subplot AttributeError：“AxesSubplot”对象没有属性“get_extent”

Question

我正在尝试在 matplotlib.pyplot 上实现一个函数，该函数可以在我的地图中插入标尺和指北针。

我正在尝试为 Geopandas 地理数据集改编“http://stackoverflow.com/a/35705477/1072212”中的代码。

在我的尝试中，主要问题是获取每个我的地块（轴）的边界框坐标。出现的错误是：“subplot AttributeError: 'AxesSubplot' object has no attribute 'get_extent'”

我尝试以多种方式规避此问题，但均未成功（参见附件中的代码）。

如下例所示（代码在附件中），我使用的是来自巴西的社会经济数据（来自 IBGE - https://www.ibge.gov.br/estatisticas-novoportal/sociais/populacao/9109-projecao-da-populacao.html?=&t=downloads）。

此社会经济数据已根据来自巴西的 shapefile（获得于：http://www.codegeo.com.br/2013/04/shapefiles-do-brasil-para-download.html）进行地理定位，并在以下代码中命名为“SHP_joined”。因此，为了保持良好的描述，SHP_joined 是一个 geopandas 地理数据框，我试图在它的图中实现标尺和指北针。

还提供了我想要的结果图像的示例。 "In this Image example, it is still missing the ruler and north arrow"

感谢您抽出宝贵时间，希望尽快收到您的来信。

`# -*- coding: utf-8 -*-
"""
Created on Fri Jul 20 14:53:26 2018

@author: Terry Brown - Adapted by Philipe Leal
"""

import os
import cartopy.crs as ccrs
from math import floor
import matplotlib.pyplot as plt
from matplotlib import patheffects
import numpy as np
import matplotlib
if os.name == 'nt':
    matplotlib.rc('font', family='Arial')
else:  
    # might need tweaking, must support black triangle for N arrow
    matplotlib.rc('font', family='DejaVu Sans')


def utm_from_lon(lat,lon):
    """

    :param float lon: longitude
    :return: UTM zone number
    :rtype: int
    """

    UTM_zone_number = np.int(np.floor( ( lon + 180 ) / 6) + 1)
    print("UTM Zone algorithm 1: ", UTM_zone_number)

    import utm


    UTM_zone_number2 = utm.latlon_to_zone_number(-14.2393, -54.39)

    print("UTM Zone algorithm 2: ", UTM_zone_number2)

    if UTM_zone_number2 == UTM_zone_number:
        print("OK: UTM algorithms are equal!")

        return UTM_zone_number

    else:
        print("UTM algorithms are different. Using library UTM instead!")
        return UTM_zone_number2

##### Caso Geopandas:


def scale_bar_geopandas(ax, Geopandas_dataset, length, location=(0.5, 0.05), linewidth=3,
              units='km', m_per_unit=1000):
    """

    http://stackoverflow.com/a/35705477/1072212
    ax is the axes to draw the scalebar on.
    proj is the projection the axes are in
    location is center of the scalebar in axis coordinates ie. 0.5 is the middle of the plot
    length is the length of the scalebar in km.
    linewidth is the thickness of the scalebar.
    units is the name of the unit
    m_per_unit is the number of meters in a unit
    """
    # find lat/lon center to find best UTM zone

    Minx, Miny, Maxx, Maxy = Geopandas_dataset.total_bounds

    Latitude_central = (Miny+ Maxy) /2.

    Longitude_central = (Minx + Maxx) /2.

    print("Latitude_central: ", Latitude_central)

    print("Longitude_central: ", Longitude_central)
    # Projection in metres

    try: 
        utm = ccrs.UTM(utm_from_lon( Latitude_central, Longitude_central))

    except:
        utm = ccrs.UTM(utm_from_lon(Latitude_central, Longitude_central),
                        southern_hemisphere=True)


    # Get the extent of the plotted area in coordinates in metres

    # find lat/lon center to find best UTM zone

    x0, x1, y0, y1 = Minx, Miny, Maxx, Maxy

    # Turn the specified scalebar location into coordinates in metres
    sbcx, sbcy = x0 + (x1 - x0) * location[0], y0 + (y1 - y0) * location[1]
    # Generate the x coordinate for the ends of the scalebar
    bar_xs = [sbcx - length * m_per_unit/2, sbcx + length * m_per_unit/2]
    # buffer for scalebar
    buffer = [patheffects.withStroke(linewidth=5, foreground="w")]
    # Plot the scalebar with buffer
    ax.plot(bar_xs, [sbcy, sbcy], transform=ax.transAxes, color='k',
        linewidth=linewidth, path_effects=buffer)
    # buffer for text
    buffer = [patheffects.withStroke(linewidth=3, foreground="w")]
    # Plot the scalebar label
    t0 = ax.text(sbcx, sbcy, str(length) + ' ' + units, transform=ax.transAxes,
        horizontalalignment='center', verticalalignment='bottom',
        path_effects=buffer, zorder=2)
    left = x0+(x1-x0)*0.05
    # Plot the N arrow
    t1 = ax.text(left, sbcy, u'\u25B2\nN', transform=ax.transAxes,
        horizontalalignment='center', verticalalignment='bottom',
        path_effects=buffer, zorder=2)
    # Plot the scalebar without buffer, in case covered by text buffer
    ax.plot(bar_xs, [sbcy, sbcy], transform=ax.transAxes, color='k',
        linewidth=linewidth, zorder=3)








