Merge pull request #33 from kmnhan/dev-2.5

2.5 Update

.pre-commit-config.yaml

@@ -1,3 +1,7 @@
+ci:
+  autoupdate_commit_msg: "ci(pre-commit): pre-commit autoupdate"
+  autofix_commit_msg: "style: pre-commit auto fixes [...]"
+
 repos:
 
   # Meta hooks

docs/source/conf.py

@@ -192,6 +192,8 @@ def linkcode_resolve(domain, info):
     "cmasher": ("https://cmasher.readthedocs.io/", None),
     "ipywidgets": ("https://ipywidgets.readthedocs.io/en/stable/", None),
     "joblib": ("https://joblib.readthedocs.io/en/latest/", None),
+    "panel": ("https://panel.holoviz.org/", None),
+    "hvplot": ("https://hvplot.holoviz.org/", None),
 }
 
 

docs/source/user-guide/curve-fitting.ipynb

@@ -784,7 +784,7 @@
             "metadata": {},
             "outputs": [],
             "source": [
-                "darr.modelfit(\n",
+                "result_ds = darr.modelfit(\n",
                 "    coords=\"alpha\",\n",
                 "    model=GaussianModel() + LinearModel(),\n",
                 "    params={\n",
@@ -795,7 +795,42 @@
                 "        },\n",
                 "        \"slope\": -0.1,\n",
                 "    },\n",
-                ")"
+                ")\n",
+                "result_ds"
+            ]
+        },
+        {
+            "cell_type": "raw",
+            "metadata": {
+                "editable": true,
+                "raw_mimetype": "text/restructuredtext",
+                "slideshow": {
+                    "slide_type": ""
+                },
+                "tags": [],
+                "vscode": {
+                    "languageId": "raw"
+                }
+            },
+            "source": [
+                "Visualizing fits\n",
+                "~~~~~~~~~~~~~~~~\n",
+                "\n",
+                "If `hvplot <https://github.com/holoviz/hvplot>`_ is installed, we can visualize the fit\n",
+                "results interactively with the `qshow` accessor.\n",
+                "\n",
+                ".. note::\n",
+                "\n",
+                "    If you are viewing this documentation online, the plot will not be interactive. Run the code locally to try it out."
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "result_ds.qshow(plot_components=True)"
             ]
         },
         {

docs/source/user-guide/plotting.ipynb

@@ -204,7 +204,7 @@
                 }
             },
             "source": [
-                ":func:`plot_array <erlab.plotting.general.plot_array>` can also be accessed (for 2D data) through an :class:`accessor <erlab.accessors.utils.PlotAccessor>`."
+                ":func:`plot_array <erlab.plotting.general.plot_array>` can also be accessed (for 2D data) through the :class:`qplot <erlab.accessors.utils.PlotAccessor>` accessor."
             ]
         },
         {
@@ -316,7 +316,7 @@
             "source": [
                 "Here, we plotted each constant energy surface with :func:`plot_array\n",
                 "<erlab.plotting.general.plot_array>`. To remove the duplicated y axis labels and add\n",
-                "some annotations, we can use :func:`clean_labels <erlab.plotting.erplot.clean_labels>`\n",
+                "some annotations, we can use :func:`clean_labels <erlab.plotting.general.clean_labels>`\n",
                 "and :func:`label_subplot_properties\n",
                 "<erlab.plotting.annotations.label_subplot_properties>`:"
             ]

pyproject.toml

@@ -235,6 +235,7 @@ exclude = [
 module = [
     "astropy.*",
     "h5netcdf.*",
+    "hvplot.*",
     "igor2.*",
     "iminuit.*",
     "ipywidgets.*",

src/erlab/accessors/__init__.py

@@ -18,7 +18,8 @@
 """  # noqa: D205
 
 __all__ = [
-    "ImageToolAccessor",
+    "InteractiveDataArrayAccessor",
+    "InteractiveDatasetAccessor",
     "ModelFitDataArrayAccessor",
     "ModelFitDatasetAccessor",
     "MomentumAccessor",
@@ -34,4 +35,9 @@
     ParallelFitDataArrayAccessor,
 )
 from erlab.accessors.kspace import MomentumAccessor, OffsetView
-from erlab.accessors.utils import ImageToolAccessor, PlotAccessor, SelectionAccessor
+from erlab.accessors.utils import (
+    InteractiveDataArrayAccessor,
+    InteractiveDatasetAccessor,
+    PlotAccessor,
+    SelectionAccessor,
+)

src/erlab/accessors/utils.py

@@ -1,14 +1,17 @@
 __all__ = [
-    "ImageToolAccessor",
+    "InteractiveDataArrayAccessor",
+    "InteractiveDatasetAccessor",
     "PlotAccessor",
     "SelectionAccessor",
 ]
 
