matplotlib:x轴上时间戳的格式 [英] matplotlib: formatting of timestamp on x-axis
问题描述
我正在尝试在天气数据图中设置x轴的格式.我对y轴感到满意，但是到目前为止，我为使x轴成为一种体面的，人类可读的格式所做的所有尝试都没有奏效.因此，经过数小时的反复试验，希望能对您有所帮助.
I'm trying to format the x-axis in my weather data plot. I'm happy with the y-axis but all my tries to get the x-axis into a decent, human-readable format didn't work so far. So after several hours of trial and error I hope for your help.
最后，我希望每30分钟有一个刻度线，每小时有一条垂直的虚线网格线，其下方写有HH:MM的时间，另外还有每晚00:00时写的日期.像这样(注意，前面的ASCII艺术不好！):
In the end I would like to have tick marks every 30 minutes, a vertical dotted grid line every hour with the time written as HH:MM beneath it and additionally the date written every night at 00:00 hours. Something like this (caution, bad ASCII art ahead!):
: : :
: : :
: : :
: : :
: : :
|====|====|====|====|====|====|====
23:00 00:00 01:00
09JAN18
所有时间都是UTC，这将是最终的豪华版本.但是我的问题是从更早开始的.
All times in UTC and this would be the ultimate deluxe version. But my problems started way earlier.
一开始，我试图将其转换为可读的格式.我想出了
For the beginning I tried to get it into a readable format. I came up with
locator = mdates.AutoDateLocator()
plt.gca().xaxis.set_major_locator(locator)
plt.gca().xaxis.set_major_formatter(mdates.AutoDateFormatter(locator))
，希望我能摆脱这个麻烦
and hoped I'll get rid of the exp
输出结果并非我所希望的:
The output isn't exactly what I hoped for:
pi@raspi3b:~/wx-logging $ python plot.py
[( 15.94, 57.86, 992.65, 1019.99, 1515460740)
( 15.96, 57.8 , 992.65, 1019.99, 1515460745)
( 15.99, 57.79, 992.68, 1020.02, 1515460750) ...,
( 13.25, 55.7 , 990.16, 1017.43, 1515496060)
( 13.31, 56. , 990.14, 1017.41, 1515496065)
( 13.34, 56.32, 990.13, 1017.4 , 1515496070)]
Traceback (most recent call last):
File "plot.py", line 123, in <module>
plt.savefig("plot.png", dpi=150)
File "/usr/lib/python2.7/dist-packages/matplotlib/pyplot.py", line 697, in savefig
res = fig.savefig(*args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/figure.py", line 1572, in savefig
self.canvas.print_figure(*args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/backend_bases.py", line 2244, in print_figure
**kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.py", line 545, in print_png
FigureCanvasAgg.draw(self)
File "/usr/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.py", line 464, in draw
self.figure.draw(self.renderer)
File "/usr/lib/python2.7/dist-packages/matplotlib/artist.py", line 63, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/figure.py", line 1143, in draw
renderer, self, dsu, self.suppressComposite)
File "/usr/lib/python2.7/dist-packages/matplotlib/image.py", line 139, in _draw_list_compositing_images
a.draw(renderer)
File "/usr/lib/python2.7/dist-packages/mpl_toolkits/axes_grid1/parasite_axes.py", line 295, in draw
self._get_base_axes_attr("draw")(self, renderer)
File "/usr/lib/python2.7/dist-packages/mpl_toolkits/axisartist/axislines.py", line 778, in draw
super(Axes, self).draw(renderer, inframe)
File "/usr/lib/python2.7/dist-packages/matplotlib/artist.py", line 63, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "/usr/lib/python2.7/dist-packages/matplotlib/axes/_base.py", line 2409, in draw
mimage._draw_list_compositing_images(renderer, self, dsu)
File "/usr/lib/python2.7/dist-packages/matplotlib/image.py", line 139, in _draw_list_compositing_images
a.draw(renderer)
File "/usr/lib/python2.7/dist-packages/mpl_toolkits/axisartist/axis_artist.py", line 915, in draw
gl = self._grid_helper.get_gridlines(self._which, self._axis)
File "/usr/lib/python2.7/dist-packages/mpl_toolkits/axisartist/axislines.py", line 546, in get_gridlines
locs.extend(self.axes.xaxis.major.locator())
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 983, in __call__
self.refresh()
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 1003, in refresh
dmin, dmax = self.viewlim_to_dt()
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 760, in viewlim_to_dt
return num2date(vmin, self.tz), num2date(vmax, self.tz)
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 401, in num2date
return _from_ordinalf(x, tz)
File "/usr/lib/python2.7/dist-packages/matplotlib/dates.py", line 254, in _from_ordinalf
dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC)
ValueError: year is out of range
pi@raspi3b:~/wx-logging $
不太有前途.我不知道为什么它说ValueError: year is out of range，因为它是一个Unix时代的时间戳.
