replot/replot.py

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Python
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2016-03-01 14:51:25 +01:00
"""
* Saner default config.
* Matplotlib API methods have an immediate effect on the figure. We do not want
it, then we write a buffer on top of matplotlib API.
"""
import matplotlib.pyplot as plt
import numpy as np
import seaborn
plt.rcParams['figure.figsize'] = (10.0, 8.0) # Larger figures by default
plt.rcParams['text.usetex'] = True # Use LaTeX rendering
class Figure():
def __init__(self,
xlabel="", ylabel="", title="", palette="hls",
legend=None):
self.max_colors = 10
self.default_points_number = 1000
self.default_x_interval = np.linspace(-10, 10,
self.default_points_number)
self.xlabel = xlabel
self.ylabel = ylabel
self.title = title
self.palette = palette
# TODO: Legend should be automatic if labelled data is found
self.legend = legend
self.plots = []
def __enter__(self):
return self
def __exit__(self, exception_type, exception_value, traceback):
self.show()
def show(self):
"""
"""
seaborn.set()
with seaborn.color_palette(self.palette, self.max_colors):
# Create figure
figure, axes = plt.subplots()
# Add plots
for plot in self.plots:
axes.plot(*(plot[0]), **(plot[1]))
# Set properties
axes.set_xlabel(self.xlabel)
axes.set_ylabel(self.ylabel)
axes.set_title(self.title)
if self.legend is not None:
self._legend(axes, location=self.legend)
# Draw figure
figure.show()
seaborn.reset_orig()
#def palette(self, palette):
# """
# """
# if isinstance(palette, str):
# self.current_palette = palette
# with seaborn.color_palette(self.current_palette, self.max_colors):
# # TODO
# pass
def plot(self, data, *args, **kwargs):
"""
Plot something on the figure.
>>> plot(np.sin)
>>> plot(np.sin, (-1, 1))
>>> plot(np.sin, [-1, -0.9, , 1])
>>> plot([1, 2, 3], [4, 5, 6])
"""
if hasattr(data, "__call__"):
self._plot_function(data, *args, **kwargs)
else:
self.plots.append(((data,) + args, kwargs))
def _plot_function(self, data, *args, **kwargs):
"""
"""
# TODO: Better default interval and so on
if len(args) == 0:
# No interval specified, using default one
x_values = self.default_x_interval
elif isinstance(args[0], (list, np.ndarray)):
x_values = args[0]
elif isinstance(args[0], tuple):
x_values = np.linspace(args[0][0], args[0][1],
self.default_points_number)
else:
# TODO: Error
assert False
y_values = [data(i) for i in x_values]
self.plots.append(((x_values, y_values) + args[1:], kwargs))
def _legend(self, axes, location="best"):
"""
"""
# If there should be a legend, but no location provided, put it at best
# location
if location is True:
location = "best"
location.replace("top ", "upper ")
location.replace("bottom ", "lower ")
axes.legend(loc=location)