Domanda

I'm trying to plot a image with imshow but I am getting outputs that I didn't expected... The method to show my image is:

def generate_data_black_and_white_heat_map(data, x_axis_label, y_axis_label, plot_title, file_path):
        plt.figure()
        plt.title(plot_title)
        plt.imshow(data.data, extent=[0, data.cols, data.rows, 0], cmap='Greys')
        plt.xlabel(x_axis_label)
        plt.ylabel(y_axis_label)
        plt.savefig(file_path + '.png')
        plt.close()

My data is represented as:

def __init__(self, open_image=False):
        """
        The Data constructor
        """
        self.data = misc.lena() / 255.0
        x, y = self.data.shape
        self.rows = x
        self.cols = y

I do some calculation and at some point I have to do this:

# A -> 2D ndarray
A.data[A.data >= 0.5] = 1.0
A.data[A.data < 0.5] = 0.0

Which gives me:

enter image description here

But I want the opposite (white background). So, I just did this:

# A -> 2D ndarray
A.data[A.data >= 0.5] = 0.0
A.data[A.data < 0.5] = 1.0

And then, I got this (!!!):

enter image description here

I just didn't get it. This makes any sense for me. And the weird thing is 'cause if I do:

for x in range(A.cols):
        for y in range(A.rows):
            if A.data[x][y] >= 0.5:
                A.data[x][y] = 0.0
            else:
                A.data[x][y] = 1.0

It works. Am I accessing something in the wrong way?

Any help to clarify this in my mind would be very appreciated.

Thank you in advance.

È stato utile?

Soluzione

It is doing exactly what you are telling it to do:

A[A >= 0.5] = 0.0  #  all of you values are now < 0.5
A[A < 0.5] = 1.0   # all of your values are now 1

It is far better to just do

B = A > .5  # true (1) where above thershold
iB = B < .5 # true (1) where below threshold
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