Python matplotlib.colorbar.ColorbarBase() Examples

def spikesplot_cb(position, cmap="viridis", fig=None):
    # Add colorbar
    if fig is None:
        fig = plt.gcf()

    cax = fig.add_axes(position)
    cb = ColorbarBase(
        cax,
        cmap=cm.get_cmap(cmap),
        spacing="proportional",
        orientation="horizontal",
        drawedges=False,
    )
    cb.set_ticks([0, 0.5, 1.0])
    cb.set_ticklabels(["Inferior", "(axial slice)", "Superior"])
    cb.outline.set_linewidth(0)
    cb.ax.xaxis.set_tick_params(width=0)
    return cax 

def plotTZ(filename=None):
    cmap = cm.get_cmap('cool')
    fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw = {'width_ratios':[19, 1]})
    ax1.add_patch(pl.Rectangle(xy=[0, 0], width=0.5, height=0.5, facecolor=cmap(0.0), linewidth='2.0'))
    ax1.add_patch(pl.Rectangle(xy=[0.5, 0.5], width=0.5, height=0.5, facecolor=cmap(0.0), linewidth='2.0'))
    ax1.add_patch(pl.Rectangle(xy=[0, 0.5], width=0.5, height=0.5, facecolor=cmap(1.0), linewidth='2.0'))
    ax1.add_patch(pl.Rectangle(xy=[0.5, 0], width=0.5, height=0.5, facecolor=cmap(1.0), linewidth='2.0'))
    ax1.set_xlabel('x1', size=22)
    ax1.set_ylabel('x2', size=22)
    ax1.set_title('True Data', size=28)
    colorbar.ColorbarBase(ax2, cmap=cmap, format='%.1f')
    ax2.set_ylabel('Output y', size=22)
    plt.show()
    if not filename is None:
        plt.savefig(filename, format="pdf", bbox_inches="tight")
        plt.close() 

def plotTZ(filename=None):
    t = np.linspace(0, 1, 101)
    z = 0.25 + 0.5 / (1 + np.exp(- 20 * (t - 0.5))) + 0.05 * np.cos(t * 2 * np.pi)
    cmap = cm.get_cmap('cool')
    fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw = {'width_ratios':[19, 1]})
    poly1 = [[0, 0]]
    poly1.extend([[t[i], z[i]] for i in range(t.size)])
    poly1.extend([[1, 0], [0, 0]])
    poly2 = [[0, 1]]
    poly2.extend([[t[i], z[i]] for i in range(t.size)])
    poly2.extend([[1, 1], [0, 1]])
    poly1 = plt.Polygon(poly1,fc=cmap(0.0))
    poly2 = plt.Polygon(poly2,fc=cmap(1.0))
    ax1.add_patch(poly1)
    ax1.add_patch(poly2)
    ax1.set_xlabel('x1', size=22)
    ax1.set_ylabel('x2', size=22)
    ax1.set_title('True Data', size=28)
    colorbar.ColorbarBase(ax2, cmap=cmap, format='%.1f')
    ax2.set_ylabel('Output y', size=22)
    plt.show()
    if not filename is None:
        plt.savefig(filename, format="pdf", bbox_inches="tight")
        plt.close() 

def _colorbar_extension_length(spacing):
    '''
    Produce 12 colorbars with variable length extensions for either
    uniform or proportional spacing.

    Helper function for test_colorbar_extension_length.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=.6)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        for j, extendfrac in enumerate((None, 'auto', 0.1)):
            # Create a subplot.
            cax = fig.add_subplot(12, 1, i*3 + j + 1)
            # Generate the colorbar.
            ColorbarBase(cax, cmap=cmap, norm=norm,
                         boundaries=boundaries, values=values,
                         extend=extension_type, extendfrac=extendfrac,
                         orientation='horizontal', spacing=spacing)
            # Turn off text and ticks.
            cax.tick_params(left=False, labelleft=False,
                            bottom=False, labelbottom=False)
    # Return the figure to the caller.
    return fig 

def _colorbar_extension_shape(spacing):
    '''
    Produce 4 colorbars with rectangular extensions for either uniform
    or proportional spacing.

