new poster template
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weygoldt
@@ -23,16 +23,16 @@ def PlotStyle() -> None:
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sky = "#89dceb"
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teal = "#94e2d5"
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green = "#a6e3a1"
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yellow = "#f9e2af"
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orange = "#fab387"
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maroon = "#eba0ac"
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red = "#f38ba8"
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purple = "#cba6f7"
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pink = "#f5c2e7"
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yellow = "#f9d67f"
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orange = "#faa472"
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maroon = "#eb8486"
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red = "#f37588"
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purple = "#d89bf7"
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pink = "#f59edb"
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lavender = "#b4befe"
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gblue1 = "#8cb8ff"
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gblue2 = "#7cdcdc"
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gblue3 = "#82e896"
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gblue1 = "#89b4fa"
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gblue2 = "#89dceb"
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gblue3 = "#a6e3a1"
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@classmethod
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def lims(cls, track1, track2):
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@@ -108,6 +108,9 @@ def PlotStyle() -> None:
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@classmethod
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def set_boxplot_color(cls, bp, color):
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plt.setp(bp["boxes"], color=color)
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plt.setp(bp["whiskers"], color=color)
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plt.setp(bp["caps"], color=color)
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plt.setp(bp["medians"], color=color)
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@classmethod
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def label_subplots(cls, labels, axes, fig):
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@@ -226,7 +229,7 @@ def PlotStyle() -> None:
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plt.rc("legend", fontsize=SMALL_SIZE) # legend fontsize
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plt.rc("figure", titlesize=BIGGER_SIZE) # fontsize of the figure title
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plt.rcParams["image.cmap"] = 'cmo.haline'
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plt.rcParams["image.cmap"] = "cmo.haline"
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plt.rcParams["axes.xmargin"] = 0.05
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plt.rcParams["axes.ymargin"] = 0.1
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plt.rcParams["axes.titlelocation"] = "left"
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@@ -247,42 +250,44 @@ def PlotStyle() -> None:
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# dark mode modifications
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plt.rcParams["boxplot.flierprops.color"] = white
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plt.rcParams["boxplot.flierprops.markeredgecolor"] = white
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plt.rcParams["boxplot.flierprops.markeredgecolor"] = gray
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plt.rcParams["boxplot.boxprops.color"] = gray
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plt.rcParams["boxplot.whiskerprops.color"] = white
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plt.rcParams["boxplot.capprops.color"] = white
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plt.rcParams["boxplot.medianprops.color"] = white
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plt.rcParams["boxplot.whiskerprops.color"] = gray
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plt.rcParams["boxplot.capprops.color"] = gray
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plt.rcParams["boxplot.medianprops.color"] = gray
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plt.rcParams["text.color"] = white
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plt.rcParams["axes.facecolor"] = black # axes background color
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plt.rcParams["axes.edgecolor"] = gray # axes edge color
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# plt.rcParams["axes.grid"] = True # display grid or not
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# plt.rcParams["axes.grid.axis"] = "y" # which axis the grid is applied to
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plt.rcParams["axes.labelcolor"] = white
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plt.rcParams["axes.axisbelow"] = True # draw axis gridlines and ticks:
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plt.rcParams["axes.axisbelow"] = True # draw axis gridlines and ticks:
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plt.rcParams["axes.spines.left"] = True # display axis spines
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plt.rcParams["axes.spines.bottom"] = True
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plt.rcParams["axes.spines.top"] = False
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plt.rcParams["axes.spines.right"] = False
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plt.rcParams["axes.prop_cycle"] = cycler(
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'color', [
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'#b4befe',
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'#89b4fa',
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'#74c7ec',
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'#89dceb',
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'#94e2d5',
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'#a6e3a1',
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'#f9e2af',
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'#fab387',
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'#eba0ac',
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'#f38ba8',
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'#cba6f7',
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'#f5c2e7',
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])
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"color",
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[
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"#b4befe",
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"#89b4fa",
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"#74c7ec",
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"#89dceb",
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"#94e2d5",
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"#a6e3a1",
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"#f9e2af",
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"#fab387",
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"#eba0ac",
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"#f38ba8",
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"#cba6f7",
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"#f5c2e7",
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],
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)
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plt.rcParams["xtick.color"] = gray # color of the ticks
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plt.rcParams["ytick.color"] = gray # color of the ticks
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plt.rcParams["grid.color"] = dark_gray # grid color
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plt.rcParams["figure.facecolor"] = black # figure face color
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plt.rcParams["figure.edgecolor"] = black # figure edge color
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plt.rcParams["figure.facecolor"] = black # figure face color
