class内での計算結果をprintで出力したいです。

class Something:
    def __init__(self):
        # something
        pass
    
    def depth_estimation(self, axis="vertical",threshold=(0.0,2.0), save=None, show=True):
        assert self._disparity_map is not None, "Plz run stereo matching first."
        height = self._left_image.shape[0]
        width = self._left_image.shape[1]
        self._depth_map = np.zeros(self._disparity_map.shape , np.float32)
        if axis == "vertical":
            for y in range(height):
                for x in range(width):
                    lamb = (1.0 - y/(height/2.0)) * (math.pi/2.0)
                    phi = (x/(width/2.0) - 1.0) * (math.pi/2.0)
                    delta_phi = self._disparity_map[y,x] / (width/2.0) * (math.pi/2.0)
                    distance = self._baseline * math.sin(math.pi/2.0 - phi) / (1e-7+math.sin(delta_phi) * math.cos(lamb))
                    self._depth_map[y,x] = distance *math.cos(phi) * math.cos(lamb)
        elif axis == "horizontal":
            for y in range(height):
                for x in range(width):
                    lamb = (1.0 + y/(height/2.0)) * (math.pi/2.0)
                    phi = (1.0 - x/(width/2.0)) * (math.pi/2.0)
                    delta_lamb = -(self._disparity_map[y,x] / (width/2.0)) * (math.pi/2.0)
                    distance = self._baseline * math.sin(math.pi/2.0 - lamb) / (1e-7+math.sin(delta_lamb) * math.cos(phi))
                    self._depth_map[y,x] = distance * math.cos(phi)
        self._depth_map = np.where((self._depth_map < threshold[0]) | (self._depth_map > threshold[1]), 0.0, self._depth_map)
        if save:
            fig = plt.figure(figsize=(15,15))
            plt.imshow(self._depth_map)
            plt.axis("off")
            fig.savefig(save)
        if show:
            self._show_images(images=[cv2.cvtColor(self._image, cv2.COLOR_BGR2RGB), self._depth_map], titles=["Original", "Depth"], figsize=(30,20), subplot=(1,2),color_bar=True)
        return self._depth_map
    print(self._depth_map[222,202])

    def _show_images(self, images, titles, figsize, subplot, color_bar=False):
        # images -> show images
        plt.figure(figsize=figsize)
        for i, (image, title) in enumerate(zip(images, titles)):
            plt.subplot(subplot[0], subplot[1], i+1)
            plt.imshow(image)
            plt.title(title)
            plt.axis("off")
            if i==1 and color_bar:
                plt.colorbar()
        plt.show()

def depth_estimation(self, axis="vertical",threshold=(0.0,2.0), save=None, show=True):
    assert self._disparity_map is not None, "Plz run stereo matching first."
    height = self._left_image.shape[0]
    width = self._left_image.shape[1]
    self._depth_map = np.zeros(self._disparity_map.shape , np.float32)
    if axis == "vertical":
        for y in range(height):
            for x in range(width):
                lamb = (1.0 - y/(height/2.0)) * (math.pi/2.0)
                phi = (x/(width/2.0) - 1.0) * (math.pi/2.0)
                delta_phi = self._disparity_map[y,x] / (width/2.0) * (math.pi/2.0)
                distance = self._baseline * math.sin(math.pi/2.0 - phi) / (1e-7+math.sin(delta_phi) * math.cos(lamb))
                self._depth_map[y,x] = distance *math.cos(phi) * math.cos(lamb)
    elif axis == "horizontal":
        for y in range(height):
            for x in range(width):
                lamb = (1.0 + y/(height/2.0)) * (math.pi/2.0)
                phi = (1.0 - x/(width/2.0)) * (math.pi/2.0)
                delta_lamb = -(self._disparity_map[y,x] / (width/2.0)) * (math.pi/2.0)
                distance = self._baseline * math.sin(math.pi/2.0 - lamb) / (1e-7+math.sin(delta_lamb) * math.cos(phi))
                self._depth_map[y,x] = distance * math.cos(phi)
    self._depth_map = np.where((self._depth_map < threshold[0]) | (self._depth_map > threshold[1]), 0.0, self._depth_map)
    if save:
        fig = plt.figure(figsize=(15,15))
        plt.imshow(self._depth_map)
        plt.axis("off")
        fig.savefig(save)
    if show:
        self._show_images(images=[cv2.cvtColor(self._image, cv2.COLOR_BGR2RGB), self._depth_map], titles=["Original", "Depth"], figsize=(30,20), subplot=(1,2),color_bar=True)
    # 変更箇所
    print(self._depth_map[222,202])
    return self._depth_map

something = Something()
depth_map = something.depth_estimation()
print(depth_map[222,202])

def depth_estimation(self, axis="vertical",threshold=(0.0,2.0), save=None, show=True):
       assert self._disparity_map is not None, "Plz run stereo
       ...
       return self._depth_map
    
   print(self._depth_map[222,202])

   def _show_images(self, images, titles, figsize, subplot, color_bar=False):
       ...
       plt.show()