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+--- Thread: Some of Python's linalg commands in HP Prime (/thread-16897.html)
Some of Python's linalg commands in HP Prime - Eddie W. Shore - 05-08-2021 01:49 PM
Matrix Format [ [ row ], [ row ], … [ row ] ]
linspace(start, stop, number of points desired + 1)
arange(start, stop, step size); default step size: 1; returns a 1 row array from start to stop using step size
identity(n): returns an identity matrix as n x n
transpose(matrix): transpose of a matrix
inv(matrix): inverse of a matrix
shape(matrix): returns the dimensions of the matrix in an ordered pair (row, columns)
rref(matrix): row reduced echelon form of a matrix
det(matrix): determinant of a square matrix
peval(array of coefficients, x): polynomial evaluation (order is from high to low), can take complex arguments
horner(array of coefficients, x): polynomial evaluation using Horner’s method
pceoff(array of roots): returns an array representing a polynomial’s coefficients, can take complex arguments
proot(array of coefficients): returns an array of roots, can take complex arguments
add(array, array) or add(matrix, matrix): addition element by element
sub(array, array) or sub(matrix, matrix): subtraction element by element
dot(array, array): dot product
cross(array, array): cross product
imag(complex number): imaginary part – works on arrays and matrices
real(complex number): real part – works on arrays and matrices
I believe that fft and ifft have to do with fast fourier transforms.
RE: Some of Python's linalg commands in HP Prime - cdmackay - 05-08-2021 11:00 PM
thanks Eddie.
(05-08-2021 01:49 PM)Eddie W. Shore Wrote: I believe that fft and ifft have to do with fast fourier transforms.
yup; the integrated Help has a few examples…
RE: Some of Python's linalg commands in HP Prime - John Keith - 05-09-2021 05:36 PM
Those sound like the function names from the Prime CAS and the 50g.
BTW, pcoeff is misspelled.
RE: Some of Python's linalg commands in HP Prime - Eddie W. Shore - 05-09-2021 05:58 PM
(05-09-2021 05:36 PM)John Keith Wrote: Those sound like the function names from the Prime CAS and the 50g.
BTW, pcoeff is misspelled.
Sorry. Good catch!
RE: Some of Python's linalg commands in HP Prime - cdmackay - 05-11-2021 06:47 PM
oops, sorry, my comment re Help of course refers to the CAS commands, whereas this thread is about Python… I need more coffee.
RE: Some of Python's linalg commands in HP Prime - robmio - 09-08-2021 10:10 PM
(05-08-2021 01:49 PM)Eddie W. Shore Wrote: Matrix Format [ [ row ], [ row ], … [ row ] ]
linspace(start, stop, number of points desired + 1)
arange(start, stop, step size); default step size: 1; returns a 1 row array from start to stop using step size
identity(n): returns an identity matrix as n x n
transpose(matrix): transpose of a matrix
inv(matrix): inverse of a matrix
shape(matrix): returns the dimensions of the matrix in an ordered pair (row, columns)
rref(matrix): row reduced echelon form of a matrix
det(matrix): determinant of a square matrix
peval(array of coefficients, x): polynomial evaluation (order is from high to low), can take complex arguments
horner(array of coefficients, x): polynomial evaluation using Horner’s method
pceoff(array of roots): returns an array representing a polynomial’s coefficients, can take complex arguments
proot(array of coefficients): returns an array of roots, can take complex arguments
add(array, array) or add(matrix, matrix): addition element by element
sub(array, array) or sub(matrix, matrix): subtraction element by element
dot(array, array): dot product
cross(array, array): cross product
imag(complex number): imaginary part – works on arrays and matrices
real(complex number): real part – works on arrays and matrices
I believe that fft and ifft have to do with fast fourier transforms.
Hi, I found it difficult to transpose a matrix with PYTHON. For instance:
transpose ([[1,2,3], [4,5,6]]) gives me this result: [[1,4], [3,2], [5,6]]
The correct result is: [[1,4], [2,5], [3,6]].
Is there a bag perhaps?
RE: Some of Python's linalg commands in HP Prime - parisse - 09-10-2021 04:55 AM
There is indeed a bug in transpose for non square matrices.
RE: Some of Python's linalg commands in HP Prime - robmio - 09-11-2021 09:13 AM
(09-10-2021 04:55 AM)parisse Wrote: There is indeed a bug in transpose for non square matrices.
Thanks for the answer, Parisse. Since I had to use the "transpose" command in my Python program, I had to write a subroutine to transpose the arrays:
Code:
from linalg import *
def transposeRr(matriceRr):
L=shape(matriceRr);
r=L[0];
c=L[1];
matricezero=zeros(c,r);
for u in range(0,r):
for uu in range (0,c):
matricezero[uu][u]=matriceRr[u][uu];
return matricezero;RE: Some of Python's linalg commands in HP Prime - Albert Chan - 09-11-2021 10:36 AM
(09-11-2021 09:13 AM)robmio Wrote: Since I had to use the "transpose" command in my Python program, I had to write a subroutine to transpose the arrays ...
Is matrix simply list of list ? If yes, we can transpose with a 1-liner.
>>> transpose = lambda a: [list(r) for r in zip(*a)]
>>> transpose([[1,2,3], [4,5,6]])
[[1, 4], [2, 5], [3, 6]]
RE: Some of Python's linalg commands in HP Prime - robmio - 09-11-2021 11:17 AM
(09-11-2021 10:36 AM)Albert Chan Wrote:(09-11-2021 09:13 AM)robmio Wrote: Since I had to use the "transpose" command in my Python program, I had to write a subroutine to transpose the arrays ...
Is matrix simply list of list ? If yes, we can transpose with a 1-liner.
>>> transpose = lambda a: [list(r) for r in zip(*a)]
>>> transpose([[1,2,3], [4,5,6]])
[[1, 4], [2, 5], [3, 6]]
Congratulations! This short solution you proposed works very well in my program
RE: Some of Python's linalg commands in HP Prime - Ioncubekh - 10-27-2022 07:43 PM
matrix() doesn't follow rules of matrix dot product. Possible bug related to post#7
Code:
from linalg import *
M1= matrix([ [1,2,3], [10,100,1000] ])
# Sum of rows of any Matrix
EachRowSum= dot( M1, ones( len(M1[0]), 1 ) )
# Sum of columns of any Matrix ... NOT WORKING
EachColSum= dot( ones( 1, len(M1) ), M1 )RE: Some of Python's linalg commands in HP Prime - Ioncubekh - 11-02-2022 02:20 AM
In the absence of multi-dimensional arrays (numpy) following commands using native zip(), map(), lambda, list constructions ...can be used to have similar effect while considering dimensions as well.
Few array examples & their equivalents
Code:
# x + b21 * k1 + b32 * k2
# where x, k1 & k2 are numpy arrays while b21 & b32 is some scalar value
[sum(i) for i in zip(x, [b21*i for i in k1], [b32*i for i in k2] )]
# r / ( q*( abs(x)+abs(k1) ) )
# where r, x & k1 are equal shaped arrays & q is scalar value
[ (r[i] / ( q*( abs(x[i]) + abs(k1[i]) ) ) ) for i in range(len(x) ) ]