def der_plot(step, der_index, f, ax1, ax2, ax3):
np_filenames = []
locations = []
for idx in range(99):
np_filenames.append("tube_pt_ppank_" + str(idx) + ".npy")
locations.append(idx / 100.0)
data_der = []
for np_filename in np_filenames:
arr_t, arr_der = load_from_np("./result/" + np_filename, der_index)
data_der.append(arr_der[step])
# shift locations so we could input it in analytic coordination.
locations_aly = []
for location in locations:
location_aly = location - 0.5
locations_aly.append(location_aly)
analytic_solver = analytic.Solver()
analytic_solution = analytic_solver.get_analytic_solution(locations_aly,
t=arr_t[step])
data_der_analytic = []
for location_idx in range(len(locations)):
if der_index == 1:
title = 'RHO'
elif der_index == 2:
title = 'M'
elif der_index == 3:
title = 'PRESSURE'
else:
title = 'UNKNOWN'
data_der_analytic.append(analytic_solution[location_idx][der_index])
data_der_deviation = []
for idx in range(len(data_der)):
data_der_deviation.append(data_der[idx] - data_der_analytic[idx])
ax1.set_title('3D - ' + title)
ax1.scatter(locations, data_der, s=10, c='b', marker='s')
ax2.set_title('1D - ' + title)
ax2.scatter(locations, data_der_analytic, s=10, c='b', marker='8')
ax3.set_title('DEVIATION')
ax3.scatter(locations, data_der_deviation, s=10, c='b', marker='o')
return str(arr_t[step])
def load_from_analytic(location, arr_time):
# load analytic solution data of 1D tube
# note the coordination of analytic solution is different from the one that
# SOLVCON used.
mesh_1d = (location, )
analytic_solver = analytic.Solver()
vals = list()
for t_step in arr_time:
solution_analytic = analytic_solver.get_analytic_solution(mesh_1d,
t=t_step)
# refer to gas probe.py:Probe::__call__
vlist = [t_step, solution_analytic[0][1], solution_analytic[0][3]]
vals.append(vlist)
arr_aly = np.array(vals, dtype='float64')
arr_aly_t = arr_time
arr_aly_rho = arr_aly[:, 1]
arr_aly_p = arr_aly[:, 2]
return arr_aly_t, arr_aly_rho, arr_aly_p
def load_from_analytic(location, arr_time, arr_idx_der):
# load analytic solution data of 1D tube
# note the coordination of analytic solution is different from
# the one that SOLVCON used.
mesh_1d = (location, )
analytic_solver = analytic.Solver()
# parse the analytic data object to be arr type data object
vals = list()
for t_step in arr_time:
solution_analytic = analytic_solver.get_analytic_solution(mesh_1d,
t=t_step)
# refer to gas probe.py:Probe::__call__
vlist = [t_step, solution_analytic[0][1], solution_analytic[0][3]]
vals.append(vlist)
arr_aly = np.array(vals, dtype='float64')
# parsed.
arr_aly_t = arr_time
arr_aly_der = arr_aly[:, arr_idx_der]
return arr_aly_t, arr_aly_der
# Description: # An example to show how to use sodtube1d class # solvers import sodtube1d.generator_mesh as gmesh import sodtube1d.solver_analytic as analytic import sodtube1d.solver_cese as cese import sodtube1d.solver_porting as solver_porting # helper handlers import sodtube1d.handler_data as hd import sodtube1d.handler_plot as hp generator_mesh = gmesh.Mesher() generator_mesh.gen_mesh() mesh = generator_mesh.get_mesh() analytic_solver = analytic.Solver() solution_analytic = analytic_solver.get_analytic_solution(mesh) solver_cese = cese.Solver() solver_cese.run_cese_iteration() solution_cese = solver_cese.get_cese_solution() solution_porting = solver_porting.get_specific_solution_for_unit_test_high_precision( ) dm = hd.DataManager() pm = hp.PlotManager() #solution_deviation = dm.get_deviation(solution_analytic, solution_cese_porting) solution_deviation = dm.get_deviation(solution_porting, solution_cese) #solution_deviation_percent = dm.get_deviation_percent(solution_analytic, solution_cese_porting)
def der_plot(step, der_index, base_subplot_idx):
"""Plot one plot of a derived quantity.
