PyPlot - 棘手的轴颜色和标签问题
PyPlot - Tricky axis color and labeling issues
我是 Matplotlib 的新手。这个数字背后的想法是绘制温度高点和低点。我 运行 遇到了 x 轴和右 ya 轴的问题。
对于xaxis,即使我调用tick_params(labelcolor='#b6b6b6')
,字体的颜色也不想改变。此外,日期应该只跨越一月到十二月。出于未知原因,Matplotlib 会在前面加上一个额外的十二月并附加一个额外的一月,导致文本超出图表的脊柱边界。我想删除这些额外的月份。
对于正确的 yaxis,我不确定我是否正确理解了子图的使用。我想将左侧 yaxis 中的 °C 温度转换为 °F,并将转换后的温度用于辅助 yaxis。
这里有一些代码可以重现与我所得到的类似的内容。
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.dates as dates
import matplotlib.ticker as ticker
# generate some data to plot
highs = np.linspace(0, 40, 365) # these numbers will escalate instead of fluctuate, but the problem with the axes will still be the same.
lows = np.linspace(-40, 0, 365)
date_rng = pd.date_range('1/1/2015', '12/31/2015', freq='D')
data = {'highs': highs, 'lows': lows}
to_plot = pd.DataFrame(data, index=date_rng)
fig, ax = plt.subplots()
# plot the basic data
lines = ax.plot(date_rng, to_plot['lows'], '-',
date_rng, to_plot['highs'], '-')
# get the axes reference
ax1 = plt.gca()
# fill in between the lines
ax1.fill_between(date_rng,
to_plot['lows'], to_plot['highs'],
facecolor='#b6b6b6', # gradient fillbetween
alpha=.2)
# set the xaxis to only 12 months and space the names.
ax1.xaxis.set_major_locator(dates.MonthLocator())
ax1.xaxis.set_minor_locator(dates.MonthLocator(bymonthday=15, interval=1))
ax1.xaxis.set_major_formatter(ticker.NullFormatter())
ax1.xaxis.set_minor_formatter(dates.DateFormatter('%b'))
for tick in ax1.xaxis.get_minor_ticks():
tick.tick1line.set_markersize(0)
tick.tick2line.set_markersize(0)
tick.label1.set_horizontalalignment('center')
# add a right y axis and set all yaxis properties
ax1.set_ylim([-50, 50])
# change the color and sizes scheme
info_colors = '#b6b6b6'
bold_colors = '#777777'
# graph lines
ax1.lines[0].set_color('#e93c00') # top redish orange
ax1.lines[1].set_color('#009ae9') # btm blue
plt.setp(lines, lw=.8, alpha=1)
# spines
ax.spines['top'].set_visible(False)
for pos in ['bottom', 'right', 'left']:
ax.spines[pos].set_edgecolor(info_colors)
# set the title
plt.title('Record Temps, 2005-15: Ann Arbour, MI', fontsize=10, color=bold_colors)
# ticks
ax1.tick_params(axis='both', color=info_colors, labelcolor=info_colors, length=5, direction='out', pad=7, labelsize=8)
# add a legend and edit its properties
leg = plt.legend(['Highs','Lows'], frameon=False, loc=0, fontsize='small')
for text in leg.get_texts():
text.set_color(info_colors)
plt.ylabel('˚C', color=info_colors)
# set extra yaxis label
ax2 = ax.twinx()
ax2.set_ylabel('˚F', color=info_colors)
ax2.tick_params('y', colors=info_colors)
要更改次要标签的颜色,请在 ax1.xaxis.set_minor_formatter(dates.DateFormatter('%b'))
之后添加以下代码:
ax1.xaxis.set_tick_params(which='minor', colors=info_colors)
我是 Matplotlib 的新手。这个数字背后的想法是绘制温度高点和低点。我 运行 遇到了 x 轴和右 ya 轴的问题。
对于xaxis,即使我调用tick_params(labelcolor='#b6b6b6')
,字体的颜色也不想改变。此外,日期应该只跨越一月到十二月。出于未知原因,Matplotlib 会在前面加上一个额外的十二月并附加一个额外的一月,导致文本超出图表的脊柱边界。我想删除这些额外的月份。
对于正确的 yaxis,我不确定我是否正确理解了子图的使用。我想将左侧 yaxis 中的 °C 温度转换为 °F,并将转换后的温度用于辅助 yaxis。
这里有一些代码可以重现与我所得到的类似的内容。
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.dates as dates
import matplotlib.ticker as ticker
# generate some data to plot
highs = np.linspace(0, 40, 365) # these numbers will escalate instead of fluctuate, but the problem with the axes will still be the same.
lows = np.linspace(-40, 0, 365)
date_rng = pd.date_range('1/1/2015', '12/31/2015', freq='D')
data = {'highs': highs, 'lows': lows}
to_plot = pd.DataFrame(data, index=date_rng)
fig, ax = plt.subplots()
# plot the basic data
lines = ax.plot(date_rng, to_plot['lows'], '-',
date_rng, to_plot['highs'], '-')
# get the axes reference
ax1 = plt.gca()
# fill in between the lines
ax1.fill_between(date_rng,
to_plot['lows'], to_plot['highs'],
facecolor='#b6b6b6', # gradient fillbetween
alpha=.2)
# set the xaxis to only 12 months and space the names.
ax1.xaxis.set_major_locator(dates.MonthLocator())
ax1.xaxis.set_minor_locator(dates.MonthLocator(bymonthday=15, interval=1))
ax1.xaxis.set_major_formatter(ticker.NullFormatter())
ax1.xaxis.set_minor_formatter(dates.DateFormatter('%b'))
for tick in ax1.xaxis.get_minor_ticks():
tick.tick1line.set_markersize(0)
tick.tick2line.set_markersize(0)
tick.label1.set_horizontalalignment('center')
# add a right y axis and set all yaxis properties
ax1.set_ylim([-50, 50])
# change the color and sizes scheme
info_colors = '#b6b6b6'
bold_colors = '#777777'
# graph lines
ax1.lines[0].set_color('#e93c00') # top redish orange
ax1.lines[1].set_color('#009ae9') # btm blue
plt.setp(lines, lw=.8, alpha=1)
# spines
ax.spines['top'].set_visible(False)
for pos in ['bottom', 'right', 'left']:
ax.spines[pos].set_edgecolor(info_colors)
# set the title
plt.title('Record Temps, 2005-15: Ann Arbour, MI', fontsize=10, color=bold_colors)
# ticks
ax1.tick_params(axis='both', color=info_colors, labelcolor=info_colors, length=5, direction='out', pad=7, labelsize=8)
# add a legend and edit its properties
leg = plt.legend(['Highs','Lows'], frameon=False, loc=0, fontsize='small')
for text in leg.get_texts():
text.set_color(info_colors)
plt.ylabel('˚C', color=info_colors)
# set extra yaxis label
ax2 = ax.twinx()
ax2.set_ylabel('˚F', color=info_colors)
ax2.tick_params('y', colors=info_colors)
要更改次要标签的颜色,请在 ax1.xaxis.set_minor_formatter(dates.DateFormatter('%b'))
之后添加以下代码:
ax1.xaxis.set_tick_params(which='minor', colors=info_colors)