title: Matplotlib: change subplot size
body: <p>The following code snipped works just fine. However, I would like to increase the size of the sub-images that are being plotted. How can I change the sub-figure sizes and increase the image quality?</p>
  <pre><code>from keras.applications.vgg16 import VGG16
  from keras.applications.vgg16 import preprocess_input
  from keras.preprocessing.image import load_img
  from keras.preprocessing.image import img_to_array
  from keras.models import Model
  from matplotlib import pyplot
  from numpy import expand_dims
  
  # load the model
  model = VGG16()
  # redefine model to output right after the first hidden layer
  ixs = [2, 5, 9, 13, 17]
  outputs = [model.layers[i].output for i in ixs]
  model = Model(inputs=model.inputs, outputs=outputs)
  # load the image with the required shape
  img = load_img('your_image.jpg', target_size=(224, 224))
  # convert the image to an array
  img = img_to_array(img)
  # expand dimensions so that it represents a single 'sample'
  img = expand_dims(img, axis=0)
  # prepare the image (e.g. scale pixel values for the vgg)
  img = preprocess_input(img)
  # get feature map for first hidden layer
  feature_maps = model.predict(img)
  # plot the output from each block
  square = 8
  for fmap in feature_maps:
      # plot all 64 maps in an 8x8 squares
      ix = 1
      for _ in range(square):
          for _ in range(square):
              # specify subplot and turn of axis
              ax = pyplot.subplot(square, square, ix)
              ax.set_xticks([])
              ax.set_yticks([])
              # plot filter channel in grayscale
              pyplot.imshow(fmap[0, :, :, ix-1], cmap='gray')
              ix += 1
      # show the figure
      pyplot.show()
  </code></pre>