steffen/self-replicating-neural-networks
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Fixed exp pickle save. Added exp results. Fixed soup plot issue.

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This commit is contained in:
Maximilian Zorn
2021-06-20 17:09:17 +02:00
parent 1da5bd95d6
commit cf6eec639f
20 changed files with 64 additions and 47 deletions
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18
visualization.py
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@ -92,7 +92,6 @@ def plot_3d(matrices_weights_history, directory: Union[str, Path], population_si
wm = np.array(wh)
n, x, y = wm.shape
wm = wm.reshape(n, x * y)
#print(wm.shape, wm)
weight_histories.append(wm)
weight_data = np.array(weight_histories)
@ -104,7 +103,6 @@ def plot_3d(matrices_weights_history, directory: Union[str, Path], population_si
for transformed_trajectory, start_time in zip(np.split(weight_data_pca, n), start_times):
start_log_time = int(start_time / batch_size)
#print(start_time, start_log_time)
xdata = transformed_trajectory[start_log_time:, 0]
ydata = transformed_trajectory[start_log_time:, 1]
zdata = np.arange(start_time, len(ydata)*batch_size+start_time, batch_size).tolist()
@ -139,7 +137,7 @@ def plot_3d(matrices_weights_history, directory: Union[str, Path], population_si
else:
ax.scatter(np.asarray(xdata), np.asarray(ydata), zdata, s=3)
steps = mpatches.Patch(color="white", label=f"{z_axis_legend}: {len(matrices_weights_history)} steps")
#steps = mpatches.Patch(color="white", label=f"{z_axis_legend}: {len(matrices_weights_history)} steps")
population_size = mpatches.Patch(color="white", label=f"Population: {population_size} networks")
if z_axis_legend == "Self-application":
@ -147,14 +145,14 @@ def plot_3d(matrices_weights_history, directory: Union[str, Path], population_si
trained = mpatches.Patch(color="white", label=f"Trained: true")
else:
trained = mpatches.Patch(color="white", label=f"Trained: false")
ax.legend(handles=[steps, population_size, trained])
ax.legend(handles=[population_size, trained])
else:
ax.legend(handles=[steps, population_size])
ax.legend(handles=[population_size])
ax.set_title(f"PCA Weights history")
ax.set_xlabel("PCA X")
ax.set_ylabel("PCA Y")
ax.set_zlabel(f"Epochs")
ax.set_title(f"PCA Transformed Weight Trajectories")
ax.set_xlabel("PCA Transformed X-Axis")
ax.set_ylabel("PCA Transformed Y-Axis")
ax.set_zlabel(f"Self Training Steps")
# FIXME: Replace this kind of operation with pathlib.Path() object interactions
directory = Path(directory)
@ -168,7 +166,7 @@ def plot_3d(matrices_weights_history, directory: Union[str, Path], population_si
else:
plt.savefig(str(filepath))
# plt.show()
plt.show()
def plot_3d_self_train(nets_array: List, exp_name: str, directory: Union[str, Path], batch_size: int, plot_pca_together: bool):