Python plot使用matplotlib的大矩阵

Question

I am trying to plot a matrix with 2000 columns and 200000 rows. I can test plot and test export the matrix figure fine when the matrix is small using

matshow(my_matrix)
show()

However, when more rows are added to my_matrix, the figure becomes very narrow as there are way more rows than columns, thus losing the precision when zooming in. Can I make matrix figure scrollable? If not, how can I visualize such matrix without losing precision?

I also tried to call savefig('filename', dpi=300) in order to save the image without losing too much precision, but it throws MemoryError when the matrix is big. Many thanks!

Answer 1

I ended up taking a combination of @tcaswell and @lesnikow's suggestions.

Get current axes in order to set auto aspect ratio properly, I also split the matrix into smaller matrices:

    import matplotlib.pylab as plt

    for j in range(lower_bound_on_rows, upper_bound_on_rows): nums.append(j)
    partial_matrix = my_matrix[nums, :] 

    plt.matshow(partial_matrix, fignum=100)
    plt.gca().set_aspect('auto')
    plt.savefig('filename.png', dpi=600)

My matrix is long vertically, so I sliced by rows and preserved all columns in the smaller matrices. If your matrix is long horizontally, flip the index like this my_matrix[:, nums]