Bump to v1.6.0

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pyCirclize"
-version = "1.5.0"
+version = "1.6.0"
 description = "Circular visualization in Python"
 authors = ["moshi4"]
 license = "MIT"
@@ -19,7 +19,6 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Bio-Informatics",
     "Framework :: Matplotlib",
 ]
-include = ["tests"]
 
 [tool.pytest.ini_options]
 minversion = "6.0"

src/pycirclize/__init__.py

@@ -1,6 +1,6 @@
 from pycirclize.circos import Circos
 
-__version__ = "1.5.0"
+__version__ = "1.6.0"
 
 __all__ = [
     "Circos",

src/pycirclize/circos.py

@@ -38,6 +38,12 @@
 class Circos:
     """Circos Visualization Class"""
 
+    # By default, after saving a figure using the `savefig()` method, figure object is
+    # automatically deleted to avoid memory leaks (no display on jupyter notebook)
+    # If you want to display the figure on jupyter notebook using `savefig()` method,
+    # set clear_savefig=False.
+    clear_savefig: bool = True
+
     def __init__(
         self,
         sectors: Mapping[str, int | float | tuple[float, float]],
@@ -522,8 +528,10 @@ def initialize_from_tree(
 
         Returns
         -------
-        circos, tv : tuple[Circos, TreeViz]
-            Circos & TreeViz instances initialized from tree
+        circos : Circos
+            Circos instance
+        tv : TreeViz
+            TreeViz instance
         """
         # Initialize circos sector with tree size
         tree = TreeViz.load_tree(tree_data, format=format)
@@ -946,7 +954,9 @@ def colorbar(
         vmax: float = 1,
         cmap: str | Colormap = "bwr",
         orientation: str = "vertical",
+        label: str | None = None,
         colorbar_kws: dict[str, Any] | None = None,
+        label_kws: dict[str, Any] | None = None,
         tick_kws: dict[str, Any] | None = None,
     ) -> None:
         """Plot colorbar
@@ -964,27 +974,35 @@ def colorbar(
             <https://matplotlib.org/stable/tutorials/colors/colormaps.html>
         orientation : str, optional
             Colorbar orientation (`vertical`|`horizontal`)
+        label : str | None, optional
+            Colorbar label. If None, no label shown.
         colorbar_kws : dict[str, Any] | None, optional
-            Colorbar properties (e.g. `dict(label="name", format="%.1f", ...)`)
+            Colorbar properties (e.g. `dict(format="%.1f", ...)`)
             <https://matplotlib.org/stable/api/colorbar_api.html>
+        label_kws : dict[str, Any] | None, optional
+            Text properties (e.g. `dict(size=15, color="red", ...)`)
+            <https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.text.html>
         tick_kws : dict[str, Any] | None, optional
             Axes.tick_params properties (e.g. `dict(labelsize=12, colors="red", ...)`)
             <https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.tick_params.html>
         """
         colorbar_kws = {} if colorbar_kws is None else deepcopy(colorbar_kws)
+        label_kws = {} if label_kws is None else deepcopy(label_kws)
         tick_kws = {} if tick_kws is None else deepcopy(tick_kws)
 
         def plot_colorbar(ax: PolarAxes) -> None:
             axin: Axes = ax.inset_axes(bounds)
             norm = Normalize(vmin=vmin, vmax=vmax)
-            Colorbar(
+            cb = Colorbar(
                 axin,
                 cmap=cmap,  # type: ignore
                 norm=norm,
                 orientation=orientation,  # type: ignore
                 **colorbar_kws,
             )
             axin.tick_params(**tick_kws)
+            if label:
+                cb.set_label(label, **label_kws)
 
         self._plot_funcs.append(plot_colorbar)
 
@@ -1055,9 +1073,6 @@ def savefig(
     ) -> None:
         """Save figure to file
 
-        `circos.savefig("result.png")` is alias for
-        `circos.plotfig().savefig("result.png")`
-
         Parameters
         ----------
         savefile : str | Path
@@ -1068,6 +1083,11 @@ def savefig(
             Figure size
         pad_inches : float, optional
             Padding inches
+
+        Warnings
+        --------
+        To plot a figure that settings a user-defined legend, subtracks, or annotations,
+        call `fig.savefig()` instead of `gv.savefig()`.
         """
         fig = self.plotfig(dpi=dpi, figsize=figsize)
         fig.savefig(
@@ -1077,8 +1097,9 @@ def savefig(
             bbox_inches="tight",
         )
         # Clear & close figure to suppress memory leak
-        fig.clear()
-        plt.close(fig)
+        if self.clear_savefig:
+            fig.clear()
+            plt.close(fig)
 
     ############################################################
     # Private Method
@@ -1136,8 +1157,10 @@ def _initialize_figure(
 
         Returns
         -------
-        fig, ax : tuple[Figure, PolarAxes]
-            Figure, PolarAxes
+        fig : Figure
+            Figure
+        ax : PolarAxes
+            PolarAxes
         """
         fig = plt.figure(figsize=figsize, dpi=dpi, tight_layout=True)
         ax = fig.add_subplot(projection="polar")

src/pycirclize/parser/genbank.py

@@ -148,8 +148,10 @@ def calc_gc_skew(
 
         Returns
         -------
-        gc_skew_result_tuple : tuple[NDArray[np.int64], NDArray[np.float64]]
-            Position list & GC skew list
+        pos_list : NDArray[np.int64]
+            Position list
+        gc_skew_list : NDArray[np.float64]
+            GC skew list
         """
         pos_list, gc_skew_list = [], []
         seq = self.genome_seq if seq is None else seq
@@ -200,8 +202,10 @@ def calc_gc_content(
 
