solve_triangular(a, b, trans=0, lower=False, unit_diagonal=False, overwrite_b=False, debug=None, check_finite=True)
A triangular matrix
Right-hand side matrix in :None:None:`a x = b`
Use only data contained in the lower triangle of a. Default is to use upper triangle.
Type of system to solve:
======== ========= trans system ======== ========= 0 or 'N' a x = b 1 or 'T' a^T x = b 2 or 'C' a^H x = b ======== =========
If True, diagonal elements of a are assumed to be 1 and will not be referenced.
Allow overwriting data in b (may enhance performance)
Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.
If a is singular
Solve the equation :None:None:`a x = b` for x, assuming a is a triangular matrix.
[3 0 0 0] [4]
a = [2 1 0 0] b = [2]
[1 0 1 0] [4] [1 1 1 1] [2]
>>> from scipy.linalg import solve_triangular
... a = np.array([[3, 0, 0, 0], [2, 1, 0, 0], [1, 0, 1, 0], [1, 1, 1, 1]])
... b = np.array([4, 2, 4, 2])
... x = solve_triangular(a, b, lower=True)
... x array([ 1.33333333, -0.66666667, 2.66666667, -1.33333333])
>>> a.dot(x) # Check the result array([ 4., 2., 4., 2.])See :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.linalg._basic.solve_triangular
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