Adapt 2D-plot tick label attributes to dates

savecancel

Hello, @MrDvbnhbq! I can see that you already got an answer for your question. However, I have an alternative approach.

As far as I know, there is no direct way to do this in SageMath, so we are going to use a mix of Sage plots and Matplotlib plots, i.e., we will use the matplotlib() command. All the arguments that you passed to list_plot() can be passed to the matplotlib() command, except for the thickness and the plotjoined parameters, which are exclusive of the former.

Consider the following instructions:

%matplotlib inline
import csv
from datetime import datetime
from matplotlib import ticker
from matplotlib import dates
import matplotlib.pyplot as plt

data = [ ( '04/22/20', '04/23/20', '04/24/20','04/25/20','04/26/20', '04/27/20' ), (20, 40, 80, 160, 320, 640) ]
labels = data[0]
labels = map(lambda x: dates.date2num(datetime.strptime(x, '%m/%d/%y')), labels)
labels = list(labels)
values = data[1]
values = map(lambda x: int(x), values)

Z = zip(labels, values)
Z = list(Z)

p = list_plot(Z, plotjoined=true, thickness=2)

G = p.matplotlib(figure=plt.gcf(),scale='semilogy',tick_formatter=[dates.DateFormatter('%d.%m.%Y'), None], axes_labels=[ 'Days', '$\\log \\;{N}$' ], ticks=[1, None], figsize=4)
G.autofmt_xdate(rotation=45)
G.show()

I have made only three changes to your code:

1. I have used the magic %matplotlib inline as the first line, so that Matplotlib figures are shown in SageCell or Jupyter(lab).
2. I have imported pyplot under the name plt on line 6.
3. I have moved all the arguments you used in list_plot to the matplotlib() command, including the additional argument figure=plt.gcf().
4. Concerning the rotation of the xticks, I used the G.autofmt_xdate(rotation=45) command. However, you can also use the plt.xticks(rotation=45) instruction; since Matplotlib already knows you are working with the current figure (that's the plt.gcf()), it will apply the changes directly to it, in that case.

That's it!

By the way, you can remove the G.show() line, which I included for completeness.

The problem with your previous approach, and @Sébastien's is that the matplotlib() command does not preserve the semilog y-axis, nor the ticks formatter, etc. So, instead of using those options in list_plot where they will be overwritten later by matplotlib(), I passed them to the latter, so it can't ignore them.

The final result should look like this:

I hope this helps!

Ok, so it seems what was missing is the "get current graphics", see this other question. Now this works:

sage: import matplotlib.pyplot as mpl
sage: figure = p.matplotlib(figure=mpl.gcf())
sage: figure.autofmt_xdate(rotation=45)
sage: figure.show()
sage: figure.savefig('a.png')

But then, the dates and log y scales need more work. There must be a way to fix this... Alternatively, you may use pandas (which is an optional python library that one can install by doing sage -pip install pandas):

sage: from datetime import datetime
sage: data = [ ( '04/22/20', '04/23/20', '04/24/20','04/25/20','04/26/20', '04/27/20'), (20, 40, 80,160, 320, 640) ]
sage: labels = [datetime.strptime(x, '%m/%d/%y') for x in data[0]]
sage: values = [int(a) for a in data[1]]
sage: import pandas as pd
sage: df = pd.DataFrame({'dates':labels,'values':values})
sage: df
       dates  values
0 2020-04-22      20
1 2020-04-23      40
2 2020-04-24      80
3 2020-04-25     160
4 2020-04-26     320
5 2020-04-27     640
sage: df.plot(x='dates', y='values', title='title', rot=30, logy=True, figsize=[4,4], yticks=[10,100,1000])

For the image to appear in a Jupyter notebook, add the following in the first cell:

%matplotlib inline