Delete digit.py

multimodal/datasets/digit.py

-from sklearn import datasets
-import numpy as np
-import PIL
-import matplotlib.pyplot as plt
-import os
-import matplotlib.pyplot as plt
-from multimodal.datasets.base import load_dict, save_dict
-from multimodal.tests.data.get_dataset_path import get_dataset_path
-from multimodal.datasets.data_sample import MultiModalArray
-from multimodal.kernels.mvml import MVML
-#Load the digits dataset
-digits = datasets.load_digits()
-
-#Display the first digit
-plt.figure(1, figsize=(3, 3))
-plt.imshow(digits.images[-1], cmap=plt.cm.gray_r, interpolation='nearest')
-plt.show()
-colors = digits.data
-gradiant = np.gradient(digits.images, axis=[1,2])
-print(gradiant[0].shape)
-gradiant0 = gradiant[0].reshape(colors.shape[0], colors.shape[1])
-gradiant1 = gradiant[1].reshape(colors.shape[0], colors.shape[1])
-for ind in range(digits.images.shape[0]):
-    ima0 = digits.images[ind, :,:]
-    ima1 = gradiant[0][ind, :,:]
-    ima2 = gradiant[1][ind, :,:]
-    ama_pil0 = PIL.Image.fromarray(ima0, mode=None)
-    ama_pil1 = PIL.Image.fromarray(ima1, mode=None)
-    ama_pil2 = PIL.Image.fromarray(ima2, mode=None)
-    histo_color = np.asarray(ama_pil0.histogram())
-    histo_gradiant0 = np.asarray(ama_pil1.histogram())
-    histo_gradiant1 = np.asarray(ama_pil2.histogram())
-    if ind==0:
-        list_histogram_color = histo_color
-        list_histogram_gradiant0 = histo_gradiant0
-        list_histogram_gradiant1 = histo_gradiant1
-    else:
-        list_histogram_color = np.vstack((list_histogram_color, histo_color))
-        list_histogram_gradiant0 = np.vstack((list_histogram_gradiant0, histo_gradiant0))
-        list_histogram_gradiant1 = np.vstack((list_histogram_gradiant1, histo_gradiant1))
-
-dict_digit = {0: list_histogram_color, 1: list_histogram_gradiant0, 2: list_histogram_gradiant1}
-
-
-print(list_histogram_color.shape)
-print(list_histogram_gradiant0.shape)
-print(list_histogram_gradiant1.shape)
-file = get_dataset_path("digit_histogram.npy")
-save_dict(dict_digit, file)
-
-d2 = load_dict(file)
-
-figure = plt.figure(figsize=(27, 9))
-ax = plt.subplot(2,1,1)
-
-ax.scatter(list_histogram_color[:,3], list_histogram_color[:,4], c=digits.target, edgecolors='k')
-ax = plt.subplot(2,1,2)
-ax.scatter(list_histogram_color[:,0], list_histogram_color[:,1], c=digits.target, edgecolors='k')
-plt.show()
-
-mvml = MVML(lmbda=0.1, eta=1, nystrom_param=0.2)
-mvml.fit(d2)