Python style.context函数代码示例

def test_context_with_badparam():
    original_value = 'gray'
    other_value = 'blue'
    d = OrderedDict([(PARAM, original_value), ('badparam', None)])
    with style.context({PARAM: other_value}):
        assert mpl.rcParams[PARAM] == other_value
        x = style.context([d])
        assert_raises(KeyError, x.__enter__)
        assert mpl.rcParams[PARAM] == other_value

def test_context_with_badparam():
    if sys.version_info[:2] >= (2, 7):
        from collections import OrderedDict
    else:
        m = "Test can only be run in Python >= 2.7 as it requires OrderedDict"
        raise SkipTest(m)

    original_value = 'gray'
    other_value = 'blue'
    d = OrderedDict([(PARAM, original_value), ('badparam', None)])
    with style.context({PARAM: other_value}):
        assert mpl.rcParams[PARAM] == other_value
        x = style.context([d])
        assert_raises(KeyError, x.__enter__)
        assert mpl.rcParams[PARAM] == other_value

def test_stationlayout_api():
    'Test the StationPlot api'
    setup_font()
    with style.context(test_style):
        fig = make_figure(figsize=(9, 9))

        # testing data
        x = np.array([1, 5])
        y = np.array([2, 4])
        data = dict()
        data['temp'] = np.array([32., 212.]) * units.degF
        data['u'] = np.array([2, 0]) * units.knots
        data['v'] = np.array([0, 5]) * units.knots
        data['stid'] = ['KDEN', 'KSHV']
        data['cover'] = [3, 8]

        # Set up the layout
        layout = StationPlotLayout()
        layout.add_barb('u', 'v', units='knots')
        layout.add_value('NW', 'temp', fmt='0.1f', units=units.degC, color='darkred')
        layout.add_symbol('C', 'cover', sky_cover, color='magenta')
        layout.add_text((0, 2), 'stid', color='darkgrey')
        layout.add_value('NE', 'dewpt', color='green')  # This should be ignored

        # Make the plot
        sp = StationPlot(fig.add_subplot(1, 1, 1), x, y, fontsize=12)
        layout.plot(sp, data)

        sp.ax.set_xlim(0, 6)
        sp.ax.set_ylim(0, 6)
        hide_tick_labels(sp.ax)

        return fig

def test_nws_layout():
    'Test metpy\'s NWS layout for station plots'
    setup_font()
    with style.context(test_style):
        fig = make_figure(figsize=(3, 3))

        # testing data
        x = np.array([1])
        y = np.array([2])
        data = dict()
        data['air_temperature'] = np.array([77]) * units.degF
        data['dew_point_temperature'] = np.array([71]) * units.degF
        data['air_pressure_at_sea_level'] = np.array([999.8]) * units('mbar')
        data['eastward_wind'] = np.array([15.]) * units.knots
        data['northward_wind'] = np.array([15.]) * units.knots
        data['cloud_coverage'] = [7]
        data['present_weather'] = [80]
        data['high_cloud_type'] = [1]
        data['medium_cloud_type'] = [3]
        data['low_cloud_type'] = [2]
        data['visibility_in_air'] = np.array([5.]) * units.mile
        data['tendency_of_air_pressure'] = np.array([-0.3]) * units('mbar')
        data['tendency_of_air_pressure_symbol'] = [8]

        # Make the plot
        sp = StationPlot(fig.add_subplot(1, 1, 1), x, y, fontsize=12, spacing=16)
        nws_layout.plot(sp, data)

        sp.ax.set_xlim(0, 3)
        sp.ax.set_ylim(0, 3)
        hide_tick_labels(sp.ax)

        return fig

def test_skewt_gridspec():
    'Test using SkewT on a sub-plot'
    with style.context(test_style):
        fig = make_figure(figsize=(9, 9))
        gs = GridSpec(1, 2)
        hide_tick_labels(SkewT(fig, subplot=gs[0, 1]).ax)
        return fig

