Added a few more tips

handout-tips.tex

@@ -40,7 +40,7 @@
     dash_capstyle, projection, Stroke, Normal, add_axes, label, savefig,
     get_cmap, histtype, annotate, set_minor_formatter, tick_params,
     fill_betweenx, text, legend, errorbar, boxplot, hist, title, xlabel,
-    ylabel, suptitle },
+    ylabel, suptitle, fraction, pad, set_fontname, get_xticklabels},
   emphstyle = {\ttfamily\bfseries}
 }
 
@@ -188,6 +188,29 @@ \subsection*{\rmfamily Combining axes}
 \raisebox{-0.75em}{\includegraphics[width=\linewidth]{tip-dual-axis.pdf}}
 \end{tabular}
 
+\subsection*{\rmfamily Colorbar adjustment}
+You can adjust colorbar aspect when adding it.
+
+\begin{tabular}{@{}m{.754\linewidth}m{.236\linewidth}}
+\begin{lstlisting}[belowskip=-\baselineskip]
+ im = ax.imshow(Z)
+
+ cb = plt.colorbar(im,
+         fraction=0.046, pad=0.04)
+ cb.set_ticks([])
+\end{lstlisting} &
+\raisebox{-0.75em}{\includegraphics[width=\linewidth]{tip-colorbar.pdf}}
+\end{tabular}
+
+\subsection*{\rmfamily Take advantage of typography}
+You can use a condensed face such as Roboto
+Condensed to save space on tick labels.
+\begin{lstlisting}
+ for tick in ax.get_xticklabels():
+     tick.set_fontname("Roboto Condensed")
+\end{lstlisting}
+\includegraphics[width=\linewidth]{tip-font-family.pdf}
+
 
 \vfill
 %

scripts/tip-color-range.py

@@ -16,8 +16,8 @@
 
 X = np.random.seed(1)
 X = np.random.randn(1000, 4)
-cmap = plt.get_cmap("Blues")
-colors = [cmap(i) for i in [.2,.4,.6,.8]]
+cmap = plt.get_cmap("Oranges")
+colors = [cmap(i) for i in [.1,.3,.5,.7]]
 ax.hist(X, 2, density=True, histtype='bar', color=colors)
 
 plt.savefig("../figures/tip-color-range.pdf")

scripts/tip-colorbar.py

@@ -0,0 +1,25 @@
+# -----------------------------------------------------------------------------
+# Matplotlib cheat sheet
+# Released under the BSD License
+# -----------------------------------------------------------------------------
+
+# Scripts to generate all the basic plots 
+import numpy as np
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import matplotlib.patheffects as path_effects
+
+fig = plt.figure(figsize=(2.15,2))
+mpl.rcParams['axes.linewidth'] = 1.5
+d = 0.01
+ax = fig.add_axes([d,d,1-2*d,1-2*d], xticks=[], yticks=[])
+
+np.random.seed(1)
+Z = np.random.uniform(0,1,(8,8))
+cmap = plt.get_cmap("Oranges")
+im = ax.imshow(Z, interpolation="nearest", cmap=cmap, vmin=0, vmax=2)
+cb = fig.colorbar(im, fraction=0.046, pad=0.04)
+cb.set_ticks([])
+
+plt.savefig("../figures/tip-colorbar.pdf")
+# plt.show()

scripts/tip-font-family.py

@@ -0,0 +1,48 @@
+# ----------------------------------------------------------------------------
+# Title:   Scientific Visualisation - Python & Matplotlib
+# Author:  Nicolas P. Rougier
+# License: BSD
+# ----------------------------------------------------------------------------
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.ticker as ticker
+
+# Setup a plot such that only the bottom spine is shown
+def setup(ax):
+    ax.spines['right'].set_color('none')
+    ax.spines['left'].set_color('none')
+    ax.yaxis.set_major_locator(ticker.NullLocator())
+    ax.spines['top'].set_color('none')
+
+    ax.spines['bottom'].set_position("center")
+
+    ax.xaxis.set_ticks_position('bottom')
+    ax.tick_params(which='major', width=1.00)
+    ax.tick_params(which='major', length=5)
+    ax.tick_params(which='minor', width=0.75)
+    ax.tick_params(which='minor', length=2.5)
+    ax.set_xlim(0, 5)
+    ax.set_ylim(0, 1)
+    ax.patch.set_alpha(0.0)
+
+
+fig = plt.figure(figsize=(5, .5))
+fig.patch.set_alpha(0.0)
+n = 1
+
+fontsize = 18
+ax = plt.subplot(n, 1, 1)
+ax.tick_params(axis='both', which='minor', labelsize=6)
+setup(ax)
+ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
+ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.2))
+ax.xaxis.set_major_formatter(ticker.ScalarFormatter())
+ax.xaxis.set_minor_formatter(ticker.ScalarFormatter())
+ax.tick_params(axis='x', which='minor', rotation=0)
+
+for tick in ax.get_xticklabels():
+    tick.set_fontname("Roboto Condensed")
+
+plt.tight_layout()
+plt.savefig("../figures/tip-font-family.pdf", transparent=True)
+# plt.show()

scripts/tip-outline.py

@@ -17,8 +17,8 @@
 
 np.random.seed(1)
 Z = np.random.uniform(0,1,(8,8))
-cmap = plt.get_cmap("Blues")
-ax.imshow(Z, interpolation="nearest", cmap=cmap, vmin=0, vmax=1)
+cmap = plt.get_cmap("Oranges")
+ax.imshow(Z, interpolation="nearest", cmap=cmap, vmin=0, vmax=2)
 
 text = ax.text(0.5, 0.1, "Label", transform=ax.transAxes,
              color=cmap(0.9), size=32, weight="bold", ha="center", va="bottom")