Not exactly promising. I couldn't figure out why it says ValueError: year is out of range as it is a unix epoch timestamp.
我做错了什么?如何获得上面概述的预期结果?我非常感谢朝着正确方向前进.谢谢您的帮助！
What am I doing wrong? How can I achieve the desired result outlined above? I would really appreciate a nudge in the right direction. Thank you for your help!
祝一切顺利， 克里斯
为了给您一些背景，到目前为止我完整的脚本.
To give you some context here my complete script so far.
#!/usr/bin/python
# -*- coding: utf-8 -*-
import matplotlib
matplotlib.use('AGG')
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as aa
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.ticker import FuncFormatter
import numpy as np
from numpy import vectorize
import datetime
import shutil
import math
# Dewpoint calculation
def dewpoint(tempC, rlHum):
r = 8314.3
mw = 18.016
if tempC >= 0:
a = 7.5
b = 237.3
# over water:
# elif tempC < 0:
# a = 7.6
# b = 240.7
#
# over ice:
elif tempC < 0:
a = 9.5
b = 265.5
saettDampfDruck = 6.1078 * 10**((a*tempC)/(b+tempC))
dampfDruck = rlHum / 100.0 * saettDampfDruck
v = math.log10(dampfDruck/6.1078)
dewpC = b*v/(a-v)
return dewpC
# translate cm into inches
def cm2inch(*tupl):
inch = 2.54
if isinstance(tupl[0], tuple):
return tuple(i/inch for i in tupl[0])
else:
return tuple(i/inch for i in tupl)
vdewpoint = vectorize(dewpoint)
convertDate = lambda x: datetime.datetime.utcfromtimestamp(x)
data = np.genfromtxt('/home/pi/wx-logging/wx-log2.txt',
delimiter=';',
usecols=(1, 2, 3, 5, 6),
names=['temp', 'humidity', 'press', 'slp', 'time'],
converters={'6': convertDate},
dtype='float, float, float, float, int')
print data
plt.figure(figsize=cm2inch(29.7, 21))
host = host_subplot(111, axes_class=aa.Axes)
plt.subplots_adjust(right=0.75)
par1 = host.twinx()
par2 = host.twinx()
offset = 70 # offset of detached axis
new_fixed_axis = par2.get_grid_helper().new_fixed_axis
par2.axis["right"] = par2.get_grid_helper().new_fixed_axis(loc="right",
axes=par2,
offset=(offset, 0))
par1.axis["right"].toggle(all=True)
par2.axis["right"].toggle(all=True)
host.set_title("Weather Station")
host.set_xlabel("Time")
host.set_ylabel("Temperature & Dewpoint [" + u'\u00b0'+ "C]")
par1.set_ylabel("Sealevel Pressure [hPa]")
par2.set_ylabel("relative Humidity [%]")
host.set_ylim([-20, 40]) # temperature range -20C ... +40C
par1.set_ylim([980, 1040]) # slp range 980hPa ... 1040hPa
par2.set_ylim([0, 100]) # percent
p1, = host.plot(data['time'],
data['temp'],
label="Temperature",
color="red",
linewidth=2)
p2, = host.plot(data['time'],
vdewpoint(data['temp'],
data['humidity']),
label="Dewpoint",
color="salmon",
linewidth=0.75)
p3, = par1.plot(data['time'],
data['slp'],
label="Sealevel Pressure",
color="blue",
linewidth=0.75)
p4, = par2.plot(data['time'],
data['humidity'],
label="rel. Humidity",
color="grey",
linewidth=0.5)
locator = mdates.AutoDateLocator()
plt.gca().xaxis.set_major_locator(locator)
plt.gca().xaxis.set_major_formatter(mdates.AutoDateFormatter(locator))
plt.legend(bbox_to_anchor=(0.05, 0.05),
loc=3,
ncol=2,
borderaxespad=0.)