         Returns
         -------
-        gc_content_result_tuple : tuple[NDArray[np.int64], NDArray[np.float64]]
-            Position list & GC content list
+        pos_list : NDArray[np.int64]
+            Position list
+        gc_content_list : NDArray[np.float64]
+            GC content list
         """
         pos_list, gc_content_list = [], []
         seq = self.genome_seq if seq is None else seq

src/pycirclize/parser/gff.py

@@ -271,8 +271,12 @@ def _parse_gff(
 
         Returns
         -------
-        gff_records, start, end : tuple[list[GffRecord], int, int]
-            GFF record list, start, end
+        gff_records : list[GffRecord]
+            GFF record list
+        start : int
+            Start position of target_seqid record
+        end : int
+            End position of target_seqid record
         """
         gff_file = Path(gff_file)
         if gff_file.suffix == ".gz":
@@ -308,8 +312,12 @@ def _parse_gff_textio(
 
         Returns
         -------
-        gff_records, start, end : tuple[list[GffRecord], int, int]
-            GFF record list, start, end
+        gff_records : list[GffRecord]
+            GFF record list
+        start : int
+            Start position of target_seqid record
+        end : int
+            End position of target_seqid record
         """
         # Parse GFF lines
         gff_all_lines = handle.read().splitlines()

src/pycirclize/parser/matrix.py

@@ -202,16 +202,19 @@ def to_links(
     ) -> list[tuple[tuple[str, float, float], tuple[str, float, float]]]:
         """Convert matrix to links data for `circos.link()` method
 
-        >>> # Example usage
+        Returns
+        -------
+        link_target1 : tuple[str, float, float]
+            name1, start1, end1
+        link_target2 : tuple[str, float, float]
+            name2, start2, end2
+
+        Examples
+        --------
         >>> matrix = Matrix(matrix_file)
         >>> circos = Circos(matrix.to_sectors())
         >>> for link in matrix.to_links():
         >>>    circos.link(*link)
-
-        Returns
-        -------
-        links : list[tuple[tuple[str, float, float], tuple[str, float, float]]]
-            List of link `((name1, start1, end1), (name2, end2, start2))`
         """
         return self._links
 

src/pycirclize/track.py

@@ -1318,8 +1318,10 @@ def _to_arc_radr(
 
         Returns
         -------
-        arc_rad, arc_r : tuple[list[float], list[float]]
-            Arc radian list, Ard radius list
+        arc_rad : list[float]
+            Arc radian list
+        arc_r : list[float]
+            Arc radius list
         """
         all_arc_rad, all_arc_r = [], []
         for i in range(len(rad) - 1):

src/pycirclize/tree.py

@@ -442,8 +442,10 @@ def _set_uniq_innode_name(self, tree: Tree) -> tuple[Tree, list[str]]:
 
         Returns
         -------
-        tree, uniq_node_names: tuple[Tree, list[str]]
-            Unique node name set tree object & set unique node names
+        tree : Tree
+            Tree (set unique node names)
+        uniq_node_names : list[str]
+            Unique node names
         """
         tree = deepcopy(tree)
         uniq_innode_names: list[str] = []

src/pycirclize/utils/__init__.py

@@ -6,7 +6,7 @@
     load_example_tree_file,
     load_prokaryote_example_file,
 )
-from pycirclize.utils.helper import ColorCycler, calc_group_spaces
+from pycirclize.utils.helper import ColorCycler, calc_group_spaces, is_pseudo_feature
 
 __all__ = [
     "plot",
@@ -17,4 +17,5 @@
     "load_example_tree_file",
     "ColorCycler",
     "calc_group_spaces",
+    "is_pseudo_feature",
 ]

src/pycirclize/utils/dataset.py

@@ -96,8 +96,12 @@ def load_eukaryote_example_dataset(
 
     Returns
     -------
-    chr_bed_file, cytoband_file, chr_links : tuple[Path, Path, list[ChrLink]]
-        BED file, Cytoband file, Chromosome links
+    chr_bed_file : Path
+        BED file
+    cytoband_file : Path
+        Cytoband file
+    chr_links : list[ChrLink]
+        Chromosome links
     """
     # Check specified name dataset exists or not
     if name not in config.EUKARYOTE_DATASET:

src/pycirclize/utils/helper.py

@@ -2,6 +2,7 @@
 
 import matplotlib as mpl
 import numpy as np
+from Bio.SeqFeature import SeqFeature
 from matplotlib.colors import Colormap, to_hex
 
 
@@ -129,3 +130,20 @@ def calc_group_spaces(
         return spaces
     else:
         return spaces[:-1]
+
+
+def is_pseudo_feature(feature: SeqFeature) -> bool:
+    """Check target feature is pseudo or not from qualifiers tag
+
+    Parameters
+    ----------
+    feature : SeqFeature
+        Target feature
+
+    Returns
+    -------
+    check_result : bool
+        pseudo check result
+    """
+    quals = feature.qualifiers
+    return True if "pseudo" in quals or "pseudogene" in quals else False