# Creates two identical panels.  Zooming in on the right panel will show
# a rectangle in the first panel, denoting the zoomed region.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle


# We just subclass Rectangle so that it can be called with an Axes
# instance, causing the rectangle to update its shape to match the
# bounds of the Axes
class UpdatingRect(Rectangle):
    def __call__(self, ax):
        self.set_bounds(*ax.viewLim.bounds)
        ax.figure.canvas.draw_idle()


# A class that will regenerate a fractal set as we zoom in, so that you
# can actually see the increasing detail.  A box in the left panel will show
# the area to which we are zoomed.
class MandelbrotDisplay(object):
    def __init__(self, h=500, w=500, niter=50, radius=2., power=2):
        self.height = h
        self.width = w
        self.niter = niter
        self.radius = radius
        self.power = power

    def __call__(self, xstart, xend, ystart, yend):
        self.x = np.linspace(xstart, xend, self.width)
        self.y = np.linspace(ystart, yend, self.height).reshape(-1, 1)
        c = self.x + 1.0j * self.y
        threshold_time = np.zeros((self.height, self.width))
        z = np.zeros(threshold_time.shape, dtype=np.complex)
        mask = np.ones(threshold_time.shape, dtype=np.bool)
        for i in range(self.niter):
            z[mask] = z[mask]**self.power + c[mask]
            mask = (np.abs(z) < self.radius)
            threshold_time += mask
        return threshold_time

    def ax_update(self, ax):
        ax.set_autoscale_on(False)  # Otherwise, infinite loop

        # Get the number of points from the number of pixels in the window
        dims = ax.axesPatch.get_window_extent().bounds
        self.width = int(dims[2] + 0.5)
        self.height = int(dims[2] + 0.5)

        # Get the range for the new area
        xstart, ystart, xdelta, ydelta = ax.viewLim.bounds
        xend = xstart + xdelta
        yend = ystart + ydelta

        # Update the image object with our new data and extent
        im = ax.images[-1]
        im.set_data(self.__call__(xstart, xend, ystart, yend))
        im.set_extent((xstart, xend, ystart, yend))
        ax.figure.canvas.draw_idle()

md = MandelbrotDisplay()
Z = md(-2., 0.5, -1.25, 1.25)

fig1, (ax1, ax2) = plt.subplots(1, 2)
ax1.imshow(Z, origin='lower', extent=(md.x.min(), md.x.max(), md.y.min(), md.y.max()))
ax2.imshow(Z, origin='lower', extent=(md.x.min(), md.x.max(), md.y.min(), md.y.max()))

rect = UpdatingRect([0, 0], 0, 0, facecolor='None', edgecolor='black', linewidth=1.0)
rect.set_bounds(*ax2.viewLim.bounds)
ax1.add_patch(rect)

# Connect for changing the view limits
ax2.callbacks.connect('xlim_changed', rect)
ax2.callbacks.connect('ylim_changed', rect)

ax2.callbacks.connect('xlim_changed', md.ax_update)
ax2.callbacks.connect('ylim_changed', md.ax_update)
ax2.set_title("Zoom here")

plt.show() 

　

　

Traceback (most recent call last):
  File "M:\______\viewlims.py", line 61, in 
    Z = md(-2., 0.5, -1.25, 1.25)
        ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "M:\______\viewlims.py", line 33, in __call__
    z = np.zeros(threshold_time.shape, dtype=np.complex)
                                             ^^^^^^^^^^
  File "C:\Users\______\AppData\Local\Programs\Python
    \Python311\Lib\site-packages\numpy\__init__.py", line 305, in __getattr__
    raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'complex'.
`np.complex` was a deprecated alias for the builtin `complex`. 
  To avoid this error in existing code, use `complex` by itself. 
  Doing this will not modify any behavior and is safe. 
  If you specifically wanted the numpy scalar type, use `np.complex128` here.
The aliases was originally deprecated in NumPy 1.20; for more details and 
  guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'complex_'?  