    Helper function for test_colorbar_extension_shape.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=4)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        # Create a subplot.
        cax = fig.add_subplot(4, 1, i + 1)
        # Generate the colorbar.
        cb = ColorbarBase(cax, cmap=cmap, norm=norm,
                boundaries=boundaries, values=values,
                extend=extension_type, extendrect=True,
                orientation='horizontal', spacing=spacing)
        # Turn off text and ticks.
        cax.tick_params(left=False, labelleft=False,
                        bottom=False, labelbottom=False)
    # Return the figure to the caller.
    return fig 

def test_SymLogNorm_single_zero():
    """
    Test SymLogNorm to ensure it is not adding sub-ticks to zero label
    """
    fig = plt.figure()
    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    ticks = cbar.get_ticks()
    assert sum(ticks == 0) == 1
    plt.close(fig) 

def test_SymLogNorm_colorbar():
    """
    Test un-called SymLogNorm in a colorbar.
    """
    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
    fig = plt.figure()
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    plt.close(fig) 

def test_colorbar_powernorm_extension():
    # Test that colorbar with powernorm is extended correctly
    f, ax = plt.subplots()
    cb = ColorbarBase(ax, norm=PowerNorm(gamma=0.5, vmin=0.0, vmax=1.0),
                      orientation='vertical', extend='both')
    assert cb._values[0] >= 0.0 

def test_colorbarbase():
    # smoke test from #3805
    ax = plt.gca()
    ColorbarBase(ax, plt.cm.bone) 

def _colorbar_extension_length(spacing):
    '''
    Produce 12 colorbars with variable length extensions for either
    uniform or proportional spacing.

    Helper function for test_colorbar_extension_length.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=.6)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        for j, extendfrac in enumerate((None, 'auto', 0.1)):
            # Create a subplot.
            cax = fig.add_subplot(12, 1, i*3 + j + 1)
            # Generate the colorbar.
            ColorbarBase(cax, cmap=cmap, norm=norm,
                         boundaries=boundaries, values=values,
                         extend=extension_type, extendfrac=extendfrac,
                         orientation='horizontal', spacing=spacing)
            # Turn off text and ticks.
            cax.tick_params(left=False, labelleft=False,
                            bottom=False, labelbottom=False)
    # Return the figure to the caller.
    return fig 

def _colorbar_extension_shape(spacing):
    '''
    Produce 4 colorbars with rectangular extensions for either uniform
    or proportional spacing.

    Helper function for test_colorbar_extension_shape.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=4)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        # Create a subplot.
        cax = fig.add_subplot(4, 1, i + 1)
        # Generate the colorbar.
        cb = ColorbarBase(cax, cmap=cmap, norm=norm,
                boundaries=boundaries, values=values,
                extend=extension_type, extendrect=True,
                orientation='horizontal', spacing=spacing)
        # Turn off text and ticks.
        cax.tick_params(left=False, labelleft=False,
                        bottom=False, labelbottom=False)
    # Return the figure to the caller.
    return fig 

def test_SymLogNorm_single_zero():
    """
    Test SymLogNorm to ensure it is not adding sub-ticks to zero label
    """
    fig = plt.figure()
    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    ticks = cbar.get_ticks()
    assert sum(ticks == 0) == 1
    plt.close(fig) 

def test_SymLogNorm_colorbar():
    """
    Test un-called SymLogNorm in a colorbar.
    """
    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
    fig = plt.figure()
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    plt.close(fig) 

def plot_dos_gradient(self):

        import matplotlib.pyplot as plt
        import matplotlib.colors as colors
        import matplotlib.colorbar as colorbar

        volumes = self.phonopy_qha.get_volume_temperature()
        temperatures = self.fc_fit.get_temperature_range()

        fig, ax = plt.subplots(1,1)
        for t, v in zip(temperatures[::40], volumes[::20]):
            print ('temperature: {} K'.format(t))
            dos = self.fc_fit.get_dos(t, v)
            cNorm = colors.Normalize(vmin=temperatures[0], vmax=temperatures[-1])
            scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=plt.cm.get_cmap('plasma'))
            ax.plot(dos[0], dos[1], color=scalarMap.to_rgba(t))

        plt.suptitle('Phonon density of states')
        plt.xlabel('Frequency [THz]')

        ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
        colorbar.ColorbarBase(ax2, cmap=plt.cm.get_cmap('plasma'), norm=cNorm,
                              spacing='proportional', ticks=temperatures[::40],
                              boundaries=None, format='%1i')

        plt.show() 

def plot_gmm(weights, means, covariances, X=None, ax=None, xlim=[0,1], ylim=[0,1], xlabel='', ylabel='',
             bar=True, bar_side='right',no_y=False, color=None):
    ft_off = 15

    ax = ax or plt.gca()
    cmap = truncate_colormap(plt.cm.autumn_r, minval=0.2,maxval=1.0)
    #colors = [plt.cm.jet(i) for i in X[:, -1]]
    if X is not None:
        colors = [cmap(i) for i in X[:, -1]]
        sizes = [5+np.interp(i,[0,1],[0,10]) for i in X[:, -1]]
        ax.scatter(X[:, 0], X[:, 1], c=colors, s=sizes, zorder=2)
        #ax.axis('equal')
    w_factor = 0.6 / weights.max()
    for pos, covar, w in zip(means, covariances, weights):
        draw_ellipse(pos, covar, alpha=0.6, ax=ax, color=color)

    #plt.margins(0, 0)
    ax.set_xlim(left=xlim[0], right=xlim[1])
    ax.set_ylim(bottom=ylim[0], top=ylim[1])
    if bar:
        cax, _ = cbar.make_axes(ax, location=bar_side, shrink=0.8)
        cb = cbar.ColorbarBase(cax, cmap=cmap)
        cb.set_label('Absolute Learning Progress', fontsize=ft_off + 5)
        cax.tick_params(labelsize=ft_off + 0)
        cax.yaxis.set_ticks_position(bar_side)
        cax.yaxis.set_label_position(bar_side)
    #ax.yaxis.tick_right()
    if no_y:
        ax.set_yticks([])
    else:
        ax.set_ylabel(ylabel, fontsize=ft_off + 5)
        #ax.yaxis.set_label_position("right")
    ax.set_xlabel(xlabel, fontsize=ft_off + 5)
    ax.tick_params(axis='both', which='major', labelsize=ft_off + 5)
    ax.set_aspect('equal', 'box') 

def draw_competence_grid(ax, comp_grid, x_bnds, y_bnds, bar=True):
    comp_grid[comp_grid == 100] = 1000
    ax.pcolor(x_bnds, y_bnds, np.transpose(comp_grid),cmap=plt.cm.gray, edgecolors='k', linewidths=2,
              alpha=0.3)
    if bar:
        cax, _ = cbar.make_axes(ax,location='left')
        cb = cbar.ColorbarBase(cax, cmap=plt.cm.gray)
        cb.set_label('Competence')
        cax.yaxis.set_ticks_position('left')
        cax.yaxis.set_label_position('left') 

def test_colorbarbase():
    # smoke test from #3805
    ax = plt.gca()
    ColorbarBase(ax, plt.cm.bone) 

def change_cbar_text(cbar: ColorbarBase, tick: List[Number_T], text: List[str]):
    cbar.set_ticks(tick)
    cbar.set_ticklabels(text) 

