Updating extents to include some padding. Fixing watermark issues.

Author: Samreay

README.md

@@ -64,6 +64,10 @@ post, it can be solved by explicitly install the `matplotlib` dependency `dvipng
 
 ### Update History
 
+##### 0.33.0
+* Adding extra padding to bin extents for KDE and smoothing
+* Updating watermarking to work with matplotlib v3.0.0+
+
 ##### 0.32.0
 * Fixing matplotlib axis formatter issue.
 

chainconsumer/analysis.py

@@ -314,14 +314,14 @@ def get_covariance_table(self, chain=0, parameters=None, caption="Parameter Cova
         parameters, cov = self.get_covariance(chain=chain, parameters=parameters)
         return self._get_2d_latex_table(parameters, cov, caption, label)
 
-    def _get_smoothed_histogram(self, chain, parameter):
+    def _get_smoothed_histogram(self, chain, parameter, pad=False):
         data = chain.get_data(parameter)
         smooth = chain.config["smooth"]
         if chain.grid:
             bins = get_grid_bins(data)
         else:
             bins = chain.config["bins"]
-            bins, smooth = get_smoothed_bins(smooth, bins, data, chain.weights)
+            bins, smooth = get_smoothed_bins(smooth, bins, data, chain.weights, pad=pad)
 
         hist, edges = np.histogram(data, bins=bins, density=True, weights=chain.weights)
         if chain.power is not None:

chainconsumer/chainconsumer.py

@@ -20,7 +20,7 @@ class ChainConsumer(object):
 
     """
 
-    __version__ = "0.32.0"
+    __version__ = "0.33.0"
 
     def __init__(self):
         logging.basicConfig(level=logging.INFO)

chainconsumer/helpers.py

@@ -2,7 +2,7 @@
 import numpy as np
 
 
-def get_extents(data, weight, plot=False, wide_extents=True, tiny=False):
+def get_extents(data, weight, plot=False, wide_extents=True, tiny=False, pad=False):
     hist, be = np.histogram(data, weights=weight, bins=2000)
     bc = 0.5 * (be[1:] + be[:-1])
     cdf = hist.cumsum()
@@ -17,16 +17,22 @@ def get_extents(data, weight, plot=False, wide_extents=True, tiny=False):
         threshold = 0.3
     i1 = np.where(cdf > threshold)[0][0]
     i2 = np.where(icdf > threshold)[0][0]
-    return bc[i1], bc[-i2]
+    lower = bc[i1]
+    upper = bc[-i2]
+    if pad:
+        width = upper - lower
+        lower -= 0.2 * width
+        upper += 0.2 * width
+    return lower, upper
 
 
 def get_bins(chains):
     proposal = [max(35, np.floor(1.0 * np.power(chain.chain.shape[0] / chain.chain.shape[1], 0.25))) for chain in chains]
     return proposal
 
 
-def get_smoothed_bins(smooth, bins, data, weight, marginalised=True, plot=False):
-    minv, maxv = get_extents(data, weight, plot=plot)
+def get_smoothed_bins(smooth, bins, data, weight, marginalised=True, plot=False, pad=False):
+    minv, maxv = get_extents(data, weight, plot=plot, pad=pad)
     if smooth is None or not smooth or smooth == 0:
         return np.linspace(minv, maxv, int(bins)), 0
     else:

chainconsumer/plotter.py

@@ -3,6 +3,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib
+from matplotlib.font_manager import FontProperties
 from matplotlib.ticker import MaxNLocator, ScalarFormatter, LogLocator
 from matplotlib.textpath import TextPath
 from numpy import meshgrid
@@ -315,31 +316,33 @@ def _add_watermark(self, fig, axes, figsize, text, dpi=300, size_scale=1.0):  #
         dx, dy = figsize
         dy, dx = dy * dpi, dx * dpi
         rotation = 180 / np.pi * np.arctan2(-dy, dx)
-        fontdict = self.parent.config["watermark_text_kwargs"]
-        if "usetex" in fontdict:
-            usetex = fontdict["usetex"]
-        else:
-            usetex = self.parent.config["usetex"]
-            fontdict["usetex"] = usetex
-        if fontdict["usetex"]:
+        property_dict = self.parent.config["watermark_text_kwargs"]
+
+        keys_in_font_dict = ["family", "style", "variant", "weight", "stretch", "size"]
+        fontdict = {k: property_dict[k] for k in keys_in_font_dict if k in property_dict}
+        font_prop = FontProperties(**fontdict)
+        usetex = property_dict.get("usetex", self.parent.config["usetex"])
+        if usetex:
             px, py, scale = 0.5, 0.5, 1.0
         else:
-            px, py, scale = 0.45, 0.55, 0.8
-        bb0 = TextPath((0, 0), text, size=50, prop=fontdict, usetex=usetex).get_extents()
-        bb1 = TextPath((0, 0), text, size=51, prop=fontdict, usetex=usetex).get_extents()
+            px, py, scale = 0.5, 0.5, 0.8
+
+        bb0 = TextPath((0, 0), text, size=50, prop=font_prop, usetex=usetex).get_extents()
+        bb1 = TextPath((0, 0), text, size=51, prop=font_prop, usetex=usetex).get_extents()
         dw = (bb1.width - bb0.width) * (dpi / 100)
         dh = (bb1.height - bb0.height) * (dpi / 100)
         size = np.sqrt(dy ** 2 + dx ** 2) / (dh * abs(dy / dx) + dw) * 0.6 * scale * size_scale
         if axes is not None:
-            if fontdict["usetex"]:
+            if usetex:
                 size *= 0.7
             else:
-                size *= 0.85
-        fontdict["size"] = int(size)
+                size *= 0.8
+        size = int(size)
+        print(f"Font size is {size}")
         if axes is None:
-            fig.text(px, py, text, fontdict=fontdict, rotation=rotation)
+            fig.text(px, py, text, fontdict=property_dict, rotation=rotation, fontsize=size)
         else:
-            axes.text(px, py, text, transform=axes.transAxes, fontdict=fontdict, rotation=rotation)
+            axes.text(px, py, text, transform=axes.transAxes, fontdict=property_dict, rotation=rotation, fontsize=size)
 
     def plot_walks(
         self,
@@ -1215,11 +1218,10 @@ def _plot_bars(self, ax, parameter, chain, flip=False, summary=False):  # pragma
         kde = chain.config["kde"]
         zorder = chain.config["zorder"]
         title_size = self.parent.config["label_font_size"]
-
         chain_row = chain.get_data(parameter)
         weights = chain.weights
         if smooth or kde:
-            xs, ys, _ = self.parent.analysis._get_smoothed_histogram(chain, parameter)
+            xs, ys, _ = self.parent.analysis._get_smoothed_histogram(chain, parameter, pad=True)
             if flip:
                 ax.plot(ys, xs, color=colour, ls=linestyle, lw=linewidth, zorder=zorder)
             else: