Merge pull request #1 from aertslab/plotting

Plotting + bugfixes + small features

docs/api/plotting.md

@@ -17,4 +17,55 @@ Plotting description
     :toctree: _autosummary
 
     pl.contribution_scores
-```
+```
+
+## Bar plots
+
+```{eval-rst}
+.. autosummary::
+    :toctree: _autosummary
+
+    pl.bar.region
+    pl.bar.region_predictions
+    pl.bar.normalization_weights
+```
+
+## Distribution plots
+
+```{eval-rst}
+.. autosummary::
+    :toctree: _autosummary
+
+    pl.hist.distribution
+```
+
+## Heatmap
+
+Correlations
+
+```{eval-rst}
+.. autosummary::
+    :toctree: _autosummary
+
+    pl.heatmap.correlations_self
+    pl.heatmap.correlations_predictions
+```
+
+## Scatter plots
+
+```{eval-rst}
+.. autosummary::
+    :toctree: _autosummary
+
+    pl.scatter.class_density
+```
+
+## Utility functions
+
+```{eval-rst}
+.. autosummary::
+    :toctree: _autosummary
+
+    pl.render_plot
+```
+

docs/conf.py

@@ -94,8 +94,6 @@
     "python": ("https://docs.python.org/3", None),
     "anndata": ("https://anndata.readthedocs.io/en/stable/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
-    "tensorflow": ("https://www.tensorflow.org/api_docs/python", None),
-    "keras": ("https://keras.io/api/", None),
 }
 
 # List of patterns, relative to source directory, that match files and

pyproject.toml

@@ -31,6 +31,7 @@ dependencies = [
     "loguru",
     "logomaker",
     "pybigtools",
+    "seaborn"
 ]
 
 [project.optional-dependencies]

src/crested/__init__.py

@@ -10,8 +10,8 @@
 
 __version__ = version("crested")
 
-os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
-os.environ["AUTOGRAPH_VERBOSITY"] = "1"
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
+os.environ["AUTOGRAPH_VERBOSITY"] = "0"
 
 # Setup loguru logging
 setup_logging(log_level="INFO", log_file=None)

src/crested/_io.py

@@ -167,7 +167,7 @@ def import_topics(
         will be included.
         Topics should be named after the topics file name without the extension.
     chromsizes_file
-        File path of the chromsizes file.
+        File path of the chromsizes file.  Used for checking if the new regions are within the chromosome boundaries.
     remove_empty_regions
         Remove regions that are not open in any topic.
     compress
@@ -302,7 +302,7 @@ def import_bigwigs(
     regions_file
         File name of the consensus regions BED file.
     chromsizes_file
-        File name of the chromsizes file.
+        File name of the chromsizes file. Used for checking if the new regions are within the chromosome boundaries.
     target
         Target value to extract from bigwigs. Can be 'mean', 'max', 'count', or 'logcount'
     target_region_width

src/crested/pl/__init__.py

@@ -1 +1,3 @@
+from . import bar, heatmap, hist, scatter
 from ._contribution_scores import contribution_scores
+from ._utils import render_plot

src/crested/pl/_contribution_scores.py

@@ -73,6 +73,8 @@ def contribution_scores(
     >>> seqs_one_hot = np.random.randint(0, 2, (1, 100, 4))
     >>> class_names = ["class1"]
     >>> crested.pl.contribution_scores(scores, seqs_one_hot, class_names)
+
+    .. image:: ../../../docs/_static/img/examples/contribution_scores.png
     """
     # Center and zoom
     _check_contrib_params(zoom_n_bases, scores)

src/crested/pl/_utils.py

@@ -1,15 +1,68 @@
+"""Utility functions for plotting in CREsted."""
+
+from __future__ import annotations
+
 import logomaker
+import matplotlib.pyplot as plt
 import numpy as np
 
 
+def render_plot(
+    fig,
+    width: int = 8,
+    height: int = 8,
+    title: str | None = None,
+    xlabel: str | None = None,
+    ylabel: str | None = None,
+    save_path: str | None = None,
+) -> None:
+    """
+    Render a plot with customization options.
+
+    Note
+    ----
+    This function should never be called directly. Rather, the other plotting functions call this function.
+
+    Parameters
+    ----------
+    fig
+        The figure object to render.
+    width
+        Width of the plot (inches).
+    height
+        Height of the plot (inches).
+    title
+        Title of the plot.
+    xlabel
+        Label for the X-axis.
+    ylabel
+        Label for the Y-axis.
+    fig_path
+        Optional path to save the figure. If None, the figure is displayed but not saved.
+    """
+    fig.set_size_inches(width, height)
+    if title:
+        fig.suptitle(title)
+    for ax in fig.axes:
+        if xlabel:
+            ax.set_xlabel(xlabel)
+        if ylabel:
+            ax.set_ylabel(ylabel)
+
+    plt.tight_layout()
+    if save_path:
+        plt.savefig(save_path)
+    plt.show()
+
+
 def grad_times_input_to_df(x, grad, alphabet="ACGT"):
     """Generate pandas dataframe for saliency plot based on grad x inputs"""
     x_index = np.argmax(np.squeeze(x), axis=1)
     grad = np.squeeze(grad)
     L, A = grad.shape
 
     seq = ""
-    saliency = np.zeros((L))
+    saliency = np.zeros(L)
     for i in range(L):
         seq += alphabet[x_index[i]]
         saliency[i] = grad[i, x_index[i]]

src/crested/pl/bar/__init__.py

@@ -0,0 +1,2 @@
+from ._normalization_weights import normalization_weights
+from ._region import region, region_predictions

src/crested/pl/bar/_normalization_weights.py

@@ -0,0 +1,65 @@
+"""Bar plot of normalization weights."""
+
+from __future__ import annotations
+
+import matplotlib.pyplot as plt
+from anndata import AnnData
+
+from crested._logging import log_and_raise
+from crested.pl._utils import render_plot
+
+
+def normalization_weights(adata: AnnData, **kwargs):
+    """
+    Plot the distribution of normalization scaling factors per cell type.
+
+    Parameters
+    ----------
+    adata
+        AnnData object containing the normalization weights in `obsm["weights"]`.
+    kwargs
+        Additional arguments passed to :func:`~crested.pl.render_plot` to
+        control the final plot output. Please see :func:`~crested.pl.render_plot`
+        for details.
+
+    See Also
+    --------
+    crested.pl.render_plot
+
+    Example
+    -------
+    >>> crested.pl.bar.normalization_weights(
+    ...     adata,
+    ...     xlabel="Cell type",
+    ...     ylabel="Scaling factor",
+    ...     width=20,
+    ...     height=3,
+    ...     title="Normalization scaling factors",
+    ... )
+
+    .. image:: ../../../docs/_static/img/examples/bar_normalization_weights.png
+    """
+
+    @log_and_raise(ValueError)
+    def _check_input_params():
+        if "weights" not in adata.obsm:
+            raise ValueError("Normalization weights not found in adata.obsm['weights']")
+
+    _check_input_params()
+
+    weights = adata.obsm["weights"]
+    classes = list(adata.obs_names)
+
+    fig, ax = plt.subplots()
+    ax.bar(classes, weights)
+
+    # default plot size
+    default_width = 20
+    default_height = 3
+
+    if "width" not in kwargs:
+        kwargs["width"] = default_width
+    if "height" not in kwargs:
+        kwargs["height"] = default_height
+
+    render_plot(fig, **kwargs)