plt.savefig("plot.png", dpi=150)
shutil.copyfile('/home/pi/wx-logging/plot.png', '/var/www/html/plot.png')
EDIT1 :您可以下载 wx-log2.txt (〜58KB)，其中包含用于实验脚本的示例数据. tiago的正确建议
You can download wx-log2.txt (~58KB) with sample data for experimenting with the script. Rightly suggested by tiago
推荐答案
您的代码有些错误.首先，在converters={'6':中的引号中使用该列意味着永远不会应用转换函数.使用不带引号的列号:
There are a few things wrong with your code. First, using the column in quotes in converters={'6': means that the conversion function will never be applied. Use column number without quotes:
converters={6: convertDate},
另一个问题是您需要从字符串转换为整数，否则您的日期时间转换将不起作用:
Another problem is that you need to convert from string to integer, otherwise your datetime conversion will not work:
convertDate = lambda x: datetime.datetime.utcfromtimestamp(int(x))
最后，您的time字段的数据类型必须为numpy.datatype64(并以微秒为单位进行指定，因为这是utcfromtimestamp返回的结果).在np.genfromtxt调用中分配数据类型的正确方法如下:
Finally, the datatype of your time field has to be numpy.datatype64 (and specify in micro seconds because that is what utcfromtimestamp returns). The proper way to assign the datatypes in your np.genfromtxt call is the following:
data = np.genfromtxt('wx-log2.txt',
delimiter=';',
converters={6: convertDate},
usecols=(1,2,3,5,6),
dtype=[('temp', 'f'), ('humidity', 'f'), ('press', 'f'),
('slp', 'f'), ('time', 'datetime64[us]')])
使用上述内容，您应该如何以plt.plot_date可以理解的格式来安排时间.
With the following above, you should how have the time in a format that plt.plot_date can understand.
对于日期格式，您可以通过将次要刻度标签设置为HH:MM，将主要刻度号设置为一年中的日期来获得与尝试实现的功能类似的功能，但是我不知道每30分钟还有一个未标记的刻度线.
For the date format, you can have something similar to what you are trying to achieve by setting the minor tick mark labels to be HH:MM and the major to be day of year, but I don't know a way to have in addition unlabelled tick marks every 30 min.
这是一个简单的示例，具有正确的时间数组，并以与所需格式相似的格式进行绘制.为简单起见，每隔4个小时只写一次刻度线，但是您可以更改它.
Here is a simple example that has a proper time array and plots in a similar format to what you want. For simplicity, only writing tick marks every 4 hours, but you can change it.
import numpy as np
import matplotlib.dates as dates
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
idx = pd.date_range('2018-01-07', '2018-01-09', freq='10min')
# generate a time range series with 10 min intervals
idx = np.arange('2018-01-07T00', '2018-01-09T02', 10, dtype='datetime64[m]')
# some random data
y = np.sin(np.arange(idx.shape[0]) / 0.01)
ax.plot_date(idx, y, '-')
ax.xaxis.set_minor_locator(dates.HourLocator(interval=4)) # every 4 hours
ax.xaxis.set_minor_formatter(dates.DateFormatter('%H:%M')) # hours and minutes
ax.xaxis.set_major_locator(dates.DayLocator(interval=1)) # every day
ax.xaxis.set_major_formatter(dates.DateFormatter('\n%d-%m-%Y'))
这篇关于matplotlib:x轴上时间戳的格式的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