+import importlib
 import warnings
 from collections.abc import Hashable, Mapping
 from typing import Any, TypeGuard, TypeVar, cast
 
 import matplotlib.pyplot as plt
+import numpy as np
 import xarray as xr
 
 import erlab.plotting.erplot as eplt
@@ -90,16 +93,245 @@ def __call__(self, *args, **kwargs):
 
 
 @xr.register_dataarray_accessor("qshow")
-class ImageToolAccessor(ERLabDataArrayAccessor):
+class InteractiveDataArrayAccessor(ERLabDataArrayAccessor):
     """`xarray.DataArray.qshow` accessor for interactive visualization."""
 
     def __call__(self, *args, **kwargs):
+        """Visualize the data interactively.
+
+        Chooses the appropriate interactive visualization method based on the number of
+        dimensions in the data.
+
+        Parameters
+        ----------
+        *args
+            Positional arguments passed onto the interactive visualization function.
+        **kwargs
+            Keyword arguments passed onto the interactive visualization function.
+        """
+        if self._obj.ndim >= 2 and self._obj.ndim <= 4:
+            return self.itool(*args, **kwargs)
+        else:
+            if importlib.util.find_spec("hvplot"):
+                return self._obj.hvplot(*args, **kwargs)
+
+            raise ValueError("Data must have at least two dimensions.")
+
+    def itool(self, *args, **kwargs):
+        """Shortcut for :func:`itool <erlab.interactive.imagetool.itool>`.
+
+        Parameters
+        ----------
+        *args
+            Positional arguments passed onto :func:`itool <erlab.interactive.imagetool.itool>`.
+        **kwargs
+            Keyword arguments passed onto :func:`itool <erlab.interactive.imagetool.itool>`.
+
+        """
+        from erlab.interactive.imagetool import itool
+
+        return itool(self._obj, *args, **kwargs)
+
+    def hvplot(self, *args, **kwargs):
+        """:mod:`hvplot`-based interactive visualization.
+
+        Parameters
+        ----------
+        *args
+            Positional arguments passed onto :meth:`DataArray.hvplot`.
+        **kwargs
+            Keyword arguments passed onto :meth:`DataArray.hvplot`.
+
+        Raises
+        ------
+        ImportError
+            If :mod:`hvplot` is not installed.
+        """
+        if not importlib.util.find_spec("hvplot"):
+            raise ImportError("hvplot is required for qshow.hvplot()")
+        import hvplot.xarray  # noqa: F401
+
+        return self._obj.hvplot(*args, **kwargs)
+
+
+@xr.register_dataset_accessor("qshow")
+class InteractiveDatasetAccessor(ERLabDatasetAccessor):
+    """`xarray.Dataset.qshow` accessor for interactive visualization."""
+
+    def __call__(self, *args, **kwargs):
+        """Visualize the data interactively.
+
+        Chooses the appropriate interactive visualization method based on the data
+        variables.
+
+        Parameters
+        ----------
+        *args
+            Positional arguments passed onto the interactive visualization function.
+        **kwargs
+            Keyword arguments passed onto the interactive visualization function.
+        """
+        if self._is_fitresult:
+            return self.fit(*args, **kwargs)
+        else:
+            return self.itool(*args, **kwargs)
+
+    @property
+    def _is_fitresult(self) -> bool:
+        from erlab.accessors.fit import ParallelFitDataArrayAccessor
+
+        for var in set(ParallelFitDataArrayAccessor._VAR_KEYS) - {"modelfit_results"}:
+            if var not in self._obj.data_vars:
+                return False
+        return True
+
+    def itool(self, *args, **kwargs):
         from erlab.interactive.imagetool import itool
 