###### Casos Normais:

def scale_bar(ax, proj, length, location=(0.5, 0.05), linewidth=3,
              units='km', m_per_unit=1000):
    """

    http://stackoverflow.com/a/35705477/1072212
    ax is the axes to draw the scalebar on.
    proj is the projection the axes are in
    location is center of the scalebar in axis coordinates ie. 0.5 is the middle of the plot
    length is the length of the scalebar in km.
    linewidth is the thickness of the scalebar.
    units is the name of the unit
    m_per_unit is the number of meters in a unit
    """
    # find lat/lon center to find best UTM zone
    try:
        x0, x1, y0, y1 = ax.get_extent(proj.as_geodetic())
    except:
        try:
            print("Trying to extract tje image extent by ax.get_window_extent()")
            x0, x1, y0, y1 = ax.get_window_extent(proj.as_geodetic())

        except:
            try:
                print("Trying to extract tje image extent by np.ravel(ax.get_window_extent())")
                x0, x1, y0, y1 = np.ravel(ax.get_window_extent(proj.as_geodetic()))
                print("\n\n x0, x1, y0 e y1 acquired succesfully: \n\n")
                print(x0, x1, y0, y1, "\n\n")
            except: 
                print("Error. x0, x1, y0 e y1 not extracted!")


    Latitude_central = (y0+y1)/2.

    Longitude_central = (x0+x1)/2.

    print("Latitude_central: ", Latitude_central)

    print("Longitude_central: ", Longitude_central)
    # Projection in metres

    try: 
        utm = ccrs.UTM(utm_from_lon( Latitude_central, Longitude_central))

    except:
        utm = ccrs.UTM(utm_from_lon(Latitude_central, Longitude_central),
                        southern_hemisphere=True)


    print(utm)
    # Get the extent of the plotted area in coordinates in metres

    # find lat/lon center to find best UTM zone
    try:
        x0, x1, y0, y1 = ax.get_extent(utm)
    except:
        print("Trying to extract the image extent by ax.get_window_extent()")
        try:
            x0, x1, y0, y1 = ax.get_window_extent(utm)
        except:
            try:
                print("Trying to extract the image extent by np.ravel(ax.get_window_extent())")

                x0, x1, y0, y1 = np.ravel(ax.get_window_extent(utm))
                print("\n\n x0, x1, y0 e y1 in UTM Projection acquired succesfully: \n\n")
                print(x0, x1, y0, y1, "\n\n")

            except: 
                print("Error. x0, x1, y0 e y1 not extracted!")



    # Turn the specified scalebar location into coordinates in metres
    sbcx, sbcy = x0 + (x1 - x0) * location[0], y0 + (y1 - y0) * location[1]
    # Generate the x coordinate for the ends of the scalebar
    bar_xs = [sbcx - length * m_per_unit/2, sbcx + length * m_per_unit/2]
    # buffer for scalebar
    buffer = [patheffects.withStroke(linewidth=5, foreground="w")]
    # Plot the scalebar with buffer
    ax.plot(bar_xs, [sbcy, sbcy], transform=ax.transAxes, color='k',
        linewidth=linewidth, path_effects=buffer)
    # buffer for text
    buffer = [patheffects.withStroke(linewidth=3, foreground="w")]
    # Plot the scalebar label
    t0 = ax.text(sbcx, sbcy, str(length) + ' ' + units, transform=ax.transAxes,
        horizontalalignment='center', verticalalignment='bottom',
        path_effects=buffer, zorder=2)
    left = x0+(x1-x0)*0.05
    # Plot the N arrow
    t1 = ax.text(left, sbcy, u'\u25B2\nN', transform=ax.transAxes,
        horizontalalignment='center', verticalalignment='bottom',
        path_effects=buffer, zorder=2)
    # Plot the scalebar without buffer, in case covered by text buffer
    ax.plot(bar_xs, [sbcy, sbcy], transform=ax.transAxes, color='k',
        linewidth=linewidth, zorder=3)



############ Testing Data example:


import pandas as pd

import geopandas as gpd


file_name = r'C:\Doutorado\Tese\SINAN\Casos_hepatite_A_por_estado_por_ano\Por_Regioes_BR_por_Ano.xlsx'

## Fluxo temporal 1 ano em 1 ano:


df = pd.read_excel(file_name, sheet_name='prevalencias', header=[1,2])


stacked = df.stack()
stacked.reset_index(inplace=True)


stacked_keys = stacked.keys()

