diff --git a/Plotting.py b/Plotting.py
index ff5e608617c5ebe88c11abf1662e5142a5abf2a4..2ce4ec9c53c829c196f78a98a655fc69839e3fad 100644
--- a/Plotting.py
+++ b/Plotting.py
@@ -3,16 +3,22 @@
@author: Laura C. Kühle
TODO: Give option to select plotting color
-TODO: Add documentation to plot_boxplot()
-TODO: Adjust documentation for plot_classification_accuracy()
+TODO: Add documentation to plot_boxplot() -> Done
+TODO: Adjust documentation for plot_classification_accuracy() -> Done
"""
+from typing import Tuple
+
import numpy as np
import matplotlib
from matplotlib import pyplot as plt
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')
@@ -20,16 +26,17 @@ z = Symbol('z')
sns.set()
-def plot_solution_and_approx(grid, exact, approx, color_exact, color_approx):
- """"Plots approximate and exact solution against each other.
+def plot_solution_and_approx(grid: ndarray, exact: ndarray, approx: ndarray,
+ color_exact: str, color_approx: str) -> None:
+ """Plots approximate and exact solution against each other.
Parameters
----------
- grid : np.array
+ grid : ndarray
List of mesh evaluation points.
- exact : np.array
+ exact : ndarray
Array containing exact evaluation of a function.
- approx : np.array
+ approx : ndarray
Array containing approximate evaluation of a function.
color_exact : str
String describing color to plot exact solution.
@@ -46,14 +53,14 @@ def plot_solution_and_approx(grid, exact, approx, color_exact, color_approx):
plt.title('Solution and Approximation')
-def plot_semilog_error(grid, pointwise_error):
- """"Plots semi-logarithmic error between approximate and exact solution.
+def plot_semilog_error(grid: ndarray, pointwise_error: ndarray) -> None:
+ """Plots semi-logarithmic error between approximate and exact solution.
Parameters
----------
- grid : np.array
+ grid : ndarray
List of mesh evaluation points.
- pointwise_error : np.array
+ pointwise_error : ndarray
Array containing pointwise difference between exact and approximate solution.
"""
@@ -64,16 +71,16 @@ def plot_semilog_error(grid, pointwise_error):
plt.title('Semilog Error plotted at Evaluation points')
-def plot_error(grid, exact, approx):
- """"Plots error between approximate and exact solution.
+def plot_error(grid: ndarray, exact: ndarray, approx: ndarray) -> None:
+ """Plots error between approximate and exact solution.
Parameters
----------
- grid : np.array
+ grid : ndarray
List of mesh evaluation points.
- exact : np.array
+ exact : ndarray
Array containing exact evaluation of a function.
- approx : np.array
+ approx : ndarray
Array containing approximate evaluation of a function.
"""
@@ -84,8 +91,8 @@ def plot_error(grid, exact, approx):
plt.title('Errors')
-def plot_shock_tube(num_grid_cells, troubled_cell_history, time_history):
- """"Plots shock tube.
+def plot_shock_tube(num_grid_cells: int, troubled_cell_history: list, time_history: list) -> None:
+ """Plots shock tube.
Plots detected troubled cells over time to depict the evolution of shocks as shock tubes.
@@ -95,7 +102,7 @@ def plot_shock_tube(num_grid_cells, troubled_cell_history, time_history):
Number of cells in the mesh. Usually exponential of 2.
troubled_cell_history : list
List of detected troubled cells for each time step.
- time_history:
+ time_history: list
List of value of each time step.
"""
@@ -110,21 +117,22 @@ def plot_shock_tube(num_grid_cells, troubled_cell_history, time_history):
plt.title('Shock Tubes')
-def plot_details(fine_projection, fine_mesh, coarse_projection, basis, wavelet, multiwavelet_coeffs,
- num_coarse_grid_cells, polynomial_degree):
- """"Plots details of projection to coarser mesh..
