Style: ggplot ============= .. image:: _images/ggplot.png :scale: 75 % Style Sheet ~~~~~~~~~~~ Note that this is not the same syntax as the original style sheet. .. code-block:: text axes.axisbelow: True axes.edgecolor: white axes.facecolor: #E5E5E5 axes.grid: True axes.labelcolor: #555555 axes.labelsize: large axes.linewidth: 1.0 axes.prop_cycle: cycler(color, [#E24A33, #348ABD, #988ED5, #777777, #FBC15E, #8EBA42, #FFB5B8]) axes.titlesize: x-large figure.edgecolor: 0.50 figure.facecolor: white font.size: 10.0 grid.color: white grid.linestyle: - patch.antialiased: True patch.edgecolor: #EEEEEE patch.facecolor: #348ABD patch.linewidth: 0.5 xtick.color: #555555 xtick.direction: out ytick.color: #555555 ytick.direction: out Example Source Code ~~~~~~~~~~~~~~~~~~~ .. code-block:: python import matplotlib from matplotlib.colors import ListedColormap import numpy as np import viscid from viscid.plot import vpyplot as vlt import matplotlib.pyplot as plt matplotlib.rcParams.update(matplotlib.rcParamsDefault) fld = viscid.empty((np.linspace(1, 5, 64), np.linspace(1, 5, 64)), name="F", pretty_name="Generic Field") X, Y = fld.get_crds(shaped=True) fld[:, :] = 1e-4 * (np.sin(X)**10 + np.cos(10 + X * Y) * np.cos(X)) with plt.style.context(("ggplot",)): fig = plt.figure(figsize=(11, 7)) ax = plt.subplot2grid((2, 9), (0, 0), rowspan=2) pal = vlt.get_current_colorcycle() size = 1 n = len(pal) ax.imshow(np.arange(n).reshape(n, 1), cmap=ListedColormap(list(pal)), interpolation="nearest", aspect="auto") ax.set_xticks([]) ax.set_yticks([]) ax.set_xticklabels([]) ax.set_yticklabels([]) ax.set_ylabel("Color Cycle") plt.subplot2grid((2, 9), (0, 1), rowspan=2, colspan=4) x = np.linspace(0, 2 * np.pi) for phase in np.linspace(0, np.pi / 4, n): plt.plot(x, (1 + np.sqrt(phase)) * np.sin(x - phase), label=r"$\phi = {0:.2g}$".format(phase)) plt.legend(loc=0) plt.subplot2grid((2, 9), (0, 5), colspan=4) vlt.plot(fld) plt.title("Sequential") plt.subplot2grid((2, 9), (1, 5), colspan=4) vlt.plot(fld, lin=0) plt.title("Symmetric") vlt.auto_adjust_subplots(subplot_params=dict(top=0.93, bottom=0.1)) txt = ("Matplotlib Version: {0}\nViscid Version: {1}" "".format(matplotlib.__version__, viscid.__version__)) fig.text(0.05, 0.01, txt, color='grey', size='small')