwql`` automation platform. This module provides decorators\",\n \"t2_cpu = time.clock() t2_time = time.time() # Log execution time\",\n \"log if user-supplied path; default to working dir. \\\"\\\"\\\" #\",\n \"= get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules =\",\n \"module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user\",\n \"hours_time, remainder_time = divmod(t2_time - t1_time, 60 * 60) minutes_time,\",\n \"' Path: ' + mod.__path__[0]) except ImportError as err: logging.warning(err)\",\n \"= time.clock() t1_time = time.time() func(*a, **kw) t2_cpu = time.clock()\",\n \"logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu,\",\n \"environement. path : str Where to write the log if\",\n \"if user != admin_account and module not in exempt_modules and\",\n \"'') configure_logging(module) my_main_function() Dependencies ------------ The user must have a\",\n \"# Call the function and time it t1_cpu = time.clock()\",\n \"admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if\",\n \"2013 (WFC3 QL Version) Use --- To log the execution\",\n \"``logging_functions.py`` written by Alex Viana, 2013 for the WFC3 Quicklook\",\n \"import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = ''\",\n \"the ``jwql`` automation platform. This module provides decorators to log\",\n \"time.clock() t2_time = time.time() # Log execution time hours_cpu, remainder_cpu\",\n \"global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode\",\n \"want to track can be added or removed as necessary.\",\n \"Executable Path: ' + sys.executable) # Read in setup.py file\",\n \"name based on the module name. The name of the\",\n \"= settings['setup_file'] with open(setup_file_name) as setup: for line in setup:\",\n \"line[0:8] == \\\"REQUIRES\\\": module_required = line[12:-2] module_list = module_required.split(',') #\",\n \"on the module name. The name of the ``log_file`` is\",\n \"the function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED')\",\n \"permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file)\",\n \"current datetime. Parameters ---------- module : str The name of\",\n \"wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists\",\n \"of the module being logged. production_mode : bool Whether or\",\n \"import os import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions\",\n \"LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode #\",\n \"exempt_modules and production_mode: module = os.path.join('dev', module) if production_mode: log_file\",\n \"e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>, 2013\",\n \"from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC\",\n \"+ ' Version: ' + mod.__version__) logging.info(module + ' Path:\",\n \"a configuration file named ``config.json`` placed in the ``utils`` directory.\",\n \"provides decorators to log the execution of modules. Log files\",\n \"function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): # Log environment information\",\n \"log_info(func): \\\"\\\"\\\"Decorator to log useful system information. This function can\",\n \"log file location if production_mode: log_file = make_log_file(module) else: log_file\",\n \"else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL\",\n \"configure_logging(module) my_main_function() Dependencies ------------ The user must have a configuration\",\n \"platform. \\\"\\\"\\\" import datetime import getpass import importlib import logging\",\n \"%p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create the log\",\n \"working dir. \\\"\\\"\\\" # Determine log file location if production_mode:\",\n \"Call the function and time it t1_cpu = time.clock() t1_time\",\n \"logging.info(module + ' Path: ' + mod.__path__[0]) except ImportError as\",\n \"datetime import getpass import importlib import logging import os import\",\n \"decorators to log the execution of modules. Log files are\",\n \"os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return\",\n \"import log_fail @log_info @log_fail def my_main_function(): pass if __name__ ==\",\n \"divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time,\",\n \"importlib import logging import os import pwd import socket import\",\n \"system information. This function can be used as a decorator\",\n \"The wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): # Log\",\n \"settings['setup_file'] with open(setup_file_name) as setup: for line in setup: if\",\n \"= divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time, 60\",\n \"file with a standard logging format. Parameters ---------- module :\",\n \"storage area, named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log``\",\n \"if production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False,\",\n \"the output should be written to the production environement. path\",\n \"= make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC\",\n \"logged. production_mode : bool Whether or not the output should\",\n \"module provides decorators to log the execution of modules. Log\",\n \"jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass if __name__\",\n \"can be used as a decorator to log user environment\",\n \"def log_info(func): \\\"\\\"\\\"Decorator to log useful system information. This function\",\n \"production environment. path : str Where to write the log\",\n \"Authors ------- - <NAME> 2018 - <NAME>, 2013 (WFC3 QL\",\n \"2018 - <NAME>, 2013 (WFC3 QL Version) Use --- To\",\n \"socket import sys import time import traceback from functools import\",\n \"datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create\",\n \"func The wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): try:\",\n \"log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global\",\n \"import socket import sys import time import traceback from functools\",\n \"remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu\",\n \"PRODUCTION_BOOL = production_mode # Create the log file and set\",\n \"'{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account =\",\n \"log file with a standard logging format. Parameters ---------- module\",\n \"Read in setup.py file to build list of required modules\",\n \"import datetime import getpass import importlib import logging import os\",\n \"Log common module version information for module in module_list: try:\",\n \"60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time:\",\n \"module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME>\",\n \"return wrapped def log_fail(func): \\\"\\\"\\\"Decorator to log crashes in the\",\n \"modules settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as\",\n \"in setup: if line[0:8] == \\\"REQUIRES\\\": module_required = line[12:-2] module_list\",\n \"and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 -\",\n \"= divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time =\",\n \"# Create the log file and set the permissions logging.basicConfig(filename=log_file,\",\n \"function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): try: # Run the\",\n \"# Log common module version information for module in module_list:\",\n \"a standard logging format. Parameters ---------- module : str The\",\n \"This function can be used as a decorator to log\",\n \"my_main_function(): pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '')\",\n \": bool Whether or not the output should be written\",\n \"if user-supplied path; default to working dir. Returns ------- log_file\",\n \"files are written to the ``logs/`` directory in the ``jwql``\",\n \"def configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure the log file with a\",\n \"file location if production_mode: log_file = make_log_file(module) else: log_file =\",\n \"import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def\",\n \"must have a configuration file named ``config.json`` placed in the\",\n \"and the current datetime. Parameters ---------- module : str The\",\n \"the execution of a module, use: :: import os import\",\n \"' + sys.executable) # Read in setup.py file to build\",\n \"os import pwd import socket import sys import time import\",\n \"to track can be added or removed as necessary. Parameters\",\n \"in module_list] module_list = [module.split('=')[0] for module in module_list] #\",\n \"func The wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): #\",\n \"try: mod = importlib.import_module(module) logging.info(module + ' Version: ' +\",\n \"directory in the ``jwql`` central storage area, named by module\",\n \"information. This function can be used as a decorator to\",\n \"be written to the production environment. path : str Where\",\n \"module : str The name of the module being logged.\",\n \"production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path)\",\n \"This code is adopted and updated from python routine ``logging_functions.py``\",\n \"log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s',\",\n \"= datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings\",\n \"production_mode=True, path='./'): \\\"\\\"\\\"Create the log file name based on the\",\n \"use: :: import os import logging from jwql.logging.logging_functions import configure_logging\",\n \"user-supplied path; default to working dir. \\\"\\\"\\\" # Determine log\",\n \"+ mod.__path__[0]) except ImportError as err: logging.warning(err) # Call the\",\n \"module being logged. production_mode : bool Whether or not the\",\n \"+ sys.version.replace('\\\\n', '')) logging.info('Python Executable Path: ' + sys.executable) #\",\n \"the function and time it t1_cpu = time.clock() t1_time =\",\n \"def make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create the log file name based\",\n \"setup: if line[0:8] == \\\"REQUIRES\\\": module_required = line[12:-2] module_list =\",\n \"' + mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0])\",\n \"ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \\\"\\\"\\\"Decorator to log useful system\",\n \"from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass if\",\n \"or removed as necessary. Parameters ---------- func : func The\",\n \"function to decorate. Returns ------- wrapped : func The wrapped\",\n \"import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info\",\n \"%(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True,\",\n \"line in setup: if line[0:8] == \\\"REQUIRES\\\": module_required = line[12:-2]\",\n \"Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu))\",\n \"def my_main_function(): pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py',\",\n \"os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \\\"\\\"\\\"Decorator to log\",\n \"setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for line in\",\n \"+ sys.executable) # Read in setup.py file to build list\",\n \"+ socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\\\n', '')) logging.info('Python Executable\",\n \"area, named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors\",\n \"divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu,\",\n \"!= admin_account and module not in exempt_modules and production_mode: module\",\n \"to the ``logs/`` directory in the ``jwql`` central storage area,\",\n \"the execution of modules. Log files are written to the\",\n \"and updated from python routine ``logging_functions.py`` written by Alex Viana,\",\n \"in exempt_modules and production_mode: module = os.path.join('dev', module) if production_mode:\",\n \": func The wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw):\",\n \"--- To log the execution of a module, use: ::\",\n \"sys import time import traceback from functools import wraps from\",\n \"information for module in module_list: try: mod = importlib.import_module(module) logging.info(module\",\n \"dir. \\\"\\\"\\\" # Determine log file location if production_mode: log_file\",\n \"module_list = module_required.split(',') # Clean up the module list module_list\",\n \"logging.info(module + ' Version: ' + mod.__version__) logging.info(module + '\",\n \"= '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure\",\n \"full path to where the log file will be written\",\n \"and production_mode: module = os.path.join('dev', module) if production_mode: log_file =\",\n \"QL Version) Use --- To log the execution of a\",\n \"for the WFC3 Quicklook automation platform. \\\"\\\"\\\" import datetime import\",\n \"output should be written to the production environement. path :\",\n \"the log file with a standard logging format. Parameters ----------\",\n \"or not the output should be written to the production\",\n \"level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create the log file\",\n \"in setup.py file to build list of required modules settings\",\n \"+ mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0]) except\",\n \"60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real\",\n \"of a module, use: :: import os import logging from\",\n \"make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file\",\n \"modules. Log files are written to the ``logs/`` directory in\",\n \"``jwql`` central storage area, named by module name and timestamp,\",\n \"the ``jwql`` central storage area, named by module name and\",\n \"module_list: try: mod = importlib.import_module(module) logging.info(module + ' Version: '\",\n \"**kw): # Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System:\",\n \"str Where to write the log if user-supplied path; default\",\n \"will be written to. \\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename =\",\n \"module) if production_mode: log_file = os.path.join(log_path, module, filename) else: log_file\",\n \"configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure the log file with a standard\",\n \"{0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return\",\n \"named ``config.json`` placed in the ``utils`` directory. References ---------- This\",\n \"= importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__) logging.info(module\",\n \"the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO)\",\n \"Use --- To log the execution of a module, use:\",\n \"' Version: ' + mod.__version__) logging.info(module + ' Path: '\",\n \"for the ``jwql`` automation platform. This module provides decorators to\",\n \"Alex Viana, 2013 for the WFC3 Quicklook automation platform. \\\"\\\"\\\"\",\n \"Log environment information logging.info('User: ' + getpass.getuser()) logging.info('System: ' +\",\n \"have a configuration file named ``config.json`` placed in the ``utils``\",\n \"should be written to the production environement. path : str\",\n \": str Where to write the log if user-supplied path;\",\n \"pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path = settings['log_dir']\",\n \"<NAME> 2018 - <NAME>, 2013 (WFC3 QL Version) Use ---\",\n \"the log if user-supplied path; default to working dir. \\\"\\\"\\\"\",\n \"log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC\",\n \"path; default to working dir. Returns ------- log_file : str\",\n \"Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \\\"\\\"\\\"Decorator to\",\n \"file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y\",\n \"the module being logged and the current datetime. Parameters ----------\",\n \"The name of the ``log_file`` is a combination of the\",\n \"version information for module in module_list: try: mod = importlib.import_module(module)\",\n \"decorated code. Parameters ---------- func : func The function to\",\n \"logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\\\n', ''))\",\n \"\\\"\\\"\\\"Create the log file name based on the module name.\",\n \"written to. \\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp)\",\n \"= get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for\",\n \"= [module.split('=')[0] for module in module_list] # Log common module\",\n \"__name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies\",\n \"' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\\\n', '')) logging.info('Python\",\n \"= os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \\\"\\\"\\\"Decorator to\",\n \"This module provides decorators to log the execution of modules.\",\n \"module version information for module in module_list: try: mod =\",\n \"set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p',\",\n \"\\\"\\\"\\\"Decorator to log useful system information. This function can be\",\n \"for module in module_list: try: mod = importlib.import_module(module) logging.info(module +\",\n \"filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def\",\n \"not the output should be written to the production environment.\",\n \"\\\"\\\"\\\" Logging functions for the ``jwql`` automation platform. This module\",\n \"time.time() # Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu -\",\n \"(WFC3 QL Version) Use --- To log the execution of\",\n \"and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S\",\n \"logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version:\",\n \"in the decorated code. Parameters ---------- func : func The\",\n \"' + mod.__path__[0]) except ImportError as err: logging.warning(err) # Call\",\n \"return log_file def log_info(func): \\\"\\\"\\\"Decorator to log useful system information.\",\n \"as setup: for line in setup: if line[0:8] == \\\"REQUIRES\\\":\",\n \"execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 *\",\n \"{0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \\\"\\\"\\\"Decorator to log\",\n \"def log_fail(func): \\\"\\\"\\\"Decorator to log crashes in the decorated code.\",\n \"automation platform. \\\"\\\"\\\" import datetime import getpass import importlib import\",\n \"central storage area, named by module name and timestamp, e.g.\",\n \"* 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time:\",\n \"configuration file named ``config.json`` placed in the ``utils`` directory. References\",\n \"'__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The\",\n \"log file will be written to. \\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M')\",\n \"make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create the log file name based on\",\n \"------- log_file : str The full path to where the\",\n \"path; default to working dir. \\\"\\\"\\\" # Determine log file\",\n \"\\\"\\\"\\\"Configure the log file with a standard logging format. Parameters\",\n \"time import traceback from functools import wraps from jwql.utils.permissions import\",\n \"Create the log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s\",\n \"log useful system information. This function can be used as\",\n \"are written to the ``logs/`` directory in the ``jwql`` central\",\n \"importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__) logging.info(module +\",\n \"directory. References ---------- This code is adopted and updated from\",\n \"wrapped(*a, **kw): # Log environment information logging.info('User: ' + getpass.getuser())\",\n \"The user must have a configuration file named ``config.json`` placed\",\n \"in module_list: try: mod = importlib.import_module(module) logging.info(module + ' Version:\",\n \"my_main_function() Dependencies ------------ The user must have a configuration file\",\n \"\\\"\\\"\\\"Decorator to log crashes in the decorated code. Parameters ----------\",\n \"platform. This module provides decorators to log the execution of\",\n \"file name based on the module name. The name of\",\n \"datetime. Parameters ---------- module : str The name of the\",\n \"decorate. Returns ------- wrapped : func The wrapped function. \\\"\\\"\\\"\",\n \"', '') for module in module_list] module_list = [module.split('=')[0] for\",\n \"\\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): # Log environment information logging.info('User:\",\n \"func : func The function to decorate. Returns ------- wrapped\",\n \"ImportError as err: logging.warning(err) # Call the function and time\",\n \"production environement. path : str Where to write the log\",\n \"to log crashes in the decorated code. Parameters ---------- func\",\n \"name of the module being logged and the current datetime.\",\n \"= module_required.split(',') # Clean up the module list module_list =\",\n \"module, use: :: import os import logging from jwql.logging.logging_functions import\",\n \"divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time, 60 *\",\n \"set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create the log file name\",\n \"log_file = os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename)\",\n \"from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL =\",\n \"logging.info('Python Executable Path: ' + sys.executable) # Read in setup.py\",\n \"logging.info('Python Version: ' + sys.version.replace('\\\\n', '')) logging.info('Python Executable Path: '\",\n \"Version: ' + sys.version.replace('\\\\n', '')) logging.info('Python Executable Path: ' +\",\n \"written to the ``logs/`` directory in the ``jwql`` central storage\",\n \"getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\\\n',\",\n \"@log_info @log_fail def my_main_function(): pass if __name__ == '__main__': module\",\n \"logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from\",\n \"execution of modules. Log files are written to the ``logs/``\",\n \"divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU\",\n \"file will be written to. \\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename\",\n \"seconds_cpu)) return wrapped def log_fail(func): \\\"\\\"\\\"Decorator to log crashes in\",\n \"Future packages we want to track can be added or\",\n \"minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time,\",\n \"file to build list of required modules settings = get_config()\",\n \"t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed\",\n \"[] if user != admin_account and module not in exempt_modules\",\n \"sys.version.replace('\\\\n', '')) logging.info('Python Executable Path: ' + sys.executable) # Read\",\n \"60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time\",\n \"= settings['log_dir'] exempt_modules = [] if user != admin_account and\",\n \"logged and the current datetime. Parameters ---------- module : str\",\n \"\\\"\\\"\\\" import datetime import getpass import importlib import logging import\",\n \"= production_mode # Create the log file and set the\",\n \"get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules = []\",\n \"func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED') return wrapped\",\n \"in module_list] # Log common module version information for module\",\n \"t2_time = time.time() # Log execution time hours_cpu, remainder_cpu =\",\n \"time.clock() t1_time = time.time() func(*a, **kw) t2_cpu = time.clock() t2_time\",\n \"t1_time = time.time() func(*a, **kw) t2_cpu = time.clock() t2_time =\",\n \"production_mode : bool Whether or not the output should be\",\n \"useful system information. This function can be used as a\",\n \"Parameters ---------- func : func The function to decorate. Returns\",\n \"== '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------\",\n \"log_file PRODUCTION_BOOL = production_mode # Create the log file and\",\n \"module_list = [module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ', '') for module in\",\n \"minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped\",\n \"timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>,\",\n \"log user environment and system information. Future packages we want\",\n \"jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import\",\n \"Determine log file location if production_mode: log_file = make_log_file(module) else:\",\n \"import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function():\",\n \"to the production environement. path : str Where to write\",\n \"Version: ' + mod.__version__) logging.info(module + ' Path: ' +\",\n \"function can be used as a decorator to log user\",\n \"environment information logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname())\",\n \"working dir. Returns ------- log_file : str The full path\",\n \"system information. Future packages we want to track can be\",\n \"PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure the log\",\n \"To log the execution of a module, use: :: import\",\n \"\\\"REQUIRES\\\": module_required = line[12:-2] module_list = module_required.split(',') # Clean up\",\n \"name of the ``log_file`` is a combination of the name\",\n \"# Clean up the module list module_list = [module.replace('\\\"', '').replace(\\\"'\\\",\",\n \"logging.warning(err) # Call the function and time it t1_cpu =\",\n \"admin_account and module not in exempt_modules and production_mode: module =\",\n \"of the module being logged and the current datetime. Parameters\",\n \"necessary. Parameters ---------- func : func The function to decorate.\",\n \"---------- module : str The name of the module being\",\n \"the production environment. path : str Where to write the\",\n \"traceback from functools import wraps from jwql.utils.permissions import set_permissions from\",\n \"str The name of the module being logged. production_mode :\",\n \"user-supplied path; default to working dir. Returns ------- log_file :\",\n \"settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if user !=\",\n \"``logs/`` directory in the ``jwql`` central storage area, named by\",\n \"production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL\",\n \"socket.gethostname()) logging.info('Python Version: ' + sys.version.replace('\\\\n', '')) logging.info('Python Executable Path:\",\n \"seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time - t1_time,\",\n \"getpass import importlib import logging import os import pwd import\",\n \"Parameters ---------- module : str The name of the module\",\n \"being logged. production_mode : bool Whether or not the output\",\n \"Path: ' + mod.