Fix type

jcvi/apps/base.py

@@ -25,7 +25,7 @@
 from socket import gethostname
 from subprocess import PIPE, call, check_output
 from optparse import OptionParser as OptionP, OptionGroup, SUPPRESS_HELP
-from typing import Any, Collection, List, Optional, Union
+from typing import Any, Collection, List, Optional, Tuple, Union
 
 from natsort import natsorted
 from rich.console import Console
@@ -39,7 +39,7 @@
 os.environ["LC_ALL"] = "C"
 JCVIHELP = "JCVI utility libraries {} [{}]\n".format(__version__, __copyright__)
 
-TextCollection = Union[str, Iterable[str]]
+TextCollection = Union[str, List[str], Tuple[str]]
 
 
 def debug(level=logging.DEBUG):

jcvi/assembly/geneticmap.py

@@ -12,6 +12,7 @@
 from functools import lru_cache
 from itertools import combinations, groupby
 from random import sample
+from typing import List
 
 import numpy as np
 import seaborn as sns
@@ -20,7 +21,7 @@
 from ..algorithms.matrix import symmetrize
 from ..formats.base import BaseFile, LineFile, must_open, read_block
 from ..formats.bed import Bed, fastaFromBed
-from ..graphics.base import plt, savefig, Rectangle, draw_cmap
+from ..graphics.base import Rectangle, draw_cmap, plt, plot_heatmap, savefig
 
 
 MSTheader = """population_type {0}
@@ -332,7 +333,10 @@ def dotplot(args):
 
 
 @lru_cache(maxsize=None)
-def calc_ldscore(a, b):
+def calc_ldscore(a: List[str], b: List[str]) -> float:
+    """
+    Calculate Linkage disequilibrium (r2) between two genotypes.
+    """
     assert len(a) == len(b), "{0}\n{1}".format(a, b)
     # Assumes markers as A/B
     c = Counter(zip(a, b))

jcvi/assembly/hic.py

@@ -46,7 +46,7 @@
     savefig,
 )
 from ..graphics.dotplot import dotplot
-from ..utils.cbook import gene_name, human_size
+from ..utils.cbook import gene_name
 
 # Map orientations to ints
 FF = {"+": 1, "-": -1, "?": 1}
@@ -782,9 +782,7 @@ def heatmap(args):
     breaks = sorted(breaks)[1:]
     if contig or opts.nobreaks:
         breaks = []
-    binsize = human_size(resolution, precision=0)
-    title = f"Resolution = {binsize} per bin"
-    plot_heatmap(ax, B, breaks, iopts, groups=new_groups, title=title)
+    plot_heatmap(ax, B, breaks, groups=new_groups, binsize=resolution)
 
     # Title
     pf = npyfile.rsplit(".", 1)[0]
@@ -1639,7 +1637,7 @@ def movieframe(args):
     ax2_root = fig.add_axes([0.5, 0, 0.5, 1])  # dot plot canvas
 
     # Left axis: heatmap
-    plot_heatmap(ax1, M, breaks, iopts)
+    plot_heatmap(ax1, M, breaks, binsize=BINSIZE)
 
     # Right axis: synteny
     qbed, sbed, qorder, sorder, is_self = check_beds(anchorsfile, p, opts, sorted=False)

jcvi/graphics/base.py

@@ -11,7 +11,6 @@
 logging.getLogger("numexpr").setLevel(logging.WARNING)
 logging.getLogger("PIL").setLevel(logging.INFO)
 
-
 from functools import partial
 
 import numpy as np
@@ -39,6 +38,7 @@
 
 from ..apps.base import datadir, glob, listify, logger, sample_N, which
 from ..formats.base import LineFile
+from ..utils.cbook import human_size
 
 
 CHARS = {
@@ -333,7 +333,7 @@ def savefig(figname, dpi=150, iopts=None, cleanup=True):
 
 
 # human readable size (Kb, Mb, Gb)
-def human_readable(x, pos, base=False):
+def human_readable(x: Union[str, int], _, base=False):
     x = str(int(x))
     if x.endswith("000000000"):
         x = x[:-9] + "G"
@@ -504,10 +504,9 @@ def plot_heatmap(
     ax,
     M: np.array,
     breaks: List[int],
-    iopts: ImageOptions,
     groups: List[Tuple[int, int, List[Tuple[int, str]], str]] = [],
     plot_breaks: bool = False,
-    title: str = "",
+    binsize: Optional[int] = None,
 ):
     """Plot heatmap illustrating the contact probabilities in Hi-C data.
 
@@ -518,7 +517,7 @@ def plot_heatmap(
         iopts (OptionParser options): Graphical options passed in from commandline
         groups (List, optional): [(start, end, [(position, seqid)], color)]. Defaults to [].
         plot_breaks (bool): Whether to plot white breaks. Defaults to False.
-        title (str): Title of the heatmap at bottom
+        binsize (int, optional): Resolution of the heatmap.
     """
     cmap = sns.cubehelix_palette(rot=0.5, as_cmap=True)
     ax.imshow(M, cmap=cmap, interpolation="none")
@@ -550,13 +549,14 @@ def simplify_seqid(seqid):
     ax.set_xticklabels(ax.get_xticks(), family="Helvetica", color="gray")
     ax.set_yticklabels(ax.get_yticks(), family="Helvetica", color="gray", rotation=90)
     ax.tick_params(left=True, bottom=True, labelleft=True, labelbottom=True)
-    formatter = ticker.FuncFormatter(
-        lambda x, pos: human_readable(int(x) * binsize, pos, base=True)
-    )
-    ax.xaxis.set_major_formatter(formatter)
-    ax.yaxis.set_major_formatter(formatter)
-    binlabel = "Resolution = {} per bin".format(human_size(binsize, precision=0))
-    ax.set_xlabel(binlabel)
+    if binsize is not None:
+        formatter = ticker.FuncFormatter(
+            lambda x, pos: human_readable(int(x) * binsize, pos, base=True)
+        )
+        ax.xaxis.set_major_formatter(formatter)
+        ax.yaxis.set_major_formatter(formatter)
+        title = f"Resolution = {human_size(binsize, precision=0)} per bin"
+        ax.set_xlabel(title)
 
 
 def discrete_rainbow(N=7, cmap=cm.Set1, usepreset=True, shuffle=False, plot=False):