opensource/ManimML
1
0
Fork 0
mirror of https://github.com/helblazer811/ManimML.git synced 2025-05-20 20:16:32 +08:00
Code Issues Packages Projects Releases Wiki Activity

Removed Conv2D because it can be done using just Conv3D and renamed Conv3D to Conv2D to correspond to the spatial conv dimenson not the scene dimension, which is more inline with convention.

Browse Source
This commit is contained in:
Alec Helbling
2023-01-15 14:35:26 +09:00
parent ba63116b37
commit 42b6e37b16
23 changed files with 358 additions and 467 deletions
Download Patch File Download Diff File Expand all files Collapse all files

5
tests/test_decision_tree.py
View File

@ -9,7 +9,6 @@ from sklearn import datasets
import sklearn
import matplotlib.pyplot as plt
def learn_iris_decision_tree(iris):
decision_tree = DecisionTreeClassifier(
random_state=1, max_depth=3, max_leaf_nodes=6
@ -18,13 +17,11 @@ def learn_iris_decision_tree(iris):
# output the decisioin tree in some format
return decision_tree
def make_sklearn_tree(dataset, max_tree_depth=3):
tree = learn_iris_decision_tree(dataset)
feature_names = dataset.feature_names[0:2]
return tree, tree.tree_
class DecisionTreeScene(Scene):
def construct(self):
"""Makes a decision tree object"""
@ -32,7 +29,6 @@ class DecisionTreeScene(Scene):
clf, sklearn_tree = make_sklearn_tree(iris_dataset)
# sklearn.tree.plot_tree(clf, node_ids=True)
# plt.show()
decision_tree = DecisionTreeDiagram(
sklearn_tree,
class_images_paths=[
@ -48,7 +44,6 @@ class DecisionTreeScene(Scene):
self.play(create_decision_tree)
# self.play(create_decision_tree)
class SurfacePlot(Scene):
def construct(self):
iris_dataset = datasets.load_iris()