diff --git a/Plotting.py b/Plotting.py
index 0db5713422ac89ee249757f7e0b96186ed61d1f3..5c63e04dcce824b480b00d81ced9b58a2ca65940 100644
--- a/Plotting.py
+++ b/Plotting.py
@@ -5,7 +5,6 @@
TODO: Give option to select plotting color
"""
-from typing import Tuple
import numpy as np
import matplotlib
@@ -14,9 +13,6 @@ import seaborn as sns
from numpy import ndarray
from sympy import Symbol
-from Quadrature import Quadrature
-from Initial_Condition import InitialCondition
-
matplotlib.use('Agg')
x = Symbol('x')
@@ -171,96 +167,6 @@ def plot_details(fine_projection: ndarray, fine_mesh: ndarray,
plt.title('Wavelet Coefficients')
-def calculate_approximate_solution(
- projection: ndarray, points: ndarray, polynomial_degree: int,
- basis: ndarray) -> ndarray:
- """Calculates approximate solution.
-
- Parameters
- ----------
- projection : ndarray
- Matrix of projection for each polynomial degree.
- points : ndarray
- List of evaluation points for mesh.
- polynomial_degree : int
- Polynomial degree.
- basis : ndarray
- Basis vector for calculation.
-
- Returns
- -------
- ndarray
- Array containing approximate evaluation of a function.
-
- """
- num_points = len(points)
-
- basis_matrix = [[basis[degree].subs(x, points[point])
- for point in range(num_points)]
- for degree in range(polynomial_degree+1)]
-
- approx = [[sum(projection[degree][cell] * basis_matrix[degree][point]
- for degree in range(polynomial_degree+1))
- for point in range(num_points)]
- for cell in range(len(projection[0]))]
-
- return np.reshape(np.array(approx), (1, len(approx) * num_points))
-
-
-def calculate_exact_solution(
- mesh: ndarray, cell_len: float, wave_speed: float, final_time:
- float, interval_len: float, quadrature: Quadrature, init_cond:
- InitialCondition) -> Tuple[ndarray, ndarray]:
- """Calculates exact solution.
-
- Parameters
- ----------
- mesh : ndarray
- List of mesh valuation points.
- cell_len : float
- Length of a cell in mesh.
- wave_speed : float
- Speed of wave in rightward direction.
- final_time : float
- Final time for which approximation is calculated.
- interval_len : float
- Length of the interval between left and right boundary.
- quadrature : Quadrature object
- Quadrature for evaluation.
- init_cond : InitialCondition object
- Initial condition for evaluation.
-
- Returns
- -------
- grid : ndarray
- Array containing evaluation grid for a function.
- exact : ndarray
- Array containing exact evaluation of a function.
-
- """
- grid = []
- exact = []
- num_periods = np.floor(wave_speed * final_time / interval_len)
-
- for cell in range(len(mesh)):
- eval_points = mesh[cell]+cell_len / 2 * quadrature.get_eval_points()
-
- eval_values = []
- for point in range(len(eval_points)):
- new_entry = init_cond.calculate(eval_points[point]
- - wave_speed * final_time
- + num_periods * interval_len)
- eval_values.append(new_entry)
-
- grid.append(eval_points)
- exact.append(eval_values)
-
- exact = np.reshape(np.array(exact), (1, len(exact) * len(exact[0])))
- grid = np.reshape(np.array(grid), (1, len(grid) * len(grid[0])))
-
- return grid, exact
-
-
def plot_classification_barplot(evaluation_dict: dict, colors: dict) -> None:
"""Plots classification accuracy.