+def plot_details(fine_projection: ndarray, fine_mesh: ndarray, coarse_projection: ndarray,
+ basis: ndarray, wavelet: ndarray, multiwavelet_coeffs: ndarray,
+ num_coarse_grid_cells: int, polynomial_degree: int) -> None:
+ """Plots details of projection to coarser mesh.
Parameters
----------
- fine_projection, coarse_projection : np.array
+ fine_projection, coarse_projection : ndarray
Matrix of projection for each polynomial degree.
- fine_mesh : np.array
+ fine_mesh : ndarray
List of evaluation points for fine mesh.
- basis : np.array
+ basis : ndarray
Basis vector for calculation.
- wavelet : np.array
+ wavelet : ndarray
Wavelet vector for calculation.
- multiwavelet_coeffs : np.array
+ multiwavelet_coeffs : ndarray
Matrix of multiwavelet coefficients.
num_coarse_grid_cells : int
Number of cells in the coarse mesh (half the cells of the fine mesh).
@@ -157,23 +165,24 @@ def plot_details(fine_projection, fine_mesh, coarse_projection, basis, wavelet,
plt.title('Wavelet Coefficients')
-def calculate_approximate_solution(projection, points, polynomial_degree, basis):
+def calculate_approximate_solution(projection: ndarray, points: ndarray, polynomial_degree: int,
+ basis: ndarray) -> ndarray:
"""Calculates approximate solution.
Parameters
----------
- projection : np.array
+ projection : ndarray
Matrix of projection for each polynomial degree.
- points : np.array
+ points : ndarray
List of evaluation points for mesh.
polynomial_degree : int
Polynomial degree.
- basis : np.array
+ basis : ndarray
Basis vector for calculation.
Returns
-------
- np.array
+ ndarray
Array containing approximate evaluation of a function.
"""
@@ -190,13 +199,14 @@ def calculate_approximate_solution(projection, points, polynomial_degree, basis)
return np.reshape(np.array(approx), (1, len(approx) * num_points))
-def calculate_exact_solution(mesh, cell_len, wave_speed, final_time, interval_len, quadrature,
- init_cond):
+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 : array
+ mesh : ndarray
List of mesh valuation points.
cell_len : float
Length of a cell in mesh.
@@ -213,7 +223,9 @@ def calculate_exact_solution(mesh, cell_len, wave_speed, final_time, interval_le
Returns
-------
- np.array
+ grid: ndarray
+ Array containing evaluation grid for a function.
+ exact: ndarray
Array containing exact evaluation of a function.
"""
@@ -239,21 +251,17 @@ def calculate_exact_solution(mesh, cell_len, wave_speed, final_time, interval_le
return grid, exact
-def plot_classification_accuracy(evaluation_dict, colors):
+def plot_classification_accuracy(evaluation_dict: dict, colors: dict) -> None:
"""Plots classification accuracy.
- Plots the accuracy, precision, and recall in a bar plot.
+ Plots given evaluation measures in a bar plot for each model.
Parameters
----------
- precision : float
- Precision of classification.
- recall : float
- Recall of classification.
- accuracy : float
- Accuracy of classification.
- xlabels : list
- List of strings for x-axis labels.
+ evaluation_dict: dict
+ Dictionary containing classification evaluation data.
+ colors: dict
+ Dictionary containing plotting colors.
"""
model_names = evaluation_dict[list(colors.keys())[0]].keys()
@@ -277,7 +285,19 @@ def plot_classification_accuracy(evaluation_dict, colors):
ax.legend(loc='upper right')
-def plot_boxplot(evaluation_dict, colors):
+def plot_boxplot(evaluation_dict: dict, colors: dict) -> None:
+ """Plots classification accuracy.
+
+ Plots given evaluation measures in a boxplot for each model.
+
+ Parameters
+ ----------
+ evaluation_dict: dict
+ Dictionary containing classification evaluation data.
+ colors: dict
+ Dictionary containing plotting colors.
+
+ """
model_names = evaluation_dict[list(colors.keys())[0]].keys()
font_size = 16 - (len(max(model_names, key=len))//3)
fig = plt.figure('boxplot_accuracy')