Question

我正在使用六个自定义颜色绘制散点图。我希望散点图的值介于[-0.15，-0.05]之间，且介于中间四种颜色之间，散点图的范围超出了第一种和最后一种颜色。

这是用于绘制散点图的。我试图使用“级别”和“扩展”参数来实现我想要的功能，但这在m.contourf中起作用，而在m.scatter中不起作用。我还尝试在m.scatter中使用“ vmin”和“ vmax”参数，但结果并不令人满意。

import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
from mpl_toolkits.basemap import Basemap

def plot_scatter():
    fig = plt.figure(figsize=(6,4))
    ax_0 = plt.gca()

    colors = ['lightskyblue', 'deepskyblue', 'dodgerblue', 'royalblue', 'mediumblue', 'navy']
    cmap = mpl.colors.ListedColormap(colors[::-1]) # let deeper blues indicates smaller values

    m = Basemap(llcrnrlon=113.7, llcrnrlat=22.35, urcrnrlon=114.7, urcrnrlat=22.9,\
            rsphere=(6378137.00,6356752.3142),\
            resolution='l', area_thresh=1000., projection='lcc', lat_1=22.5, lat_0=22.5, lon_0=114) #- shape文件，画出区域轮廓

    lons = [114.1267222, 114.111825, 114.04908059999998, 113.8175, 114.47, 114.1122222, 114.1658333, 114.0036111, 113.8936271, 113.8855675, 114.104705, 114.1508333, 114.5002778, 113.7672222, 114.1011111, 113.9536389, 113.8911111, 113.8979694, 114.5340278, 114.1436111, 114.2238889, 114.3366799, 114.3044444, 113.9308333, 114.3922222, 113.9147222, 113.8361111, 114.02916670000002, 114.2236111, 113.8686111, 114.1488889, 114.1230556, 114.1933333, 114.02916670000002, 113.9727778, 114.48444440000002, 114.2752778, 114.2422222, 114.01416670000002, 113.9288889, 114.5264328, 113.94485559999998, 114.19001670000002, 114.4861111, 114.1794444, 114.2430556, 114.1508333, 114.09555559999998, 114.2622222, 114.0163889, 114.3002778, 114.3552778, 113.8602778, 113.8797222, 114.2338889, 114.0708333, 114.43194440000002, 113.89305559999998]
    lats = [22.55097222, 22.55905833, 22.52501111, 22.67416667, 22.60055556, 22.60555556, 22.56472222, 22.54166667, 22.65377067, 22.47006253, 22.54966819, 22.55166667, 22.56944444, 22.72333333, 22.57194444, 22.76244444, 22.78166667, 22.70483, 22.59697222, 22.57166667, 22.555, 22.59546331, 22.7775, 22.48861111, 22.615, 22.5475, 22.77916667, 22.62305556, 22.64638889, 22.495, 22.61638889, 22.69611111, 22.64638889, 22.5725, 22.59638889, 22.53444444, 22.56666667, 22.72416667, 22.54888889, 22.67888889, 22.48137411, 22.50378611, 22.57101111, 22.48277778, 22.66222222, 22.58388889, 22.65611111, 22.5375, 22.76694444, 22.53027778, 22.67888889, 22.7125, 22.80166667, 22.55277778, 22.68527778, 22.56861111, 22.61888889, 22.58861111]
    values = [-0.03101638020010544, -0.059602408594572324, -0.08074725429957398, -0.052523178817571285, -0.06097954730989012, -0.048576189387818935, -0.05321303447484441, -0.08990485880945824, -0.07035292627778422, -0.08904485101486563, -0.050582862579880206, -0.08667040863306046, -0.2381958334486063, -0.09043589588854052, -0.015791558268944444, -0.04750735872842685, -0.0827816789190754, -0.0495746307369816, -0.09748174185420576, -0.05328468550193526, -0.0385492789056475, -0.12603457458801204, -0.03785426812465535, -0.10934222695289253, -0.06257603144203898, -0.05322345906174508, -0.0437720889282609, -0.029440526555296737, -0.0446847919726688, -0.05879880517527025, -0.042610207214769935, -0.07981280621664595, -0.056233334347744406, -0.07486982006522186, -0.064798640683293, -0.060273137801299975, -0.08829009917157292, -0.02696058143578384, -0.047529515842470234, -0.051839812353009496, -0.05970518244018841, -0.08892429975993077, -0.2594588992844997, -0.0853022809983619, -0.11143855759589913, -0.05064439000559071, -0.02366547879452241, -0.1743014882414493, -0.05539755391763087, -0.04722722346208863, -0.04903534243112728, -0.0613871242134162, -0.05259194456906426, -0.0933057542530412, -0.05063961430132472, -0.05351251987776765, -0.03849744311833736, -0.04819026109972248]

    sgt_scatter = m.scatter(lons, lats, s=60, c=values, marker="o", vmin=-0.15, vmax=-0.05, latlon=True, cmap=cmap)

    bounds = [ round(elem, 3) for elem in np.linspace(-0.15, -0.05, 5)] # 
    m.colorbar(extend='both', ticks=bounds)

    m.drawmeridians(np.arange(10, 125, 0.5), labels=[1,0,0,1])
    m.drawparallels(np.arange(15, 30, 0.3),labels=[1,0,0,0])
    plt.show()

# by referring to ImportanceOfBeingErnest's answer, I changed my code as below, appreciation to ImportanceOfBeingErnest
def plot_scatter_new():
    fig = plt.figure(figsize=(6,4))

