Log and save selection of lfc-lfc plots.

plot_lfclfc_scatter.py

 #!/usr/bin/env python3
 # vim: set fileencoding=<utf-8> :
 """This script reads data from "tidy" files and makes plots out of
-it, at the same scale."""
+it, at the same scale.
+It also outputs a table containing the plotted data points."""
 
 import argparse
 import os
 import sys
 import warnings
+from operator import attrgetter, contains
+# from functools import partial
 import matplotlib as mpl
 # To be able to run the script without a defined $DISPLAY
 # mpl.use("PDF")
 from matplotlib.backends.backend_pgf import FigureCanvasPgf
 import pandas as pd
-from cytoolz import concat
+from cytoolz import compose, concat, curry
 from libhts import plot_scatter
 from libworkflows import save_plot, strip_split
 
@@ -86,8 +89,7 @@ class Scatterplot:
                  y_input_file,
                  x_column,
                  y_column,
-                 x_label,
-                 y_label,
+                 labels,
                  extra_cols=None):
         if extra_cols is None:
             x_usecols = ["gene", x_column].__contains__
@@ -127,8 +129,7 @@ class Scatterplot:
             self.grouping_col = "_".join(extra_cols)
         else:
             self.grouping_col = None
-        self.x_label = x_label
-        self.y_label = y_label
+        (self.x_label, self.y_label) = labels
 
     def apply_selector(self, selector, chose_from=None):
         """Returns a list of gene ids based on a *selector* string.
@@ -142,8 +143,7 @@ class Scatterplot:
         if chose_from:
             return [gene_id for gene_id in self.data.query(selector).index
                     if gene_id in chose_from]
-        else:
-            return [gene_id for gene_id in self.data.query(selector).index]
+        return [gene_id for gene_id in self.data.query(selector).index]
 
     def plot_maker(self, grouping=None, group2colour=None, **kwargs):
         """Builds a plotting function that can colour dots based on them
@@ -153,12 +153,19 @@ class Scatterplot:
             *save_plot* can include it in the bounding box."""
             # fig, axis = plot_scatter(
             # print(kwargs["x_range"])
-            axis = plot_scatter(
-                self.data,
-                "x", "y",
-                grouping=grouping,
-                group2colour=group2colour,
-                **kwargs)
+            try:
+                axis = plot_scatter(
+                    self.data,
+                    "x", "y",
+                    grouping=grouping,
+                    group2colour=group2colour,
+                    **kwargs)
+            except ValueError as err:
+                if str(err) == "No data to plot.":
+                    warnings.warn("No data to plot.")
+                    return None
+                else:
+                    raise
             # Lines indicating 2-fold threshold.
             # Assumes the data are in log2 fold changes
             line_style = {
@@ -281,8 +288,7 @@ class Scatterplot:
                     bbox_to_anchor=(0, 1),
                     bbox_transform=axis.transAxes, loc="lower left")
                 return legend,
-            else:
-                return None
+            return None
             # Not working:
             # fig.tight_layout()
             # strange behaviour (interaction with tight_layout?)
@@ -351,10 +357,10 @@ def main():
     parser.add_argument(
         "--data_range",
         help="min and max of the data values to display. "
-        "If the range is to narrow to plot data, it will be ignored.",
-        type = int,
-        nargs = 2,
-        default = [-12, 12])
+        "If the range is too narrow to plot data, it will be ignored.",
+        type=int,
+        nargs=2,
+        default=[-12, 12])
     parser.add_argument(
         "--extra_cols",
         help="Columns containing categorical information "
@@ -405,8 +411,7 @@ def main():
         args.y_input_data,
         args.x_column,
         args.y_column,
-        args.x_label,
-        args.y_label,
+        (args.x_label, args.y_label),
         extra_cols=args.extra_cols)
     # if args.transform == "log2":
     #     transform = 2
@@ -425,14 +430,29 @@ def main():
         assert args.selection_label, msg
         gene_list = plot_data.apply_selector(args.selector, base_gene_list)
     else:
-        gene_list = base_gene_list
+        gene_list = list(plot_data.data.index.intersection(base_gene_list))
     if args.plot_name:
         # https://stackoverflow.com/a/14364249/1878788
         os.makedirs(args.plot_dir, exist_ok=True)
         out_pdf = OPJ(
             args.plot_dir,
             "%s.pdf" % args.plot_name)
+        out_table = OPJ(
+            args.plot_dir,
+            "%s.tsv" % args.plot_name)
+        out_log = OPJ(
+            args.plot_dir,
+            "%s.log" % args.plot_name)
+        with open(out_log, "w") as log_file:
+            print(" \\\n\t".join(sys.argv), file=log_file)
         if gene_list and args.selection_label:
+            plot_data.data.assign(hightlighted=plot_data.data.apply(
+                # apply takes a function of row
+                # get the row name
+                # check whether it belongs to gene_list
+                compose(curry(contains)(gene_list), attrgetter("name")),
+                axis=1)).to_csv(
+                    out_table, sep="\t")
             list_name = args.selection_label
             # if args.gene_list:
             #     if args.selection_label:
@@ -455,6 +475,7 @@ def main():
                     "linewidth": 0.5, "color": "0.5", "linestyle": "-"},
                 regression=args.plot_regression)
         else:
+            plot_data.data.to_csv(out_table, sep="\t")
             plot_data.save_plot(
                 # args.x_axis, args.y_axis,
                 out_pdf,