def plotRule(mdl, X, d1, d2, alpha=0.8, filename='', rnum=-1, plot_line=[]):
    cmap = cm.get_cmap('cool')
    fig, (ax1, ax2) = plt.subplots(1, 2, gridspec_kw = {'width_ratios':[19, 1]})
    if rnum <= 0:
        rnum = len(mdl.rule_)
    else:
        rnum = min(len(mdl.rule_), rnum)
    idx = np.argsort(mdl.weight_[:rnum])
    for i in range(rnum):
        r = mdl.rule_[idx[i]]
        box, vmin, vmax = __r2boxWithX(r, X)
        if mdl.modeltype_ == 'regression':
            c = cmap(mdl.pred_[idx[i]])
        elif mdl.modeltype_ == 'classification':
            r = mdl.pred_[idx[i]] / max(np.unique(mdl.pred_).size - 1, 1)
            c = cmap(r)
        ax1.add_patch(pl.Rectangle(xy=[box[0, d1], box[0, d2]], width=(box[1, d1] - box[0, d1]), height=(box[1, d2] - box[0, d2]), facecolor=c, linewidth='2.0', alpha=alpha))
    if len(plot_line) > 0:
        for l in plot_line:
            ax1.plot(l[0], l[1], 'k--')
    ax1.set_xlabel('x1', size=22)
    ax1.set_ylabel('x2', size=22)
    ax1.set_title('Simplified Model (K = %d)' % (rnum,), size=28)
    colorbar.ColorbarBase(ax2, cmap=cmap, format='%.1f')
    ax2.set_ylabel('Predictor y', size=22)
    plt.show()
    if not filename == '':
        plt.savefig(filename, format="pdf", bbox_inches="tight")
        plt.close() 

def plotEachRule(mdl, X, d1, d2, alpha=0.8, filename='', rnum=-1, plot_line=[]):
    if rnum <= 0:
        rnum = len(mdl.rule_)
    else:
        rnum = min(len(mdl.rule_), rnum)
    m = rnum // 4
    if m * 4 < rnum:
        m += 1
    cmap = cm.get_cmap('cool')
    fig, ax = plt.subplots(m, 4 + 1, figsize=(4 * 4, 3 * m), gridspec_kw = {'width_ratios':[15, 15, 15, 15, 1]})
    idx = np.argsort(mdl.weight_[:rnum])
    for i in range(rnum):
        j = i // 4
        k = i - 4 * j
        r = mdl.rule_[idx[i]]
        box, vmin, vmax = __r2boxWithX(r, X)
        if mdl.modeltype_ == 'regression':
            c = cmap(mdl.pred_[idx[i]])
        elif mdl.modeltype_ == 'classification':
            r = mdl.pred_[idx[i]] / max(np.unique(mdl.pred_).size - 1, 1)
            c = cmap(r)
        ax[j, k].add_patch(pl.Rectangle(xy=[box[0, d1], box[0, d2]], width=(box[1, d1] - box[0, d1]), height=(box[1, d2] - box[0, d2]), facecolor=c, linewidth='2.0', alpha=alpha))
        if len(plot_line) > 0:
            for l in plot_line:
                ax[j, k].plot(l[0], l[1], 'k--')
        ax[j, k].set_xlim([0, 1])
        ax[j, k].set_ylim([0, 1])
        if k == 3:
            cbar = colorbar.ColorbarBase(ax[j, -1], cmap=cmap, format='%.1f', ticks=[0.0, 0.5, 1.0])
            cbar.ax.set_yticklabels([0.0, 0.5, 1.0])
            ax[j, -1].set_ylabel('Predictor y', size=12)
    plt.show()
    if not filename == '':
        plt.savefig(filename, format="pdf", bbox_inches="tight")
        plt.close() 

def _colorbar_extension_shape(spacing):
    '''
    Produce 4 colorbars with rectangular extensions for either uniform
    or proportional spacing.

    Helper function for test_colorbar_extension_shape.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=4)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        # Create a subplot.
        cax = fig.add_subplot(4, 1, i + 1)
        # Turn off text and ticks.
        for item in cax.get_xticklabels() + cax.get_yticklabels() +\
                cax.get_xticklines() + cax.get_yticklines():
            item.set_visible(False)
        # Generate the colorbar.
        cb = ColorbarBase(cax, cmap=cmap, norm=norm,
                boundaries=boundaries, values=values,
                extend=extension_type, extendrect=True,
                orientation='horizontal', spacing=spacing)
    # Return the figure to the caller.
    return fig 

def _colorbar_extension_length(spacing):
    '''
    Produce 12 colorbars with variable length extensions for either
    uniform or proportional spacing.

