Plot matrix of weighted cells in grid with Matplotlib












1















I have a square matrix built from an array of random integers, defined below:



import numpy as np

dim_low, dim_high = 0, 20 #array of random integers' dimensions

matrix = np.random.random_integers(low = dim_low,high = dim_high, size=(dim_high,dim_high))
print(matrix) #the matrix of defined with repetitions of the array.


Resulted matrix in the picture:
https://i.stack.imgur.com/eEcCh.png



What could I do to plot the matrix generated in a grid with Matplotlib, in a way that the values of each cell (the weights) are printed in the center of each cell, and there's a scale from 0 to 20 in x an y axis, as in the picture below (notice that 'x' and 'o' are text in the example, what I need is the weights, in integer form, not text form):



https://i.stack.imgur.com/9mBuG.png (here)










share|improve this question























  • If you are capable of producing the image shown, what's the difference to putting your matrix elements in the text instead of some letters "o"? Which exact problem are you trying to solve?

    – ImportanceOfBeingErnest
    Nov 25 '18 at 15:18
















1















I have a square matrix built from an array of random integers, defined below:



import numpy as np

dim_low, dim_high = 0, 20 #array of random integers' dimensions

matrix = np.random.random_integers(low = dim_low,high = dim_high, size=(dim_high,dim_high))
print(matrix) #the matrix of defined with repetitions of the array.


Resulted matrix in the picture:
https://i.stack.imgur.com/eEcCh.png



What could I do to plot the matrix generated in a grid with Matplotlib, in a way that the values of each cell (the weights) are printed in the center of each cell, and there's a scale from 0 to 20 in x an y axis, as in the picture below (notice that 'x' and 'o' are text in the example, what I need is the weights, in integer form, not text form):



https://i.stack.imgur.com/9mBuG.png (here)










share|improve this question























  • If you are capable of producing the image shown, what's the difference to putting your matrix elements in the text instead of some letters "o"? Which exact problem are you trying to solve?

    – ImportanceOfBeingErnest
    Nov 25 '18 at 15:18














1












1








1








I have a square matrix built from an array of random integers, defined below:



import numpy as np

dim_low, dim_high = 0, 20 #array of random integers' dimensions

matrix = np.random.random_integers(low = dim_low,high = dim_high, size=(dim_high,dim_high))
print(matrix) #the matrix of defined with repetitions of the array.


Resulted matrix in the picture:
https://i.stack.imgur.com/eEcCh.png



What could I do to plot the matrix generated in a grid with Matplotlib, in a way that the values of each cell (the weights) are printed in the center of each cell, and there's a scale from 0 to 20 in x an y axis, as in the picture below (notice that 'x' and 'o' are text in the example, what I need is the weights, in integer form, not text form):



https://i.stack.imgur.com/9mBuG.png (here)










share|improve this question














I have a square matrix built from an array of random integers, defined below:



import numpy as np

dim_low, dim_high = 0, 20 #array of random integers' dimensions

matrix = np.random.random_integers(low = dim_low,high = dim_high, size=(dim_high,dim_high))
print(matrix) #the matrix of defined with repetitions of the array.


Resulted matrix in the picture:
https://i.stack.imgur.com/eEcCh.png



What could I do to plot the matrix generated in a grid with Matplotlib, in a way that the values of each cell (the weights) are printed in the center of each cell, and there's a scale from 0 to 20 in x an y axis, as in the picture below (notice that 'x' and 'o' are text in the example, what I need is the weights, in integer form, not text form):



https://i.stack.imgur.com/9mBuG.png (here)







python matplotlib matrix grid






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asked Nov 25 '18 at 15:00









L'utilisatriceL'utilisatrice

83119




83119













  • If you are capable of producing the image shown, what's the difference to putting your matrix elements in the text instead of some letters "o"? Which exact problem are you trying to solve?

    – ImportanceOfBeingErnest
    Nov 25 '18 at 15:18



















  • If you are capable of producing the image shown, what's the difference to putting your matrix elements in the text instead of some letters "o"? Which exact problem are you trying to solve?

    – ImportanceOfBeingErnest
    Nov 25 '18 at 15:18

















If you are capable of producing the image shown, what's the difference to putting your matrix elements in the text instead of some letters "o"? Which exact problem are you trying to solve?

– ImportanceOfBeingErnest
Nov 25 '18 at 15:18





If you are capable of producing the image shown, what's the difference to putting your matrix elements in the text instead of some letters "o"? Which exact problem are you trying to solve?

– ImportanceOfBeingErnest
Nov 25 '18 at 15:18












2 Answers
2






active

oldest

votes


















0














I pulled most of this from this post.



import numpy as np
import matplotlib.pyplot as plt

low_dim = 0
high_dim = 20

matrix = np.random.randint(low_dim, high_dim, (high_dim,high_dim))

fig, ax = plt.subplots()

for i in range(0, high_dim):
for j in range(0, high_dim):
val = matrix[i,j]
ax.text(i+0.5, j+0.5, str(val), va='center', ha='center')

ax.set_xlim(low_dim, high_dim)
ax.set_ylim(low_dim, high_dim)
ax.set_xticks(np.arange(high_dim))
ax.set_yticks(np.arange(high_dim))
ax.grid()

plt.show()





share|improve this answer































    -1














    The right module for this would be seaborn. It has all the functionality you ask for and more...

