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journal_basins.py debugged II

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Questions for functionalities_test.py
corrected some fixes
Redo and implementation of everything path related now using pathlib.Path
This commit is contained in:
steffen-illium
2021-05-16 13:35:38 +02:00
parent 042188f15a
commit b1472479cb
4 changed files with 54 additions and 53 deletions
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71
visualization.py
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@ -7,7 +7,6 @@ import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import numpy as np
from sklearn.decomposition import PCA
import os.path
import random
import string
@ -20,7 +19,7 @@ def plot_output(output):
plt.show()
def plot_loss(loss_array, directory_name, batch_size=1):
def plot_loss(loss_array, directory, batch_size=1):
""" Plotting the evolution of the loss function."""
fig = plt.figure()
@ -34,15 +33,15 @@ def plot_loss(loss_array, directory_name, batch_size=1):
plt.xlabel("Epochs")
plt.ylabel("Loss")
filepath = f"./{directory_name}"
filename = f"{filepath}/_nets_loss_function.png"
plt.savefig(f"{filename}")
directory = Path(directory)
filename = "nets_loss_function.png"
file_path = directory / filename
plt.savefig(str(file_path))
# plt.show()
plt.clf()
def bar_chart_fixpoints(fixpoint_counter: Dict, population_size: int, directory_name: String, learning_rate: float,
def bar_chart_fixpoints(fixpoint_counter: Dict, population_size: int, directory: String, learning_rate: float,
exp_details: String, source_check=None):
""" Plotting the number of fixpoints in a barchart. """
@ -66,15 +65,15 @@ def bar_chart_fixpoints(fixpoint_counter: Dict, population_size: int, directory_
plt.bar(range(len(fixpoint_counter)), list(fixpoint_counter.values()), align='center')
plt.xticks(range(len(fixpoint_counter)), list(fixpoint_counter.keys()))
filepath = f"./{directory_name}"
filename = f"{filepath}/{str(population_size)}_nets_fixpoints_barchart.png"
plt.savefig(f"{filename}")
directory = Path(directory)
filename = f"{str(population_size)}_nets_fixpoints_barchart.png"
filepath = directory / filename
plt.savefig(str(filepath))
plt.clf()
# plt.show()
def plot_3d(matrices_weights_history, folder_name, population_size, z_axis_legend, exp_name="experiment", is_trained="",
def plot_3d(matrices_weights_history, directory, population_size, z_axis_legend, exp_name="experiment", is_trained="",
batch_size=1):
""" Plotting the the weights of the nets in a 3d form using principal component analysis (PCA) """
@ -121,10 +120,10 @@ def plot_3d(matrices_weights_history, folder_name, population_size, z_axis_legen
ax.set_zlabel(f"Epochs")
# FIXME: Replace this kind of operation with pathlib.Path() object interactions
folder = Path(folder_name)
folder.mkdir(parents=True, exist_ok=True)
directory = Path(directory)
directory.mkdir(parents=True, exist_ok=True)
filename = f"{exp_name}{is_trained}.png"
filepath = folder / filename
filepath = directory / filename
if filepath.exists():
letters = string.ascii_lowercase
random_letters = ''.join(random.choice(letters) for _ in range(5))
@ -133,10 +132,9 @@ def plot_3d(matrices_weights_history, folder_name, population_size, z_axis_legen
plt.savefig(str(filepath))
plt.show()
#plt.clf()
def plot_3d_self_train(nets_array: List, exp_name: String, directory_name: String, batch_size: int):
def plot_3d_self_train(nets_array: List, exp_name: String, directory: String, batch_size: int):
""" Plotting the evolution of the weights in a 3D space when doing self training. """
matrices_weights_history = []
@ -149,7 +147,7 @@ def plot_3d_self_train(nets_array: List, exp_name: String, directory_name: Strin
z_axis_legend = "epochs"
return plot_3d(matrices_weights_history, directory_name, len(nets_array), z_axis_legend, exp_name, "", batch_size)
return plot_3d(matrices_weights_history, directory, len(nets_array), z_axis_legend, exp_name, "", batch_size)
def plot_3d_self_application(nets_array: List, exp_name: String, directory_name: String, batch_size: int) -> None:
@ -168,23 +166,23 @@ def plot_3d_self_application(nets_array: List, exp_name: String, directory_name:
else:
is_trained = "_not_trained"
# Fixme: Are the both following lines on the correct intendation? -> Value of "is_trained" changes multiple times!
z_axis_legend = "epochs"
plot_3d(matrices_weights_history, directory_name, len(nets_array), z_axis_legend, exp_name, is_trained, batch_size)
def plot_3d_soup(nets_list, exp_name, directory_name):
def plot_3d_soup(nets_list, exp_name, directory):
""" Plotting the evolution of the weights in a 3D space for the soup environment. """
# This batch size is not relevant for soups. To not affect the number of epochs shown in the 3D plot,
# will send forward the number "1" for batch size with the variable <irrelevant_batch_size>.
irrelevant_batch_size = 1
plot_3d_self_train(nets_list, exp_name, directory_name, irrelevant_batch_size)
plot_3d_self_train(nets_list, exp_name, directory, irrelevant_batch_size)
def line_chart_fixpoints(fixpoint_counters_history: list, epochs: int, ST_steps_between_SA: int,
SA_steps, directory_name: String, population_size: int):
SA_steps, directory: String, population_size: int):
""" Plotting the percentage of fixpoints after each iteration of SA & ST steps. """
fig = plt.figure()
@ -205,15 +203,15 @@ def line_chart_fixpoints(fixpoint_counters_history: list, epochs: int, ST_steps_
plt.plot(ST_steps_per_SA, fixpoint_counters_history, color="green", marker="o")
filepath = f"./{directory_name}"
filename = f"{filepath}/{str(population_size)}_nets_fixpoints_linechart.png"
plt.savefig(f"{filename}")
directory = Path(directory)
filename = f"{str(population_size)}_nets_fixpoints_linechart.png"
filepath = directory / filename
plt.savefig(str(filepath))
plt.clf()
# plt.show()
def box_plot(data, directory_name, population_size):
def box_plot(data, directory, population_size):
fig, axs = plt.subplots(nrows=1, ncols=2, figsize=(10, 7))
# ax = fig.add_axes([0, 0, 1, 1])
@ -226,16 +224,17 @@ def box_plot(data, directory_name, population_size):
axs[1].boxplot(data)
axs[1].set_title('Box plot')
filepath = f"./{directory_name}"
filename = f"{filepath}/{str(population_size)}_nets_fixpoints_barchart.png"
plt.savefig(f"{filename}")
directory = Path(directory)
filename = f"{str(population_size)}_nets_fixpoints_barchart.png"
filepath = directory / filename
# plt.show()
plt.savefig(str(filepath))
plt.clf()
def write_file(text, directory_name):
filepath = f"./{directory_name}"
f = open(f"{filepath}/experiment.txt", "w+")
f.write(text)
f.close()
def write_file(text, directory):
directory = Path(directory)
filepath = directory / 'experiment.txt'
with filepath.open('w+') as f:
f.write(text)
f.close()