Traceback (most recent call last):
  File "E:\______\viewlims.py", line 61, in 
    Z = md(-2., 0.5, -1.25, 1.25)
        ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\______\viewlims.py", line 33, in __call__
    z = np.zeros(threshold_time.shape, dtype=np.complex)
                                             ^^^^^^^^^^
  File "C:\Users\______\AppData\Roaming\Python
    \Python312\site-packages\numpy\__init__.py", line 338, in __getattr__
    raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'complex'.
`np.complex` was a deprecated alias for the builtin `complex`. 
  To avoid this error in existing code, use `complex` by itself. 
  Doing this will not modify any behavior and is safe. If you specifically wanted 
  the numpy scalar type, use `np.complex128` here.
The aliases was originally deprecated in NumPy 1.20; 
  for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'complex_'?  

"""
========
Viewlims
========

Creates two identical panels.  Zooming in on the right panel will show
a rectangle in the first panel, denoting the zoomed region.

.. note::
    This example exercises the interactive capabilities of Matplotlib, and this
    will not appear in the static documentation. Please run this code on your
    machine to see the interactivity.

    You can copy and paste individual parts, or download the entire example
    using the link at the bottom of the page.
"""
import matplotlib.pyplot as plt
import numpy as np

from matplotlib.patches import Rectangle


# We just subclass Rectangle so that it can be called with an Axes
# instance, causing the rectangle to update its shape to match the
# bounds of the Axes
class UpdatingRect(Rectangle):
    def __call__(self, ax):
        self.set_bounds(*ax.viewLim.bounds)
        ax.figure.canvas.draw_idle()


# A class that will regenerate a fractal set as we zoom in, so that you
# can actually see the increasing detail.  A box in the left panel will show
# the area to which we are zoomed.
class MandelbrotDisplay:
    def __init__(self, h=500, w=500, niter=50, radius=2., power=2):
        self.height = h
        self.width = w
        self.niter = niter
        self.radius = radius
        self.power = power

    def compute_image(self, xstart, xend, ystart, yend):
        self.x = np.linspace(xstart, xend, self.width)
        self.y = np.linspace(ystart, yend, self.height).reshape(-1, 1)
        c = self.x + 1.0j * self.y
        threshold_time = np.zeros((self.height, self.width))
        z = np.zeros(threshold_time.shape, dtype=complex)
        mask = np.ones(threshold_time.shape, dtype=bool)
        for i in range(self.niter):
            z[mask] = z[mask]**self.power + c[mask]
            mask = (np.abs(z) < self.radius)
            threshold_time += mask
        return threshold_time

    def ax_update(self, ax):
        ax.set_autoscale_on(False)  # Otherwise, infinite loop
        # Get the number of points from the number of pixels in the window
        self.width, self.height = \
            np.round(ax.patch.get_window_extent().size).astype(int)
        # Get the range for the new area
        vl = ax.viewLim
        extent = vl.x0, vl.x1, vl.y0, vl.y1
        # Update the image object with our new data and extent
        im = ax.images[-1]
        im.set_data(self.compute_image(*extent))
        im.set_extent(extent)
        ax.figure.canvas.draw_idle()


md = MandelbrotDisplay()
Z = md.compute_image(-2., 0.5, -1.25, 1.25)

fig1, (ax1, ax2) = plt.subplots(1, 2)
ax1.imshow(Z, origin='lower',
           extent=(md.x.min(), md.x.max(), md.y.min(), md.y.max()))
ax2.imshow(Z, origin='lower',
           extent=(md.x.min(), md.x.max(), md.y.min(), md.y.max()))

rect = UpdatingRect(
    [0, 0], 0, 0, facecolor='none', edgecolor='black', linewidth=1.0)
rect.set_bounds(*ax2.viewLim.bounds)
ax1.add_patch(rect)

# Connect for changing the view limits
ax2.callbacks.connect('xlim_changed', rect)
ax2.callbacks.connect('ylim_changed', rect)

ax2.callbacks.connect('xlim_changed', md.ax_update)
ax2.callbacks.connect('ylim_changed', md.ax_update)
ax2.set_title("Zoom here")

plt.show() 

　Python 3.11.6 (matplotlib 3.7.1) 及び Python 3.12.0 (matplotlib 3.8.1) 共に、正常実行できる。

　

　

• 2023/11/14 Ver=1.04 Python 3.12.0 (matplotlib 3.8.1)で確認
• 2023/11/14 Ver=1.04 Python 3.11.6 (matplotlib 3.7.1)で確認
• 2023/03/30 Ver=1.03 Python 3.11.2 で確認
• 2020/10/30 Ver=1.01 Python 3.7.8 で確認
• 2018/11/25 Ver=1.01 初版リリース

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