How to insert value in numpy ndArray?

Question

I have two ndArray.

ex: 
x = np.array([110,200, 500,100])
y = np.array([50,150,30,70])

Now based on their value I have created an image.

x_shape = np.max(x)   #x_shape=500
y_shape = np.max(y)   #y-shape=150
image = np.zeros((x_shape+1, y_shape+1))

according to my data now my image size is (501,151)

Now, How can I insert data from (x, y) as x,y pair? I mean for the pixel value: (110,50), (200,150), (500,30), (100,70) I want the image will be white and the rest pixel will be dark. How can I achieve this?

norok2 · Accepted Answer · 2020-01-02 16:35:47Z

2

Based on OP's own answer, one can improve it by using a vectorized approach:

import numpy as np
import matplotlib.pyplot as plt

x = np.array([110,200, 500,100])
y = np.array([50,150,30,70])
x = np.floor(x / 10).astype(int)
y = np.floor(y / 10).astype(int)
x_shape = np.max(x)   # x_shape = 500
y_shape = np.max(y)   # y_shape = 150
image = np.zeros((x_shape + 10, y_shape + 10))
image[x, y] = 10

plt.imshow(image)

(To be fair, I did not understand from the question that this is what OP was after).

EDIT

To address the "visualization issue" without resizing from the comments:

import numpy as np
import matplotlib.pyplot as plt

x = np.array([110, 200, 500, 100])
y = np.array([50, 150, 30, 70])

x_shape = np.max(x)
y_shape = np.max(y)
image = np.zeros((x_shape + 1, y_shape + 1))
image[x, y] = 10

plt.figure(figsize=(20, 20))
plt.imshow(image.transpose(), interpolation='nearest', aspect='equal')

edited Jan 2, 2020 at 16:35

answered Jan 2, 2020 at 15:40

norok2

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4 Comments

Mad Physicist Over a year ago

This is called fancy indexing by the way

Kazi Over a year ago

thanks for the answer. But if we dont device by 10 then its not visible. I guess singel pixel is too small to see. Can you suggest any modification without devide by 10? @norok2

Kazi Over a year ago

answer accepted and upvorted. thanks. Will be glad if you give me the modified version. @norok2

norok2 Over a year ago

@Kazi that is a visualization, issue.. take a look here. I have also included an edit to address this.

Kazi · Accepted Answer · 2020-01-02 15:38:46Z

0

Well, I got the answer. It was easy and as I am new it makes me confused.

   import numpy as np
   import matplotlib.pyplot as plt
   x = np.array([110,200, 500,100])
   y = np.array([50,150,30,70])

   x = np.floor(x/10).astype(int)  #devided by 10 to reduce the img size
   y = np.floor(y/10).astype(int)  #devided by 10 to reduce the img size
   x_shape = np.max(x)   #x_shape=500
   y_shape = np.max(y)   #y-shape=150
   image = np.zeros((x_shape+10, y_shape+10))
   for x, y in zip(x,y):

        image[x,y]=200

   plt.imshow(image)

edited Jan 2, 2020 at 15:38

answered Jan 2, 2020 at 15:10

Kazi

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3 Comments

norok2 Over a year ago

This approach is not very efficient. You can achieve much better performances with a vectorized code.

Kazi Over a year ago

I have no idea about vectorized. can you create an answer. I might accept if it works. thanks. @norok2

norok2 Over a year ago

done... basically you just take advantage of advanced indexing

olena · Accepted Answer · 2020-01-02 16:34:45Z

0

not sure exactly what do you need you may try

a = np.array([110, 200, 500, 100])
b = np.array([50, 150, 30, 70])

np.array([zip(x,y) for x,y in zip(a,b)])
pd.DataFrame(list(zipped))```
##or another representation
np.dstack((x,y))


both are taken from  https://stackoverflow.com/questions/49461605/why-do-we-need-to-convert-a-zipped-object-into-a-list


  [1]: https://stackoverflow.com/questions/49461605/why-do-we-need-to-convert-a-zipped-object-into-a-list

edited Jan 2, 2020 at 16:34

answered Jan 2, 2020 at 14:20

olena

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2 Comments

Kazi Over a year ago

thanks for the answer. it helped to find the solution. actually i want to create a image from some values which is in cartesian coordinates. anyway upvoted for your help @olena

Mad Physicist Over a year ago

This is not a good way. You are discarding all the benefits of numpy, and don't specify what a and b are supposed to be.

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