Exemplo n.º 1
0
def test_stacked_bar_graph():
    sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_SONDE1)

    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.plot_stacked_bar_graph('tdry', bins=np.arange(-60, 10, 1))
    sonde_ds.close()

    return histdisplay.fig
Exemplo n.º 2
0
def test_stacked_bar_graph_sorted():
    sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_SONDE1)

    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.plot_stacked_bar_graph('tdry',
                                       bins=np.arange(-60, 10, 1),
                                       sortby_field="alt",
                                       sortby_bins=np.linspace(0, 10000., 6))
    sonde_ds.close()

    return histdisplay.fig
Exemplo n.º 3
0
def test_size_distribution():
    sigma = 10
    mu = 50
    bins = np.linspace(0, 100, 50)
    ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-(bins - mu)**2 / (2 * sigma**2))
    y_array = xr.DataArray(ydata, dims={'bins': bins})
    bins = xr.DataArray(bins, dims={'bins': bins})
    my_fake_ds = xr.Dataset({'bins': bins, 'ydata': y_array})
    histdisplay = HistogramDisplay(my_fake_ds)
    histdisplay.plot_size_distribution('ydata', 'bins', set_title='Fake distribution.')
    return histdisplay.fig
Exemplo n.º 4
0
def test_stair_graph():
    sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_SONDE1)

    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.plot_stairstep_graph('tdry', bins=np.arange(-60, 10, 1))
    sonde_ds.close()

    try:
        return histdisplay.fig
    finally:
        matplotlib.pyplot.close(histdisplay.fig)
Exemplo n.º 5
0
def test_heatmap():
    sonde_ds = arm.read_netcdf(
        sample_files.EXAMPLE_SONDE1)

    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.plot_heatmap(
        'tdry', 'alt', x_bins=np.arange(-60, 10, 1),
        y_bins=np.linspace(0, 10000., 50), cmap='coolwarm')
    sonde_ds.close()

    return histdisplay.fig
Exemplo n.º 6
0
def test_size_distribution():
    sigma = 10
    mu = 50
    bins = np.linspace(0, 100, 50)
    ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-((bins - mu) ** 2) / (2 * sigma**2))
    y_array = xr.DataArray(ydata, dims={'time': bins})
    bins = xr.DataArray(bins, dims={'time': bins})
    my_fake_ds = xr.Dataset({'time': bins, 'ydata': y_array})
    histdisplay = HistogramDisplay(my_fake_ds)
    histdisplay.plot_size_distribution('ydata', 'time', set_title='Fake distribution.')
    try:
        return histdisplay.fig
    finally:
        matplotlib.pyplot.close(histdisplay.fig)
Exemplo n.º 7
0
def test_stacked_bar_graph_sorted():
    sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_SONDE1)

    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.plot_stacked_bar_graph(
        'tdry',
        bins=np.arange(-60, 10, 1),
        sortby_field='alt',
        sortby_bins=np.linspace(0, 10000.0, 6),
    )
    sonde_ds.close()

    try:
        return histdisplay.fig
    finally:
        matplotlib.pyplot.close(histdisplay.fig)
Exemplo n.º 8
0
def test_stacked_bar_graph2():
    sonde_ds = arm.read_netcdf(
        sample_files.EXAMPLE_SONDE1)

    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.plot_stacked_bar_graph('tdry')
    histdisplay.set_yrng([0, 400])
    histdisplay.set_xrng([-70, 0])
    sonde_ds.close()

    return histdisplay.fig
Exemplo n.º 9
0
def test_histogram_errors():
    files = sample_files.EXAMPLE_MET1
    obj = arm.read_netcdf(files)

    histdisplay = HistogramDisplay(obj)
    histdisplay.axes = None
    with np.testing.assert_raises(RuntimeError):
        histdisplay.set_yrng([0, 10])
    with np.testing.assert_raises(RuntimeError):
        histdisplay.set_xrng([-40, 40])
    histdisplay.fig = None
    histdisplay.plot_stacked_bar_graph('temp_mean', bins=np.arange(-40, 40, 5))
    histdisplay.set_yrng([0, 0])
    assert histdisplay.yrng[0][1] == 1.
    assert histdisplay.fig is not None
    assert histdisplay.axes is not None

    with np.testing.assert_raises(AttributeError):
        HistogramDisplay([])

    histdisplay.axes = None
    histdisplay.fig = None
    histdisplay.plot_stairstep_graph('temp_mean', bins=np.arange(-40, 40, 5))
    assert histdisplay.fig is not None
    assert histdisplay.axes is not None

    sigma = 10
    mu = 50
    bins = np.linspace(0, 100, 50)
    ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-(bins - mu)**2 /
                                                      (2 * sigma**2))
    y_array = xr.DataArray(ydata, dims={'bins': bins})
    bins = xr.DataArray(bins, dims={'bins': bins})
    my_fake_ds = xr.Dataset({'bins': bins, 'ydata': y_array})
    histdisplay = HistogramDisplay(my_fake_ds)
    histdisplay.axes = None
    histdisplay.fig = None
    histdisplay.plot_size_distribution('ydata',
                                       'bins',
                                       set_title='Fake distribution.')
    assert histdisplay.fig is not None
    assert histdisplay.axes is not None

    sonde_ds = arm.read_netcdf(sample_files.EXAMPLE_SONDE1)
    histdisplay = HistogramDisplay({'sgpsondewnpnC1.b1': sonde_ds})
    histdisplay.axes = None
    histdisplay.fig = None
    histdisplay.plot_heatmap('tdry',
                             'alt',
                             x_bins=np.arange(-60, 10, 1),
                             y_bins=np.linspace(0, 10000., 50),
                             cmap='coolwarm')
    assert histdisplay.fig is not None
    assert histdisplay.axes is not None

    matplotlib.pyplot.close(fig=histdisplay.fig)