__path__[0]) except ImportError as err: logging.warning(err) #\",\n \"it t1_cpu = time.clock() t1_time = time.time() func(*a, **kw) t2_cpu\",\n \"seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time))\",\n \"crashes in the decorated code. Parameters ---------- func : func\",\n \"can be added or removed as necessary. Parameters ---------- func\",\n \"get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup: for line\",\n \"for module in module_list] module_list = [module.split('=')[0] for module in\",\n \"python routine ``logging_functions.py`` written by Alex Viana, 2013 for the\",\n \"written to the production environement. path : str Where to\",\n \"removed as necessary. Parameters ---------- func : func The function\",\n \"try: # Run the function func(*a, **kw) logging.info('Completed Successfully') except\",\n \"= os.path.join(log_path, module, filename) else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file))\",\n \"``jwql`` automation platform. This module provides decorators to log the\",\n \"the log file name based on the module name. The\",\n \"in the ``jwql`` central storage area, named by module name\",\n \"routine ``logging_functions.py`` written by Alex Viana, 2013 for the WFC3\",\n \"str The full path to where the log file will\",\n \"decorator to log user environment and system information. Future packages\",\n \"log if user-supplied path; default to working dir. Returns -------\",\n \"+ getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: ' +\",\n \"log crashes in the decorated code. Parameters ---------- func :\",\n \"get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module,\",\n \"if line[0:8] == \\\"REQUIRES\\\": module_required = line[12:-2] module_list = module_required.split(',')\",\n \"the production environement. path : str Where to write the\",\n \"log_fail(func): \\\"\\\"\\\"Decorator to log crashes in the decorated code. Parameters\",\n \"is adopted and updated from python routine ``logging_functions.py`` written by\",\n \"a module, use: :: import os import logging from jwql.logging.logging_functions\",\n \"for line in setup: if line[0:8] == \\\"REQUIRES\\\": module_required =\",\n \"if user-supplied path; default to working dir. \\\"\\\"\\\" # Determine\",\n \"import getpass import importlib import logging import os import pwd\",\n \"code is adopted and updated from python routine ``logging_functions.py`` written\",\n \"the module list module_list = [module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ', '')\",\n \"the decorated code. Parameters ---------- func : func The function\",\n \"Where to write the log if user-supplied path; default to\",\n \"added or removed as necessary. Parameters ---------- func : func\",\n \"functools import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import\",\n \"placed in the ``utils`` directory. References ---------- This code is\",\n \"[module.split('=')[0] for module in module_list] # Log common module version\",\n \"* 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time =\",\n \"Version) Use --- To log the execution of a module,\",\n \"Returns ------- log_file : str The full path to where\",\n \"The function to decorate. Returns ------- wrapped : func The\",\n \"filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \\\"\\\"\\\"Decorator to log useful\",\n \"seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def\",\n \"production_mode=True, path='./'): \\\"\\\"\\\"Configure the log file with a standard logging\",\n \"= settings['admin_account'] log_path = settings['log_dir'] exempt_modules = [] if user\",\n \"module in module_list] module_list = [module.split('=')[0] for module in module_list]\",\n \"of modules. Log files are written to the ``logs/`` directory\",\n \"function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc()) logging.critical('CRASHED') return\",\n \"minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time = divmod(t2_time -\",\n \"%(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'):\",\n \"from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail\",\n \"# Read in setup.py file to build list of required\",\n \"Quicklook automation platform. \\\"\\\"\\\" import datetime import getpass import importlib\",\n \"wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): # Log environment\",\n \"jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = ''\",\n \"The full path to where the log file will be\",\n \"path : str Where to write the log if user-supplied\",\n \"execution of a module, use: :: import os import logging\",\n \"+ ' Path: ' + mod.__path__[0]) except ImportError as err:\",\n \"common module version information for module in module_list: try: mod\",\n \"a decorator to log user environment and system information. Future\",\n \"module_list] module_list = [module.split('=')[0] for module in module_list] # Log\",\n \"logging import os import pwd import socket import sys import\",\n \"os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module, filename) else:\",\n \"CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \\\"\\\"\\\"Decorator\",\n \"and time it t1_cpu = time.clock() t1_time = time.time() func(*a,\",\n \"we want to track can be added or removed as\",\n \"settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name) as setup:\",\n \"log_fail @log_info @log_fail def my_main_function(): pass if __name__ == '__main__':\",\n \"The wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): try: #\",\n \"set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL\",\n \"automation platform. This module provides decorators to log the execution\",\n \"60) hours_time, remainder_time = divmod(t2_time - t1_time, 60 * 60)\",\n \"= '' def configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure the log file\",\n \"named by module name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors -------\",\n \"jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config, ensure_dir_exists LOG_FILE_LOC =\",\n \"= divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed\",\n \"module = os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module,\",\n \"import traceback from functools import wraps from jwql.utils.permissions import set_permissions\",\n \"production_mode # Create the log file and set the permissions\",\n \"for module in module_list] # Log common module version information\",\n \"to. \\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user\",\n \"the module name. The name of the ``log_file`` is a\",\n \"the WFC3 Quicklook automation platform. \\\"\\\"\\\" import datetime import getpass\",\n \"path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL =\",\n \"log_file : str The full path to where the log\",\n \"wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): try: # Run\",\n \"import sys import time import traceback from functools import wraps\",\n \"by Alex Viana, 2013 for the WFC3 Quicklook automation platform.\",\n \"settings = get_config() admin_account = settings['admin_account'] log_path = settings['log_dir'] exempt_modules\",\n \"standard logging format. Parameters ---------- module : str The name\",\n \"PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create the\",\n \"the module being logged. production_mode : bool Whether or not\",\n \"= line[12:-2] module_list = module_required.split(',') # Clean up the module\",\n \"**kw): try: # Run the function func(*a, **kw) logging.info('Completed Successfully')\",\n \"of the ``log_file`` is a combination of the name of\",\n \"' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python Version: '\",\n \"minutes_cpu, seconds_cpu)) return wrapped def log_fail(func): \\\"\\\"\\\"Decorator to log crashes\",\n \"global PRODUCTION_BOOL LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create\",\n \"Clean up the module list module_list = [module.replace('\\\"', '').replace(\\\"'\\\", '').replace('\",\n \"remainder_time = divmod(t2_time - t1_time, 60 * 60) minutes_time, seconds_time\",\n \"dir. Returns ------- log_file : str The full path to\",\n \"------------ The user must have a configuration file named ``config.json``\",\n \"the ``log_file`` is a combination of the name of the\",\n \"import time import traceback from functools import wraps from jwql.utils.permissions\",\n \"path to where the log file will be written to.\",\n \"as a decorator to log user environment and system information.\",\n \"used as a decorator to log user environment and system\",\n \"------- wrapped : func The wrapped function. \\\"\\\"\\\" @wraps(func) def\",\n \"import importlib import logging import os import pwd import socket\",\n \"= log_file PRODUCTION_BOOL = production_mode # Create the log file\",\n \"err: logging.warning(err) # Call the function and time it t1_cpu\",\n \"production_mode: module = os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path,\",\n \"---------- This code is adopted and updated from python routine\",\n \"user environment and system information. Future packages we want to\",\n \"not in exempt_modules and production_mode: module = os.path.join('dev', module) if\",\n \"the log file and set the permissions logging.basicConfig(filename=log_file, format='%(asctime)s %(levelname)s:\",\n \"function and time it t1_cpu = time.clock() t1_time = time.time()\",\n \"\\\"\\\"\\\" @wraps(func) def wrapped(*a, **kw): try: # Run the function\",\n \"[module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ', '') for module in module_list] module_list\",\n \"from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions\",\n \"t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time,\",\n \"to write the log if user-supplied path; default to working\",\n \"configure_logging from jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info\",\n \"'' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure the\",\n \"the log file will be written to. \\\"\\\"\\\" timestamp =\",\n \": func The function to decorate. Returns ------- wrapped :\",\n \"logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu, seconds_cpu)) return wrapped def log_fail(func):\",\n \"user != admin_account and module not in exempt_modules and production_mode:\",\n \"os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user must have\",\n \"import wraps from jwql.utils.permissions import set_permissions from jwql.utils.utils import get_config,\",\n \"= time.clock() t2_time = time.time() # Log execution time hours_cpu,\",\n \"# Run the function func(*a, **kw) logging.info('Completed Successfully') except Exception:\",\n \"module being logged and the current datetime. Parameters ---------- module\",\n \"log the execution of modules. Log files are written to\",\n \"Viana, 2013 for the WFC3 Quicklook automation platform. \\\"\\\"\\\" import\",\n \"bool Whether or not the output should be written to\",\n \"based on the module name. The name of the ``log_file``\",\n \"= divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu, seconds_cpu =\",\n \"mod = importlib.import_module(module) logging.info(module + ' Version: ' + mod.__version__)\",\n \"module_required.split(',') # Clean up the module list module_list = [module.replace('\\\"',\",\n \"2013 for the WFC3 Quicklook automation platform. \\\"\\\"\\\" import datetime\",\n \"'').replace(\\\"'\\\", '').replace(' ', '') for module in module_list] module_list =\",\n \"``config.json`` placed in the ``utils`` directory. References ---------- This code\",\n \"updated from python routine ``logging_functions.py`` written by Alex Viana, 2013\",\n \": str The name of the module being logged. production_mode\",\n \"wrapped(*a, **kw): try: # Run the function func(*a, **kw) logging.info('Completed\",\n \"user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path\",\n \"from python routine ``logging_functions.py`` written by Alex Viana, 2013 for\",\n \"LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True, path='./'):\",\n \"as necessary. Parameters ---------- func : func The function to\",\n \"to log useful system information. This function can be used\",\n \"log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func): \\\"\\\"\\\"Decorator\",\n \"the current datetime. Parameters ---------- module : str The name\",\n \"module list module_list = [module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ', '') for\",\n \"be written to. \\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module,\",\n \"log file name based on the module name. The name\",\n \"path='./'): \\\"\\\"\\\"Configure the log file with a standard logging format.\",\n \"mod.__path__[0]) except ImportError as err: logging.warning(err) # Call the function\",\n \"import logging import os import pwd import socket import sys\",\n \"= make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global PRODUCTION_BOOL LOG_FILE_LOC =\",\n \"== \\\"REQUIRES\\\": module_required = line[12:-2] module_list = module_required.split(',') # Clean\",\n \"Logging functions for the ``jwql`` automation platform. This module provides\",\n \"the log if user-supplied path; default to working dir. Returns\",\n \"log the execution of a module, use: :: import os\",\n \"pass if __name__ == '__main__': module = os.path.basename(__file__).replace('.py', '') configure_logging(module)\",\n \"packages we want to track can be added or removed\",\n \"timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account']\",\n \"log_file def log_info(func): \\\"\\\"\\\"Decorator to log useful system information. This\",\n \"'' def configure_logging(module, production_mode=True, path='./'): \\\"\\\"\\\"Configure the log file with\",\n \"with a standard logging format. Parameters ---------- module : str\",\n \"of the name of the module being logged and the\",\n \"Returns ------- wrapped : func The wrapped function. \\\"\\\"\\\" @wraps(func)\",\n \"'') for module in module_list] module_list = [module.split('=')[0] for module\",\n \"up the module list module_list = [module.replace('\\\"', '').replace(\\\"'\\\", '').replace(' ',\",\n \"default to working dir. \\\"\\\"\\\" # Determine log file location\",\n \"the ``logs/`` directory in the ``jwql`` central storage area, named\",\n \"should be written to the production environment. path : str\",\n \"mod.