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NumPy | tri method
schedule Aug 12, 2023
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Numpy's tri(~) method creates a 2D Numpy array that represents a lower triangular matrix. The values at and below the main diagonal are filled with 1s, while everywhere else with 0s.
Parameters
1. N | int
The number of rows of the resulting array.
2. M | int | optional
The number of columns of the resulting array. By default, M=N.
3. klink | int | optional
The number of diagonals to exclude or include.
A positive value for k represents inclusion. k=1 means that we include an additional diagonal on top of main diagonal.
A negative value for k represents exclusion. k=-1 means that the main diagonal is excluded. k=-2 means that the main diagonal and the diagonal underneath are excluded.
By default, k=0, which means that a perfect lower triangle is returned.
4. dtype | string or type | optional
The data type of the resulting array. By default, dtype=float.
Return value
A Numpy array representing a lower triangular matrix.
Examples
Basic usage
To create a 3 by 3 lower triangular matrix:
np.tri(3)
array([[ 1., 0., 0.], [ 1., 1., 0.], [ 1., 1., 1.]])
To create a 3 by 4 lower triangular matrix of type int:
np.tri(3, 4, dtype=int)
array([[1, 0, 0, 0], [1, 1, 0, 0], [1, 1, 1, 0]])
Specifying a positive k
To include an additional diagonal, set k=1:
np.tri(3, k=1, dtype=int)
array([[1, 1, 0], [1, 1, 1], [1, 1, 1]])
Specifying a negative k
To exclude the main diagonal, set k=-1:
np.tri(3, k=-1)
array([[ 0., 0., 0.], [ 1., 0., 0.], [ 1., 1., 0.]])
Published by Isshin Inada
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