How to create a function that takes elements of a list as parameters to graph a function [closed]

I have written the following code:

m = np.arange(-5, 5, 0.1)
q = np.arange(-500, 500, 0.1)
m, q = np.meshgrid(m, q)


Next, say:

a = [[1,2],[2,3]]


I want:

y = np.sqrt((a[0][0]*m + q - a[0][1])**2 + (a[1][0]*m + q - a[1][1])**2)


However I want to write it as:

y = np.sqrt((x[0]*m + q - x[1])**2 + (x[0]*m + q - x[1])**2)


where x in a, (i.e. x = [1,2] in the first case and x = [2,3])

and in general I am looking for a way to generalise this, so that I can write something like:

y = np.sqrt(sum((m*x[0]+q - x[1])**2 for x in a))


How can I do this?

(In the particular example it should return, but it needs to work for any a that is a list of a list of two numbers):
y = np.sqrt((1*m + q - 2)**2 + (2*m + q - 3)**2)

EDIT:

y = np.sqrt(sum((m*x[0]+q - x[1])**2 for x in a))


is actually correct code, my mistake was somewhere else.

This question appears to be off-topic. The users who voted to close gave this specific reason:

a

2 Answers
2

You can do exactly what you describe

>>> def y(x):
... return np.sqrt((x[0]*m + q - x[1])**2 + (x[0]*m + q - x[1])**2)
>>> y(a[0])
array([[ 717.00627612, 716.86485477, 716.72343341, ..., 703.28840457,
703.14698321, 703.00556186],
[ 716.86485477, 716.72343341, 716.58201205, ..., 703.14698321,
703.00556186, 702.8641405 ],
[ 716.72343341, 716.58201205, 716.4405907 , ..., 703.00556186,
702.8641405 , 702.72271914],
...,
[ 696.78302218, 696.92444354, 697.06586489, ..., 710.50089374,
710.64231509, 710.78373645],
[ 696.92444354, 697.06586489, 697.20728625, ..., 710.64231509,
710.78373645, 710.92515781],
[ 697.06586489, 697.20728625, 697.34870761, ..., 710.78373645,
710.92515781, 711.06657916]])
>>> y(a[1])
array([[ 725.4915575 , 725.20871478, 724.92587207, ..., 698.05581439,
697.77297167, 697.49012896],
[ 725.35013614, 725.06729343, 724.78445072, ..., 697.91439303,
697.63155032, 697.34870761],
[ 725.20871478, 724.92587207, 724.64302936, ..., 697.77297167,
697.49012896, 697.20728625],
...,
[ 688.29774081, 688.58058352, 688.86342623, ..., 715.73348392,
716.01632663, 716.29916934],
[ 688.43916216, 688.72200488, 689.00484759, ..., 715.87490527,
716.15774799, 716.4405907 ],
[ 688.58058352, 688.86342623, 689.14626894, ..., 716.01632663,
716.29916934, 716.58201205]])

>>> Y = [y(x) for x in a]
>>> for yy in Y:
... print('do something')


try

m = np.arange(-5, 5, 0.1)
q = np.arange(-500, 500, 0.1)
m, q = np.meshgrid(m, q)

a = np.array([[1,2],[2,3]])

y = np.sqrt(np.power(m[..., np.newaxis] * a[:, 0] + q[..., np.newaxis] - a[:, 1], 2).sum(axis=-1))