__version__) logging.info(module + ' Path: ' + mod.__path__[0]) except ImportError\",\n \"Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60\",\n \"' + sys.version.replace('\\\\n', '')) logging.info('Python Executable Path: ' + sys.executable)\",\n \"= os.path.basename(__file__).replace('.py', '') configure_logging(module) my_main_function() Dependencies ------------ The user must\",\n \"WFC3 Quicklook automation platform. \\\"\\\"\\\" import datetime import getpass import\",\n \"sys.executable) # Read in setup.py file to build list of\",\n \"``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018 - <NAME>, 2013 (WFC3\",\n \"module_list] # Log common module version information for module in\",\n \"location if production_mode: log_file = make_log_file(module) else: log_file = make_log_file(module,\",\n \"information. Future packages we want to track can be added\",\n \"and module not in exempt_modules and production_mode: module = os.path.join('dev',\",\n \"filename = '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config()\",\n \"format='%(asctime)s %(levelname)s: %(message)s', datefmt='%m/%d/%Y %H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module,\",\n \"Whether or not the output should be written to the\",\n \"default to working dir. Returns ------- log_file : str The\",\n \"jwql.logging.logging_functions import log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def\",\n \"logging format. Parameters ---------- module : str The name of\",\n \"write the log if user-supplied path; default to working dir.\",\n \"------- - <NAME> 2018 - <NAME>, 2013 (WFC3 QL Version)\",\n \"- <NAME> 2018 - <NAME>, 2013 (WFC3 QL Version) Use\",\n \"wrapped : func The wrapped function. \\\"\\\"\\\" @wraps(func) def wrapped(*a,\",\n \"to the production environment. path : str Where to write\",\n \"LOG_FILE_LOC = log_file PRODUCTION_BOOL = production_mode # Create the log\",\n \"written by Alex Viana, 2013 for the WFC3 Quicklook automation\",\n \"environment. path : str Where to write the log if\",\n \"import pwd import socket import sys import time import traceback\",\n \"\\\"\\\"\\\" timestamp = datetime.datetime.now().strftime('%Y-%m-%d-%H-%M') filename = '{0}_{1}.log'.format(module, timestamp) user =\",\n \"- t1_time, 60 * 60) minutes_time, seconds_time = divmod(remainder_time, 60)\",\n \"be used as a decorator to log user environment and\",\n \"be added or removed as necessary. Parameters ---------- func :\",\n \"Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time, minutes_time, seconds_time)) logging.info('Elapsed CPU Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_cpu, minutes_cpu,\",\n \"# Log execution time hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu,\",\n \"60) minutes_time, seconds_time = divmod(remainder_time, 60) logging.info('Elapsed Real Time: {0:.0f}:{1:.0f}:{2:f}'.format(hours_time,\",\n \"required modules settings = get_config() setup_file_name = settings['setup_file'] with open(setup_file_name)\",\n \"@wraps(func) def wrapped(*a, **kw): try: # Run the function func(*a,\",\n \"not the output should be written to the production environement.\",\n \"= os.path.join('dev', module) if production_mode: log_file = os.path.join(log_path, module, filename)\",\n \"information logging.info('User: ' + getpass.getuser()) logging.info('System: ' + socket.gethostname()) logging.info('Python\",\n \"make_log_file(module) else: log_file = make_log_file(module, production_mode=False, path=path) global LOG_FILE_LOC global\",\n \"log_info from jwql.logging.logging_functions import log_fail @log_info @log_fail def my_main_function(): pass\",\n \"hours_cpu, remainder_cpu = divmod(t2_cpu - t1_cpu, 60 * 60) minutes_cpu,\",\n \"Path: ' + sys.executable) # Read in setup.py file to\",\n \"track can be added or removed as necessary. Parameters ----------\",\n \"adopted and updated from python routine ``logging_functions.py`` written by Alex\",\n \"else: log_file = os.path.join(path, filename) ensure_dir_exists(os.path.dirname(log_file)) return log_file def log_info(func):\",\n \"exempt_modules = [] if user != admin_account and module not\",\n \"%H:%M:%S %p', level=logging.INFO) set_permissions(log_file) def make_log_file(module, production_mode=True, path='./'): \\\"\\\"\\\"Create the\",\n \"of required modules settings = get_config() setup_file_name = settings['setup_file'] with\",\n \"except ImportError as err: logging.warning(err) # Call the function and\",\n \"- t1_cpu, 60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60)\",\n \"Run the function func(*a, **kw) logging.info('Completed Successfully') except Exception: logging.critical(traceback.format_exc())\",\n \"60 * 60) minutes_cpu, seconds_cpu = divmod(remainder_cpu, 60) hours_time, remainder_time\",\n \"settings['log_dir'] exempt_modules = [] if user != admin_account and module\",\n \"\\\"\\\"\\\" # Determine log file location if production_mode: log_file =\",\n \"the ``utils`` directory. References ---------- This code is adopted and\",\n \"written to the production environment. path : str Where to\",\n \"to log user environment and system information. Future packages we\",\n \"with open(setup_file_name) as setup: for line in setup: if line[0:8]\",\n \"module_required = line[12:-2] module_list = module_required.split(',') # Clean up the\",\n \"def wrapped(*a, **kw): try: # Run the function func(*a, **kw)\",\n \"wrapped def log_fail(func): \\\"\\\"\\\"Decorator to log crashes in the decorated\",\n \"path='./'): \\\"\\\"\\\"Create the log file name based on the module\",\n \"``log_file`` is a combination of the name of the module\",\n \"setup: for line in setup: if line[0:8] == \\\"REQUIRES\\\": module_required\",\n \": str The full path to where the log file\",\n \"module not in exempt_modules and production_mode: module = os.path.join('dev', module)\",\n \"to build list of required modules settings = get_config() setup_file_name\",\n \"log_path = settings['log_dir'] exempt_modules = [] if user != admin_account\",\n \"to working dir. \\\"\\\"\\\" # Determine log file location if\",\n \"ensure_dir_exists LOG_FILE_LOC = '' PRODUCTION_BOOL = '' def configure_logging(module, production_mode=True,\",\n \"name and timestamp, e.g. ``monitor_filesystem/monitor_filesystem_2018-06-20-15:22:51.log`` Authors ------- - <NAME> 2018\",\n \"module_list = [module.split('=')[0] for module in module_list] # Log common\",\n \"= '{0}_{1}.log'.format(module, timestamp) user = pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account\",\n \"setup.py file to build list of required modules settings =\",\n \"= pwd.getpwuid(os.getuid()).pw_name settings = get_config() admin_account = settings['admin_account'] log_path =\",\n \"func The function to decorate. Returns ------- wrapped : func\",\n \"environment and system information. Future packages we want to track\",\n \"import os import pwd import socket import sys import time\",\n \"code. Parameters ---------- func : func The function to decorate.\"\n]","isConversational":false}}},{"rowIdx":398,"cells":{"ngram":{"kind":"list like","value":["typing import Optional session: Optional[ClientSession] = None __all__ = (session,)","from typing import Optional session: Optional[ClientSession] = None __all__ =","from aiohttp import ClientSession from typing import Optional session: Optional[ClientSession]","aiohttp import ClientSession from typing import Optional session: Optional[ClientSession] =","import ClientSession from typing import Optional session: Optional[ClientSession] = None","ClientSession from typing import Optional session: Optional[ClientSession] = None __all__"],"string":"[\n \"typing import Optional session: Optional[ClientSession] = None __all__ = (session,)\",\n \"from typing import Optional session: Optional[ClientSession] = None __all__ =\",\n \"from aiohttp import ClientSession from typing import Optional session: Optional[ClientSession]\",\n \"aiohttp import ClientSession from typing import Optional session: Optional[ClientSession] =\",\n \"import ClientSession from typing import Optional session: Optional[ClientSession] = None\",\n \"ClientSession from typing import Optional session: Optional[ClientSession] = None __all__\"\n]","isConversational":false}}},{"rowIdx":399,"cells":{"ngram":{"kind":"list like","value":["_md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb')","= open(path, 'rb') if start > 0: fh.seek(start) if stop","os.path.getsize(path) pos = start while pos < stop: size =","= start while pos < stop: size = min(CHUNK, stop","break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384()","= fh.read(size) if not chunk: break pos += len(chunk) _md5.update(chunk)","& 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh","fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh =","GPLv3 license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import","fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def","if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path):","_sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh","_sha384 = hashlib.sha384() fh = open(path, 'rb') while True: chunk","return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh = open(path,","chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return","def sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb') while","if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path):","chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def","stop == -1: stop = os.path.getsize(path) pos = start while","hashlib.sha256() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)","while True: chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk)","0: fh.seek(start) if stop == -1: stop = os.path.getsize(path) pos","chunk = fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk,","start > 0: fh.seek(start) if stop == -1: stop =","= hashlib.sha224() fh = open(path, 'rb') while True: chunk =","_sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh","= hashlib.sha256() fh = open(path, 'rb') while True: chunk =","start while pos < stop: size = min(CHUNK, stop -","= fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest()","= fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk, _crc)","crc(path): _crc = 0 fh = open(path, 'rb') while True:","LiuLang <<EMAIL>> # Use of this source code is governed","break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512()","fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh =","stop - pos) chunk = fh.read(size) if not chunk: break","# Use of this source code is governed by GPLv3","def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh = open(path,","= os.path.getsize(path) pos = start while pos < stop: size","if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path):","2 ** 20 def crc(path): _crc = 0 fh =","start=0, stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb') if","_sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb')","_sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb')","hashlib.sha512() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)","hashlib.sha384() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)","zlib CHUNK = 2 ** 20 def crc(path): _crc =","return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh = open(path,","= fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest()","_crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF) def md5(path,","= min(CHUNK, stop - pos) chunk = fh.read(size) if not","while True: chunk = fh.read(CHUNK) if not chunk: break _crc","open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk:","return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh = open(path,","sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb') while True:","break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224()","not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X'","import zlib CHUNK = 2 ** 20 def crc(path): _crc","not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224","chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return","20 def crc(path): _crc = 0 fh = open(path, 'rb')","not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256","(_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5()","= 0 fh = open(path, 'rb') while True: chunk =","Use of this source code is governed by GPLv3 license","def sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb') while","sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb') while True:","chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return","# in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK","len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1()","True: chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close()","fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh =","def sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb') while","not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384","_crc = 0 fh = open(path, 'rb') while True: chunk","os import zlib CHUNK = 2 ** 20 def crc(path):","_sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh","pos) chunk = fh.read(size) if not chunk: break pos +=","fh.seek(start) if stop == -1: stop = os.path.getsize(path) pos =","= fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest()","while pos < stop: size = min(CHUNK, stop - pos)","def sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb') while","chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 =","pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1","fh.close() return '%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0,","while True: chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk)","chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return","= zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF)","<<EMAIL>> # Use of this source code is governed by","return '%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1):","break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path):","source code is governed by GPLv3 license that can be","True: chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close()","sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb') while True:","-1: stop = os.path.getsize(path) pos = start while pos <","chunk = fh.read(size) if not chunk: break pos += len(chunk)","sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb') while True:","if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path):","chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X' %","_sha224 = hashlib.sha224() fh = open(path, 'rb') while True: chunk","break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256()","# Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of this","= fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close() return _sha512.hexdigest()","def crc(path): _crc = 0 fh = open(path, 'rb') while","pos = start while pos < stop: size = min(CHUNK,","stop: size = min(CHUNK, stop - pos) chunk = fh.read(size)","_sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb')","'%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5","_md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh","while True: chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk)","= 2 ** 20 def crc(path): _crc = 0 fh","= fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest()","is governed by GPLv3 license that can be found #","fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close()","fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def","% (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 =","== -1: stop = os.path.getsize(path) pos = start while pos","_sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb')","while True: chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk)","be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import","in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK =","md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb')","this source code is governed by GPLv3 license that can","open(path, 'rb') if start > 0: fh.seek(start) if stop ==","'rb') while True: chunk = fh.read(CHUNK) if not chunk: break","import hashlib import os import zlib CHUNK = 2 **","CHUNK = 2 ** 20 def crc(path): _crc = 0","_sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh","if not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return","break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc","+= len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 =","return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh = open(path,","return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh = open(path,","= open(path, 'rb') while True: chunk = fh.read(CHUNK) if not","that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import","hashlib.md5() fh = open(path, 'rb') if start > 0: fh.seek(start)","code is governed by GPLv3 license that can be found","chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 =","True: chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close()","= hashlib.sha384() fh = open(path, 'rb') while True: chunk =","chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 =","stop = os.path.getsize(path) pos = start while pos < stop:","chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close() return","_sha256 = hashlib.sha256() fh = open(path, 'rb') while True: chunk","hashlib import os import zlib CHUNK = 2 ** 20","sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb') while True:","= hashlib.sha1() fh = open(path, 'rb') while True: chunk =","True: chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close()","True: chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close()","= hashlib.md5() fh = open(path, 'rb') if start > 0:","governed by GPLv3 license that can be found # in","if stop == -1: stop = os.path.getsize(path) pos = start","can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os","by GPLv3 license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html","not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512","_md5 = hashlib.md5() fh = open(path, 'rb') if start >","fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh =","fh.read(size) if not chunk: break pos += len(chunk) _md5.update(chunk) fh.close()","while True: chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk)","(C) 2014-2015 LiuLang <<EMAIL>> # Use of this source code","'rb') if start > 0: fh.seek(start) if stop == -1:","Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of this source","- pos) chunk = fh.read(size) if not chunk: break pos","True: chunk = fh.read(CHUNK) if not chunk: break _crc =","hashlib.sha1() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)","< stop: size = min(CHUNK, stop - pos) chunk =","zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF) def","import os import zlib CHUNK = 2 ** 20 def","fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh =","0 fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)","chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 =","_crc = zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc &","2014-2015 LiuLang <<EMAIL>> # Use of this source code is","found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib","not chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest()","_sha1 = hashlib.sha1() fh = open(path, 'rb') while True: chunk","size = min(CHUNK, stop - pos) chunk = fh.read(size) if","pos < stop: size = min(CHUNK, stop - pos) chunk","min(CHUNK, stop - pos) chunk = fh.read(size) if not chunk:","_sha512 = hashlib.sha512() fh = open(path, 'rb') while True: chunk","** 20 def crc(path): _crc = 0 fh = open(path,","stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb') if start","http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK = 2","fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if","hashlib.sha224() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)","= hashlib.sha512() fh = open(path, 'rb') while True: chunk =","<gh_stars>0 # Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of","0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh =","of this source code is governed by GPLv3 license that","fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def","fh = open(path, 'rb') if start > 0: fh.seek(start) if","> 0: fh.seek(start) if stop == -1: stop = os.path.getsize(path)","if start > 0: fh.seek(start) if stop == -1: stop","if not chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return","license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib","fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def","def sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb') while"],"string":"[\n \"_md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb')\",\n \"= open(path, 'rb') if start > 0: fh.seek(start) if stop\",\n \"os.path.getsize(path) pos = start while pos < stop: size =\",\n \"= start while pos < stop: size = min(CHUNK, stop\",\n \"break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384()\",\n \"= fh.read(size) if not chunk: break pos += len(chunk) _md5.update(chunk)\",\n \"& 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh\",\n \"fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh =\",\n \"GPLv3 license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import\",\n \"fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def\",\n \"if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path):\",\n \"_sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh\",\n \"_sha384 = hashlib.sha384() fh = open(path, 'rb') while True: chunk\",\n \"return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh = open(path,\",\n \"chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return\",\n \"def sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb') while\",\n \"if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path):\",\n \"chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def\",\n \"stop == -1: stop = os.path.getsize(path) pos = start while\",\n \"hashlib.sha256() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)\",\n \"while True: chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk)\",\n \"0: fh.seek(start) if stop == -1: stop = os.path.getsize(path) pos\",\n \"chunk = fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk,\",\n \"start > 0: fh.seek(start) if stop == -1: stop =\",\n \"= hashlib.sha224() fh = open(path, 'rb') while True: chunk =\",\n \"_sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh\",\n \"= hashlib.sha256() fh = open(path, 'rb') while True: chunk =\",\n \"start while pos < stop: size = min(CHUNK, stop -\",\n \"= fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest()\",\n \"= fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk, _crc)\",\n \"crc(path): _crc = 0 fh = open(path, 'rb') while True:\",\n \"LiuLang <<EMAIL>> # Use of this source code is governed\",\n \"break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512()\",\n \"fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh =\",\n \"stop - pos) chunk = fh.read(size) if not chunk: break\",\n \"# Use of this source code is governed by GPLv3\",\n \"def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh = open(path,\",\n \"= os.path.getsize(path) pos = start while pos < stop: size\",\n \"if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path):\",\n \"2 ** 20 def crc(path): _crc = 0 fh =\",\n \"start=0, stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb') if\",\n \"_sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb')\",\n \"_sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb')\",\n \"hashlib.sha512() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)\",\n \"hashlib.sha384() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)\",\n \"zlib CHUNK = 2 ** 20 def crc(path): _crc =\",\n \"return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh = open(path,\",\n \"= fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest()\",\n \"_crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF) def md5(path,\",\n \"= min(CHUNK, stop - pos) chunk = fh.read(size) if not\",\n \"while True: chunk = fh.read(CHUNK) if not chunk: break _crc\",\n \"open(path, 'rb') while True: chunk = fh.read(CHUNK) if not chunk:\",\n \"return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh = open(path,\",\n \"sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb') while True:\",\n \"break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224()\",\n \"not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X'\",\n \"import zlib CHUNK = 2 ** 20 def crc(path): _crc\",\n \"not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224\",\n \"chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return\",\n \"20 def crc(path): _crc = 0 fh = open(path, 'rb')\",\n \"not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256\",\n \"(_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5()\",\n \"= 0 fh = open(path, 'rb') while True: chunk =\",\n \"Use of this source code is governed by GPLv3 license\",\n \"def sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb') while\",\n \"sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb') while True:\",\n \"chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return\",\n \"# in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK\",\n \"len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1()\",\n \"True: chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close()\",\n \"fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh =\",\n \"def sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb') while\",\n \"not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384\",\n \"_crc = 0 fh = open(path, 'rb') while True: chunk\",\n \"os import zlib CHUNK = 2 ** 20 def crc(path):\",\n \"_sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh\",\n \"pos) chunk = fh.read(size) if not chunk: break pos +=\",\n \"fh.seek(start) if stop == -1: stop = os.path.getsize(path) pos =\",\n \"= fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest()\",\n \"while pos < stop: size = min(CHUNK, stop - pos)\",\n \"def sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb') while\",\n \"chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path): _sha224 =\",\n \"pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1\",\n \"fh.close() return '%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0,\",\n \"while True: chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk)\",\n \"chunk = fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return\",\n \"= zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF)\",\n \"<<EMAIL>> # Use of this source code is governed by\",\n \"return '%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1):\",\n \"break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path):\",\n \"source code is governed by GPLv3 license that can be\",\n \"True: chunk = fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close()\",\n \"sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb') while True:\",\n \"-1: stop = os.path.getsize(path) pos = start while pos <\",\n \"chunk = fh.read(size) if not chunk: break pos += len(chunk)\",\n \"sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb') while True:\",\n \"if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def sha224(path):\",\n \"chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X' %\",\n \"_sha224 = hashlib.sha224() fh = open(path, 'rb') while True: chunk\",\n \"break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256()\",\n \"# Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of this\",\n \"= fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close() return _sha512.hexdigest()\",\n \"def crc(path): _crc = 0 fh = open(path, 'rb') while\",\n \"pos = start while pos < stop: size = min(CHUNK,\",\n \"stop: size = min(CHUNK, stop - pos) chunk = fh.read(size)\",\n \"_sha384.hexdigest() def sha512(path): _sha512 = hashlib.sha512() fh = open(path, 'rb')\",\n \"'%X' % (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5\",\n \"_md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh\",\n \"while True: chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk)\",\n \"= 2 ** 20 def crc(path): _crc = 0 fh\",\n \"= fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest()\",\n \"is governed by GPLv3 license that can be found #\",\n \"fh.read(CHUNK) if not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close()\",\n \"fh.read(CHUNK) if not chunk: break _sha1.update(chunk) fh.close() return _sha1.hexdigest() def\",\n \"% (_crc & 0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 =\",\n \"== -1: stop = os.path.getsize(path) pos = start while pos\",\n \"_sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh = open(path, 'rb')\",\n \"while True: chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk)\",\n \"be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import\",\n \"in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK =\",\n \"md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb')\",\n \"this source code is governed by GPLv3 license that can\",\n \"open(path, 'rb') if start > 0: fh.seek(start) if stop ==\",\n \"'rb') while True: chunk = fh.read(CHUNK) if not chunk: break\",\n \"import hashlib import os import zlib CHUNK = 2 **\",\n \"CHUNK = 2 ** 20 def crc(path): _crc = 0\",\n \"_sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh\",\n \"if not chunk: break _crc = zlib.crc32(chunk, _crc) fh.close() return\",\n \"break _crc = zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc\",\n \"+= len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest() def sha1(path): _sha1 =\",\n \"return _sha1.hexdigest() def sha224(path): _sha224 = hashlib.sha224() fh = open(path,\",\n \"return _sha256.hexdigest() def sha384(path): _sha384 = hashlib.sha384() fh = open(path,\",\n \"= open(path, 'rb') while True: chunk = fh.read(CHUNK) if not\",\n \"that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import\",\n \"hashlib.md5() fh = open(path, 'rb') if start > 0: fh.seek(start)\",\n \"code is governed by GPLv3 license that can be found\",\n \"chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def sha256(path): _sha256 =\",\n \"True: chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close()\",\n \"= hashlib.sha384() fh = open(path, 'rb') while True: chunk =\",\n \"chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512 =\",\n \"stop = os.path.getsize(path) pos = start while pos < stop:\",\n \"chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close() return\",\n \"_sha256 = hashlib.sha256() fh = open(path, 'rb') while True: chunk\",\n \"hashlib import os import zlib CHUNK = 2 ** 20\",\n \"sha256(path): _sha256 = hashlib.sha256() fh = open(path, 'rb') while True:\",\n \"= hashlib.sha1() fh = open(path, 'rb') while True: chunk =\",\n \"True: chunk = fh.read(CHUNK) if not chunk: break _sha256.update(chunk) fh.close()\",\n \"True: chunk = fh.read(CHUNK) if not chunk: break _sha512.update(chunk) fh.close()\",\n \"= hashlib.md5() fh = open(path, 'rb') if start > 0:\",\n \"governed by GPLv3 license that can be found # in\",\n \"if stop == -1: stop = os.path.getsize(path) pos = start\",\n \"can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os\",\n \"by GPLv3 license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html\",\n \"not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def sha512(path): _sha512\",\n \"_md5 = hashlib.md5() fh = open(path, 'rb') if start >\",\n \"fh.close() return _md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh =\",\n \"fh.read(size) if not chunk: break pos += len(chunk) _md5.update(chunk) fh.close()\",\n \"while True: chunk = fh.read(CHUNK) if not chunk: break _sha224.update(chunk)\",\n \"(C) 2014-2015 LiuLang <<EMAIL>> # Use of this source code\",\n \"'rb') if start > 0: fh.seek(start) if stop == -1:\",\n \"Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of this source\",\n \"- pos) chunk = fh.read(size) if not chunk: break pos\",\n \"True: chunk = fh.read(CHUNK) if not chunk: break _crc =\",\n \"hashlib.sha1() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)\",\n \"< stop: size = min(CHUNK, stop - pos) chunk =\",\n \"zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc & 0xFFFFFFFF) def\",\n \"import os import zlib CHUNK = 2 ** 20 def\",\n \"fh.close() return _sha224.hexdigest() def sha256(path): _sha256 = hashlib.sha256() fh =\",\n \"0 fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)\",\n \"chunk: break _sha256.update(chunk) fh.close() return _sha256.hexdigest() def sha384(path): _sha384 =\",\n \"_crc = zlib.crc32(chunk, _crc) fh.close() return '%X' % (_crc &\",\n \"2014-2015 LiuLang <<EMAIL>> # Use of this source code is\",\n \"found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib\",\n \"not chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return _md5.hexdigest()\",\n \"_sha1 = hashlib.sha1() fh = open(path, 'rb') while True: chunk\",\n \"size = min(CHUNK, stop - pos) chunk = fh.read(size) if\",\n \"pos < stop: size = min(CHUNK, stop - pos) chunk\",\n \"min(CHUNK, stop - pos) chunk = fh.read(size) if not chunk:\",\n \"_sha512 = hashlib.sha512() fh = open(path, 'rb') while True: chunk\",\n \"** 20 def crc(path): _crc = 0 fh = open(path,\",\n \"stop=-1): _md5 = hashlib.md5() fh = open(path, 'rb') if start\",\n \"http://www.gnu.org/licenses/gpl-3.0.html import hashlib import os import zlib CHUNK = 2\",\n \"fh = open(path, 'rb') while True: chunk = fh.read(CHUNK) if\",\n \"hashlib.sha224() fh = open(path, 'rb') while True: chunk = fh.read(CHUNK)\",\n \"= hashlib.sha512() fh = open(path, 'rb') while True: chunk =\",\n \"<gh_stars>0 # Copyright (C) 2014-2015 LiuLang <<EMAIL>> # Use of\",\n \"0xFFFFFFFF) def md5(path, start=0, stop=-1): _md5 = hashlib.md5() fh =\",\n \"of this source code is governed by GPLv3 license that\",\n \"fh.read(CHUNK) if not chunk: break _sha384.update(chunk) fh.close() return _sha384.hexdigest() def\",\n \"fh = open(path, 'rb') if start > 0: fh.seek(start) if\",\n \"> 0: fh.seek(start) if stop == -1: stop = os.path.getsize(path)\",\n \"if start > 0: fh.seek(start) if stop == -1: stop\",\n \"if not chunk: break pos += len(chunk) _md5.update(chunk) fh.close() return\",\n \"license that can be found # in http://www.gnu.org/licenses/gpl-3.0.html import hashlib\",\n \"fh.read(CHUNK) if not chunk: break _sha224.update(chunk) fh.close() return _sha224.hexdigest() def\",\n \"def sha384(path): _sha384 = hashlib.sha384() fh = open(path, 'rb') while\"\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":3,"numItemsPerPage":100,"numTotalItems":12866649,"offset":300,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3NTI3NTU1MCwic3ViIjoiL2RhdGFzZXRzL3RlcnJ5eXovc3RhcmNvZGVyZGF0YV9uZ3JhbV8xMCIsImV4cCI6MTc3NTI3OTE1MCwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.wq2g7XuJGud8MwUwx0oOjrcdFm6Jgd9H33F0TWBV499Ugu6bvHuZEXImTzv2NNFDVz8872y49jUDvFs5sjO7AQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":12866649,"numBytesParquet":126831957853}]},"discussionsStats":{"closed":0,"open":0,"total":0},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
ngram listlengths 0 82k |
|---|
[
"# все транзакты Terminate(sgm, label=\"to_term\", deltaTerminate=0) # ЗАПУСК ---------------------- m.start(terminationCount=MAX_TIME,",
"MAX_TIME = 20 # list_all_transact = [] # MAX_TIME =",
"t[k]) for k in t.keys() if k in [TIME_CREATED, TERMINATED_TIME]])",
"self.assertNotIn(F_1, t[FACILITY])) # Terminate... |
[
"compute_gradients(self, samples): \"\"\"Returns critic, actor gradients.\"\"\" return self.model.compute_gradients(samples) def apply_gradients(self,",
"samples): \"\"\"Returns critic, actor gradients.\"\"\" return self.model.compute_gradients(samples) def apply_gradients(self, grads):",
"gradients.\"\"\" retu... |
[
"e.g. hosts or switches. And the connections between them. '''",
"List[dict] ''' return self._vertexes.hosts + self._vertexes.switches @property def switches(self): '''",
"''' Draw a dot graph of the network graph. :params",
"contains the entities in the network e.g. hosts or switches.",
"graphargs: Argumen... |
[
"for idx, (blobs, color, title) in enumerate(sequence): ax[idx].set_title(title) ax[idx].imshow(image) for",
"axes.ravel() for idx, (blobs, color, title) in enumerate(sequence): ax[idx].set_title(title) ax[idx].imshow(image)",
"'Determinant of Hessian'] sequence = zip(blobs_list, colors, titles) fig, axes",
"... |
[
"value): if value in listofnames: value_index = listofnames.index(value) return(listofnames, value_index)",
"value in listofnames: value_index = listofnames.index(value) return(listofnames, value_index) else: return(-1)",
"if value in listofnames: value_index = listofnames.index(value) return(listofnames, value... |
[
"1 def move(self): new_x = self.xcor() + SPEED*self.x_bounce new_y =",
"self.move_speed = 0.1 self.y_bounce = 1 self.x_bounce = 1 def",
"= 10 class Ball(Turtle): def __init__(self): super().__init__() self.penup() self.color(\"white\") self.shape(\"circle\")",
"def move(self): new_x = self.xcor() + SPEED*self... |
[
"self.term class TreeInnerNode(TreeNode): def __init__(self, pred, left, right): self.pred =",
"pred, left, right): self.pred = pred self.left = left self.right",
"getExpr(self): return self.term class TreeInnerNode(TreeNode): def __init__(self, pred, left, right):",
"class TreeNode: pass class TreeLeaf(TreeN... |
[
"base ring as well. zeta = self._zeta if zeta_order is",
"\\frac{B_{k,\\varepsilon}}{k!} t^k. ALGORITHM: The ``'recurrence'`` algorithm computes generalized Bernoulli numbers",
"fixed:: sage: G = DirichletGroup(1) sage: chi = G.one() sage:",
"sum associated to `\\chi` is .. MATH:: g_a(\\chi) = \\sum_{r",
"t... |
[
"write(self, file): \"\"\" Write the contents of this :class:`File` object",
"Base class for all line based text files. When reading",
"name if isinstance(file, str): with open(file, \"r\") as f: while",
"file (or file-like object). Parameters ---------- file_name : file-like object",
"isinstance(file, str)... |
[
"if res.status_code == 200: logger.info(\"%r sent, FCM id: %r\", pnt,",
"prepared push notification translation to be sent :type pnt: ~cms.models.push_notifications.push_notification_translation.PushNotificationTranslation",
").slug # Testumgebung - prevent sending PNs to actual users",
"\"\"\" status = True ... |
[
"decription: CREATE ASC INDEX # # Dependencies: # CREATE DATABASE",
"id: functional.index.create.03 # title: CREATE ASC INDEX # decription: CREATE",
"# resources: None substitutions_1 = [] init_script_1 = \"\"\"CREATE TABLE",
"from firebird.qa import db_factory, isql_act, Action # version: 1.0 #",
"substitu... |
[
"information about the pare we are refering, index, items per",
"contains information about the pare we are refering, index, items",
"are refering, index, items per page, etc. \"\"\" page_index =",
"we are refering, index, items per page, etc. \"\"\" page_index",
"Page object file \"\"\" class Page(): \"\"\... |
[
"# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law",
"get_names(): return list(__factory.keys()) def init_dataset(name, *args, **kwargs): if name not",
"# # Licensed under the Apache License, Version 2.0 (the",
"compliance with the License. # You may obtain a copy",
"an \"... |
[
"Decrease in Profits: {minmonth} (${minpl})\\\")\\n\" ] }, { \"cell_type\": \"code\",",
"\"print(f\\\"Total Months: {n_months}\\\")\\n\", \"print(f\\\"Total: ${round(pl_total,2)}\\\")\\n\", \"print(f\\\"Average Change: ${round(avg_pl_change,2)}\\\")\\n\", \"print(f\\\"Greatest Increase",
"for max and min PL cha... |
[
"@dll_import('OleAut32') def VariantInit( pvarg : POINTER(VARIANT) ) -> None: ...",
