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)
