tatamiya

def linear_fit(x, y):
    N_ = len(x)
    X_, y_ = np.vstack([x, np.ones(N_)]).T, np.array(y)

    fit_results = np.linalg.lstsq(X_, y_, rcond=None)

    a_, b_ = fit_results[0]
    r2error_ = fit_results[1][0]

    return a_, b_, r2error_

tatamiya

def sum_from_one(k):
    sum = 0
    for i in range(1, k+1):
        sum += i

    return sum

sum_list = []
for i in range(0, N):
    sum_list.append(sum_from_one(i))

tatamiya

from PIL import Image
import numpy as np
from sklearn.decomposition import PCA

n_components=10
ncomp_selected = 0 # the index of the PCA component to select (int or list)

# read image
pilimg_pumpkin = Image.open('pumpkin.jpg')
npimg_pumpkin = np.array(pilimg_pumpkin)