    Try using https://seaborn.pydata.org/generated/seaborn.heatmap.html. I won't take you through the different options because they're really well documented.

    Goodluck!



    BTW, you'll want to use a panda pivot table for comfortable compatibility.






    share|improve this answer























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      2 Answers
      2






      active

      oldest

      votes








      2 Answers
      2






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      0














      I pulled most of this from this post.



      import numpy as np
      import matplotlib.pyplot as plt

      low_dim = 0
      high_dim = 20

      matrix = np.random.randint(low_dim, high_dim, (high_dim,high_dim))

      fig, ax = plt.subplots()

      for i in range(0, high_dim):
      for j in range(0, high_dim):
      val = matrix[i,j]
      ax.text(i+0.5, j+0.5, str(val), va='center', ha='center')

      ax.set_xlim(low_dim, high_dim)
      ax.set_ylim(low_dim, high_dim)
      ax.set_xticks(np.arange(high_dim))
      ax.set_yticks(np.arange(high_dim))
      ax.grid()

      plt.show()





      share|improve this answer




























        0














        I pulled most of this from this post.



        import numpy as np
        import matplotlib.pyplot as plt

        low_dim = 0
        high_dim = 20

        matrix = np.random.randint(low_dim, high_dim, (high_dim,high_dim))

        fig, ax = plt.subplots()

        for i in range(0, high_dim):
        for j in range(0, high_dim):
        val = matrix[i,j]
        ax.text(i+0.5, j+0.5, str(val), va='center', ha='center')

        ax.set_xlim(low_dim, high_dim)
        ax.set_ylim(low_dim, high_dim)
        ax.set_xticks(np.arange(high_dim))
        ax.set_yticks(np.arange(high_dim))
        ax.grid()

        plt.show()





        share|improve this answer


























          0












          0








          0







          I pulled most of this from this post.



          import numpy as np
          import matplotlib.pyplot as plt

          low_dim = 0
          high_dim = 20

          matrix = np.random.randint(low_dim, high_dim, (high_dim,high_dim))

          fig, ax = plt.subplots()

          for i in range(0, high_dim):
          for j in range(0, high_dim):
          val = matrix[i,j]
          ax.text(i+0.5, j+0.5, str(val), va='center', ha='center')

          ax.set_xlim(low_dim, high_dim)
          ax.set_ylim(low_dim, high_dim)
          ax.set_xticks(np.arange(high_dim))
          ax.set_yticks(np.arange(high_dim))
          ax.grid()

          plt.show()





          share|improve this answer













          I pulled most of this from this post.



          import numpy as np
          import matplotlib.pyplot as plt

          low_dim = 0
          high_dim = 20

          matrix = np.random.randint(low_dim, high_dim, (high_dim,high_dim))

          fig, ax = plt.subplots()

          for i in range(0, high_dim):
          for j in range(0, high_dim):
          val = matrix[i,j]
          ax.text(i+0.5, j+0.5, str(val), va='center', ha='center')

          ax.set_xlim(low_dim, high_dim)
          ax.set_ylim(low_dim, high_dim)
          ax.set_xticks(np.arange(high_dim))
          ax.set_yticks(np.arange(high_dim))
          ax.grid()

          plt.show()






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 25 '18 at 15:27









          drbabaghanoushdrbabaghanoush

          563




          563

























              -1














              The right module for this would be seaborn. It has all the functionality you ask for and more...

              Try using https://seaborn.pydata.org/generated/seaborn.heatmap.html. I won't take you through the different options because they're really well documented.

              Goodluck!



              BTW, you'll want to use a panda pivot table for comfortable compatibility.






              share|improve this answer




























                -1














                The right module for this would be seaborn. It has all the functionality you ask for and more...

                Try using https://seaborn.pydata.org/generated/seaborn.heatmap.html. I won't take you through the different options because they're really well documented.

                Goodluck!



                BTW, you'll want to use a panda pivot table for comfortable compatibility.






                share|improve this answer


























                  -1












                  -1








                  -1







                  The right module for this would be seaborn. It has all the functionality you ask for and more...

                  Try using https://seaborn.pydata.org/generated/seaborn.heatmap.html. I won't take you through the different options because they're really well documented.

                  Goodluck!



                  BTW, you'll want to use a panda pivot table for comfortable compatibility.






                  share|improve this answer













                  The right module for this would be seaborn. It has all the functionality you ask for and more...

                  Try using https://seaborn.pydata.org/generated/seaborn.heatmap.html. I won't take you through the different options because they're really well documented.

                  Goodluck!



                  BTW, you'll want to use a panda pivot table for comfortable compatibility.







                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 25 '18 at 15:22









                  ShlomiFShlomiF

                  839410




                  839410






























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