added some examples for ulab module - see https://micropython-ulab.readthedocs.io/en/stable/index.html for full documentation
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# PacMan par Kevin FEDYNA
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# https://nsi.xyz/numapps/pac-man-en-python-numworks/
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from kandinsky import fill_rect, draw_string
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from ion import keydown
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from math import sqrt
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# Snake from Golem64
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# https://my.numworks.com/python/golem64/snake
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#Version 1.7 STABLE
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#Tip: You should try to press
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#some keys in the menu...
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# code to be run in micropython
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from ulab import numpy as np
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x = np.linspace(0, 10, num=1024)
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y = np.sin(x)
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z = np.zeros(len(x))
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a, b = np.fft.fft(x)
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print('real part:\t', a)
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print('\nimaginary part:\t', b)
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c, d = np.fft.fft(x, z)
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print('\nreal part:\t', c)
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print('\nimaginary part:\t', d)
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from ulab import numpy as np
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array = np.array([
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[3, 7, 1],
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[10, 3, 2],
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[5, 6, 7]
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])
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print(array)
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print()
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# Sort the whole array
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print(np.sort(array, axis=None))
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# Sort along each row
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print(np.sort(array, axis=1))
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# Sort along each column
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print(np.sort(array, axis=0))
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from ulab import numpy as np
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list = [
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np.array([3, 2, 8, 9]),
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np.array([4, 12, 34, 25, 78]),
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np.array([23, 12, 67])
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]
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result = []
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for i in range(len(list)):
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result.append(np.mean(list[i]))
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print(result)
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# code to be run in micropython
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from ulab import numpy as np
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a = np.array([1, 2, 3, 4], dtype=np.uint8)
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b = np.array([1+1j, 2-2j, 3+3j, 4-4j], dtype=np.complex)
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print('a:\t\t', a)
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print('conjugate(a):\t', np.conjugate(a))
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print()
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print('b:\t\t', b)
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print('conjugate(b):\t', np.conjugate(b))
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# code to be run in micropython
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from ulab import numpy as np
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a = np.array([1, 2, 3, 4, 5])
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print("a: \t", a)
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print("a flipped:\t", np.flip(a))
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a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.uint8)
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print("\na flipped horizontally\n", np.flip(a, axis=1))
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print("\na flipped vertically\n", np.flip(a, axis=0))
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print("\na flipped horizontally+vertically\n", np.flip(a))
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# code to be run in micropython
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from ulab import numpy as np
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m = np.array([[1, 2, 3], [4, 5, 6], [7, 10, 9]], dtype=np.uint8)
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n = np.linalg.inv(m)
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print("m:\n", m)
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print("\nm^-1:\n", n)
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# this should be the unit matrix
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print("\nm*m^-1:\n", np.dot(m, n))
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m = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype=np.uint8)
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n = np.array([[1, 2], [3, 4], [5, 6], [7, 8]], dtype=np.uint8)
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print(m)
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print(n)
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print(np.dot(m, n))
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# code to be run in micropython
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from ulab import numpy as np
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a = np.array([1, 2, 3], dtype=np.uint16)
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print("a:\t\t", a)
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print("imag(a):\t", np.imag(a))
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b = np.array([1, 2+1j, 3-1j], dtype=np.complex)
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print("\nb:\t\t", b)
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print("imag(b):\t", np.imag(b))
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# code to be run in micropython
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from ulab import numpy as np
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from ulab import scipy as spy
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a = np.array([[3, 2, 1, 0], [2, 1, 0, 1], [1, 0, 1, 4], [1, 2, 1, 8]])
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b = np.array([4, 2, 4, 2])
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print('a:\n')
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print(a)
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print('\nb: ', b)
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x = spy.linalg.solve_triangular(a, b, lower=True)
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print('='*20)
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print('x: ', x)
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print('\ndot(a, x): ', np.dot(a, x))
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try:
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from ulab import numpy
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from ulab import scipy
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except ImportError:
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import numpy
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import scipy.special
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x = numpy.array([1, 2, 3])
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scipy.special.erf(x)
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import ulab
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print('you are running ulab version', ulab.__version__)
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version = ulab.__version__
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version_dims = version.split('-')[1]
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version_num = int(version_dims.replace('D', ''))
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print('version string: ', version)
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print('version dimensions: ', version_dims)
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print('numerical value of dimensions: ', version_num)
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