    # customized colormap
    colors = ['lightskyblue', 'deepskyblue', 'dodgerblue', 'royalblue', 'mediumblue', 'navy']
    cmap = mpl.colors.ListedColormap(colors[::-1]) # let deeper blues indicates smaller values

    # even bounds gives a contour-like effect
    bounds = [ round(elem, 3) for elem in np.linspace(-0.15, -0.05, 5)] # 
    # get one more color than bounds from colormap
    colors = plt.get_cmap(cmap)(np.linspace(0,1,len(bounds)+1))
    # create colormap without the outmost colors
    cmap = mcolors.ListedColormap(colors[1:-1]) # 1:-1是从第二个到倒数第二个，左闭右开
    # set upper/lower color
    cmap.set_over(colors[-1])
    cmap.set_under(colors[0])

    m = Basemap(llcrnrlon=113.7, llcrnrlat=22.35, urcrnrlon=114.7, urcrnrlat=22.9,\
            rsphere=(6378137.00,6356752.3142),\
            resolution='l', area_thresh=1000., projection='lcc', lat_1=22.5, lat_0=22.5, lon_0=114) #- shape文件，画出区域轮廓

    lons = [114.1267222, 114.111825, 114.04908059999998, 113.8175, 114.47, 114.1122222, 114.1658333, 114.0036111, 113.8936271, 113.8855675, 114.104705, 114.1508333, 114.5002778, 113.7672222, 114.1011111, 113.9536389, 113.8911111, 113.8979694, 114.5340278, 114.1436111, 114.2238889, 114.3366799, 114.3044444, 113.9308333, 114.3922222, 113.9147222, 113.8361111, 114.02916670000002, 114.2236111, 113.8686111, 114.1488889, 114.1230556, 114.1933333, 114.02916670000002, 113.9727778, 114.48444440000002, 114.2752778, 114.2422222, 114.01416670000002, 113.9288889, 114.5264328, 113.94485559999998, 114.19001670000002, 114.4861111, 114.1794444, 114.2430556, 114.1508333, 114.09555559999998, 114.2622222, 114.0163889, 114.3002778, 114.3552778, 113.8602778, 113.8797222, 114.2338889, 114.0708333, 114.43194440000002, 113.89305559999998]
    lats = [22.55097222, 22.55905833, 22.52501111, 22.67416667, 22.60055556, 22.60555556, 22.56472222, 22.54166667, 22.65377067, 22.47006253, 22.54966819, 22.55166667, 22.56944444, 22.72333333, 22.57194444, 22.76244444, 22.78166667, 22.70483, 22.59697222, 22.57166667, 22.555, 22.59546331, 22.7775, 22.48861111, 22.615, 22.5475, 22.77916667, 22.62305556, 22.64638889, 22.495, 22.61638889, 22.69611111, 22.64638889, 22.5725, 22.59638889, 22.53444444, 22.56666667, 22.72416667, 22.54888889, 22.67888889, 22.48137411, 22.50378611, 22.57101111, 22.48277778, 22.66222222, 22.58388889, 22.65611111, 22.5375, 22.76694444, 22.53027778, 22.67888889, 22.7125, 22.80166667, 22.55277778, 22.68527778, 22.56861111, 22.61888889, 22.58861111]
    values = [-0.03101638020010544, -0.059602408594572324, -0.08074725429957398, -0.052523178817571285, -0.06097954730989012, -0.048576189387818935, -0.05321303447484441, -0.08990485880945824, -0.07035292627778422, -0.08904485101486563, -0.050582862579880206, -0.08667040863306046, -0.2381958334486063, -0.09043589588854052, -0.015791558268944444, -0.04750735872842685, -0.0827816789190754, -0.0495746307369816, -0.09748174185420576, -0.05328468550193526, -0.0385492789056475, -0.12603457458801204, -0.03785426812465535, -0.10934222695289253, -0.06257603144203898, -0.05322345906174508, -0.0437720889282609, -0.029440526555296737, -0.0446847919726688, -0.05879880517527025, -0.042610207214769935, -0.07981280621664595, -0.056233334347744406, -0.07486982006522186, -0.064798640683293, -0.060273137801299975, -0.08829009917157292, -0.02696058143578384, -0.047529515842470234, -0.051839812353009496, -0.05970518244018841, -0.08892429975993077, -0.2594588992844997, -0.0853022809983619, -0.11143855759589913, -0.05064439000559071, -0.02366547879452241, -0.1743014882414493, -0.05539755391763087, -0.04722722346208863, -0.04903534243112728, -0.0613871242134162, -0.05259194456906426, -0.0933057542530412, -0.05063961430132472, -0.05351251987776765, -0.03849744311833736, -0.04819026109972248]

    sgt_scatter = m.scatter(lons, lats, s=60, c=values, marker="o", vmin=-0.15, vmax=-0.05, latlon=True, cmap=cmap)

    m.colorbar(extend='both', ticks=bounds)

    m.drawmeridians(np.arange(10, 125, 0.5), labels=[1,0,0,1])
    m.drawparallels(np.arange(15, 30, 0.3),labels=[1,0,0,0])
    plt.show()

if __name__ == '__main__':
    plot_scatter()
    plot_scatter_new()

以上代码的结果如下：但是我希望第一个和最后一个颜色显示作为颜色栏的扩展部分。

如何使用自定义颜色绘制散点图

0 个答案: