53 docs viz i

alpharaw/viz/plot_utils.py

@@ -7,14 +7,39 @@
 
 
 def plot_scatter(
-    x_values,
-    y_values,
-    color,
-    marker_size,
-    hovertext,
-    hovertemplate,
-    name="",
-):
+    x_values: np.ndarray,
+    y_values: np.ndarray,
+    color: str,
+    marker_size: int,
+    hovertext: str,
+    hovertemplate: str,
+    name: str = "",
+) -> go.Scatter:
+    """
+    plotly scatter based on x and y points.
+
+    Parameters
+    ----------
+    x_values : np.ndarray
+        x values for :class:`go.Scatter`
+    y_values : np.ndarray
+        y values for :class:`go.Scatter`
+    color : str
+        color name
+    marker_size : int
+        marker size of the point (x,y)
+    hovertext : str
+        `hovertext` parameter of :class:`go.Scatter`
+    hovertemplate : str
+        `hovertemplate` parameter of :class:`go.Scatter`
+    name : str, optional
+        `name` parameter of :class:`go.Scatter`, by default ''
+
+    Returns
+    -------
+    go.Scatter
+        go.Scatter of plotly
+    """
     return go.Scatter(
         x=x_values,
         y=y_values,
@@ -43,7 +68,34 @@ def plot_line_tims(
     view_dim: typing.Literal["rt", "im"] = "rt",  # or 'im'
     intensity_scale: float = 1.0,
     rt_unit: str = "minute",
-):
+) -> go.Figure:
+    """
+    Plot an XIC line on alphatims `TimsTOF` data
+
+    Parameters
+    ----------
+    tims_data : TimsTOF
+        The alphatims `TimsTOF` object
+    tims_raw_indices : np.ndarray
+        Raw indices on `TimsTOF` object
+    tims_view_indices : np.array
+        View indices on `TimsTOF` object
+    name : str
+        Display name
+    legend_group : str
+        Lines will be grouped by `legend_group`
+    marker_color : str
+        Color of the scatter (x, y)
+    view_dim : "rt", "im", optional
+        View dimension, "rt" or "im", by default "rt"
+    rt_unit : str, optional
+        RT unit, by default "minute"
+
+    Returns
+    -------
+    go.Figure
+        Line plot
+    """
     x_dimension = alphatims_labels[view_dim]
 
     intensities = tims_data.bin_intensities(tims_raw_indices, [x_dimension])
@@ -73,11 +125,42 @@ def plot_line_tims_fast(
     name: str,
     legend_group: str,
     marker_color: str,
-    view_dim: typing.Literal["rt", "im"] = "rt",  # or 'im'
+    view_dim: typing.Literal["rt", "im"] = "rt",
     intensity_scale: float = 1.0,
     rt_unit: str = "minute",
     add_peak_area=True,
-):
+) -> go.Figure:
+    """
+    Plot an XIC line on alphatims `TimsTOF` data
+
+    Parameters
+    ----------
+    tims_data : TimsTOF
+        The alphatims `TimsTOF` object
+    tims_raw_indices : np.ndarray
+        Raw indices on `TimsTOF` object
+    tims_view_indices : np.array
+        View indices on `TimsTOF` object
+    name : str
+        Display name
+    legend_group : str
+        Lines will be grouped by `legend_group`
+    marker_color : str
+        Color of the scatter (x, y)
+    view_dim : "rt", "im", optional
+        View dimension, "rt" or "im", by default "rt"
+    intensity_scale : float, optional
+        Intensity scale of mirror plot, by default 1.0
+    rt_unit : str, optional
+        RT unit, by default "minute"
+    add_peak_area : bool, optional
+        If add peak area in the hover text, by default True
+
+    Returns
+    -------
+    go.Figure
+        _description_
+    """
     x_dimension = alphatims_labels[view_dim]
 
     intensities = tims_data.bin_intensities(tims_raw_indices, [x_dimension])
@@ -113,7 +196,35 @@ def plot_line(
     x_text: str = "RT",
     other_info: str = "",
     hovertemplate: str = "%{text} <br>Intensity: %{y}",
-):
+) -> go.Scatter:
+    """
+    Plot a line for given x and y points, this is usually for XIC plots.
+
+    Parameters
+    ----------
+    x_values : np.ndarray
+        x values for :class:`go.Scatter`
+    y_values : np.ndarray
+        y values for :class:`go.Scatter`
+    name : str
+        Legend name for the plotted line
+    marker_color : str
+        Marker color of the point (x,y)
+    legend_group : str
+        Different lines can be grouped by the same `legend_group`
+    x_text : str, optional
+        Hover text of the x axis, by default "RT"
+    other_info: str, optional
+        Other hover information, by default ""
+    hovertemplate : str, optional
+        `hovertemplate` parameter of :class:`go.Scatter`,
+        by default '%{text} <br><b>Intensity:</b> %{y}'
+
+    Returns
+    -------
+    go.Scatter
+        The plotted line
+    """
     return go.Scatter(
         x=x_values,
         y=y_values,
@@ -136,7 +247,10 @@ def plot_line_df(
     legend_group: str,
     marker_color: str,
     view_dim: str = "rt",  # or 'im'
-):
+) -> go.Figure:
+    """
+    TODO deprecated
+    """
     if view_dim == "rt":
         tims_sliced_df = tims_sliced_df.groupby("frame_indices", as_index=False).agg(
             {

alpharaw/viz/psm_plot.py

@@ -13,6 +13,24 @@
 from .plot_utils import plot_scatter
 
 color_map: dict = defaultdict(lambda: "brown")
+"""
+The colors of different peak annotations. By default:
+```
+{
+    '-': 'lightgrey', # umnatched peaks
+    'a': 'darkskyblue',
+    'b': 'blue',
+    'c': 'skyblue',
+    'x': 'darkred',
+    'y': 'red',
+    'z': 'deeppink',
+    'M': 'purple', # precursor
+    'Y': 'orange',
+    'B': 'darkgreen',
+}
+```
+For other annotations, the default color is "brown".
+"""
 color_map.update(
     {
         "-": "lightgrey",  # umnatched peaks
@@ -50,6 +68,55 @@ def plot_multi_psms(
     query_left_margin: float = 100000.0,
     query_right_margin: float = 100000.0,
 ):
+    """
+    Annotate multiple spectra for a peptide in a single plotly go.Figure.
+
+    Parameters
+    ----------
+    spec_masses_list : typing.List[np.ndarray]
+        The list of peak masses of multiple spectra to be annotated
+    spec_intens_list : typing.List[np.ndarray]
+        The list of peak intensities of multiple spectra to be annotated
+    sequence : str
+        Peptide sequence
+    mods : str
+        Modifications in alphabase format
+    mod_sites : str
+        Modification sites in alphabase format
+    charge : int
+        Charge state of the precursor
+    title : str, optional
+        Plotting title, by default ""
+    ppm : float, optional
+        Matching mass tolerance in ppm, by default 20.0
+    charged_frag_types : list, optional
+        Fragment charge states, by default ["b_z1","b_z2","y_z1","y_z2"]
+    include_fragments : bool, optional
+        If annotate fragments, by default True
+    include_precursor_isotopes : bool, optional
+        If annotate precursor isotopes, by default False
+    max_isotope : int, optional
+        Maximal number of isotopes, by default 6
+    min_frag_mz : float, optional
+        Minimal fragment m/z value to annotate, by default 100.0
+    plot_unmatched_peaks : bool, optional
+        If plot unmatched peaks (ion_name='-'), by default True
+    match_mode : "closest", "highest", optional
+        Match the closest or highest peak within the matching tolerance, by default "closest"
+    plot_template : str, optional
+        Plot template, by default 'plotly_white'
+    plot_height : int, optional
+        Plot height, by default 600
+    query_left_margin : float, optional
+        Slice margin to the left mz, by default 100000.0
+    query_right_margin : float, optional
+        Slice martin to the right mz, by default 100000.0
+
+    Returns
+    -------
+    go.Figure
+        The annotation plots of multiple spectra
+    """
     plot_df = make_query_df_for_peptide(
         sequence,
         mods,
@@ -97,6 +164,37 @@ def plot_multi_spectra(
     plot_template="plotly_white",
     plot_height=600,
 ):
+    """
+    Annotate multiple spectra for given queries in a single plotly go.Figure.
+
+    Parameters
+    ----------
+    spec_masses_list : typing.List[np.ndarray]
+        The list of peak masses of multiple spectra to be annotated
+    spec_intens_list : typing.List[np.ndarray]
+        The list of peak intensities of multiple spectra to be annotated
+    query_masses : np.ndarray
+        The query m/z values
+    query_ion_names : typing.List[str]
+        The query ion names
+    query_mass_tols : np.ndarray
+        The query mass tolerance in Da
+    title : str, optional
+        The plot title, by default ""
+    plot_unmatched_peaks : bool, optional
+        If plot unmatched peaks (ion_name='-'), by default True
+    match_mode : "closest", "highest", optional
+        Match the closest or highest peak within the matching tolerance, by default "closest"
+    plot_template : str, optional
+        Plot template, by default 'plotly_white'
+    plot_height : int, optional
+        Plot height, by default 600
+
+    Returns
+    -------
+    go.Figure
+        The annotation plots of multiple spectra
+    """
     plot_dfs = []
     for spec_masses, spec_intens in zip(spec_masses_list, spec_intens_list):
         plot_dfs.append(
@@ -138,16 +236,35 @@ def plot_multi_spectra(
 
 
 class PSM_Plot:
+    """
+    The main class for spectrum annotation of a PSM. It contains three plots:
+    1. Ladder plot (`FragCoveragePlot`) for fragment coverage of the peptide.
+    2. Peak annotation plot (`PeakPlot`) for the spectrum.
+    3. Matching mass error plot (`MassErrPlot`) for the matched peaks.
+
+
+    Parameters
+    ----------
+    peak_plot_rows : int, optional
+        The height (ratio) of peak plot, by default 4
+    mass_err_plot_rows : int, optional
+        The height (ratio) of mass error plot, by default 1
+    frag_coverage_plot_rows : int, optional
+        The height (ratio) of fragment coverage plot, by default 1
+    frag_coverage : bool, optional
+        If plot fragment coverage, by default True
+    """
+
     vertical_spacing = 0.05
     template = "plotly_white"
     plot_height = 600
 
     def __init__(
         self,
-        peak_plot_rows=4,
-        mass_err_plot_rows=1,
-        frag_coverage_plot_rows=1,
-        frag_coverage=True,
+        peak_plot_rows: int = 4,
+        mass_err_plot_rows: int = 1,
+        frag_coverage_plot_rows: int = 1,
+        frag_coverage: bool = True,
     ):
         specs = []
         if frag_coverage:
@@ -190,7 +307,35 @@ def __init__(
         self.frag_cov_row = frag_cov_row
         self.rows = peak_plot_rows + mass_err_plot_rows + frag_coverage_plot_rows
 
-    def plot(self, plot_df, sequence, title, plot_unmatched_peaks=False):
+    def plot(
+        self,
+        plot_df: pd.DataFrame,
+        sequence: str,
+        title: str,
+        plot_unmatched_peaks: bool = False,
+    ) -> go.Figure:
+        """
+        Main entry of `PSM_Plot` for peak annotation.
+
+        Parameters
+        ----------
+        plot_df : pd.DataFrame
+            The plot_df can be generated by
+            :func:`alpharaw.viz.df_utils.make_psm_plot_df_for_peptide`,
+            :func:`alpharaw.viz.df_utils.make_psm_plot_for_frag_dfs`, or
+            :func:`alpharaw.viz.df_utils.make_psm_plot_df`.
+        sequence : str
+            Peptide sequence, for fragment coverage plot
+        title : str
+            Plot title
+        plot_unmatched_peaks : bool, optional
+            If plot unmatched peaks with ion_name `-`, by default False
+
+        Returns
+        -------
+        go.Figure
+            Peak annotation plot in plotly go.Figure
+        """
         if "pcc" in plot_df.columns and len(plot_df) > 0:
             title = f"{title} (R={plot_df.pcc.values[0]:.3f})"
         self._init_plot(title)

alpharaw/viz/xic_plot_tims.py

@@ -1,3 +1,5 @@
+# TODO Deprecated
+
 import typing
 
 import numpy as np