    Helper function for test_colorbar_extension_length.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=.6)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        for j, extendfrac in enumerate((None, 'auto', 0.1)):
            # Create a subplot.
            cax = fig.add_subplot(12, 1, i*3 + j + 1)
            # Turn off text and ticks.
            for item in cax.get_xticklabels() + cax.get_yticklabels() +\
                    cax.get_xticklines() + cax.get_yticklines():
                item.set_visible(False)
            # Generate the colorbar.
            cb = ColorbarBase(cax, cmap=cmap, norm=norm,
                    boundaries=boundaries, values=values,
                    extend=extension_type, extendfrac=extendfrac,
                    orientation='horizontal', spacing=spacing)
    # Return the figure to the caller.
    return fig 

def test_colorbarbase():
    # smoke test from #3805
    ax = plt.gca()
    ColorbarBase(ax, plt.cm.bone) 

def test_SymLogNorm_colorbar():
    """
    Test un-called SymLogNorm in a colorbar.
    """
    norm = mcolors.SymLogNorm(0.1, vmin=-1, vmax=1, linscale=1)
    fig = plt.figure()
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    plt.close(fig) 

def test_SymLogNorm_single_zero():
    """
    Test SymLogNorm to ensure it is not adding sub-ticks to zero label
    """
    fig = plt.figure()
    norm = mcolors.SymLogNorm(1e-5, vmin=-1, vmax=1)
    cbar = mcolorbar.ColorbarBase(fig.add_subplot(111), norm=norm)
    ticks = cbar.get_ticks()
    assert sum(ticks == 0) == 1
    plt.close(fig) 

def _colorbar_extension_shape(spacing):
    '''
    Produce 4 colorbars with rectangular extensions for either uniform
    or proportional spacing.

    Helper function for test_colorbar_extension_shape.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=4)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        # Create a subplot.
        cax = fig.add_subplot(4, 1, i + 1)
        # Generate the colorbar.
        cb = ColorbarBase(cax, cmap=cmap, norm=norm,
                boundaries=boundaries, values=values,
                extend=extension_type, extendrect=True,
                orientation='horizontal', spacing=spacing)
        # Turn off text and ticks.
        cax.tick_params(left=False, labelleft=False,
                        bottom=False, labelbottom=False)
    # Return the figure to the caller.
    return fig 

def _colorbar_extension_length(spacing):
    '''
    Produce 12 colorbars with variable length extensions for either
    uniform or proportional spacing.

    Helper function for test_colorbar_extension_length.
    '''
    # Get a colormap and appropriate norms for each extension type.
    cmap, norms = _get_cmap_norms()
    # Create a figure and adjust whitespace for subplots.
    fig = plt.figure()
    fig.subplots_adjust(hspace=.6)
    for i, extension_type in enumerate(('neither', 'min', 'max', 'both')):
        # Get the appropriate norm and use it to get colorbar boundaries.
        norm = norms[extension_type]
        boundaries = values = norm.boundaries
        for j, extendfrac in enumerate((None, 'auto', 0.1)):
            # Create a subplot.
            cax = fig.add_subplot(12, 1, i*3 + j + 1)
            # Generate the colorbar.
            ColorbarBase(cax, cmap=cmap, norm=norm,
                         boundaries=boundaries, values=values,
                         extend=extension_type, extendfrac=extendfrac,
                         orientation='horizontal', spacing=spacing)
            # Turn off text and ticks.
            cax.tick_params(left=False, labelleft=False,
                            bottom=False, labelbottom=False)
    # Return the figure to the caller.
    return fig 

def test_colorbarbase():
    # smoke test from #3805
    ax = plt.gca()
    ColorbarBase(ax, plt.cm.bone) 

def test_colorbar_powernorm_extension():
    # Test that colorbar with powernorm is extended correctly
    f, ax = plt.subplots()
    cb = ColorbarBase(ax, norm=PowerNorm(gamma=0.5, vmin=0.0, vmax=1.0),
                      orientation='vertical', extend='both')
    assert cb._values[0] >= 0.0 

def setup_axes(fig: Any, cmap: Any, norm: Any, position: List[Number_T]) -> tuple:
    ax = fig.add_axes(position)
    cbar = ColorbarBase(
        ax, cmap=cmap, norm=norm, orientation="vertical", drawedges=False
    )
    cbar.ax.tick_params(axis="both", which="both", length=0, labelsize=10)
    cbar.outline.set_visible(False)
    return cbar