CODEWITHSUNDEEP
pythondatetimematplotlib
naughty_waves
naughty_waves

Reputation: 275

Plotting times versus dates while skipping unwanted dates in Python

I want to make a program that monitors my 5000 meters progress. Inspired by this and this, I tried to make it work by combining some of the answers without any luck.

from __future__ import division
from matplotlib import pyplot as plt
from matplotlib.ticker import FuncFormatter
import matplotlib.dates as mdates
import numpy as np
import datetime as dt

def equidate_ax(fig, ax, dates, fmt="%d.%m.%Y", label="Date"):
    N = len(dates)
    def format_date(index, pos):
        index = np.clip(int(index + 0.5), 0, N - 1)
        return dates[index].strftime(fmt)
    ax.xaxis.set_major_formatter(FuncFormatter(format_date))
    ax.set_xlabel(label)
    fig.autofmt_xdate()

def DistVel2Time(distance, velocity_kph):
    velocity_ms = velocity_kph / 3.6
    time_sec = distance / velocity_ms
    hours = int(time_sec//3600)
    minutes = int((time_sec%3600)//60)
    seconds = int(time_sec%60)
    return "{:02d}:{:02d}".format(minutes, seconds)

times = [DistVel2Time(a, b) for a, b in [(5000, 13), (5000, 15), (5000, 14)]]

dates = [dt.datetime(year, month, day) for year, month, day in [(2019,2,1), (2019,2,2), (2019,2,7)]]

fig_1, ax_1 = plt.subplots()
ax_1.plot(dates, times, 'o--')
ax_1.xaxis_date()
ax_1.xaxis.set_major_formatter(mdates.DateFormatter('%d.%m.%Y'))
#ax_1.yaxis_date()
#ax_1.yaxis.set_major_formatter(mdates.DateFormatter("%M:%S"))
fig_1.autofmt_xdate()
plt.show()

fig_2, ax_2 = plt.subplots()
ax_2.plot(dates, times, 'D--')
ax_2.xaxis_date()
ax_2.xaxis.set_major_formatter(mdates.DateFormatter('%d.%m.%Y'))
equidate_ax(fig_2, ax_2, dates)
plt.show()

fig_1.savefig('fig1.png')
fig_2.savefig('fig2.png')

I stole the equidate_ax from @ascripter (from the second link) because I would like to skip all dates that I do not run.

If I run this piece of code, and save the figures, I end up getting the following two figures that are rather strange, as the y-axis does not distinguish between lower or higher values (Figures 1 and 2), and the x-axis for Figure 2 is repeating itself. enter image description here Figure 1: fig_1 from the code above. enter image description here Figure 2: fig_2 from the code above.

If anyone could help cleaning up my mess, I would be grateful.

Upvotes: 0

Views: 720

Answers (2)

naughty_waves
naughty_waves

Reputation: 275

Although @milck answered my questions, I made a more streamlined version myself inspired by his answer and the previously mentioned answers from the question.

from matplotlib import pyplot as plt
from matplotlib.ticker import FuncFormatter

def DistVel2Time(*velocity_kph):
    distance = 5000
    times = [int(distance / (_ / 3.6)) for _ in velocity_kph]
    return times

times = DistVel2Time(13, 15, 14)

dates = ["%00d.%00d.%000d" % dmy for dmy in [(1,2,2019), (2,2,2019), (7,2,2019)]]

def format_func(x, pos):
    #hours = int(x//3600)
    minutes = int((x%3600)//60)
    seconds = int(x%60)
    return "{:02d}:{:02d}".format(minutes, seconds)

formatter = FuncFormatter(format_func)

fig, ax = plt.subplots()

ax.plot(dates, times, 'D--')
ax.yaxis.set_major_formatter(formatter)
fig.autofmt_xdate()

plt.show()

This is shorter and perhaps easier to understand.

Upvotes: 0

milck
milck

Reputation: 702

Combining the answers from the questions linked:

You basically have to make sure that matplotlib cannot guess the format of the x-axis but can guess the format of the y-axis. With this matplotlib will not try to be smart and add dates you do not want to display on the x-axis but at the same time will be smart and sort the times for you on the y-axis.

from __future__ import division
from matplotlib import pyplot as plt
from matplotlib.ticker import FuncFormatter
import matplotlib.dates as mdates
import numpy as np
import datetime as dt

def DistVel2Time(distance, velocity_kph):
    velocity_ms = velocity_kph / 3.6
    time_sec = distance / velocity_ms
    hours = int(time_sec//3600)
    minutes = int((time_sec%3600)//60)
    seconds = int(time_sec%60)
    # note that I return a timedelta object here
    return dt.timedelta(minutes=minutes, seconds=seconds)

# we have to choose a interpretable data-type here, simply take the total time needed in seconds
times = [ DistVel2Time(a, b).total_seconds() for a, b in [(5000, 13), (5000, 15), (5000, 14)]]

# here we want to make sure that matplotlib cannot interpret it so we use strings directly
# change the format as required
dates = [ "%00d.%00d.%000d" % ymd for ymd in [(2019,2,1), (2019,2,2), (2019,2,7)]]

# the formatting function taken from https://stackoverflow.com/questions/48294332/plot-datetime-timedelta-using-matplotlib-and-python
def format_func(x, pos):
    hours = int(x//3600)
    minutes = int((x%3600)//60)
    seconds = int(x%60)

    return "{:d}:{:02d}:{:02d}".format(hours, minutes, seconds)

formatter = FuncFormatter(format_func)

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)

ax.plot(dates, times, 'o--')
ax.yaxis.set_major_formatter(formatter)

plt.show()

It will produce a plot like this:

Upvotes: 1

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