Two-dimensional graph
import matplotlib.pyplot as plt
from scipy.io import loadmat
alldata = loadmat('E:\BCI\physionet\mat\s1data\Model_csp3_1\model2\model2_3\Real_fea.mat')
data=alldata['feature_L_R']
ax = plt.subplot()
ax.set_title("Input data")
# Plot the training points
ax.scatter(data[0:35, 0],data[0:35, 1] , c='r',label='left',
edgecolors = 'k') # left eigenvector selection imaginary two-dimensional
ax.scatter(data[35:70, 0],data[35:70, 1] , c='g',label='right',
edgecolors = 'k') # right eigenvector selection imaginary two-dimensional
plt.legend (loc = 'upper right') # icon in the upper right of FIG.
plt.show()
The second painting:
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
cm = plt.cm.RdBu
cm_bright = ListedColormap(['#FF0000', '#0000FF'])
ax = plt.subplot(len(datasets), len(classifiers) + 1, i)
ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright,
edgecolors='k')
# and testing points
ax.scatter(X_test[:, 0], X_test[:, 1], c=y_test, cmap=cm_bright, alpha=0.6,
edgecolors='k')
plt.show()
Code Description:
cm_bright: representation drawing two colors
X_train: data format is two-dimensional array of 2 * 100, 100 features, each feature and feature two values, corresponding to the scattergram x and y. Y_train corresponding to one-dimensional array 100 has a value of 0 or 1, class represents the training data 100 for one color, as in the scattergram to another in a scatter plot 1 0 a color.
Ibid format of test data.
Three-dimensional representation
import matplotlib.pyplot as plt
from scipy.io import loadmat
alldata = loadmat('E:\BCI\physionet\mat\s1data\Model_csp3_1\model2\model2_3\Real_fea.mat')
data=alldata['feature_L_R']
for i in range(34):
ax = plt.subplot (111, projection = '3d') # create a three-dimensional drawing Engineering
# The data points into three parts painted with the color discrimination
ax.scatter (data [0: 35, i], data [0: 35, i + 1], data [0: 35, i + 2], c = 'r') # plotted data points
ax.scatter(data[35:70,i],data[35:70,i+1],data[35:70,i+2],c='g')
ax.set_zlabel ( 'Z') # axes
ax.set_ylabel('Y')
ax.set_xlabel('X')
plt.show()
Description: data Data is 35 * 36,