 def run(self):
     scan_loader = self._make_scan_loader()
     gpsms = self._load_spectrum_matches()
     if not os.path.exists(self.output_path):
         os.makedirs(self.output_path)
     n = len(gpsms)
     self.log("%d Spectrum Matches" % (n,))
     for i, gpsm in enumerate(gpsms):
         scan = scan_loader.get_scan_by_id(gpsm.scan.scan_id)
         gpep = gpsm.structure.convert()
         if i % 10 == 0:
             self.log("... %0.2f%%: %s @ %s" % (((i + 1) / float(n) * 100.0), gpep, scan.id))
         with style.context(self._mpl_style):
             fig = figure()
             grid = plt.GridSpec(nrows=5, ncols=1)
             ax1 = fig.add_subplot(grid[1, 0])
             ax2 = fig.add_subplot(grid[2:, 0])
             ax3 = fig.add_subplot(grid[0, 0])
             match = CoverageWeightedBinomialModelTree.evaluate(scan, gpep)
             ax3.text(0, 0.5, (
                 str(match.target) + '\n' + scan.id +
                 '\nscore=%0.3f    q value=%0.3g' % (gpsm.score, gpsm.q_value)), va='center')
             ax3.axis('off')
             match.plot(ax=ax2)
             glycopeptide_match_logo(match, ax=ax1)
             fname = format_filename("%s_%s.pdf" % (scan.id, gpep))
             path = os.path.join(self.output_path, fname)
             abspath = os.path.abspath(path)
             if len(abspath) > 259 and platform.system().lower() == 'windows':
                 abspath = '\\\\?\\' + abspath
             fig.savefig(abspath, bbox_inches='tight')
             plt.close(fig)

def test_context():
    mpl.rcParams[PARAM] = 'gray'
    with temp_style('test', DUMMY_SETTINGS):
        with style.context('test'):
            assert mpl.rcParams[PARAM] == VALUE
    # Check that this value is reset after the exiting the context.
    assert mpl.rcParams[PARAM] == 'gray'

def test_simple_layout():
    'Test metpy\'s simple layout for station plots'
    setup_font()
    with style.context(test_style):
        fig = make_figure(figsize=(9, 9))

        # testing data
        x = np.array([1, 5])
        y = np.array([2, 4])
        data = dict()
        data['air_temperature'] = np.array([32., 212.]) * units.degF
        data['dew_point_temperature'] = np.array([28., 80.]) * units.degF
        data['air_pressure_at_sea_level'] = np.array([29.92, 28.00]) * units.inHg
        data['eastward_wind'] = np.array([2, 0]) * units.knots
        data['northward_wind'] = np.array([0, 5]) * units.knots
        data['cloud_coverage'] = [3, 8]
        data['present_weather'] = [65, 75]
        data['unused'] = [1, 2]

        # Make the plot
        sp = StationPlot(fig.add_subplot(1, 1, 1), x, y, fontsize=12)
        simple_layout.plot(sp, data)

        sp.ax.set_xlim(0, 6)
        sp.ax.set_ylim(0, 6)
        hide_tick_labels(sp.ax)

        return fig

def test_context_with_dict():
    original_value = 'gray'
    other_value = 'blue'
    mpl.rcParams[PARAM] = original_value
    with style.context({PARAM: other_value}):
        assert mpl.rcParams[PARAM] == other_value
    assert mpl.rcParams[PARAM] == original_value

def test_alias(equiv_styles):
    rc_dicts = []
    for sty in equiv_styles:
        with style.context(sty):
            rc_dicts.append(dict(mpl.rcParams))

    rc_base = rc_dicts[0]
    for nm, rc in zip(equiv_styles[1:], rc_dicts[1:]):
        assert rc_base == rc

def test_use_url(tmpdir):
    path = Path(tmpdir, 'file')
    path.write_text('axes.facecolor: adeade')
    with temp_style('test', DUMMY_SETTINGS):
        url = ('file:'
               + ('///' if sys.platform == 'win32' else '')
               + path.resolve().as_posix())
        with style.context(url):
            assert mpl.rcParams['axes.facecolor'] == "#adeade"

