👌 Add das_cycler and svd_cycler to plot collection functions

pyglotaran_extras/plotting/plot_data.py

@@ -12,6 +12,7 @@
 from pyglotaran_extras.plotting.plot_svd import plot_lsv_data
 from pyglotaran_extras.plotting.plot_svd import plot_rsv_data
 from pyglotaran_extras.plotting.plot_svd import plot_sv_data
+from pyglotaran_extras.plotting.style import PlotStyle
 from pyglotaran_extras.plotting.utils import MinorSymLogLocator
 from pyglotaran_extras.plotting.utils import not_single_element_dims
 from pyglotaran_extras.plotting.utils import shift_time_axis_by_irf_location
@@ -22,6 +23,7 @@
     from collections.abc import Hashable
 
     import xarray as xr
+    from cycler import Cycler
     from glotaran.project.result import Result
     from matplotlib.figure import Figure
     from matplotlib.pyplot import Axes
@@ -41,6 +43,7 @@ def plot_data_overview(
     cmap: str = "PuRd",
     vmin: float | None = None,
     vmax: float | None = None,
+    svd_cycler: Cycler | None = PlotStyle().cycler,
 ) -> tuple[Figure, Axes] | tuple[Figure, Axis]:
     """Plot data as filled contour plot and SVD components.
 
@@ -71,6 +74,8 @@ def plot_data_overview(
         Lower value to anchor the colormap. Defaults to None meaning it inferred from the data.
     vmax : float | None
         Lower value to anchor the colormap. Defaults to None meaning it inferred from the data.
+    svd_cycler : Cycler | None
+        Plot style cycler to use for SVD plots. Defaults to ``PlotStyle().cycler``.
 
     Returns
     -------
@@ -111,9 +116,16 @@ def plot_data_overview(
         linlog=linlog,
         linthresh=linthresh,
         irf_location=irf_location,
+        cycler=svd_cycler,
     )
     plot_sv_data(dataset, sv_ax)
-    plot_rsv_data(dataset, rsv_ax, indices=range(nr_of_data_svd_vectors), show_legend=False)
+    plot_rsv_data(
+        dataset,
+        rsv_ax,
+        indices=range(nr_of_data_svd_vectors),
+        show_legend=False,
+        cycler=svd_cycler,
+    )
     if show_data_svd_legend is True:
         rsv_ax.legend(title="singular value index", loc="lower right", bbox_to_anchor=(1.13, 1))
     fig.suptitle(title, fontsize=16)

pyglotaran_extras/plotting/plot_overview.py

@@ -21,6 +21,7 @@
 from pyglotaran_extras.plotting.style import PlotStyle
 from pyglotaran_extras.plotting.utils import add_cycler_if_not_none
 from pyglotaran_extras.plotting.utils import extract_irf_location
+from pyglotaran_extras.types import Unset
 
 if TYPE_CHECKING:
     from cycler import Cycler
@@ -29,6 +30,7 @@
     from matplotlib.pyplot import Axes
 
     from pyglotaran_extras.types import DatasetConvertible
+    from pyglotaran_extras.types import UnsetType
 
 
 def plot_overview(
@@ -48,6 +50,8 @@ def plot_overview(
     show_residual_svd_legend: bool = True,
     show_irf_dispersion_center: bool = True,
     show_zero_line: bool = True,
+    das_cycler: Cycler | None | UnsetType = Unset,
+    svd_cycler: Cycler | None | UnsetType = Unset,
 ) -> tuple[Figure, Axes]:
     """Plot overview of the optimization result.
 
@@ -95,13 +99,24 @@ def plot_overview(
     show_zero_line : bool
         Whether or not to add a horizontal line at zero to the plots of the spectra.
         Defaults to True.
+    das_cycler : Cycler | None | UnsetType
+        Plot style cycler to use for DAS plots. Defaults to ``Unset`` which means that the value
+        of ``cycler`` is used.
+    svd_cycler : Cycler | None | UnsetType
+        Plot style cycler to use for SVD plots. Defaults to ``Unset`` which means that the value
+        of ``cycler`` is used.
 
