Python matplotlib 模块，rcdefaults() 实例源码

def reset_matplotlib():
    """
    Reset matplotlib to a common default.
    """
    # Set all default values.
    mpl.rcdefaults()
    # Force agg backend.
    plt.switch_backend('agg')
    # These settings must be hardcoded for running the comparision tests and
    # are not necessarily the default values.
    mpl.rcParams['font.family'] = 'Bitstream Vera Sans'
    mpl.rcParams['text.hinting'] = False
    # Not available for all matplotlib versions.
    try:
        mpl.rcParams['text.hinting_factor'] = 8
    except KeyError:
        pass
    import locale
    locale.setlocale(locale.LC_ALL, str('en_US.UTF-8'))


# Most generic way to get the data folder path.

def _setup():
    # The baseline images are created in this locale, so we should use
    # it during all of the tests.
    try:
        locale.setlocale(locale.LC_ALL, str('en_US.UTF-8'))
    except locale.Error:
        try:
            locale.setlocale(locale.LC_ALL, str('English_United States.1252'))
        except locale.Error:
            warnings.warn(
                "Could not set locale to English/United States. "
                "Some date-related tests may fail")

    plt.switch_backend('Agg')  # use Agg backend for these test
    if mpl.get_backend().lower() != "agg":
        msg = ("Using a wrong matplotlib backend ({0}), "
               "which will not produce proper images")
        raise Exception(msg.format(mpl.get_backend()))

    # These settings *must* be hardcoded for running the comparison
    # tests
    mpl.rcdefaults()  # Start with all defaults
    mpl.rcParams['text.hinting'] = True
    mpl.rcParams['text.antialiased'] = True
    mpl.rcParams['text.hinting_factor'] = 8

    # make sure we don't carry over bad plots from former tests
    msg = ("no of open figs: {} -> find the last test with ' "
           "python tests.py -v' and add a '@cleanup' decorator.")
    assert len(plt.get_fignums()) == 0, msg.format(plt.get_fignums())

def reset_matplotlib():
    """
    Reset matplotlib to a common default.
    """
    # Set all default values.
    mpl.rcdefaults()
    # Force agg backend.
    plt.switch_backend('agg')

def setUp(self):
        TestPlotBase.setUp(self)
        import matplotlib as mpl
        mpl.rcdefaults()

        self.ts = tm.makeTimeSeries()
        self.ts.name = 'ts'

        self.series = tm.makeStringSeries()
        self.series.name = 'series'

        self.iseries = tm.makePeriodSeries()
        self.iseries.name = 'iseries'

def setUp(self):
        TestPlotBase.setUp(self)
        import matplotlib as mpl
        mpl.rcdefaults()

        self.tdf = tm.makeTimeDataFrame()
        self.hexbin_df = DataFrame({
            "A": np.random.uniform(size=20),
            "B": np.random.uniform(size=20),
            "C": np.arange(20) + np.random.uniform(size=20)})

        from pandas import read_csv
        path = os.path.join(curpath(), 'data', 'iris.csv')
        self.iris = read_csv(path)

def setUp(self):

        import matplotlib as mpl
        mpl.rcdefaults()

        n = 100
        with tm.RNGContext(42):
            gender = np.random.choice(['Male', 'Female'], size=n)
            classroom = np.random.choice(['A', 'B', 'C'], size=n)

            self.hist_df = DataFrame({'gender': gender,
                                      'classroom': classroom,
                                      'height': random.normal(66, 4, size=n),
                                      'weight': random.normal(161, 32, size=n),
                                      'category': random.randint(4, size=n)})

        self.mpl_le_1_2_1 = plotting._mpl_le_1_2_1()
        self.mpl_ge_1_3_1 = plotting._mpl_ge_1_3_1()
        self.mpl_ge_1_4_0 = plotting._mpl_ge_1_4_0()
        self.mpl_ge_1_5_0 = plotting._mpl_ge_1_5_0()

        if self.mpl_ge_1_4_0:
            self.bp_n_objects = 7
        else:
            self.bp_n_objects = 8
        if self.mpl_ge_1_5_0:
            # 1.5 added PolyCollections to legend handler
            # so we have twice as many items.
            self.polycollection_factor = 2
        else:
            self.polycollection_factor = 1

def setUp(self):
        TestPlotBase.setUp(self)
        import matplotlib as mpl
        mpl.rcdefaults()

        self.ts = tm.makeTimeSeries()
        self.ts.name = 'ts'

        self.series = tm.makeStringSeries()
        self.series.name = 'series'

        self.iseries = tm.makePeriodSeries()
        self.iseries.name = 'iseries'

def setUp(self):
        TestPlotBase.setUp(self)
        import matplotlib as mpl
        mpl.rcdefaults()

        self.tdf = tm.makeTimeDataFrame()
        self.hexbin_df = DataFrame({"A": np.random.uniform(size=20),
                                    "B": np.random.uniform(size=20),
                                    "C": np.arange(20) + np.random.uniform(
                                        size=20)})

        from pandas import read_csv
        path = os.path.join(curpath(), 'data', 'iris.csv')
        self.iris = read_csv(path)

def mfista_plots(fdfin, ptable, filename=None,
                 plotargs={'ms': 1., }):
    isinteractive = plt.isinteractive()
    backend = matplotlib.rcParams["backend"]

    if isinteractive:
        plt.ioff()
        matplotlib.use('Agg')

    nullfmt = NullFormatter()

    # Get model data
    modelptable = ptable.copy()
    modelptable.observe(fdfin)

    # Save fdf
    if filename is not None:
        util.matplotlibrc(nrows=4, ncols=2, width=400, height=150)
    else:
        matplotlib.rcdefaults()

    fig, axs = plt.subplots(nrows=4, ncols=2, sharex=False)
    fdfin.plot(axs=axs[:,0],color="red")
    ptable.plot(axs=axs[:,1],color="black", ploterror=True)
    modelptable.plot(axs=axs[:,1], color="red")
    if filename is not None:
        plt.savefig(filename)
        plt.close()
    else:
        plt.show()

    if isinteractive:
        plt.ion()
        matplotlib.use(backend)