Wait, i just solved it!
It is not the issue with matplotlib but with the construction of
SelectiveFormatter.
This formatter construction is incomplete. I have created two new
customized ScalarFormatters (default formatters used by matplotlib), the
second one would be a good new addition to sage along with the first one.
We can have both. I have worked out same situation but in native python
with matplotlib. Only thing is to adapt it to sage. It won't be hard to do
that, just need slight adjustments. Please look into the attached two
example python files.
Inspired from:
https://stackoverflow.com/questions/11244514/modify-tick-label-text <--
Discusses similar issue (see second answer from last)
https://stackoverflow.com/questions/63475934/skipping-certain-values-in-python-with-matplotlib
https://github.com/matplotlib/matplotlib/blob/4f5cacfde9024076d9ab0cb6ad1c9a7cf352d5f9/lib/matplotlib/ticker.py
On Saturday, July 30, 2022 at 12:05:24 AM UTC+5:30 kcrisman wrote:
> Time being solution would be to drop use of SelectiveFormatter to get
>> rid of 0 tick label if the axes cross. Let the origin be visible for some
>> time.
>>
>
> My guess is that this would not be seen as a great fix, but let's put
> images and other followup on the ticket.
>
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#!/usr/bin/python
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import rcParams
rcParams['axes.formatter.use_mathtext'] = True
class CustomScalarFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, useOffset=None, useMathText=None, useLocale=None, skip_values=[]):
super().__init__(useOffset=None, useMathText=None, useLocale=None)
self.skip_values = skip_values
def __call__(self, x, pos=None):
"""
Return the format for tick value *x* at position *pos*.
"""
if len(self.locs) == 0:
return ''
#elif x == 0:
# return ''
elif x in self.skip_values:
return ''
else:
xp = (x - self.offset) / (10. ** self.orderOfMagnitude)
if abs(xp) < 1e-8:
xp = 0
return self._format_maybe_minus_and_locale(self.format, xp)
z = np.linspace(-5000, 5000, 100)
fig, ax = plt.subplots()
ax.plot(z,z**2)
xmajorformatter = CustomScalarFormatter(skip_values=[2000,0])
ymajorformatter = CustomScalarFormatter(skip_values=[1E7,0])
ax.xaxis.set_major_formatter(xmajorformatter)
ax.yaxis.set_major_formatter(ymajorformatter)
plt.show()#!/usr/bin/python
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import rcParams
rcParams['axes.formatter.use_mathtext'] = True
class CustomScalarFormatter(matplotlib.ticker.ScalarFormatter):
def __init__(self, useOffset=None, useMathText=None, useLocale=None, replace_values=[]):
super().__init__(useOffset=None, useMathText=None, useLocale=None)
self.replace_values = replace_values
def __call__(self, x, pos=None):
"""
Return the format for tick value *x* at position *pos*.
"""
if len(self.locs) == 0:
return ''
#elif x == 0:
# return ''
elif x in self.replace_values[0]:
idx = self.replace_values[0].index(x)
return str(self.replace_values[1][idx])
else:
xp = (x - self.offset) / (10. ** self.orderOfMagnitude)
if abs(xp) < 1e-8:
xp = 0
return self._format_maybe_minus_and_locale(self.format, xp)
z = np.linspace(0, 5000, 100)
fig, ax = plt.subplots()
ax.plot(z,z**2)
xmajorformatter = CustomScalarFormatter(replace_values=([2000,0],['$x_0$','']))
ymajorformatter = CustomScalarFormatter(replace_values=([1E7,0],['$y_0$','']))
ax.xaxis.set_major_formatter(xmajorformatter)
ax.yaxis.set_major_formatter(ymajorformatter)
plt.show()
