Python pyplot.pcolor方法代碼示例

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_cmap_import():
    '''Can we import colormaps and make basic plot.

    '''

    from cmocean import cm
    # Loop through all methods in cmocean.
    for name, cmap in vars(cm).items():
        # See if it is a colormap.
        if isinstance(cmap, matplotlib.colors.LinearSegmentedColormap):
            print(name)
            x = np.linspace(0, 10)
            X, _ = np.meshgrid(x, x)
            plt.figure()
            plt.pcolor(X, cmap=cmap)
            plt.title(name)
            plt.close(plt.gcf()) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_pcolor_datetime_axis():
    fig = plt.figure()
    fig.subplots_adjust(hspace=0.4, top=0.98, bottom=.15)
    base = datetime.datetime(2013, 1, 1)
    x = np.array([base + datetime.timedelta(days=d) for d in range(21)])
    y = np.arange(21)
    z1, z2 = np.meshgrid(np.arange(20), np.arange(20))
    z = z1 * z2
    plt.subplot(221)
    plt.pcolor(x[:-1], y[:-1], z)
    plt.subplot(222)
    plt.pcolor(x, y, z)
    x = np.repeat(x[np.newaxis], 21, axis=0)
    y = np.repeat(y[:, np.newaxis], 21, axis=1)
    plt.subplot(223)
    plt.pcolor(x[:-1, :-1], y[:-1, :-1], z)
    plt.subplot(224)
    plt.pcolor(x, y, z)
    for ax in fig.get_axes():
        for label in ax.get_xticklabels():
            label.set_ha('right')
            label.set_rotation(30) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def Pcolor(xs, ys, zs, pcolor=True, contour=False, **options):
    """Makes a pseudocolor plot.
    
    xs:
    ys:
    zs:
    pcolor: boolean, whether to make a pseudocolor plot
    contour: boolean, whether to make a contour plot
    options: keyword args passed to plt.pcolor and/or plt.contour
    """
    _Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

    X, Y = np.meshgrid(xs, ys)
    Z = zs

    x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
    axes = plt.gca()
    axes.xaxis.set_major_formatter(x_formatter)

    if pcolor:
        plt.pcolormesh(X, Y, Z, **options)

    if contour:
        cs = plt.contour(X, Y, Z, **options)
        plt.clabel(cs, inline=1, fontsize=10) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def plot_colormap(data, figSizeIn, xlabel, ylabel, cbarlabel, cmapIn, ytickRange, ytickTag, xtickRange=None, xtickTag=None, title=None):
    fig = plt.figure(figsize = figSizeIn)
    plt.pcolor(data, cmap=cmapIn)
    cbar = plt.colorbar()
    cbar.set_label(cbarlabel, labelpad=-0.1)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    if xtickTag:
        plt.xticks(xtickRange, xtickTag, fontsize=10)

    plt.yticks(ytickRange, ytickTag, fontsize=10)
    plt.tight_layout()
    if title:
        plt.title(title)
    plt.show()
    return fig 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def plot_colormap_upgrade(data, figSizeIn, xlabel, ylabel, cbarlabel, cmapIn, ytickRange, ytickTag, xtickRange=None, xtickTag=None, title=None, xmin=None, xmax=None, xgran=None, ymin=None, ymax=None, ygran=None):
    if xmin != None:
        y, x = np.mgrid[slice(ymin, ymax + ygran, ygran),
                slice(xmin, xmax + xgran, xgran)]
        fig = plt.figure(figsize = figSizeIn)
#       plt.pcolor(data, cmap=cmapIn)
        plt.pcolormesh(x, y, data, cmap=cmapIn)
        plt.grid(which='major',axis='both')
        plt.axis([x.min(), x.max(), y.min(), y.max()])
    else:
        plt.pcolor(data, cmap=cmapIn)

    cbar = plt.colorbar()
    cbar.set_label(cbarlabel, labelpad=-0.1)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
#   if xtickTag:
#       plt.xticks(xtickRange, xtickTag, fontsize=10)
#
#   plt.yticks(ytickRange, ytickTag, fontsize=10)
    plt.tight_layout()
    if title:
        plt.title(title)
    plt.show()
    return fig 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def draw_pianoroll(pianoroll, name='Notes', show=False, save_path=''):

    cm = matplotlib.cm.get_cmap('Greys')
    notes_color = cm(1.0)

    notes_patch = mpatches.Patch(color=notes_color, label=name)

    plt.figure(figsize=(20.0, 10.0))
    plt.title('Pianoroll Pitch-plot of ' + name, fontsize=10)
    plt.legend(handles=[notes_patch], loc='upper right', prop={'size': 8})

    plt.pcolor(pianoroll, cmap='Greys', vmin=0, vmax=np.max(pianoroll))
    if show:
        plt.show()
    if len(save_path) > 0:
        plt.savefig(save_path)
        tikz_save(save_path + ".tex", encoding='utf-8', show_info=False)
    plt.close() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def Pcolor(xs, ys, zs, pcolor=True, contour=False, **options):
    """Makes a pseudocolor plot.
    
    xs:
    ys:
    zs:
    pcolor: boolean, whether to make a pseudocolor plot
    contour: boolean, whether to make a contour plot
    options: keyword args passed to pyplot.pcolor and/or pyplot.contour
    """
    _Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

