Add new palette functionality and new colormaps

examples/faceted_lineplot.py

@@ -2,22 +2,22 @@
 Line plots on multiple facets
 =============================
 
-_thumb: .45, .42
+_thumb: .48, .42
 
 """
 import seaborn as sns
 sns.set(style="ticks")
 
 dots = sns.load_dataset("dots")
 
-# Define a palette to ensure that colors will be
-# shared across the facets
-palette = dict(zip(dots.coherence.unique(),
-                   sns.color_palette("rocket_r", len(dots.coherence.unique()))))
+# Define the palette as a list to specify exact values
+palette = sns.color_palette("rocket_r")
 
 # Plot the lines on two facets
-sns.relplot(x="time", y="firing_rate",
-            hue="coherence", size="choice", col="align",
-            size_order=["T1", "T2"], palette=palette,
-            height=5, aspect=.75, facet_kws=dict(sharex=False),
-            kind="line", legend="full", data=dots)
+sns.relplot(
+    data=dots,
+    x="time", y="firing_rate",
+    hue="coherence", size="choice", col="align",
+    kind="line", size_order=["T1", "T2"], palette=palette,
+    height=5, aspect=.75, facet_kws=dict(sharex=False),
+)

examples/pairgrid_dotplot.py

@@ -17,7 +17,7 @@
 
 # Draw a dot plot using the stripplot function
 g.map(sns.stripplot, size=10, orient="h",
-      palette="ch:s=1,r=-.1,h=1_r", linewidth=1, edgecolor="w")
+      palette="flare_r", linewidth=1, edgecolor="w")
 
 # Use the same x axis limits on all columns and add better labels
 g.set(xlim=(0, 25), xlabel="Crashes", ylabel="")

examples/scatterplot_sizes.py

@@ -2,7 +2,7 @@
 Scatterplot with continuous hues and sizes
 ==========================================
 
-_thumb: .45, .45
+_thumb: .48, .45
 
 """
 import seaborn as sns

examples/timeseries_facets.py

@@ -0,0 +1,39 @@
+"""
+Small multiple time series
+--------------------------
+
+_thumb: .42, .58
+
+"""
+import seaborn as sns
+
+sns.set(style="dark")
+flights = sns.load_dataset("flights")
+
+# Plot each year's time series in its own facet
+g = sns.relplot(
+    data=flights,
+    x="month", y="passengers", col="year", hue="year",
+    kind="line", palette="crest", linewidth=4, zorder=5,
+    col_wrap=3, height=2, aspect=1.5, legend=False,
+)
+
+# Iterate over each subplot to customize further
+for year, ax in g.axes_dict.items():
+
+    # Add the title as an annotation within the plot
+    ax.text(.8, .85, year, transform=ax.transAxes, fontweight="bold")
+
+    # Plot every year's time series in the background
+    sns.lineplot(
+        data=flights, x="month", y="passengers", units="year",
+        estimator=None, color=".7", linewidth=1, ax=ax,
+    )
+
+# Reduce the frequency of the x axis ticks
+ax.set_xticks(ax.get_xticks()[::2])
+
+# Tweak the supporting aspects of the plot
+g.set_titles("")
+g.set_axis_labels("", "Passengers")
+g.tight_layout()

seaborn/_core.py

@@ -17,8 +17,6 @@
 from .palettes import (
     QUAL_PALETTES,
     color_palette,
-    cubehelix_palette,
-    _parse_cubehelix_args,
 )
 from .utils import (
     get_color_cycle,
@@ -236,15 +234,8 @@ def numeric_mapping(self, data, palette, norm):
 
             if isinstance(palette, mpl.colors.Colormap):
                 cmap = palette
-            elif str(palette).startswith("ch:"):
-                args, kwargs = _parse_cubehelix_args(palette)
-                cmap = cubehelix_palette(0, *args, as_cmap=True, **kwargs)
             else:
-                try:
-                    cmap = mpl.cm.get_cmap(palette)
-                except (ValueError, TypeError):
-                    err = f"Palette {palette} not understood"
-                    raise ValueError(err)
+                cmap = color_palette(palette, as_cmap=True)
 
             # Now sort out the data normalization
             if norm is None: