most basic python programs code example

Example 1: best python programs

def f(x, y):
    return np.sin(np.sqrt(x ** 2 + y ** 2))
 
x = np.linspace(-6, 6, 30)
y = np.linspace(-6, 6, 30)
 
X, Y = np.meshgrid(x, y)
Z = f(X, Y)fig = plt.figure()
ax = plt.axes(projection='3d')
ax.contour3D(X, Y, Z, 50, cmap='binary')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z');

Example 2: best python programs

import numpy as np
 
import tensorflow as tf
 
 
 
from include.data import get_data_set
 
from include.model import model
 
 
 
 
 
test_x, test_y = get_data_set("test")
 
x, y, output, y_pred_cls, global_step, learning_rate = model()
 
 
 
 
 
_BATCH_SIZE = 128
 
_CLASS_SIZE = 10
 
_SAVE_PATH = "./tensorboard/cifar-10-v1.0.0/"
 
 
 
 
 
saver = tf.train.Saver()
 
sess = tf.Session()
 
 
 
 
 
try:
 
    print("
Trying to restore last checkpoint ...")
 
    last_chk_path = tf.train.latest_checkpoint(checkpoint_dir=_SAVE_PATH)
 
    saver.restore(sess, save_path=last_chk_path)
 
    print("Restored checkpoint from:", last_chk_path)
 
except ValueError:
 
    print("
Failed to restore checkpoint. Initializing variables instead.")
 
    sess.run(tf.global_variables_initializer())
 
 
 
 
 
def main():
 
    i = 0
 
    predicted_class = np.zeros(shape=len(test_x), dtype=np.int)
 
    while i < len(test_x):
 
        j = min(i + _BATCH_SIZE, len(test_x))
 
        batch_xs = test_x[i:j, :]
 
        batch_ys = test_y[i:j, :]
 
        predicted_class[i:j] = sess.run(y_pred_cls, feed_dict={x: batch_xs, y: batch_ys})
 
        i = j
 
 
 
    correct = (np.argmax(test_y, axis=1) == predicted_class)
 
    acc = correct.mean() * 100
 
    correct_numbers = correct.sum()
 
    print()
 
    print("Accuracy on Test-Set: {0:.2f}% ({1} / {2})".format(acc, correct_numbers, len(test_x)))
 
if __name__ == "__main__":
 
    main()
 
sess.close()