use matplotlib also for momentum correction

.cspell/custom-dictionary.txt

@@ -404,6 +404,7 @@ xpos
 xratio
 xrng
 xscale
+xticks
 xtrans
 Xuser
 xval
@@ -414,6 +415,7 @@ ylabel
 ypos
 yratio
 yscale
+yticks
 ytrans
 zain
 Zenodo

src/sed/calibrator/momentum.py

@@ -1348,7 +1348,9 @@ def view(
 
         if annotated:
             tsr, tsc = kwds.pop("textshift", (3, 3))
-            txtsize = kwds.pop("textsize", 12)
+            txtsize = kwds.pop("textsize", 10)
+
+        title = kwds.pop("title", "")
 
         # Handle unexpected kwds:
         handled_kwds = {"figsize"}
@@ -1358,7 +1360,7 @@ def view(
             )
 
         if backend == "matplotlib":
-            fig_plt, ax = plt.subplots(figsize=figsize)
+            _, ax = plt.subplots(figsize=figsize)
             ax.imshow(image.T, origin=origin, cmap=cmap, **imkwds)
 
             if cross:
@@ -1368,15 +1370,12 @@ def view(
 
             # Add annotation to the figure
             if annotated:
-                for (
-                    p_keys,  # pylint: disable=unused-variable
-                    p_vals,
-                ) in points.items():
+                for p_keys, p_vals in points.items():
                     try:
-                        ax.scatter(p_vals[:, 0], p_vals[:, 1], **scatterkwds)
+                        ax.scatter(p_vals[:, 0], p_vals[:, 1], s=15, **scatterkwds)
                     except IndexError:
                         try:
-                            ax.scatter(p_vals[0], p_vals[1], **scatterkwds)
+                            ax.scatter(p_vals[0], p_vals[1], s=15, **scatterkwds)
                         except IndexError:
                             pass
 
@@ -1389,6 +1388,13 @@ def view(
                                 fontsize=txtsize,
                             )
 
+            if crosshair and self.pcent is not None:
+                for radius in crosshair_radii:
+                    circle = plt.Circle(self.pcent, radius, color="k", fill=False)
+                    ax.add_patch(circle)
+
+            ax.set_title(title)
+
         elif backend == "bokeh":
             output_notebook(hide_banner=True)
             colors = it.cycle(ColorCycle[10])

src/sed/core/processor.py

@@ -649,24 +649,28 @@ def generate_splinewarp(
         self.mc.spline_warp_estimate(use_center=use_center, **kwds)
 
         if self.mc.slice is not None and self._verbose:
-            print("Original slice with reference features")
-            self.mc.view(annotated=True, backend="bokeh", crosshair=True)
+            self.mc.view(
+                annotated=True,
+                backend="matplotlib",
+                crosshair=True,
+                title="Original slice with reference features",
+            )
 
-            print("Corrected slice with target features")
             self.mc.view(
                 image=self.mc.slice_corrected,
                 annotated=True,
                 points={"feats": self.mc.ptargs},
-                backend="bokeh",
+                backend="matplotlib",
                 crosshair=True,
+                title="Corrected slice with target features",
             )
 
-            print("Original slice with target features")
             self.mc.view(
                 image=self.mc.slice,
                 points={"feats": self.mc.ptargs},
                 annotated=True,
-                backend="bokeh",
+                backend="matplotlib",
+                title="Original slice with target features",
             )
 
     # 3a. Save spline-warp parameters to config file.
@@ -2384,7 +2388,7 @@ def view_event_histogram(
         bins: Sequence[int] = None,
         axes: Sequence[str] = None,
         ranges: Sequence[tuple[float, float]] = None,
-        backend: str = "bokeh",
+        backend: str = "matplotlib",
         legend: bool = True,
         histkwds: dict = None,
         legkwds: dict = None,
@@ -2403,7 +2407,7 @@ def view_event_histogram(
             ranges (Sequence[tuple[float, float]], optional): Value ranges of all
                 specified axes. Defaults to config["histogram"]["ranges"].
             backend (str, optional): Backend of the plotting library
-                ('matplotlib' or 'bokeh'). Defaults to "bokeh".
+                ("matplotlib" or "bokeh"). Defaults to "matplotlib".
             legend (bool, optional): Option to include a legend in the histogram plots.
                 Defaults to True.
             histkwds (dict, optional): Keyword arguments for histograms

src/sed/diagnostics.py

@@ -59,7 +59,7 @@ def grid_histogram(
     rvs: Sequence,
     rvbins: Sequence,
     rvranges: Sequence[tuple[float, float]],
-    backend: str = "bokeh",
+    backend: str = "matplotlib",
     legend: bool = True,
     histkwds: dict = None,
     legkwds: dict = None,
@@ -73,30 +73,30 @@ def grid_histogram(
         rvs (Sequence): List of names for the random variables (rvs).
         rvbins (Sequence): Bin values for all random variables.
         rvranges (Sequence[tuple[float, float]]): Value ranges of all random variables.
-        backend (str, optional): Backend for making the plot ('matplotlib' or 'bokeh').
-            Defaults to "bokeh".
+        backend (str, optional): Backend for making the plot ("matplotlib" or "bokeh").
+            Defaults to "matplotlib".
         legend (bool, optional): Option to include a legend in each histogram plot.
             Defaults to True.
         histkwds (dict, optional): Keyword arguments for histogram plots.
             Defaults to None.
         legkwds (dict, optional): Keyword arguments for legends. Defaults to None.
         **kwds:
-            - *figsize*: Figure size. Defaults to (14, 8)
+            - *figsize*: Figure size. Defaults to (6, 4)
     """
     if histkwds is None:
         histkwds = {}
     if legkwds is None:
         legkwds = {}
 
-    figsz = kwds.pop("figsize", (10, 7))
+    figsz = kwds.pop("figsize", (6, 4))
 
     if len(kwds) > 0:
         raise TypeError(f"grid_histogram() got unexpected keyword arguments {kwds.keys()}.")
 
     if backend == "matplotlib":
         nrv = len(rvs)
         nrow = int(np.ceil(nrv / ncol))
-        histtype = kwds.pop("histtype", "step")
+        histtype = kwds.pop("histtype", "bar")
 
         fig, ax = plt.subplots(nrow, ncol, figsize=figsz)
         otherax = ax.copy()
@@ -114,7 +114,7 @@ def grid_histogram(
                     **histkwds,
                 )
                 if legend:
-                    ax[axind].legend(fontsize=15, **legkwds)
+                    ax[axind].legend(fontsize=10, **legkwds)
 
                 otherax[axind] = None
 
@@ -128,13 +128,16 @@ def grid_histogram(
                     **histkwds,
                 )
                 if legend:
-                    ax[i].legend(fontsize=15, **legkwds)
+                    ax[i].legend(fontsize=10, **legkwds)
 
                 otherax[i] = None
 
         for oax in otherax.flatten():
             if oax is not None:
                 fig.delaxes(oax)
+        plt.xticks(fontsize=8)
+        plt.yticks(fontsize=8)
+        plt.tight_layout()
 
     elif backend == "bokeh":
         output_notebook(hide_banner=True)
@@ -163,7 +166,7 @@ def grid_histogram(
             gridplot(
                 plots,  # type: ignore
                 ncols=ncol,
-                width=figsz[0] * 30,
-                height=figsz[1] * 28,
+                width=figsz[0] * 100 // ncol,
+                height=figsz[1] * 100 // (len(plots) // ncol),
             ),
         )