From 53c9e96e7a21687d1efb55da209415d865e35fb2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?K=C3=BChle=2C=20Laura=20Christine=20=28lakue103=29?=
<laura.kuehle@uni-duesseldorf.de>
Date: Tue, 3 Aug 2021 14:52:58 +0200
Subject: [PATCH] Removed unnecessary comments.
---
ANN_Data_Generator.py | 8 +-------
Main.py | 18 ++++--------------
Troubled_Cell_Detector.py | 31 -------------------------------
3 files changed, 5 insertions(+), 52 deletions(-)
diff --git a/ANN_Data_Generator.py b/ANN_Data_Generator.py
index c6a22bb..860ef55 100644
--- a/ANN_Data_Generator.py
+++ b/ANN_Data_Generator.py
@@ -112,7 +112,6 @@ class TrainingDataGenerator(object):
# Calculating Cell centers for a given 1D domain with n elements, and
# Calculating Corresponding Legendre Basis Coefficients for given polynomial_degree
- num_grid_cells = self._stencil_length # former: 3
# Create stencil and basis_coefficients for smooth_function mapped onto stencil
interval, centers, h = self._build_stencil()
centers = [center[0] for center in centers]
@@ -121,7 +120,7 @@ class TrainingDataGenerator(object):
left_bound, right_bound = interval
dg_scheme = DG_Approximation.DGScheme('NoDetection', polynomial_degree=polynomial_degree,
- num_grid_cells=num_grid_cells, left_bound=left_bound,
+ num_grid_cells=self._stencil_length, left_bound=left_bound,
right_bound=right_bound, quadrature='Gauss',
quadrature_config={'num_eval_points': polynomial_degree+1})
@@ -143,11 +142,6 @@ class TrainingDataGenerator(object):
order = np.random.permutation(num_samples)
input_data = input_data[order]
- # for i in range(len(test_data)):
- # print(i)
- # print(test_data[i])
- # print()
-
output_data = np.zeros((num_samples, 2))
if is_smooth:
output_data[:, 1] = np.ones(num_samples)
diff --git a/Main.py b/Main.py
index 0c7dae2..5ae4083 100644
--- a/Main.py
+++ b/Main.py
@@ -14,7 +14,7 @@ tic = timeit.default_timer()
alpha = 1
p = 2
cfl = 0.2
-N = 256 # 40 elements work well for Condition 3
+N = 4 # 40 elements work well for Condition 3
finalTime = 1
xL = -1
xR = 1
@@ -38,9 +38,10 @@ limiter_config['erase_degree'] = 0
quadrature_config['num_eval_points'] = 12 # 12
-detector = 'Theoretical'
+# detector = 'Theoretical'
+detector = 'ArtificialNeuralNetwork'
update_scheme = 'SSPRK3'
-init_cond = 'Box'
+init_cond = 'Sine'
limiter = 'ModifiedMinMod'
quadrature = 'Gauss'
dg_scheme = DGScheme(detector, detector_config=detector_config, init_cond=init_cond, init_config=init_config,
@@ -49,22 +50,11 @@ dg_scheme = DGScheme(detector, detector_config=detector_config, init_cond=init_c
polynomial_degree=p, cfl_number=cfl, num_grid_cells=N, final_time=finalTime,
verbose=False, left_bound=xL, right_bound=xR)
-# __, __, troubled_cells, __ =
dg_scheme.approximate()
dg_scheme.save_plots()
toc = timeit.default_timer()
print('Time:', toc-tic)
-# =============================================================================
-#
-# print(troubled_cells)
-#
-# print(dg_scheme.update_scheme)
-# print(dg_scheme.init_cond)
-# print(dg_scheme.detector)
-# print(dg_scheme.limiter)
-# # print(dg_scheme.projection)
-# =============================================================================
# if __name__ == '__main__':
# pass
diff --git a/Troubled_Cell_Detector.py b/Troubled_Cell_Detector.py
index 15c32b0..8a6b5a2 100644
--- a/Troubled_Cell_Detector.py
+++ b/Troubled_Cell_Detector.py
@@ -280,32 +280,6 @@ class WaveletDetector(TroubledCellDetector):
basis = self._basis.get_basis_vector()
wavelet = self._basis.get_wavelet_vector()
-########################################################################################################################
- # For later consideration
-########################################################################################################################
- # tic = timeit.default_timer()
- # averaged_projection1 = []
- # wavelet_projection1 = []
- # for degree in range(self._polynomial_degree + 1):
- # leftMesh = coarse_projection[degree] * basis[degree].subs(x, -1 / 2)
- # rightMesh = coarse_projection[degree] * basis[degree].subs(x, 1 / 2)
- # leftTest = multiwavelet_coeffs[degree] * wavelet[degree].subs(z, 1 / 2) \
- # * (-1)**(self._polynomial_degree + 1 + degree)
- # rightTest = multiwavelet_coeffs[degree] * wavelet[degree].subs(z, 1 / 2)
- # newRowMesh = []
- # newRowTest = []
- # for i in range(len(coarse_projection[0])):
- # newRowMesh.append(leftMesh[i])
- # newRowMesh.append(rightMesh[i])
- # newRowTest.append(leftTest[i])
- # newRowTest.append(rightTest[i])
- # averaged_projection1.append(newRowMesh)
- # wavelet_projection1.append(newRowTest)
- # toc = timeit.default_timer()
- # print('Loop:', toc-tic)
-########################################################################################################################
-
- # tic = timeit.default_timer()
averaged_projection = [[coarse_projection[degree][cell] * basis[degree].subs(x, value)
for cell in range(self._num_coarse_grid_cells)
for value in [-0.5, 0.5]]
@@ -315,11 +289,6 @@ class WaveletDetector(TroubledCellDetector):
for cell in range(self._num_coarse_grid_cells)
for value in [(-1) ** (self._polynomial_degree + degree + 1), 1]]
for degree in range(self._polynomial_degree + 1)]
- # toc = timeit.default_timer()
- # print('List:', toc-tic)
-
- # print(averaged_projection1 == averaged_projection)
- # print(wavelet_projection1 == wavelet_projection)
projected_coarse = np.sum(averaged_projection, axis=0)
projected_fine = np.sum([fine_projection[degree] * basis[degree].subs(x, 0)
--
GitLab