def main():
dataset = []
# create a random dataset with points on the X=Y axis
for i in range(100):
for n in range(randint(1, 10)):
dataset.append((i+randint(-5,+5), i+randint(-5,+5)))
dataset = np.array(dataset)
draw(dataset, 'before.png')
# run a PCA to 2 dimensions for this dataset
transformed_dataset = RandomizedPCA(2).fit(dataset).transform(dataset)
from ipdb import set_trace; set_trace()
draw_2d(transformed_dataset, 'after.png')
def main():
dataset = []
# create a random dataset with points on the X=Y axis
for i in range(100):
for n in range(randint(1, 10)):
dataset.append((i + randint(-5, +5), i + randint(-5, +5)))
dataset = np.array(dataset)
draw(dataset, 'before.png')
# run a PCA to 2 dimensions for this dataset
transformed_dataset = RandomizedPCA(2).fit(dataset).transform(dataset)
from ipdb import set_trace
set_trace()
draw_2d(transformed_dataset, 'after.png')
def _draw(dataset, filename, title):
pca = RandomizedPCA(2)
pca.fit(dataset)
X = pca.transform(dataset)
draw_2d(X, filename, title)
def _draw(dataset, filename, title):
pca = RandomizedPCA(2)
pca.fit(dataset)
X = pca.transform(dataset)
draw_2d(X, filename, title)