def test_context_with_dict_after_namedstyle():
    # Test dict after style name where dict modifies the same parameter.
    original_value = 'gray'
    other_value = 'blue'
    mpl.rcParams[PARAM] = original_value
    with temp_style('test', DUMMY_SETTINGS):
        with style.context(['test', {PARAM: other_value}]):
            assert mpl.rcParams[PARAM] == other_value
    assert mpl.rcParams[PARAM] == original_value

    def __init__(self, image_path, image_name, reltol=1,
                 adjust_tolerance=True, plt_close_all_enter=True,
                 plt_close_all_exit=True, style=None, no_uploads=False, *args,
                 **kwargs):
        self.suffix = "." + image_name.split(".")[-1]
        super(ImageComparison, self).__init__(suffix=self.suffix, *args,
                                              **kwargs)
        self.image_name = image_name
        self.baseline_image = os.path.join(image_path, image_name)
        self.keep_output = "OBSPY_KEEP_IMAGES" in os.environ
        self.keep_only_failed = "OBSPY_KEEP_ONLY_FAILED_IMAGES" in os.environ
        self.output_path = os.path.join(image_path, "testrun")
        self.diff_filename = "-failed-diff.".join(self.name.rsplit(".", 1))
        self.tol = reltol * 3.0
        self.plt_close_all_enter = plt_close_all_enter
        self.plt_close_all_exit = plt_close_all_exit
        self.no_uploads = no_uploads

        if (MATPLOTLIB_VERSION < [1, 4, 0] or
                (MATPLOTLIB_VERSION[:2] == [1, 4] and style is None)):
            # No good style support.
            self.style = None
        else:
            import matplotlib.style as mstyle
            self.style = mstyle.context(style or 'classic')

        # Adjust the tolerance based on the matplotlib version. This works
        # well enough and otherwise testing is just a pain.
        #
        # The test images were generated with matplotlib tag 291091c6eb267
        # which is after https://github.com/matplotlib/matplotlib/issues/7905
        # has been fixed.
        #
        # Thus test images should accurate for matplotlib >= 2.0.1 anf
        # fairly accurate for matplotlib 1.5.x.
        if adjust_tolerance:
            # Really old versions.
            if MATPLOTLIB_VERSION < [1, 3, 0]:
                self.tol *= 30
            # 1.3 + 1.4 have slightly different text positioning mostly.
            elif [1, 3, 0] <= MATPLOTLIB_VERSION < [1, 5, 0]:
                self.tol *= 15
            # A few plots with mpl 1.5 have ticks and axis slightl shifted.
            # This is especially true for ticks with exponential numbers.
            # Thus the tolerance also has to be a bit higher here.
            elif [1, 5, 0] <= MATPLOTLIB_VERSION < [2, 0, 0]:
                self.tol *= 5.0
            # Matplotlib 2.0.0 has a bug with the tick placement. This is
            # fixed in 2.0.1 but the tolerance for 2.0.0 has to be much
            # higher. 10 is an empiric value. The tick placement potentially
            # influences the axis locations and then the misfit is really
            # quite high.
            elif [2, 0, 0] <= MATPLOTLIB_VERSION < [2, 0, 1]:
                self.tol *= 10

def test_hodograph_units():
    'Test passing unit-ed quantities to Hodograph'
    with style.context(test_style):
        fig = make_figure(figsize=(9, 9))
        ax = fig.add_subplot(1, 1, 1)
        hodo = Hodograph(ax)
        u = np.arange(10) * units.kt
        v = np.arange(10) * units.kt
        hodo.plot(u, v)
        hodo.plot_colormapped(u, v, np.sqrt(u * u + v * v), cmap='Greys')
        hide_tick_labels(ax)
        return fig

def test_hodograph_api():
    'Basic test of Hodograph API'
    with style.context(test_style):
        fig = make_figure(figsize=(9, 9))
        ax = fig.add_subplot(1, 1, 1)
        hodo = Hodograph(ax, component_range=60)
        hodo.add_grid(increment=5, color='k')
        hodo.plot([1, 10], [1, 10], color='red')
        hodo.plot_colormapped(np.array([1, 3, 5, 10]), np.array([2, 4, 6, 11]),
                              np.array([0.1, 0.3, 0.5, 0.9]), cmap='Greys')
        hide_tick_labels(ax)
        return fig