Question

First of all, i have an output array like this (in the matrix of 4×1) :

   array([[ -2.22044605e-15],
   [  2.82842712e+01],
   [ -2.22044605e-15],
   [  2.82842712e+01]])

and that output, i receive from return value of matrix multiplication of 4×3 and 3×1 just like below:

def inverse_kinematic(self,Degree):
    # [W] = (1/r)[R][V] 
    self.R = array ( [[-1, 1, self.X1+self.Y1], [1, 1, self.X2-self.Y2],
                       [-1, 1, self.X3+self.Y3], [1, 1, self.X4-self.Y4]]) 

    self.V = array ( [[self.Vt*math.cos(math.radians(Degree))],
                       [self.Vt*math.sin(math.radians(Degree))],[ self.Wv]])
    self.W = []
    self.W = (1/self.r)*dot(self.R,self.V)
    return self.W

and i really want to have and output array like above but in two digit decimal value, like this:

   array([[ 0.00],
   [  28.28],
   [ 0.00],
   [  28.28]])

i have tired to use something like “%.2f” % (number) method and still not success. i wondering is there any best method to set decimal values in list of arrays?

Best Regards,

Glenn

Answer 1

Your return values are of very different orders:

2.82842712e+01 approximately 2.8

-2.22044605e-15 = 0.0000000000000022 approximately 0

It is likely that you have a numeric evaluation that is analytically zero and the small value is just a computation error.

Matrix operations are easily done in numpy, you could use something like this:

    >>> import numpy as np
    >>> a = np.array([[11,12,13],[21,22,23],[31,32,33],[41,42,43]])
    >>> b = np.array([[1],[2],[3]])
    >>> x = np.dot(a,b)
    >>> x
    array([[ 74],
   [134],
   [194],
   [254]])

In that case you might be happy with

    >>> x = np.array([0.923423,0.12341235,0.213453241])
    >>> x.round(2)
    array([ 0.92,  0.12,  0.21])

numpy arrays are convenient, because you don’t have to iterate over their entries:

    >>> a = np.array([1,2,3,4,5])
    >>> a
    array([1, 2, 3, 4, 5])
    >>> a+2
    array([3, 4, 5, 6, 7])
    >>> a*10
    array([10, 20, 30, 40, 50])
    >>> np.sin(a)
    array([ 0.84147098,  0.90929743,  0.14112001, -0.7568025 , -0.95892427])