145 lines
4.6 KiB
Python
145 lines
4.6 KiB
Python
"""
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* Saner default config.
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* Matplotlib API methods have an immediate effect on the figure. We do not want
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it, then we write a buffer on top of matplotlib API.
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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import seaborn.apionly as sns
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__VERSION__ = "0.0.1"
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# TODO: Remove it, this is interfering with matplotlib
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plt.rcParams['figure.figsize'] = (10.0, 8.0) # Larger figures by default
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plt.rcParams['text.usetex'] = True # Use LaTeX rendering
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class Figure():
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def __init__(self,
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xlabel="", ylabel="", title="", palette="hls",
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legend=None):
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# TODO: Constants
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self.max_colors = 10
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self.default_points_number = 1000
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self.default_x_interval = np.linspace(-10, 10,
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self.default_points_number)
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# Set default values for attributes
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self.xlabel = xlabel
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self.ylabel = ylabel
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self.title = title
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self.palette = palette
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self.legend = legend
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self.plots = []
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def __enter__(self):
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return self
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def __exit__(self, exception_type, exception_value, traceback):
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self.show()
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def show(self):
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"""
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Actually render and show the figure.
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"""
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# Tweak matplotlib to use seaborn
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sns.set()
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# Plot using specified color palette
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with sns.color_palette(self.palette, self.max_colors):
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# Create figure
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figure, axes = plt.subplots()
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# Add plots
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for plot in self.plots:
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axes.plot(*(plot[0]), **(plot[1]))
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# Set properties
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axes.set_xlabel(self.xlabel)
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axes.set_ylabel(self.ylabel)
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axes.set_title(self.title)
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if self.legend is not None and self.legend is not False:
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self._legend(axes, location=self.legend)
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# Draw figure
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figure.show()
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# Do not forget to restore matplotlib state, in order not to interfere
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# with it.
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sns.reset_orig()
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#def palette(self, palette):
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# """
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# """
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# if isinstance(palette, str):
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# self.current_palette = palette
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# with seaborn.color_palette(self.current_palette, self.max_colors):
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# # TODO
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# pass
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def plot(self, data, *args, **kwargs):
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"""
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Plot something on the figure.
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>>> plot(np.sin)
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>>> plot(np.sin, (-1, 1))
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>>> plot(np.sin, [-1, -0.9, …, 1])
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>>> plot([1, 2, 3], [4, 5, 6])
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"""
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if hasattr(data, "__call__"):
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# We want to plot a function
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self._plot_function(data, *args, **kwargs)
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else:
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# Else, it is a point series, and we just have to store it for
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# later plotting.
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self.plots.append(((data,) + args, kwargs))
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# Automatically set the legend if label is found
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# (only do it if legend is not explicitly suppressed)
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if "label" in kwargs and self.legend is None:
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self.legend = True
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def _plot_function(self, data, *args, **kwargs):
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"""
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"""
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# TODO: Better default interval and so on
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if len(args) == 0:
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# No interval specified, using default one
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x_values = self.default_x_interval
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elif isinstance(args[0], (list, np.ndarray)):
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# List of points specified
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x_values = args[0]
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elif isinstance(args[0], tuple):
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# Interval specified, generate a list of points
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x_values = np.linspace(args[0][0], args[0][1],
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self.default_points_number)
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else:
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# TODO: Error
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assert False
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y_values = [data(i) for i in x_values]
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self.plots.append(((x_values, y_values) + args[1:], kwargs))
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def _legend(self, axes, location="best"):
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"""
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"""
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if location is True:
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# If there should be a legend, but no location provided, put it at
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# best location.
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location = "best"
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# Create aliases for "upper" / "top" and "lower" / "bottom"
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location.replace("top ", "upper ")
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location.replace("bottom ", "lower ")
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# Avoid warning if no labels were given for plots
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nb_labelled_plots = sum(["label" in plt[1] for plt in self.plots])
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if nb_labelled_plots > 0:
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# Add legend
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axes.legend(loc=location)
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def plot(data, **kwargs):
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"""
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"""
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figure = Figure(**kwargs)
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# TODO: Fix API, support every plot type
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for plt in data:
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figure.plot(plt)
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figure.show()
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