def test_from_hdf_format(): setup_hdf_file(SMALL_ROW_SIZE, format="table") pandas_df = pandas.read_hdf(TEST_READ_HDF_FILENAME, key="df") modin_df = pd.read_hdf(TEST_READ_HDF_FILENAME, key="df") assert modin_df_equals_pandas(modin_df, pandas_df) teardown_hdf_file()
def test_from_hdf(): setup_hdf_file(SMALL_ROW_SIZE) pandas_df = pandas.read_hdf(TEST_HDF_FILENAME, key="test") modin_df = pd.read_hdf(TEST_HDF_FILENAME, key="test") assert modin_df_equals_pandas(modin_df, pandas_df) teardown_hdf_file()
def test_from_hdf(): setup_hdf_file(SMALL_ROW_SIZE, format=None) pandas_df = pandas.read_hdf(TEST_READ_HDF_FILENAME, key="df") modin_df = pd.read_hdf(TEST_READ_HDF_FILENAME, key="df") df_equals(modin_df, pandas_df) teardown_hdf_file()
def main(): tqdm.pandas() modelpath = os.path.join(content.DATAPATH, "MODEL") df = pd.concat([pd.read_hdf(os.path.join(modelpath, f"data_preprocessed_{i}.h5"), 'X', mode='r') for i in range(8)]) filepath = os.path.join(modelpath, "data_preprocessed.h5") df.to_hdf(filepath, key='X', mode='w')
# arrowsize=0.7, # start_points=seeds.T, # maxlength=30.0, # linewidth=1.0, #) plt.savefig(pathF + "MeanFlow.svg", bbox_inches="tight") plt.show() # %%############################################################################ """ instantaneous spanwise-average flow field """ # %% Plot contour of the instantaneous flow field with isolines # MeanFlow.AddVariable('rho', 1.7**2*1.4*MeanFlow.p/MeanFlow.T) InstFlow = pd.read_hdf(pathSL + 'Z_03a/TP_2D_Z_03_01295.00.h5') var = 'w' var1 = 'vorticity_3' u = griddata((InstFlow.x, InstFlow.y), InstFlow[var], (x, y)) gradp = griddata((InstFlow.x, InstFlow.y), InstFlow[var1], (x, y)) print("u=", np.max(InstFlow.u)) print("u=", np.min(InstFlow.u)) u[corner] = np.nan cval1 = -0.3 cval2 = 0.3 fig, ax = plt.subplots(figsize=(6.0, 2.3)) matplotlib.rc("font", size=textsize) rg1 = np.linspace(cval1, cval2, 41) cbar = ax.contourf(x, y, u, cmap="bwr", levels=rg1, extend='both') # rainbow_r ax.set_xlim(0.0, 20.0) ax.set_ylim(-3.0, 4.0)