-        if len(self._obj.dims) >= 2:
-            return itool(self._obj, *args, **kwargs)
+        return itool(self._obj, *args, **kwargs)
+
+    def hvplot(self, *args, **kwargs):
+        if not importlib.util.find_spec("hvplot"):
+            raise ImportError("hvplot is required for qshow.hvplot()")
+        import hvplot.xarray  # noqa: F401
+
+        return self._obj.hvplot(*args, **kwargs)
+
+    itool.__doc__ = InteractiveDataArrayAccessor.itool.__doc__
+    hvplot.__doc__ = str(InteractiveDataArrayAccessor.hvplot.__doc__).replace(
+        "DataArray", "Dataset"
+    )
+
+    def fit(self, plot_components: bool = False):
+        """Interactive visualization of fit results.
+
+        Parameters
+        ----------
+        plot_components
+            If `True`, plot the components of the fit. Default is `False`. Requires the
+            Dataset to have a `modelfit_results` variable.
+
+        Returns
+        -------
+        :class:`panel.Column`
+            A panel containing the interactive visualization.
+        """
+        if not importlib.util.find_spec("hvplot"):
+            raise ImportError("hvplot is required for interactive fit visualization")
+
+        import hvplot.xarray
+        import panel
+        import panel.widgets
+
+        from erlab.accessors.fit import ParallelFitDataArrayAccessor
+
+        for var in set(ParallelFitDataArrayAccessor._VAR_KEYS) - {"modelfit_results"}:
+            if var not in self._obj.data_vars:
+                raise ValueError("Dataset is not a fit result")
+
+        coord_dims = [
+            d
+            for d in self._obj.modelfit_stats.dims
+            if d in self._obj.modelfit_data.dims
+        ]
+        other_dims = [d for d in self._obj.modelfit_data.dims if d not in coord_dims]
+
+        if len(other_dims) != 1:
+            raise ValueError("Only 1D fits are supported")
+
+        sliders = [
+            panel.widgets.DiscreteSlider(name=d, options=list(np.array(self._obj[d])))
+            for d in coord_dims
+        ]
+
+        def get_slice(*s):
+            return self._obj.sel(dict(zip(coord_dims, s, strict=False)))
+
+        def get_slice_params(*s):
+            res_part = get_slice(*s).rename(param="Parameter")
+            return xr.merge(
+                [
+                    res_part.modelfit_coefficients.rename("Value"),
+                    res_part.modelfit_stderr.rename("Stderr"),
+                ]
+            )
+
+        def get_comps(*s):
+            partial_res = get_slice(*s)
+            return xr.merge(
+                [
+                    xr.DataArray(
+                        v, dims=other_dims, coords=[self._obj[other_dims[0]]]
+                    ).rename(k)
+                    for k, v in partial_res.modelfit_results.item()
+                    .eval_components()
+                    .items()
+                ]
+                + [
+                    partial_res.modelfit_data,
+                    partial_res.modelfit_best_fit,
+                ]
+            )
+
+        part = hvplot.bind(get_slice, *sliders).interactive()
+        part_params = hvplot.bind(get_slice_params, *sliders).interactive()
+
+        if "modelfit_results" not in self._obj.data_vars:
+            warnings.warn(
+                "`model_results` not included in Dataset. "
+                "Components will not be plotted",
+                stacklevel=2,
+            )
+            plot_components = False
+
+        plot_kwargs = {
+            "responsive": True,
+            "min_width": 400,
+            "min_height": 500,
+            "title": "",
+        }
+        if plot_components:
+            part_comps = hvplot.bind(get_comps, *sliders).interactive()
+            data = part_comps.modelfit_data.hvplot.scatter(**plot_kwargs)
+            fit = part_comps.modelfit_best_fit.hvplot(c="k", ylabel="", **plot_kwargs)
+            components = part_comps.hvplot(
+                y=list(
+                    self._obj.modelfit_results.values.flatten()[0]
+                    .eval_components()
+                    .keys()
+                ),
+                legend="top_right",
+                group_label="Component",
+                **plot_kwargs,
+            )
+            plots = components * data * fit
         else:
-            raise ValueError("Data must have at leasst two dimensions.")
+            data = part.modelfit_data.hvplot.scatter(**plot_kwargs)
+            fit = part.modelfit_best_fit.hvplot(c="k", ylabel="", **plot_kwargs)
+            plots = data * fit
+
+        return panel.Column(
+            plots,
+            panel.Spacer(height=30),
+            panel.Tabs(
+                (
+                    "Parameters",
+                    part_params.hvplot.table(
+                        columns=["Parameter", "Value", "Stderr"],
+                        title="",
+                        responsive=True,
+                    ),
+                ),
+                (
+                    "Fit statistics",
+                    part.modelfit_stats.hvplot.table(
+                        columns=["fit_stat", "modelfit_stats"],
+                        title="",
+                        responsive=True,
+                    ),
+                ),
+            ),
+        )
 
 
 @xr.register_dataarray_accessor("qsel")