Merge pull request #509 from OpenCOMPES/style_fixes

Style fixes

.cspell/custom-dictionary.txt

@@ -334,6 +334,7 @@ scicat
 SDIAG
 sdir
 segs
+setp
 sfile
 shutil
 Sixten
@@ -404,6 +405,8 @@ xpos
 xratio
 xrng
 xscale
+xticklabels
+xticks
 xtrans
 Xuser
 xval
@@ -414,6 +417,8 @@ ylabel
 ypos
 yratio
 yscale
+yticklabels
+yticks
 ytrans
 zain
 Zenodo

docs/user_guide/config.md

@@ -12,18 +12,18 @@ The config mechanism returns the combined dictionary, and reports the loaded con
 
 ## Default configuration settings
 
-```{literalinclude} ../../sed/config/default.yaml
+```{literalinclude} ../../config/default.yaml
 :language: yaml
 ```
 
 ## Example configuration file for mpes (METIS momentum microscope at FHI-Berlin)
 
-```{literalinclude} ../../sed/config/mpes_example_config.yaml
+```{literalinclude} ../../config/mpes_example_config.yaml
 :language: yaml
 ```
 
 ## Example configuration file for flash (HEXTOF momentum microscope at FLASH, Desy)
 
-```{literalinclude} ../../sed/config/flash_example_config.yaml
+```{literalinclude} ../../config/flash_example_config.yaml
 :language: yaml
 ```

docs/user_guide/index.md

@@ -22,8 +22,9 @@ config
 ```
 
 ## Advanced Topics
-
 ```{toctree}
 :maxdepth: 1
-advanced_topics
+../tutorial/6_binning_with_time-stamped_data
+../tutorial/7_correcting_orthorhombic_symmetry
+../tutorial/8_jittering_tutorial
 ```

src/sed/calibrator/energy.py

@@ -351,11 +351,11 @@ def adjust_ranges(
 
         # make plot
         labels = kwds.pop("labels", [str(b) + " V" for b in self.biases])
-        figsize = kwds.pop("figsize", (8, 4))
+        figsize = kwds.pop("figsize", (6, 4))
         plot_segs = []
         plot_peaks = []
         fig, ax = plt.subplots(figsize=figsize)
-        colors = plt.get_cmap("rainbow")(np.linspace(0, 1, len(traces)))
+        colors = it.cycle(plt.rcParams["axes.prop_cycle"].by_key()["color"])
         for itr, color in zip(range(len(traces)), colors):
             trace = traces[itr, :]
             # main traces
@@ -378,6 +378,9 @@ def adjust_ranges(
             plot_peaks.append(scatt)
         ax.legend(fontsize=8, loc="upper right")
         ax.set_title("")
+        plt.xlabel("Time-of-flight")
+        plt.ylabel("Intensity")
+        plt.tight_layout()
 
         def update(refid, ranges):
             self.add_ranges(ranges, refid, traces=traces, **kwds)
@@ -664,15 +667,19 @@ def view(
 
         sign = 1 if energy_scale == "kinetic" else -1
 
+        figsize = kwds.pop("figsize", (6, 4))
+
         if backend == "matplotlib":
-            figsize = kwds.pop("figsize", (6, 4))
-            fig_plt, ax = plt.subplots(figsize=figsize)
-            for itr, trace in enumerate(traces):
+            colors = it.cycle(plt.rcParams["axes.prop_cycle"].by_key()["color"])
+            _, ax = plt.subplots(figsize=figsize)
+            for itr, color in zip(range(len(traces)), colors):
+                trace = traces[itr, :]
                 if align:
                     ax.plot(
                         xaxis + sign * (self.biases[itr]),
                         trace,
                         ls="-",
+                        color=color,
                         linewidth=1,
                         label=lbs[itr],
                         **linekwds,
@@ -682,6 +689,7 @@ def view(
                         xaxis,
                         trace,
                         ls="-",
+                        color=color,
                         linewidth=1,
                         label=lbs[itr],
                         **linekwds,
@@ -696,6 +704,7 @@ def view(
                         tofseg,
                         traceseg,
                         ls="-",
+                        color=color,
                         linewidth=2,
                         **linesegkwds,
                     )
@@ -710,7 +719,7 @@ def view(
 
             if show_legend:
                 try:
-                    ax.legend(fontsize=12, **legkwds)
+                    ax.legend(fontsize=8, loc="upper right", **legkwds)
                 except TypeError:
                     pass
 
@@ -721,11 +730,10 @@ def view(
             colors = it.cycle(ColorCycle[10])
             ttp = [("(x, y)", "($x, $y)")]
 
-            figsize = kwds.pop("figsize", (800, 300))
             fig = pbk.figure(
                 title=ttl,
-                width=figsize[0],
-                height=figsize[1],
+                width=figsize[0] * 100,
+                height=figsize[1] * 100,
                 tooltips=ttp,
             )
             # Plotting the main traces

src/sed/calibrator/momentum.py

@@ -102,7 +102,7 @@ def __init__(
         self.include_center: bool = False
         self.use_center: bool = False
         self.pouter: np.ndarray = None
-        self.pcent: tuple[float, ...] = None
+        self.pcent: tuple[float, float] = None
         self.pouter_ord: np.ndarray = None
         self.prefs: np.ndarray = None
         self.ptargs: np.ndarray = None
@@ -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
 
@@ -1389,15 +1388,21 @@ 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])
             ttp = [("(x, y)", "($x, $y)")]
-            figsize = kwds.pop("figsize", (320, 300))
             palette = cm2palette(cmap)  # Retrieve palette colors
             fig = pbk.figure(
-                width=figsize[0],
-                height=figsize[1],
+                width=figsize[0] * 100,
+                height=figsize[1] * 100,
                 tooltips=ttp,
                 x_range=(0, num_rows),
                 y_range=(0, num_cols),

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.
@@ -1243,8 +1247,11 @@ def load_bias_series(
         self.ec.view(
             traces=self.ec.traces_normed,
             xaxis=self.ec.tof,
-            backend="bokeh",
+            backend="matplotlib",
         )
+        plt.xlabel("Time-of-flight")
+        plt.ylabel("Intensity")
+        plt.tight_layout()
 
     # 2. extract ranges and get peak positions
     @call_logger(logger)
@@ -1303,7 +1310,7 @@ def find_bias_peaks(
                     segs=self.ec.featranges,
                     xaxis=self.ec.tof,
                     peaks=self.ec.peaks,
-                    backend="bokeh",
+                    backend="matplotlib",
                 )
             except IndexError:
                 logger.error("Could not determine all peaks!")
@@ -2381,7 +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,
@@ -2400,7 +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