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August 22, 2017 10:01
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numpy example
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import numpy as np | |
''' | |
The following code is to help you play with Numpy, which is a library | |
that provides functions that are especially useful when you have to | |
work with large arrays and matrices of numeric data, like doing | |
matrix matrix multiplications. Also, Numpy is battle tested and | |
optimized so that it runs fast, much faster than if you were working | |
with Python lists directly. | |
''' | |
''' | |
The array object class is the foundation of Numpy, and Numpy arrays are like | |
lists in Python, except that every thing inside an array must be of the | |
same type, like int or float. | |
''' | |
# Change False to True to see Numpy arrays in action | |
if True: | |
array = np.array([1, 4, 5, 8], float) | |
print array | |
print "" | |
array = np.array([[1, 2, 3], [4, 5, 6]], float) # a 2D array/Matrix | |
print array | |
''' | |
You can index, slice, and manipulate a Numpy array much like you would with a | |
a Python list. | |
''' | |
# Change False to True to see array indexing and slicing in action | |
if True: | |
array = np.array([1, 4, 5, 8], float) | |
print array | |
print "" | |
print array[1] | |
print "" | |
print array[:2] | |
print "" | |
array[1] = 5.0 | |
print array[1] | |
# Change False to True to see Matrix indexing and slicing in action | |
if True: | |
two_D_array = np.array([[1, 2, 3], [4, 5, 6]], float) | |
print two_D_array | |
print "" | |
print two_D_array[1][1] | |
print "" | |
print two_D_array[1, :] | |
print "" | |
print two_D_array[:, 2] | |
''' | |
Here are some arithmetic operations that you can do with Numpy arrays | |
''' | |
# Change False to True to see Array arithmetics in action | |
if True: | |
array_1 = np.array([1, 2, 3], float) | |
array_2 = np.array([5, 2, 6], float) | |
print array_1 + array_2 | |
print "" | |
print array_1 - array_2 | |
print "" | |
print array_1 * array_2 | |
# Change False to True to see Matrix arithmetics in action | |
if False: | |
array_1 = np.array([[1, 2], [3, 4]], float) | |
array_2 = np.array([[5, 6], [7, 8]], float) | |
print array_1 + array_2 | |
print "" | |
print array_1 - array_2 | |
print "" | |
print array_1 * array_2 | |
''' | |
In addition to the standard arthimetic operations, Numpy also has a range of | |
other mathematical operations that you can apply to Numpy arrays, such as | |
mean and dot product. | |
Both of these functions will be useful in later programming quizzes. | |
''' | |
if False: | |
array_1 = np.array([1, 2, 3], float) | |
array_2 = np.array([[6], [7], [8]], float) | |
print np.mean(array_1) | |
print np.mean(array_2) | |
print "" | |
print np.dot(array_1, array_2) |
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