"""Utility functions for static plotting."""
from functools import partial
from numbers import Number
from pathlib import Path
from typing import Iterable, Union
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from matplotlib.axes import Axes
from matplotlib.ticker import EngFormatter
from ..data.stats import get_values
from .style import plot_with_custom_style
[docs]
@plot_with_custom_style
def plot(
df: pd.DataFrame,
x_bounds: Iterable[Number],
y_bounds: Iterable[Number],
save_to: Union[str, Path],
decimals: int,
**save_kwds,
) -> Union[Axes, None]:
"""
Plot the dataset and summary statistics.
Parameters
----------
df : pandas.DataFrame
The dataset to plot.
x_bounds, y_bounds : Iterable[numbers.Number]
The plotting limits.
save_to : str or pathlib.Path
Path to save the plot frame to.
decimals : int
The number of integers to highlight as preserved.
**save_kwds
Additional keyword arguments that will be passed down to
:meth:`matplotlib.figure.Figure.savefig`.
Returns
-------
matplotlib.axes.Axes or None
When ``save_to`` is falsey, an :class:`~matplotlib.axes.Axes` object is returned.
"""
fig, ax = plt.subplots(
figsize=(7, 3), layout='constrained', subplot_kw={'aspect': 'equal'}
)
fig.get_layout_engine().set(w_pad=1.4, h_pad=0.2, wspace=0)
ax.scatter(df.x, df.y, s=1, alpha=0.7, color='black')
ax.set(xlim=x_bounds, ylim=y_bounds)
tick_formatter = EngFormatter()
ax.xaxis.set_major_formatter(tick_formatter)
ax.yaxis.set_major_formatter(tick_formatter)
res = get_values(df)
labels = ('X Mean', 'Y Mean', 'X SD', 'Y SD', 'Corr.')
locs = np.linspace(0.8, 0.2, num=len(labels))
max_label_length = max([len(label) for label in labels])
max_stat = int(np.log10(np.max(np.abs(res)))) + 1
mean_x_digits, mean_y_digits = (
int(x) + 1 for x in np.log10(np.abs([res.x_mean, res.y_mean]))
)
# If `max_label_length = 10`, this string will be "{:<10}: {:0.7f}", then we
# can pull the `.format` method for that string to reduce typing it
# repeatedly
visible_decimals = 7
offset = (
2
if (res.x_mean < 0 and mean_x_digits >= max_stat)
or (res.y_mean < 0 and mean_y_digits >= max_stat)
else 1
)
formatter = '{{:<{pad}}}: {{:{stat_pad}.{decimals}f}}'.format(
pad=max_label_length,
stat_pad=max_stat + visible_decimals + offset,
decimals=visible_decimals,
).format
corr_formatter = '{{:<{pad}}}: {{:+{corr_pad}.{decimals}f}}'.format(
pad=max_label_length,
corr_pad=max_stat + visible_decimals + offset,
decimals=visible_decimals,
).format
stat_clip = visible_decimals - decimals
add_stat_text = partial(
ax.text,
1.05,
fontsize=15,
transform=ax.transAxes,
va='center',
)
for label, loc, stat in zip(labels[:-1], locs, res):
add_stat_text(loc, formatter(label, stat), alpha=0.3)
add_stat_text(loc, formatter(label, stat)[:-stat_clip])
correlation_str = corr_formatter(labels[-1], res.correlation)
for alpha, text in zip([0.3, 1], [correlation_str, correlation_str[:-stat_clip]]):
add_stat_text(
locs[-1],
text,
alpha=alpha,
)
if not save_to:
return ax
save_to = Path(save_to)
dirname = save_to.parent
if not dirname.is_dir():
dirname.mkdir(parents=True, exist_ok=True)
fig.savefig(save_to, bbox_inches='tight', **save_kwds)
plt.close(fig)