     Returns
     -------
     tuple[Figure, Axes]
     """
     res = load_data(result, _stacklevel=3)
 
+    if das_cycler is Unset:
+        das_cycler = cycler
+    if svd_cycler is Unset:
+        svd_cycler = cycler
+
     if res.coords["time"].to_numpy().size == 1:
         fig, axes = plot_guidance(res)
         if figure_only is not None:
@@ -125,13 +140,15 @@ def plot_overview(
         main_irf_nr=main_irf_nr,
         cycler=cycler,
     )
-    plot_spectra(res, axes[0:2, 1:3], cycler=cycler, show_zero_line=show_zero_line)
+    plot_spectra(
+        res, axes[0:2, 1:3], cycler=cycler, show_zero_line=show_zero_line, das_cycler=das_cycler
+    )
     plot_svd(
         res,
         axes[2:4, 0:3],
         linlog=linlog,
         linthresh=linthresh,
-        cycler=cycler,
+        cycler=svd_cycler,
         nr_of_data_svd_vectors=nr_of_data_svd_vectors,
         nr_of_residual_svd_vectors=nr_of_residual_svd_vectors,
         show_data_svd_legend=show_data_svd_legend,
@@ -161,6 +178,7 @@ def plot_simple_overview(
     figure_only: bool | None = None,
     show_irf_dispersion_center: bool = True,
     show_data: bool | None = False,
+    svd_cycler: Cycler | None | UnsetType = Unset,
 ) -> tuple[Figure, Axes]:
     """Plot simple overview.
 
@@ -182,12 +200,17 @@ def plot_simple_overview(
     show_data : bool | None
         Whether to show the input data or residual. If set to ``None`` the plot is skipped
         which improves plotting performance for big datasets. Defaults to False.
+    svd_cycler : Cycler | None | UnsetType
+        Plot style cycler to use for SVD plots. Defaults to ``Unset`` which means that the value
+        of ``cycler`` is used.
 
     Returns
     -------
     tuple[Figure, Axes]
     """
     res = load_data(result, _stacklevel=3)
+    if svd_cycler is Unset:
+        svd_cycler = cycler
 
     fig, axes = plt.subplots(2, 3, figsize=figsize, constrained_layout=True)
     for ax in axes.flatten():
@@ -200,8 +223,8 @@ def plot_simple_overview(
 
     irf_location = extract_irf_location(res, center_λ=res.coords["spectral"].to_numpy()[0])
 
-    plot_lsv_residual(res, ax=axes[1, 0], irf_location=irf_location)
-    plot_rsv_residual(res, ax=axes[1, 1])
+    plot_lsv_residual(res, ax=axes[1, 0], irf_location=irf_location, cycler=svd_cycler)
+    plot_rsv_residual(res, ax=axes[1, 1], cycler=svd_cycler)
 
     plot_residual(
         res,

pyglotaran_extras/plotting/plot_spectra.py

@@ -7,19 +7,23 @@
 
 from pyglotaran_extras.plotting.style import PlotStyle
 from pyglotaran_extras.plotting.utils import add_cycler_if_not_none
+from pyglotaran_extras.types import Unset
 
 if TYPE_CHECKING:
     import xarray as xr
     from cycler import Cycler
     from matplotlib.axis import Axis
     from matplotlib.pyplot import Axes
 
+    from pyglotaran_extras.types import UnsetType
+
 
 def plot_spectra(
     res: xr.Dataset,
     axes: Axes,
     cycler: Cycler | None = PlotStyle().cycler,
     show_zero_line: bool = True,
+    das_cycler: Cycler | None | UnsetType = Unset,
 ) -> None:
     """Plot spectra such as SAS and DAS as well as their normalize version on ``axes``.
 
@@ -33,11 +37,17 @@ def plot_spectra(
         Plot style cycler to use. Defaults to PlotStyle().cycler.
     show_zero_line : bool
         Whether or not to add a horizontal line at zero. Defaults to True.
+    das_cycler : Cycler | None | UnsetType
+        Plot style cycler to use for DAS plots. Defaults to ``Unset`` which means that the value
+        of ``cycler`` is used.
     """
+    if das_cycler is Unset:
+        das_cycler = cycler
+
     plot_sas(res, axes[0, 0], cycler=cycler, show_zero_line=show_zero_line)
-    plot_das(res, axes[0, 1], cycler=cycler, show_zero_line=show_zero_line)
+    plot_das(res, axes[0, 1], cycler=das_cycler, show_zero_line=show_zero_line)
     plot_norm_sas(res, axes[1, 0], cycler=cycler, show_zero_line=show_zero_line)
-    plot_norm_das(res, axes[1, 1], cycler=cycler, show_zero_line=show_zero_line)
+    plot_norm_das(res, axes[1, 1], cycler=das_cycler, show_zero_line=show_zero_line)
 
 
 def plot_sas(

pyglotaran_extras/types.py

@@ -10,6 +10,18 @@
 import xarray as xr
 from glotaran.project.result import Result
 
+
+class UnsetType:
+    """Type for the ``Unset`` singleton."""
+
+    def __repr__(self) -> str:  # noqa: DOC
+        """Representation of instances in editors."""
+        return "Unset"
+
+
+Unset = UnsetType()
+"""Singleton to use when arguments are not provided where None is a valid value."""
+
 DatasetConvertible: TypeAlias = xr.Dataset | xr.DataArray | str | Path
 """Types of data which can be converted to a dataset."""
 ResultLike: TypeAlias = (