"..wintypes import VARIANT, dll_import @dll_import('OleAut32') def VariantInit( pvarg : POINTER(VARIANT)",
"from ctypes import POINTER, Structure from ..wintypes import VARIANT, dll_import",
"VARIANT, dll_import @dll_import('O... |
[
".models import EventTypeDescriptor from .models import ExternalConfigurationDescriptor from .models import",
"from .models import EventTypeDescriptor from .models import ExternalConfigurationDescriptor from .models",
"will be lost if the code is regenerated. # --------------------------------------------------... |
[
"def __init__(self): global __logger if self.__logger: raise RuntimeError(\"Logger instance already",
"\"INFO\") def log_warning(self, warning): self.__log(warning, \"WARNING\") def log_error(self, error): self.__log(error,",
"instance already exists\") @staticmethod def get_logger(): global __logger if not",
... |
[
"give unique orientations when the # Burgers transformation is applied",
"cubic_syms = Quat.symEqv(\"cubic\") # subset of cubic symmetries that give",
"unq_hex_syms = [ hex_syms[0], hex_syms[5], hex_syms[4], hex_syms[2], hex_syms[10], hex_syms[11] ]",
"the # Burgers transformation is applied unq_hex_syms = [ ... |
[] |
[
"required\" })), 400 if not VALIDATOR.username_exists(username): return jsonify({ \"status\": 404,",
"auth_token = user.generate_auth_token(username) return make_response(jsonify({ \"status\": 200, \"message\": 'Logged in",
"not email or not email.split(): return make_response(jsonify({ \"status\": 400, \"messa... |
[
"(UnitsContainer) from pint.converters import (ScaleConverter, OffsetConverter) from pint.definitions import (Definition,",
")) self.assertEqual(x.symbol, 'k') self.assertEqual(x.converter.to_reference(1000), 1) self.assertEqual(x.converter.from_reference(.001), 1) def test_baseunit_definition(self): x",
"impor... |
[
"# Check if there is a valid signature for the",
"A PARTICULAR PURPOSE AND # NONINFRINGEMENT. IN NO EVENT SHALL",
"CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN # ACTION",
"this software and associated documentation files # (the \"Software\"), to",
"# KSK-2010: dns.rrset.from_text('.', 15202, 'IN', 'DNSK... |
[
"= Enum(\"D3D11_RTV_DIMENSION\", [ \"D3D11_RTV_DIMENSION_UNKNOWN\", \"D3D11_RTV_DIMENSION_BUFFER\", \"D3D11_RTV_DIMENSION_TEXTURE1D\", \"D3D11_RTV_DIMENSION_TEXTURE1DARRAY\", \"D3D11_RTV_DIMENSION_TEXTURE2D\", \"D3D11_RTV_DIMENSION_TEXTURE2DARRAY\", \"D3D11_RTV_DIMENSION_TEXTURE2DMS\",",
"Struct(\"D3D11_TEX2DMS_D... |
[
"op == 'nop': index += 1 if op == 'acc':",
"result(input_): # Part 1 part_one = boot(input_)[1] # Part 2",
"all_seqs.append(seq) if value[:3] == 'jmp': seq = deepcopy(list_) seq[idx] =",
"== 'nop': seq = deepcopy(list_) seq[idx] = 'jmp' + value[3:]",
"from copy import deepcopy def boot(seq): index = 0 playe... |
[
"lr = tf.train.exponential_decay(0.001, global_step, 10000, 0.8, staircase=True) #lr = tf.constant(0.001,",
"samples=input_data.get_images_labels(tfRecorf_dir,num_classes,66, crop_size=[224,224], batch_size=4) batch_queue = slim.prefetch_queue.prefetch_queue(samples, capacity=128 ) tra_batch =",
"@author: LiHon... |
[
"Python :: 3.8', 'Topic :: System', 'Topic :: System ::",
":: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language",
"long_description=codecs.open('README.rst', 'r', encoding='utf-8', errors='ignore').read(), keywords='file libmagic magic infer numbers magicnumbers",
"dependencies.', long_desc... |
[
"templates from netmiko import ConnectHandler import json user = 'ntc'",
"dicts print (type(sh_ip_int_br[0])) for each_dict in sh_ip_int_br: print \"\\n\" for",
"if type(value) is list: print key + \" is \"",
"value: print list_entry if type(value) is str: print key +",
"'config_register': '0x2102', 'hardwa... |
[
"JWT passed to your App Engine app by Identity-Aware Proxy.",
"a public key from the list published by Identity-Aware Proxy,",
"found'.format(key_id)) return key # Used to cache the Identity-Aware Proxy",
"Cloud project. Returns: (user_id, user_email, error_str). \"\"\" expected_audience = '/projects/{}/apps/... |
[
"self.txt ) def compute(self): try: self.txt = str(eval(self.txt.replace(\"x\",\"*\"))) self.aff.set( self.txt",
"self.compute() elif key in [\"Delete\",\"Backspace\"]: self.clean() #-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/-/ def press(self,val): self.txt",
"# and execute it in a pywebview i... |
[
"return (x-3)*(x+2)*x*0.2 g = Graph(800,600,8,6, 'example1.svg') g.bg() g.grid() g.axes() g.graph(func)",
"g = Graph(800,600,8,6, 'example1.svg') g.bg() g.grid() g.axes() g.graph(func) g.save() g.display()",
"from giraphics.graphing.graph import Graph def func(x): return (x-3)*(x+2)*x*0.2 g =",
"<filename>res... |
[
"for i in range(0,df.shape[0]): for j in range(0,df['num'][i]): poly=json.loads(df['polygon'][i]) GeoFunc.normData(poly,scale[index])",
"name=[\"ga\",\"albano\",\"blaz1\",\"blaz2\",\"dighe1\",\"dighe2\",\"fu\",\"han\",\"jakobs1\",\"jakobs2\",\"mao\",\"marques\",\"shapes\",\"shirts\",\"swim\",\"trousers\"] print(\... |
[
"import collect_hierarchical_module_name, collect_hierarchical_parameter_name, get_batch_n, to_value, \\ # safe_lookup, len_batch from",
"\\ # safe_lookup, len_batch from .export import as_image_ui8, as_rgb_image, export_image,",
"# safe_lookup, len_batch from .export import as_image_ui8, as_rgb_image, export_i... |
[
"from tqdm import tqdm from pathos.multiprocessing import ProcessingPool as Pool",
"with Pool(opt_threads) as p: pool_results = list(tqdm(p.imap(pool_worker, pool_items), total=len(fp_items), desc=desc))",
"range(20): im = cv.blur(im, (35,35)) return result # end pool",
"default=(None, None), help='Slice list... |
[
"<filename>src/learndash/api_resources/user.py import learndash from learndash.api_resources.abstract import ListableAPIResource from learndash.api_resources.abstract import",
"User(RetrievableAPIResource[UserDict], ListableAPIResource[UserDict]): api_path = learndash.path_users def course_progress(self, id=None)... |
[
"subclasses.\"\"\" self.app_info = app_info self.resolver_kwds = kwds def _get_config_option(self, key,",
"getattr(self.app_info, key) else: return default @abstractmethod def resolve(self, enabled_container_types, tool_info,",
"argument is a :class:`galaxy.tool_util.deps.containers.ToolInfo` description of the... |
[
"file_names: df: pd.DataFrame = pd.read_csv(f'{SRC_DIR}/{file_name}').set_index('EyeTrackerTimestamp').sort_index()[ ['GazePointX (ADCSpx)', 'GazePointY (ADCSpx)', 'PupilLeft',",
"python3 import glob import os import pandas as pd import",
"df['d'] = (df['dl'] + df['dr']) / 2 # start with",
"to ms df['t'] = (d... |
[
"and ('learning_rate' in data.columns): sortedData=data.sort_values(by=\"epochs\", axis=0, ascending=True) epoch=np.array(sortedData['epochs']) trainLoss=np.array(sortedData['trainLoss']) valLoss=np.array(sortedData['valLoss'])",
"DIRECTORIES containing non-hidden files ending in FILENAME def getDataDirectories(D... |
[
"char in dic: stack.append(char) elif stack and dic.get(stack[-1])!=char: return False",
"in dic: stack.append(char) elif stack and dic.get(stack[-1])!=char: return False else:",
"elif stack and dic.get(stack[-1])!=char: return False else: stack.pop() continue return",
"[] dic = {'{':'}','[':']','(':')'} for ... |
[
"None: info = _ConcatInfo() self._cache[path] = info with open(path, 'r')",
"yaml.load(fp) info.files = config.get('files', []) info.delim = config.get('delim', \"\\n\") info.timestamp",
"getDependencies(self, path): info = self._load(path) return info.files def getOutputFilenames(self, filename):",
"import l... |
[
"CellPressed(Event): def __init__(self, position): self.position = position def get_position(self): return",
"import Event class CellPressed(Event): def __init__(self, position): self.position = position",
"from src.events import Event class CellPressed(Event): def __init__(self, position): self.position",
"E... |
[
"discriminator value allowed for non-b jets minBDiscBJets = cms.double(1.0), maxBDiscLightJets",
"useBTagging = cms.bool(False), ## choose algorithm for b-tagging bTagAlgorithm =",
"as cms # # module to make the MaxSumPtWMass jet",
"jets and ## maximum b discriminator value allowed for non-b",
"b-tagging tw... |
[
"#-*- coding:utf-8 -*- __all__ = [\"args\", \"colors\", \"libcolors\", \"routine\"] __version__",
"-*- __all__ = [\"args\", \"colors\", \"libcolors\", \"routine\"] __version__ = \"0.96\"",
"<reponame>runapp/xortool<filename>xortool/__init__.py #!/usr/bin/env python #-*- coding:utf-8 -*- __all__ = [\"args\", \"c... |
[
"# TODO : ButtonRessourcePack.style.create_surface(size) class _RessourcePack: def __init__(self): self.font =",
"class ScenesRessourcePack(RessourcePack): def __init__(self, background_color=(170, 170, 170), ): assert is_color(background_color)",
"Object from baopig.pybao.issomething import * class RessourcePa... |
[
"int(infilename.split(\".\")[0].split(\"_\")[-1]) cmatch = 0 counter = 0 # loop all",
"extent change from colormesh plt.title(title) if doText: plt.text(0.01, 0.98, \"#stations:",
"year station_names = np.array([]) fixed_station = np.array([]) latitudes = np.array([])",
"= \"MARS - SYNOP - {}\".format(year) e... |
[
"Authorized Connect Apps belonging to an account. :var Page: The",
"used to avoid listing duplicated resources if new ones are",
"get(self, FriendlyName=None, Page=None, PageSize=None, AfterSid=None): \"\"\" Fetch the Applications belonging",
"= http.Request('GET', self.get_url(), params) return request, pars... |
[
"feature extraction dimensions. Default is 64.\") args_opt = parser.parse_args() #",
"64.\") args_opt = parser.parse_args() # Runtime context.set_context(mode=context.GRAPH_MODE, device_target='Ascend', device_id=0) #",
"value t_sum = np.sum(e_x, axis=1, keepdims=True) # returns sum of",
"2.0 (the \"License\"... |
[
"= 0 elif pykeops.config.torch_found: import torch if all([type(var) in [torch.Tensor,",
"= OrderedDict([('host',0), ('device',1)]) possible_options_list = ['auto', 'CPU', 'GPU', 'GPU_1D', 'GPU_1D_device',",
"OrderedDict import pykeops import pykeops.config ######################################################... |
[
"= wavfile.read(wav_path) x = x.astype(np.float64) f0, timeaxis = pyworld.dio(x, fs,",
"y = P.adjust_frame_lengths(x, y, pad=True, divisible_by=2) # Save np.save(src_path, x)",
"= FileSourceDataset(MGCSource(DATA_ROOT, [target_speaker], max_files=max_files)) skip_feature_extraction = exists(join(dst_dir, \"X\")... |
[
"json.loads(el.deck_gl_json_chart.json) self.assertEqual(actual[\"layers\"][0][\"@@type\"], \"ScatterplotLayer\") self.assertEqual( actual[\"layers\"][0][\"data\"], [ {\"lat\": 1, \"lon\": 10},",
"# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law",
"testutil import streamlit a... |
[
"'pipeline_options'): self.project_id = ( sink.pipeline_options.view_as(GoogleCloudOptions).project) assert self.project_id is not None",
"self.project_id is not None self.dataset_id = self.sink.table_reference.datasetId self.table_id = self.sink.table_reference.tableId",
"values are not JSON compliant # This c... |
[
"version of Qt libraries when there is installed another application",
"there is installed another application (e.g. QtCreator) if is_win: from",
"import extend_system_path extend_system_path([os.path.join(x, 'PyQt5') for x in getsitepackages()]) extend_system_path([os.path.join(os.path.dirname(get_module_file_... |
[
"== 666 def test_compare_nodes(): old_node = vy_ast.parse_to_ast(\"foo = 42\") new_node",
"new_node = vy_ast.Int.from_node(old_node, value=666) assert isinstance(new_node, vy_ast.Int) def test_source(): old_node",
"new_node = vy_ast.Int.from_node(old_node, value=666) assert old_node.value == 42 assert new_node.... |
[
"cd opencv/build && \\ cmake -D CMAKE_BUILD_TYPE=RELEASE \\ -D CMAKE_INSTALL_PREFIX=/usr/local",
"WITH_GTK=ON \\ -D WITH_LIBV4L=ON \\ -D BUILD_TESTS=OFF \\ -D BUILD_PERF_TESTS=OFF",
"libopencore-amrwb-dev \\ libtheora-dev \\ libvorbis-dev \\ libxvidcore-dev \\ x264 \\",
"\\ cmake -D CMAKE_BUILD_TYPE=RELEASE \... |
[
"iterations = 1000000000 while n<iterations: for s in range(0,len(program)): arguments",
"16 stage = map(chr, range(ord('a'),ord('a')+stage_length)) def spin(amount): \"\"\"To save time,",
"history.index(stage) complete_cycles = (iterations - n) / loop_length n +=",
"elif action_list[s] == 'x': swap((int(argu... |
[
"as np from numpy.testing import assert_equal, assert_array_equal from nose.tools import",
"= felzenszwalb(img, sigma=0) # we expect 4 segments: assert_equal(len(np.unique(seg)), 4)",
"i in range(4): hist = np.histogram(img[seg == i], bins=[0, 0.1,",
"for i in range(4): hist = np.histogram(img[seg == i], bins... |
[
"from masonite.app import App from masonite.middleware import CsrfMiddleware from masonite.testsuite.TestSuite",
"generate_wsgi import pytest from masonite.exceptions import InvalidCSRFToken class TestCSRFMiddleware: def",
"[] with pytest.raises(InvalidCSRFToken): self.middleware.before() def test_incoming_toke... |
[
"as f: faq_page = f.read() return {'content': faq_page} @view_config(route_name='conventions', renderer='conventions.mako')",
"with open(conventions_file, 'r') as file: conventions_page = file.read().replace('\\n', '') return",