diff --git a/Troubled_Cell_Detector.py b/Troubled_Cell_Detector.py
index 2d8aaeb737ccff3167aeb76a7890a173ac0c9ac3..f2d8691e935c2251b1c1a504fe8872612299adff 100644
--- a/Troubled_Cell_Detector.py
+++ b/Troubled_Cell_Detector.py
@@ -13,17 +13,14 @@ import matplotlib
from matplotlib import pyplot as plt
import seaborn as sns
import torch
-from sympy import Symbol
import ANN_Model
from Plotting import plot_solution_and_approx, plot_semilog_error, \
- plot_error, plot_shock_tube, plot_details, \
+ plot_error, plot_shock_tube, plot_details
+from projection_utils import calculate_cell_average,\
calculate_approximate_solution, calculate_exact_solution
-from projection_utils import calculate_cell_average
matplotlib.use('Agg')
-x = Symbol('x')
-z = Symbol('z')
class TroubledCellDetector:
diff --git a/projection_utils.py b/projection_utils.py
index e860b102f99160a7a8400f3ca24beeb0ba8ecd15..ebc0d0941545c8c9a9e6c653416f33713cf59de2 100644
--- a/projection_utils.py
+++ b/projection_utils.py
@@ -3,9 +3,107 @@
@author: Laura C. Kühle
"""
+
+from typing import Tuple
import numpy as np
+from numpy import ndarray
+from sympy import Symbol
+
+from Quadrature import Quadrature
+from Initial_Condition import InitialCondition
+
+
+x = Symbol('x')
+
+
+def calculate_approximate_solution(
+ projection: ndarray, points: ndarray, polynomial_degree: int,
+ basis: ndarray) -> ndarray:
+ """Calculate approximate solution.
+
+ Parameters
+ ----------
+ projection : ndarray
+ Matrix of projection for each polynomial degree.
+ points : ndarray
+ List of evaluation points for mesh.
+ polynomial_degree : int
+ Polynomial degree.
+ basis : ndarray
+ Basis vector for calculation.
+
+ Returns
+ -------
+ ndarray
+ Array containing approximate evaluation of a function.
+
+ """
+ num_points = len(points)
+
+ basis_matrix = [[basis[degree].subs(x, points[point])
+ for point in range(num_points)]
+ for degree in range(polynomial_degree+1)]
+
+ approx = [[sum(projection[degree][cell] * basis_matrix[degree][point]
+ for degree in range(polynomial_degree+1))
+ for point in range(num_points)]
+ for cell in range(len(projection[0]))]
+
+ return np.reshape(np.array(approx), (1, len(approx) * num_points))
+
+
+def calculate_exact_solution(
+ mesh: ndarray, cell_len: float, wave_speed: float, final_time:
+ float, interval_len: float, quadrature: Quadrature, init_cond:
+ InitialCondition) -> Tuple[ndarray, ndarray]:
+ """Calculate exact solution.
+
+ Parameters
+ ----------
+ mesh : ndarray
+ List of mesh evaluation points.
+ cell_len : float
+ Length of a cell in mesh.
+ wave_speed : float
+ Speed of wave in rightward direction.
+ final_time : float
+ Final time for which approximation is calculated.
+ interval_len : float
+ Length of the interval between left and right boundary.
+ quadrature : Quadrature object
+ Quadrature for evaluation.
+ init_cond : InitialCondition object
+ Initial condition for evaluation.
+
+ Returns
+ -------
+ grid : ndarray
+ Array containing evaluation grid for a function.
+ exact : ndarray
+ Array containing exact evaluation of a function.
+
+ """
+ grid = []
+ exact = []
+ num_periods = np.floor(wave_speed * final_time / interval_len)
+
+ for cell_center in mesh:
+ eval_points = cell_center+cell_len / 2 * quadrature.get_eval_points()
+
+ eval_values = []
+ for eval_point in eval_points:
+ new_entry = init_cond.calculate(eval_point
+ - wave_speed * final_time
+ + num_periods * interval_len)
+ eval_values.append(new_entry)
+
+ grid.append(eval_points)
+ exact.append(eval_values)
+
+ exact = np.reshape(np.array(exact), (1, len(exact) * len(exact[0])))
+ grid = np.reshape(np.array(grid), (1, len(grid) * len(grid[0])))
-from Plotting import calculate_approximate_solution
+ return grid, exact
def calculate_cell_average(projection, basis, stencil_length,