Keys_dict = {'level_0':'ANO', 'Ano':'REGIAO', 'REGIAO':'Prevalencias'}

stacked = stacked.rename(columns=Keys_dict)

stacked.set_index('REGIAO', inplace=True)


Keys_dict_index = {'Centro-Oeste': 'Centro Oeste'}

stacked = stacked.rename(index=Keys_dict_index)

# Filtrando apenas os anos acima de 2006:
stacked = stacked[stacked['ANO'] >= 2007]


stacked['Prevalencias_relativas_%'] = stacked['Prevalencias']/np.sum(stacked['Prevalencias'])*100


SHP_path = r'c:\Doutorado\Tese\SHP\Estados_do_Brasil\Brasil_UTF_8.shp'

SHP = gpd.read_file(SHP_path)

SHP.head()


SHP.set_index('REGIAO', inplace=True)


SHP_joined = SHP.join(stacked)

SHP_joined = SHP_joined[SHP_joined['ANO'] >=2007]


SHP_joined = SHP_joined.to_crs({'init': 'epsg:4326'}) ## WGS-84

Minx, Miny, Maxx, Maxy = SHP_joined.total_bounds

Latitude_central = (Miny+ Maxy) /2.

Longitude_central = (Minx + Maxx) /2.


Anos = np.unique(SHP_joined['ANO'])

Years = []
for Ano in Anos:
    if Ano == np.nan:
        None
    elif str(Ano) == 'nan':
        None
    else:
        Years.append(Ano)

Years = np.array(Years,np.int16) 


###### ------------------------------------------#############




fig, Ax = plt.subplots(nrows=4,ncols=3, sharex='col', sharey='row',
                       )
fig.suptitle('Prevalência da Hepatite-A por Região', fontsize=16)

# definindo Vmin e Vmax para garantir range entre todos os subplots:
    # para ajuste local por subplot, deletar Vmin e Vmax.
    # ex: https://gis.stackexchange.com/questions/273273/reducing-space-in-geopandas-and-matplotlib-pyplots-subplots
Vmin = SHP_joined['Prevalencias_relativas_%'].min()
Vmax = SHP_joined['Prevalencias_relativas_%'].max()


for i in range(len(Years)):
    Ano = Years[i]
    print(Ano)

    Axes = Ax.ravel()[i]


    SHP_joined[SHP_joined['ANO']==Ano].plot(ax=Axes,
                                            column='Prevalencias_relativas_%', 
                                            legend=False,
                                            cmap='viridis',
                                            vmin=Vmin, vmax=Vmax,
                                            label=str(Ano))


    Axes.set_aspect('equal')
    Axes.set_title(str(Ano), fontsize=8)
    Axes.grid()

    scale_bar_geopandas(Axes, SHP_joined, length=100000)


Axes11 = Ax.ravel()[11] 
Axes11.set_aspect('equal')
Axes11.grid()

cax = fig.add_axes([0.9, 0.17, 0.02, 0.65])
sm = plt.cm.ScalarMappable(cmap='viridis', norm=plt.Normalize(vmin=Vmin, vmax=Vmax))
sm._A = []
cbar = fig.colorbar(sm, cax=cax)
cbar.ax.set_title('Prevalencia\n relativa (%)')


#im = plt.gca().get_children()[0]
#cax = fig.add_axes([0.90,0.1,0.03,0.8]) 
#fig.colorbar(im, cax=cax)


fig.subplots_adjust(top=0.855,
                    bottom=0.065,
                    left=1.21e-17,
                    right=0.850,
                    hspace=0.5,
                    wspace=0.005)


scale_bar_geopandas(Axes11, SHP_joined, length=100000)
plt.show()`

Answer 1

您的问题是您创建轴的方式，作为“普通”matplotlib 轴而不是配备投影的轴。您可以使用subplot_kws= 参数将其他参数传递给plt.subplots()，然后将其传递给每个单独的Axes 对象。

以下是adapted from the answer you provided，函数scale_bar()逐字使用

import cartopy.crs as ccrs
from math import floor
import matplotlib.pyplot as plt
from matplotlib import patheffects


def scale_bar(ax, proj, length, location=(0.5, 0.05), linewidth=3,
              units='km', m_per_unit=1000):
    """
    http://stackoverflow.com/a/35705477/1072212
    (...)
    """
    (...)


fig, axs = plt.subplots(nrows=4, ncols=3, sharex='col', sharey='row',
                        subplot_kw={'projection': ccrs.Mercator()})  # <--- Here is the missing piece
fig.suptitle('Cyprus')
for ax in axs.flatten():
    ax.set_extent([31, 35.5, 34, 36], ccrs.Geodetic())
    ax.coastlines(resolution='10m')
    scale_bar(ax, ccrs.Mercator(), 100)
plt.show()