"faq_file = os.path.join(dir_path, 'static/faq_with_indexes.html') with open(faq_fil... |
[
"list ordered by \"id\" in ascending order \"\"\" RESTApiTestCase.process_test(self, 'computers',",
"def test_computers_mixed3(self): \"\"\" url parameters: id, transport_type, orderby \"\"\" node_pk",
"extras_filter with pagination ############# def test_node_extras_filter_pagination(self): \"\"\" Check that n... |
[
"return False ts = datetime.now().strftime(\"%Y-%m-%d_%H-%M-%S\") filename = f\"{ts}_process-metrics-report_{name}_{duration}_{interval}.csv\" with open(f\"{filename}\",",
"print(\"interval parameter is greater than duration parameter\") return ExitStatus.INTERVAL_GT_DURATION print(\"-----------------------------... |
[
"normal_batch def test_loader(self): with tf.variable_scope('test_loader'): dataset = tf.data.Dataset.from_tensor_slices(self.test_x).repeat() normal_batch =",
"label, *_ = line.split('\\t') self.anno[filename] = label def init_train(self): train_x,",
"self.train_normal, name='normal_batch') random_crop_batch =... |
[
"= True break if not ok: stderr.write(\"No markdown file found",
"os.listdir(\".\"): if file.endswith(\".md\"): ok = True break if not ok:",
"+ \"/src\"): os.symlink(script_path + \"/src\", tmp_dir + \"/src\") copy_tree(\".\", tmp_dir)",
"args = parser.parse_args() # Check directory ok = False for",
"!= \"\... |
[
"visited, is_possible) visited[cur] = False if __name__ == '__main__': input",
"dfs(node, 0, visited, is_possible) if is_possible[0]: return 1 return 0",
"if visited[cur]: return if depth == target_depth: is_possible[0] = True",
"[False] for node in range(N): visited = [False for _",
"target_depth = 4 N, M ... |
[
"to share' 'private data on BigchainDB.'), url='https://github.com/vrde/bst/', author='<NAME>', author_email='<EMAIL>', license='AGPLv3',",
"3.5', 'Operating System :: MacOS :: MacOS X', 'Operating System",
"Developers', 'Topic :: Database', 'Topic :: Database :: Database Engines/Servers',",
"Linux', ], packa... |
[
"<gh_stars>0 from django.contrib import admin from db.models.job_resources import JobResources admin.site.register(JobResources)"
] |
[
"list_output_dict = [] # output directory path outdir = \"../results/run1/\"",
"weight_column_idx] new_X_train = np.delete(X_train, weight_column_idx, axis=1) new_questions = column_names new_questions.remove('weight')",
"= { 'criterion': ['gini', 'entropy'], 'max_depth': [2, 3, 4, 5,",
"o_models_file.write(s... |
[
"self.account.id) self.assertIn(hero.gender, (game_relations.GENDER.MALE, game_relations.GENDER.FEMALE)) self.assertEqual(hero.preferences.energy_regeneration_type, hero.race.energy_regeneration) self.assertEqual(hero.habit_honor.raw_value, 0) self.assertEqual(hero.habit_peacefulness.raw_value, 0)",
"is_fast=Fals... |
[] |
[
"information from __future__ import absolute_import from __future__ import division from",
"The code is released under the MIT Licence. # See",
"y_inlet = self.case.boundary_data(\"inlet\", sort=\"y\")[0][:, 1] inlet_edge_length = tbl.edge_lengths(self.case, \"inlet\") self.d",
"See LICENCE.txt and the Legal ... |
[
"__init__(self, frequency=10): SteppableBasePy.__init__(self, frequency) def step(self, mcs): if mcs in",
"def __init__(self, frequency=10): SteppableBasePy.__init__(self, frequency) def step(self, mcs): if mcs",
"step(self, mcs): if mcs in [3, 5, 19,20, 23, 29,",
"def step(self, mcs): if mcs in [3, 5, 19,20,... |
[
"f(local_opt): name = (kwargs and kwargs.pop(\"name\")) or local_opt.__name__ gpu_optimizer.register(name, local_opt,",
"\"matrix_ops_db2\" abstract_batch_norm_db = LocalGroupDB() abstract_batch_norm_db2 = LocalGroupDB(local_opt=GraphToGPULocalOptGroup) abstract_batch_norm_db2.__name__ = \"abstract_batch_norm_db2... |
[
"urlquote log = logging.getLogger(__name__) class Node(JenkinsBase): \"\"\" Class to hold",
"of the node :param jenkins_obj: ref to the jenkins obj",
"are taking this node offline \"\"\" if not self._data['offline']: self.toggle_temporarily_offline(message)",
"self.jenkins def __str__(self): return self.name ... |
[
"= self.createTimeRange(0, 240) self._ddhhmmTime = self.getCurrentTime( argDict, \"%d%H%M\", shiftToLocal=0, stripLeading=0)",
"the public domain, furnished \"as is\", without technical # support,",
"self.getCurrentTime( argDict, \"%l%M %p %Z %a %b %e %Y\", stripLeading=1)",
"*|\\n\\n\" ## # bullets = bullets... |
[
"= splited_aux_lig[1] pose = area[0] buried_total = \"{:.4f}\".format(area[1]) #line =",
"as normalized_buried_area FROM database a JOIN buried_area_total_sort b ON b.ligand",
"Popen(command,shell=True, stdout=PIPE, stderr=PIPE) stdout, stderr = process.communicate() sasa_complex = get_value_from_xvg_sasa(f_tem... |
[
"'smtp_server', request=request) if len(rq['smtp_server']) > 128: error_flag = True error_msg['smtp_server']",
"#todo 仮でこのエラーは名前に入れている error_msg['mail_disp_name'] += get_message('MOSJA27215', request.user.get_lang_mode()) + '\\n' logger.user_log('LOSM07005', rq['smtp_server'],",
"for key_value in defs.SMTP_PROT... |
[
"-> Dog: return self.dogs.remove() def dequeCat(self) -> Cat: return self.cats.remove()",
"= self.tail.next_node def remove(self) -> Any: if self.head is None:",
"None def __str__(self) -> str: current = self.head string =",
"__str__(self) -> str: return f\"{self.name}\" class Node: def __init__(self, data:",... |
[
"Any datum kwargs that should go to all children. \"\"\"",
"cam __all__ = ['DetectorBase', 'AreaDetector', 'AdscDetector', 'Andor3Detector', 'AndorDetector', 'BrukerDetector', 'DexelaDetector',",
"for the hardware-specific classes that follow. Note that Plugin also",
"_html_docs = ['EVTDoc.html'] cam = C(cam.... |
[
"(m): ')) area(f'A área do seu terreno {l}X{c} é de",
"(m): ')) c = float(input('Comprimento (m): ')) area(f'A área do",
"def area(msg):#declaracao da funcao com o parametro msg print(msg)#aqui msg",
"funcao com o parametro msg print(msg)#aqui msg e a area",
"20) l = float(input('Largura (m): ')) c = float(... |
[
"html template.\"\"\" pyfile_path = os.path.dirname(os.path.abspath(__file__)) path = join_path(pyfile_path, 'templates', filename)",
"Tuple with endpoints where access must not be checked. \"\"\"",
"response = authorizer.validate() return response def authorize_endpoint(function): @wraps(function) def authoriz... |
[
"name='_id', field=models.AutoField(editable=False, primary_key=True, serialize=False), ), migrations.AlterField( model_name='orderedproduct', name='_id', field=models.AutoField(editable=False, primary_key=True,",
"name='dateTimeCreated', ), migrations.AlterField( model_name='order', name='_id', field=models.Auto... |
[
"('pages', models.PositiveIntegerField(blank=True, default=0, null=True)), ('ddc', models.CharField(blank=True, default='', max_length=1024)), ('llcc', models.CharField(blank=True,",
"('description', models.TextField(blank=True, default='')), ('publisher', models.CharField(blank=True, default='', max_length=512))... |
[
"<filename>compliance_suite/exceptions/user_config_exception.py<gh_stars>1-10 # -*- coding: utf-8 -*- \"\"\"Module compliance_suite.exceptions.user_config_exception.py This module",
"module contains class definition for user config file exceptions. \"\"\"",
"# -*- coding: utf-8 -*- \"\"\"Module compliance_suite... |
[
"self._ncols @property def nrows (self): \"\"\"The number of rows in",
"RiskMap.load(filename) start = Point(0, 0) end = Point(rmap.ncols - 1,",
"def ncols (self): \"\"\"The number of columns in this `RiskMap`.\"\"\"",
"pos.x in range(0, self.ncols) def search (rmap, start, end): \"\"\"Searches",
"position ... |
[
"modify it under the terms of the MIT License; see",
"it and/or # modify it under the terms of the",
"software; you can redistribute it and/or # modify it under",
"# modify it under the terms of the MIT License;",
"free software; you can redistribute it and/or # modify it",
"terms of the MIT License; see ... |
[
"64 encoded value of the primary read-write key. :vartype primary_master_key:",
"str :ivar secondary_master_key: Base 64 encoded value of the secondary",
"key. :vartype secondary_readonly_master_key: str :ivar primary_master_key: Base 64 encoded value",
"key. :vartype secondary_master_key: str \"\"\" _validat... |
[
"link, \"displayed_link\": displayed_link, \"snippet\": snippet, \"author\": author, \"author_link\": author_link, \"date_published\":",
"a.yKioRe:nth-child(1)::attr(href)\").get() more_editions_link = book_result.css(\".R1n8Q a.yKioRe:nth-child(2)::attr(href)\").get() books_results.append({ \"title\": title, \"l... |
[
"analysis on different games. \"\"\" from hol import ( cards,",
"<reponame>AustinTSchaffer/DailyProgrammer<filename>Python/Higher-Or-Lower/hol/__init__.py r\"\"\" Contains classes and methods that can be used",
"be used when simulating the game Higher-or-Lower and performing statistical",
"constants, ) from h... |
[
"Box( (x, y, self.column_1 + self.column_2, self.text_height)) self.w.box.text = TextBox(",
"\"update\", callback=self.update_font_callback, sizeStyle=self.size_style) # x slider x = self.padding_x y",
"= self.w.x_slider.get() yValue = self.w.y_slider.get() x = self._moveX - xValue",
"def slide_callback(self,... |
[
"(str(p[0]), str(p[1])) for p in _params]).encode(\"utf-8\") sign = sha1(sign).hexdigest() sign_type",
"return value if isinstance(value, six.text_type): return value.encode(encoding) return six.binary_type(value) def",
"make_error_page(url): with io.open( os.path.join(os.path.dirname(__file__), 'contrib/error.... |
[
"from tensorflow.python.compiler.tensorrt import trt_convert as trt # pylint: enable=g-import-not-at-top #",
"from tensorflow.python.ops.ragged import ragged_operators as _ragged_operators from tensorflow.python.ops.random_ops import *",
"pylint: enable=redefined-builtin from tensorflow.python.eager import wrap... |
[
"disable=global-statement global START_TIME db = tango.Database() elapsed = time.time() -",
"num_devices)) print('>> Time taken to start devices: {:.4f} s ({:.4f}",
"print('- Register devices: {:.4f} s ({:.4f} s/device)' .format(elapsed, elapsed /",
"exported_devices = list(db.get_device_exported('test/*')) p... |
[
"\"Sample text for document-2\", 'meta': {\"source\": \"wiki2\"}}, {\"text\": \"Sample text",
"assert output[\"answers\"][0][\"answer\"].startswith(\"Using tests\") if isinstance(document_store, ElasticsearchDocumentStore): output = pipeline.run(query=\"How to",
"prediction is not None assert prediction[\"query... |
[
"polish_iterations: break if check_exist(asm_cns): return asm_cns else: print(\"polishing failed for",
"in read_list: output.write(read + \"\\n\") else: # TODO: think about",
"variant reads sv_reads = sv_reads_dir + \"/contig\" + str(k) sv_reads_rename",
"None if check_exist(consensus): consensus_rename = os.... |
[
"lib._parse_constant(composite, valid=FAMILIES, valid_modifiers=VIAS) assert parsed == expected def test_parse_constant_fails(): \"\"\"",
"pylint: disable=pointless-statement ses.create(\"session1\") assert ses.session_pointer is not None ses.destroy() with",
"GMTTempFile() as outfile: lib.call_module(\"info\",... |
[
"use these features, so I don't think its worth including",
"We don't use these features, so I don't think its",
"can always change it later. class ExceptionInfo: @property def value(self)",
"# This class actually has more functions than are specified",
"\"\"\"Type stubs for _pytest._code.\"\"\" # This clas... |
[
"prime number as not prime return primes # returns the",
"by a particular prime number prime_factors.append(prime) # add the prime",
"0: # checks if the number is divisible by a",
"prime numbers while n != 1: # keeps diving the",
"prime number else: break # if the number is not",
"# loops over all multipl... |
[
"def _extended_gcd(self, a: int, b: int) -> tuple[int, int, int]:",
"self._simple_new(_empty_range) first = self._range[::-1] if self.step < 0 else self._range",
"array is saved in ``_cache``. \"\"\" return np.arange(self.start, self.stop, self.step,",
"(attr, formatted_value) \"\"\" attrs = self._get_data_as... |
[
"forward(self, x): out = self.l1(x) out = self.relu(out) out =",
"self.relu(out) out = self.l4(out) # no activation and no softmax",
"out = self.relu(out) out = self.l4(out) # no activation and",
"out = self.l2(out) out = self.relu(out) out = self.l3(out) out",
"nn.Linear(hidden_size, hidden_size) self.l3 =... |
[
"file named ``config.json`` placed in the ``utils`` directory. References ----------",
"name. The name of the ``log_file`` is a combination of",
"os import logging from jwql.logging.logging_functions import configure_logging from jwql.logging.logging_functions import",
"<NAME>, 2013 (WFC3 QL Version) Use --- ... |
[
"typing import Optional session: Optional[ClientSession] = None __all__ = (session,)",
"from typing import Optional session: Optional[ClientSession] = None __all__ =",
"from aiohttp import ClientSession from typing import Optional session: Optional[ClientSession]",
"aiohttp import ClientSession from typing im... |
[
"_md5.hexdigest() def sha1(path): _sha1 = hashlib.sha1() fh = open(path, 'rb')",
"= open(path, 'rb') if start > 0: fh.seek(start) if stop",
"os.path.getsize(path) pos = start while pos < stop: size =",
"= start while pos < stop: size = min(CHUNK, stop",
"break _sha256.update(chunk) fh.close() return _sha256... |