Fixes #95

docs/examples/plot_6_custom_axes.py

@@ -0,0 +1,28 @@
+"""
+# Custom Axes
+
+A lot of the time you might have your own plots ready to go.
+
+In this case, you can manually invoke ChainConsumer's plotting functions.
+
+Here's an example, noting that there are also `plot_point`, `plot_surface` available
+that I haven't explicitly shown.
+"""
+import matplotlib.pyplot as plt
+
+from chainconsumer import Chain, Truth, make_sample
+from chainconsumer.plotting import plot_contour, plot_truths
+
+# %%
+
+df = make_sample(num_dimensions=2, seed=1)
+
+# Custom plotting code
+fig, axes = plt.subplots(ncols=2, figsize=(10, 5))
+axes[0].hist(df["A"], bins=50, color="skyblue", density=True)
+
+# We can use ChainConsumer to plot a truth value on top of this histogram
+truth = Truth(location={"A": 0, "B": 5}, line_style=":")
+plot_truths(axes[0], [truth], px="A")
+# And also add a contour to the other axis
+plot_contour(axes[1], Chain(samples=df, name="Example"), px="A", py="B")

src/chainconsumer/plotter.py

@@ -21,9 +21,8 @@
 from .chain import Chain, ChainName, ColumnName
 from .color_finder import colors
 from .helpers import get_bins, get_extents, get_grid_bins, get_smoothed_bins
+from .plotting import add_watermark, plot_surface
 from .plotting.config import PlotConfig
-from .plotting.contours import plot_surface
-from .plotting.watermark import add_watermark
 
 
 class PlottingBase(BetterBase):

src/chainconsumer/plotting/__init__.py

@@ -0,0 +1,12 @@
+from .contours import plot_cloud, plot_contour, plot_point, plot_surface
+from .truth import plot_truths
+from .watermark import add_watermark
+
+__all__ = [
+    "add_watermark",
+    "plot_cloud",
+    "plot_contour",
+    "plot_point",
+    "plot_surface",
+    "plot_truths",
+]

src/chainconsumer/plotting/contours.py

@@ -14,13 +14,15 @@ def plot_surface(
     chains: list[Chain],
     px: ColumnName,
     py: ColumnName,
-    config: PlotConfig,
+    config: PlotConfig | None = None,
 ) -> dict[ColumnName, PathCollection]:
     """Plot the chains onto a 2D surface, using clouds, contours and points.
 
     Returns:
         A map from column name to paths to be added as colorbars.
     """
+    if config is None:
+        config = PlotConfig()
     paths: dict[ColumnName, PathCollection] = {}
     for chain in chains:
         if px not in chain.plotting_columns or py not in chain.plotting_columns:
@@ -61,7 +63,7 @@ def plot_cloud(ax: Axes, chain: Chain, px: ColumnName, py: ColumnName) -> dict[C
     return {}
 
 
-def plot_contour(ax: Axes, chain: Chain, px: ColumnName, py: ColumnName, config: PlotConfig) -> None:
+def plot_contour(ax: Axes, chain: Chain, px: ColumnName, py: ColumnName, config: PlotConfig | None = None) -> None:
     """A lightweight method to plot contours in an external axis given two specified parameters
 
     Args:
@@ -70,6 +72,8 @@ def plot_contour(ax: Axes, chain: Chain, px: ColumnName, py: ColumnName, config:
         px: The parameter to plot on the x axis
         py: The parameter to plot on the y axis
     """
+    if config is None:
+        config = PlotConfig()
     levels = _get_levels(chain.sigmas, config)
     contour_colours = _scale_colours(colors.format(chain.color), len(levels), chain.shade_gradient)
     sub = max(0.1, 1 - 0.2 * chain.shade_gradient)