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Modulo (#734)
* add modulo operator * fix module loops * add in-place modulo operator * update readme * add test files, update documentation
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‎docs/manual/source/conf.py‎

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author = 'Zoltán Vörös'
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# The full version, including alpha/beta/rc tags
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release = '6.7.3'
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release = '6.9.0'
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# -- General configuration ---------------------------------------------------

‎docs/manual/source/ulab-ndarray.rst‎

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Binary operators
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================
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``ulab`` implements the ``+``, ``-``, ``*``, ``/``, ``**``, ``<``,
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``>``, ``<=``, ``>=``, ``==``, ``!=``, ``+=``, ``-=``, ``*=``, ``/=``,
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``**=`` binary operators, as well as the ``AND``, ``OR``, ``XOR``
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bit-wise operators that work element-wise. Note that the bit-wise
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operators will raise an exception, if either of the operands is of
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``float`` or ``complex`` type.
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``ulab`` implements the ``+``, ``-``, ``*``, ``/``, ``**``, ``%``,
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``<``, ``>``, ``<=``, ``>=``, ``==``, ``!=``, ``+=``, ``-=``, ``*=``,
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``/=``, ``**=``, ``%=`` binary operators, as well as the ``AND``,
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``OR``, ``XOR`` bit-wise operators that work element-wise. Note that the
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bit-wise operators will raise an exception, if either of the operands is
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of ``float`` or ``complex`` type.
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Broadcasting is available, meaning that the two operands do not even
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have to have the same shape. If the lengths along the respective axes

‎docs/ulab-convert.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2022-02-09T06:27:15.118699Z",
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"author = 'Zoltán Vörös'\n",
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"\n",
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"# The full version, including alpha/beta/rc tags\n",
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"release = '6.7.3'\n",
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"release = '6.9.0'\n",
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"\n",
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"\n",
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"# -- General configuration ---------------------------------------------------\n",
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2022-02-09T06:27:21.647179Z",
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 4,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2022-02-09T06:27:42.024028Z",

‎tests/2d/numpy/modulo.py‎

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try:
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from ulab import numpy as np
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except:
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import numpy as np
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dtypes = (np.uint8, np.int8, np.uint16, np.int16, np.float)
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for dtype1 in dtypes:
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x1 = np.array(range(6), dtype=dtype1).reshape((2, 3))
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for dtype2 in dtypes:
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x2 = np.array(range(1, 4), dtype=dtype2)
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print(x1 % x2)
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print()
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print('=' * 30)
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print('inplace modulo')
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print('=' * 30)
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print()
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for dtype1 in dtypes:
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x1 = np.array(range(6), dtype=dtype1).reshape((2, 3))
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for dtype2 in dtypes:
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x2 = np.array(range(1, 4), dtype=dtype2)
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x1 %= x2
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print(x1)

‎tests/2d/numpy/modulo.py.exp‎

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array([[0, 1, 2],
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[0, 0, 2]], dtype=uint8)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=uint16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int8)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 0, 1],
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[0, 2, 0]], dtype=uint8)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=uint16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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==============================
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inplace modulo
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==============================
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array([[0, 1, 2],
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[0, 0, 2]], dtype=uint8)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0, 0, 1],
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[0, 2, 0]], dtype=uint8)
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array([[0, 0, 1],
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[0, 0, 0]], dtype=int16)
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array([[0.0, 0.0, 1.0],
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[0.0, 0.0, 0.0]], dtype=float64)
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array([[0.0, 0.0, 1.0],
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[0.0, 0.0, 0.0]], dtype=float64)
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array([[0.0, 0.0, 1.0],
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[0.0, 0.0, 0.0]], dtype=float64)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0, 1, 2],
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[0, 0, 2]], dtype=int16)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)
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array([[0.0, 1.0, 2.0],
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[0.0, 0.0, 2.0]], dtype=float64)

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