Parameters
----------
step : int
nth step
der_index : int
index to indicate which derived quantity it means
base_subplot_idx : int
index to indicate which row this subplot should locate
Returns
-------
tuples
several attributes to compose of a subplot
"""
np_filenames = []
locations = []
for idx in range(99):
np_filenames.append("tube_pt_ppank_" + str(idx) + ".npy")
locations.append(idx / 100.0)
data_der = []
for np_filename in np_filenames:
arr_t, arr_der = load_from_np(
"../sod-tube-working/result/" + np_filename, der_index)
data_der.append(arr_der[step])
# shift locations so we could input it in analytic coordination.
locations_aly = []
for location in locations:
location_aly = location - 0.5
locations_aly.append(location_aly)
analytic_solver = analytic.Solver()
analytic_solution = analytic_solver.get_analytic_solution(locations_aly,
t=arr_t[step])
data_der_analytic = []
for location_idx in range(len(locations)):
if der_index == 1:
title = 'RHO'
elif der_index == 2:
title = 'V-magnitude'
elif der_index == 3:
title = 'PRESSURE'
else:
title = 'UNKNOWN'
data_der_analytic.append(analytic_solution[location_idx][der_index])
data_der_deviation = []
for idx in range(len(data_der)):
data_der_deviation.append(data_der[idx] - data_der_analytic[idx])
time_label = f"{arr_t[step]:.4f}"
# 331 means index 1 position of a 3x3 matrix
subplot_idx = 330 + base_subplot_idx
ax1 = plt.subplot(subplot_idx, title='3D - ' + title)
artist_3d = plt.scatter(locations, data_der, s=10, c='b', marker='s')
text1 = plt.text(0.1, 0.08, "Time: " + time_label, transform=ax1.transAxes)
subplot_idx = 330 + base_subplot_idx + 3
ax2 = plt.subplot(subplot_idx, title='1D - ' + title)
artist_1d = plt.scatter(locations,
data_der_analytic,
s=10,
c='b',
marker='8')
text2 = plt.text(0.1, 0.08, "Time: " + time_label, transform=ax2.transAxes)
subplot_idx = 330 + base_subplot_idx + 6
ax3 = plt.subplot(subplot_idx, title='DEVIATION - ' + title)
artist_dev = plt.scatter(locations,
data_der_deviation,
s=10,
c='b',
marker='o')
text3 = plt.text(0.1, 0.08, "Time: " + time_label, transform=ax3.transAxes)
return artist_3d, artist_1d, artist_dev, text1, text2, text3
def der_plot(step, der_index, base_subplot_idx):
np_filenames = []
locations = []
for idx in range(99):
np_filenames.append("tube_pt_ppank_" + str(idx) + ".npy")
locations.append(idx / 100.0)
data_der = []
for np_filename in np_filenames:
arr_t, arr_der = load_from_np("./result/" + np_filename, der_index)
data_der.append(arr_der[step])
# shift locations so we could input it in analytic coordination.
locations_aly = []
for location in locations:
location_aly = location - 0.5
locations_aly.append(location_aly)
analytic_solver = analytic.Solver()
analytic_solution = analytic_solver.get_analytic_solution(locations_aly,
t=arr_t[step])
data_der_analytic = []
for location_idx in range(len(locations)):
if der_index == 1:
title = 'RHO'
elif der_index == 2:
title = 'V-magnitude'
elif der_index == 3:
title = 'PRESSURE'
else:
title = 'UNKNOWN'
data_der_analytic.append(analytic_solution[location_idx][der_index])
data_der_deviation = []
for idx in range(len(data_der)):
data_der_deviation.append(data_der[idx] - data_der_analytic[idx])
subplot_idx = 330 + base_subplot_idx
ax1 = plt.subplot(subplot_idx, title='3D - ' + title)
artist_3d = plt.scatter(locations, data_der, s=10, c='b', marker='s')
text1 = plt.text(0.1,
0.08,
"Time: " + str(arr_t[step]),
transform=ax1.transAxes)
subplot_idx = 330 + base_subplot_idx + 3
ax2 = plt.subplot(subplot_idx, title='1D - ' + title)
artist_1d = plt.scatter(locations,
data_der_analytic,
s=10,
c='b',
marker='8')
text2 = plt.text(0.1,
0.08,
"Time: " + str(arr_t[step]),
transform=ax2.transAxes)
subplot_idx = 330 + base_subplot_idx + 6
ax3 = plt.subplot(subplot_idx, title='DEVIATION - ' + title)
artist_dev = plt.scatter(locations,
data_der_deviation,
s=10,
c='b',
marker='o')
text3 = plt.text(0.1,
0.08,
"Time: " + str(arr_t[step]),
transform=ax3.transAxes)
return artist_3d, artist_1d, artist_dev, text1, text2, text3