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plt.rcParams["figure.edgecolor"] = black # figure edge color
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plt.rcParams["savefig.facecolor"] = black # figure face color when saving
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return style
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@@ -292,12 +297,11 @@ if __name__ == "__main__":
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s = PlotStyle()
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import matplotlib.pyplot as plt
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import matplotlib.cbook as cbook
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import matplotlib.cm as cm
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import matplotlib.pyplot as plt
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import matplotlib.cbook as cbook
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from matplotlib.path import Path
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from matplotlib.patches import PathPatch
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from matplotlib.path import Path
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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@@ -305,14 +309,20 @@ if __name__ == "__main__":
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delta = 0.025
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x = y = np.arange(-3.0, 3.0, delta)
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X, Y = np.meshgrid(x, y)
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Z1 = np.exp(-X**2 - Y**2)
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Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
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Z1 = np.exp(-(X**2) - Y**2)
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Z2 = np.exp(-((X - 1) ** 2) - (Y - 1) ** 2)
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Z = (Z1 - Z2) * 2
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fig1, ax = plt.subplots()
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im = ax.imshow(Z, interpolation='bilinear', cmap=cm.RdYlGn,
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origin='lower', extent=[-3, 3, -3, 3],
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vmax=abs(Z).max(), vmin=-abs(Z).max())
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im = ax.imshow(
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Z,
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interpolation="bilinear",
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cmap=cm.RdYlGn,
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origin="lower",
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extent=[-3, 3, -3, 3],
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vmax=abs(Z).max(),
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vmin=-abs(Z).max(),
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)
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plt.show()
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@@ -325,22 +335,21 @@ if __name__ == "__main__":
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all_data = [np.random.normal(0, std, 100) for std in range(6, 10)]
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# plot violin plot
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axs[0].violinplot(all_data,
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showmeans=False,
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showmedians=True)
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axs[0].set_title('Violin plot')
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axs[0].violinplot(all_data, showmeans=False, showmedians=True)
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axs[0].set_title("Violin plot")
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# plot box plot
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axs[1].boxplot(all_data)
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axs[1].set_title('Box plot')
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axs[1].set_title("Box plot")
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# adding horizontal grid lines
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for ax in axs:
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ax.yaxis.grid(True)
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ax.set_xticks([y + 1 for y in range(len(all_data))],
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labels=['x1', 'x2', 'x3', 'x4'])
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ax.set_xlabel('Four separate samples')
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ax.set_ylabel('Observed values')
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ax.set_xticks(
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[y + 1 for y in range(len(all_data))], labels=["x1", "x2", "x3", "x4"]
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)
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ax.set_xlabel("Four separate samples")
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ax.set_ylabel("Observed values")
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plt.show()
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@@ -352,24 +361,42 @@ if __name__ == "__main__":
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theta = np.linspace(0.0, 2 * np.pi, N, endpoint=False)
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radii = 10 * np.random.rand(N)
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width = np.pi / 4 * np.random.rand(N)
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colors = cmo.cm.haline(radii / 10.)
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colors = cmo.cm.haline(radii / 10.0)
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ax = plt.subplot(projection='polar')
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ax = plt.subplot(projection="polar")
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ax.bar(theta, radii, width=width, bottom=0.0, color=colors, alpha=0.5)
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plt.show()
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methods = [None, 'none', 'nearest', 'bilinear', 'bicubic', 'spline16',
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'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',
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'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos']
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methods = [
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None,
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"none",
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"nearest",
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"bilinear",
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"bicubic",
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"spline16",
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"spline36",
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"hanning",
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"hamming",
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"hermite",
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"kaiser",
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"quadric",
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"catrom",
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"gaussian",
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"bessel",
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"mitchell",
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"sinc",
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"lanczos",
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]
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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grid = np.random.rand(4, 4)
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fig, axs = plt.subplots(nrows=3, ncols=6, figsize=(9, 6),
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subplot_kw={'xticks': [], 'yticks': []})
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fig, axs = plt.subplots(
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nrows=3, ncols=6, figsize=(9, 6), subplot_kw={"xticks": [], "yticks": []}
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)
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for ax, interp_method in zip(axs.flat, methods):
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ax.imshow(grid, interpolation=interp_method)
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