Issue with PP-plot and different distributions

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
28/100
Issue type
Bug
Clarity
Needs clarification
Activity status
Stale
Tech stack
matplotlib, python

Research direction

Start with the probscale.probplot call shown in the issue and compare the two dist arguments used for the PP-plots. Determine whether identical plots are expected for these distributions; completion would require documenting the behavior or resolving it if it is incorrect.

Written by the indexing model from the issue text.

Description

Documentation
  • Python version: Python 3.6.8
  • numpy version: 1.14.3
  • matplotlib version: 2.0.2
  • mpl-probscale version: 0.2.3
  • Operating System: MacOS Mojave 10.14.3
Description

I tried modifying the examples from the documentation and created two PP-plots: one using Standard Normal Distribution as the theoretical distribution, another one using N(100, 5). And both plots look exactly the same (this is not true for QQ-plots). Am I missing something?

What I Did
import warnings
warnings.simplefilter('ignore')

import numpy
from matplotlib import pyplot
import seaborn
from scipy import stats
import probscale
clear_bkgd = {'axes.facecolor':'none', 'figure.facecolor':'none'}
seaborn.set(style='ticks', context='talk', color_codes=True, rc=clear_bkgd)

# load up some example data from the seaborn package
tips = seaborn.load_dataset("tips")

%matplotlib inline
%config InlineBackend.figure_format ='retina'

common_opts = dict(
    plottype='pp',
    probax='x',
    datascale='log',
    datalabel='Total Bill (USD)',
    scatter_kws=dict(marker='+', linestyle='none', mew=1)
)

norm = stats.norm(100, 5)

fig, (ax1, ax2) = pyplot.subplots(figsize=(10, 6), ncols=2, sharex=True)
fig = probscale.probplot(tips['total_bill'], ax=ax1, dist=norm,
                         problabel='N(100, 5) Probabilities', **common_opts)

fig = probscale.probplot(tips['total_bill'], ax=ax2, dist=None,
                         problabel='Standard Normal Probabilities', **common_opts)

seaborn.despine()
Dominant language
Python
Stars
40
Forks
11
PR merge metrics
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