    X, Y = np.meshgrid(xs, ys)
    Z = zs

    x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
    axes = pyplot.gca()
    axes.xaxis.set_major_formatter(x_formatter)

    if pcolor:
        pyplot.pcolormesh(X, Y, Z, **options)

    if contour:
        cs = pyplot.contour(X, Y, Z, **options)
        pyplot.clabel(cs, inline=1, fontsize=10) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def plot_solution(X_star, u_star, index):
    
    lb = X_star.min(0)
    ub = X_star.max(0)
    nn = 200
    x = np.linspace(lb[0], ub[0], nn)
    y = np.linspace(lb[1], ub[1], nn)
    X, Y = np.meshgrid(x,y)
    
    U_star = griddata(X_star, u_star.flatten(), (X, Y), method='cubic')
    
    plt.figure(index)
    plt.pcolor(X,Y,U_star, cmap = 'jet')
    plt.colorbar() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def plot_solution(X_data, w_data, index):
    
    lb = X_data.min(0)
    ub = X_data.max(0)
    nn = 200
    x = np.linspace(lb[0], ub[0], nn)
    y = np.linspace(lb[1], ub[1], nn)
    X, Y = np.meshgrid(x,y)
    
    W_data = griddata(X_data, w_data.flatten(), (X, Y), method='cubic')
    
    plt.figure(index)
    plt.pcolor(X,Y,W_data, cmap = 'jet')
    plt.colorbar() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_mixedmode():
    if not check_for('xelatex'):
        raise SkipTest('xelatex + pgf is required')

    rc_xelatex = {'font.family': 'serif',
                  'pgf.rcfonts': False}
    mpl.rcParams.update(rc_xelatex)

    Y, X = np.ogrid[-1:1:40j, -1:1:40j]
    plt.figure()
    plt.pcolor(X**2 + Y**2).set_rasterized(True)
    compare_figure('pgf_mixedmode.pdf')


# test bbox_inches clipping 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_autoscale_masked():
    # Test for #2336. Previously fully masked data would trigger a ValueError.
    data = np.ma.masked_all((12, 20))
    plt.pcolor(data)
    plt.draw() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def Contour(obj, pcolor=False, contour=True, imshow=False, **options):
    """Makes a contour plot.
    
    d: map from (x, y) to z, or object that provides GetDict
    pcolor: boolean, whether to make a pseudocolor plot
    contour: boolean, whether to make a contour plot
    imshow: boolean, whether to use plt.imshow
    options: keyword args passed to plt.pcolor and/or plt.contour
    """
    try:
        d = obj.GetDict()
    except AttributeError:
        d = obj

    _Underride(options, linewidth=3, cmap=matplotlib.cm.Blues)

    xs, ys = zip(*d.keys())
    xs = sorted(set(xs))
    ys = sorted(set(ys))

    X, Y = np.meshgrid(xs, ys)
    func = lambda x, y: d.get((x, y), 0)
    func = np.vectorize(func)
    Z = func(X, Y)

    x_formatter = matplotlib.ticker.ScalarFormatter(useOffset=False)
    axes = plt.gca()
    axes.xaxis.set_major_formatter(x_formatter)

    if pcolor:
        plt.pcolormesh(X, Y, Z, **options)
    if contour:
        cs = plt.contour(X, Y, Z, **options)
        plt.clabel(cs, inline=1, fontsize=10)
    if imshow:
        extent = xs[0], xs[-1], ys[0], ys[-1]
        plt.imshow(Z, extent=extent, **options) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_pcolorargs_5205():
    # Smoketest to catch issue found in gh:5205
    x = [-1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5]
    y = [-1.5, -1.25, -1.0, -0.75, -0.5, -0.25, 0,
         0.25, 0.5, 0.75, 1.0, 1.25, 1.5]
    X, Y = np.meshgrid(x, y)
    Z = np.hypot(X, Y)

    plt.pcolor(Z)
    plt.pcolor(list(Z))
    plt.pcolor(x, y, Z)
    plt.pcolor(X, Y, list(Z)) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_axes_margins():
    fig, ax = plt.subplots()
    ax.plot([0, 1, 2, 3])
    assert ax.get_ybound()[0] != 0

    fig, ax = plt.subplots()
    ax.bar([0, 1, 2, 3], [1, 1, 1, 1])
    assert ax.get_ybound()[0] == 0

    fig, ax = plt.subplots()
    ax.barh([0, 1, 2, 3], [1, 1, 1, 1])
    assert ax.get_xbound()[0] == 0

    fig, ax = plt.subplots()
    ax.pcolor(np.zeros((10, 10)))
    assert ax.get_xbound() == (0, 10)
    assert ax.get_ybound() == (0, 10)

    fig, ax = plt.subplots()
    ax.pcolorfast(np.zeros((10, 10)))
    assert ax.get_xbound() == (0, 10)
    assert ax.get_ybound() == (0, 10)

    fig, ax = plt.subplots()
    ax.hist(np.arange(10))
    assert ax.get_ybound()[0] == 0

    fig, ax = plt.subplots()
    ax.imshow(np.zeros((10, 10)))
    assert ax.get_xbound() == (-0.5, 9.5)
    assert ax.get_ybound() == (-0.5, 9.5) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import pcolor [as 別名]
def test_mixedmode():
    rc_xelatex = {'font.family': 'serif',
                  'pgf.rcfonts': False}
    mpl.rcParams.update(rc_xelatex)

    Y, X = np.ogrid[-1:1:40j, -1:1:40j]
    plt.figure()
    plt.pcolor(X**2 + Y**2).set_rasterized(True)


# test bbox_inches clipping