Use different style for each figure

Question

is it possible to use a different matplotlib style for each figure I create within a script?

with plt.style.context("style.mpstyle"):
    ...

can be used to define a temporary custom style in matplotlib. I'm using this in a class, which should handle all my styles:

class Plots():
    def __init__(self):
        if style == "a":
            self.use_style_a()
        else:
            self.use_style_b()

    def use_style_a():
        with plt.style.context("style_a.mpstyle"):
            self.fig = plt.figure()
            [...]

    def use_style_b():
        with plt.style.context("style_b.mpstyle"):
            self.fig = plt.figure()
            [...]

Unfortunately, it doesn't really work. Or it's only working 50%... so if I call plt.legend() outside of the initial function call, it's not applying the style from the external style file. So is there a way to apply the figure style to that figure instance, no matter from where I call it?

Solution

ImportanceOfBeingErnest gave me the right hint, which I now use in a modified way. Unfortunately, the mpl.style.context() method doesn't work in this case - I don't know why. But I can just always overwrite the style to use. Probably not the mpl creators intention to use, but it works. Here my code:

import matplotlib.pyplot as plt

class Plot(object):
    def __init__(self, name):
        self.plot_style = name

        func = getattr(self, name)
        result = func()

    def A(self):
        plt.style.use("A.mpstyle")
        self.fig = plt.figure()
        self.ax = self.fig.add_subplot(1, 1, 1)

        # Some styles, labels, ...

    def B(self):
        plt.style.use("B.mpstyle")
        self.fig = plt.figure()
        self.ax = self.fig.add_subplot(1, 1, 1)

        # Some styles, labels, ...

    def __getattribute__(self, name):
        if name == "ax":
            plt.style.use("{}.mpstyle".format(self.plot_style))
            return object.__getattribute__(self, name)
        else:
            return object.__getattribute__(self, name)

plot_A = Plot("A")
plot_B = Plot("B")

plot_A.ax.plot([1,2,4],[4,2,3])
plot_B.ax.plot([1,2,4],[3,1,6])
plot_A.ax.legend()
plot_B.ax.legend()

# ...

Answer 1

It think it all depends on how you want to use this class. An option, if you want to create the same plot, but with different styles, would be the following:

import matplotlib.pyplot as plt

class Plots():
    def __init__(self, style):
        self.set_style(style)
        self.plot()

    def set_style(self, style):
        self.style = "style_{}.mpstyle".format(style)

    def plot(self):
        with plt.style.context(self.style):
            self.fig, self.ax = plt.subplots()
            self.ax.plot([1,2,4])
            self.ax.legend()
            plt.show()

p = Plots("a")
p2 = Plots("b")

I could also imagine that you want to use different functions to do the actual plotting and use a class to manage the styles.

import matplotlib.pyplot as plt

class Plots():
    def __init__(self, style="a"):
        self.set_style(style)

    def set_style(self, style):
        self.style = style

    def plot(self, func, *args,**kwargs):
        with plt.style.context(self.style):
            return func(*args,**kwargs)

def myplottingfunction1():
    fig, ax = plt.subplots()
    ax.plot([1,2,4],[4,2,3], label="mylabel 1")
    ax.legend()

def myplottingfunction2(color="red"):
    fig, ax = plt.subplots()
    ax.scatter([1,2,4],[3,1,6], color=color,label="mylabel 2")
    ax.legend()


p = Plots("dark_background").plot(myplottingfunction1)
p2 = Plots("ggplot").plot(myplottingfunction2, color="blue")

plt.show()

The output of this second script would be

Of course the legend can be plotted separately, e.g. like

def myplottingfunction1():
    fig, ax = plt.subplots()
    ax.plot([1,2,4],[4,2,3], label="mylabel 1")
    return ax

def myplottingfunction2(color="red"):
    fig, ax = plt.subplots()
    ax.scatter([1,2,4],[3,1,6], color=color,label="mylabel 2")
    return ax

p = Plots("dark_background")
ax = p.plot(myplottingfunction1)
p2 = Plots("ggplot")
ax2 = p2.plot(myplottingfunction2, color="blue")

# do something else with ax or ax2

p.plot(ax.legend)
p2.plot(ax2.legend)

plt.show()