fix numpy warning

README.md

@@ -3,7 +3,7 @@
     <img src="https://raw.githubusercontent.com/DeplanckeLab/ChromatinHD/main/docs/source/static/logo.png" width="300" />
   </a>
   <a href="https://chromatinhd.eu">
-    <img src="https://raw.githubusercontent.com/DeplanckeLab/ChromatinHD/main/docs/source/static/anim.gif" />
+    <img src="https://raw.githubusercontent.com/DeplanckeLab/ChromatinHD/main/docs/source/static/comparison.gif" />
   </a>
 </p>
 

src/chromatinhd/data/motifscan/download.py

@@ -100,7 +100,7 @@ def get_hocomoco(path, organism="hs", variant="CORE", overwrite=False):
     motifs = pd.DataFrame(motifs).set_index("name")
     motifs.index.name = "motif"
 
-    for thresh in motifs["standard_thresholds"][0].keys():
+    for thresh in motifs["standard_thresholds"].iloc[0].keys():
         motifs["cutoff_" + thresh] = [thresholds[thresh] for _, thresholds in motifs["standard_thresholds"].items()]
     for species in ["HUMAN", "MOUSE"]:
         motifs[species + "_gene_symbol"] = [

src/chromatinhd/data/motifscan/motifscan.py

@@ -191,6 +191,7 @@ def from_pwms(
 
         # do the actual counting by looping over the batches, extract the sequences and scanning
         progress = tqdm.tqdm(region_coordinates.groupby("batch"))
+        cur_region_index = 0
         for batch, region_coordinates_batch in progress:
             # extract onehot
             if fasta is None:
@@ -245,9 +246,9 @@ def from_pwms(
                     strands,
                 ) = scan(onehot, pwm2, cutoff=cutoff)
 
-                coordinates = positions.astype(np.int32) % onehot.shape[1]
+                coordinates = positions.astype(np.int32) % onehot.shape[-1]
 
-                region_indices = positions // onehot.shape[1]
+                region_indices = positions // onehot.shape[-1] + cur_region_index
 
                 coordinates = (
                     coordinates
@@ -282,6 +283,9 @@ def from_pwms(
             self.coordinates.extend(coordinates)
             self.region_indices.extend(region_indices)
 
+            # update current region index
+            cur_region_index += len(region_coordinates_batch)
+
         return self
 
     def create_region_indptr(self, overwrite=False):
@@ -569,14 +573,14 @@ def scan(onehot, pwm, cutoff=0.0):
     found_positive = positive >= cutoff
     scores_positive = positive[found_positive]
     positions_positive = torch.stack(torch.where(found_positive)).to(torch.int64)
-    positions_positive = positions_positive[0] * (onehot.shape[1]) + positions_positive[1]
+    positions_positive = positions_positive[0] * (onehot.shape[-1]) + positions_positive[1]
 
     negative = torch.nn.functional.conv1d(onehot_comp, pwm_rev.unsqueeze(0))[:, 0]
 
     found_negative = negative >= cutoff
     scores_negative = negative[found_negative]
     positions_negative = torch.stack(torch.where(found_negative)).to(torch.int64)
-    positions_negative = (positions_negative[0]) * (onehot.shape[1]) + positions_negative[1]
+    positions_negative = (positions_negative[0]) * (onehot.shape[-1]) + positions_negative[1]
 
     return (
         torch.cat([scores_positive, scores_negative]).cpu().numpy(),

src/chromatinhd/data/motifscan/plot.py

@@ -112,7 +112,8 @@ def __init__(
             ax.set_yticks([])
 
             ax.axis("off")
-            ax.axhspan(0, 1, color=group_motifs["color"].iloc[0], zorder=0, alpha=0.1, transform=ax.transAxes, lw=0)
+            color = group_motifs["color"].iloc[0] if group_motifs.shape[0] == 1 else "black"
+            ax.axhspan(0, 1, color=color, zorder=0, alpha=0.1, transform=ax.transAxes, lw=0)
 
             if label_motifs:
                 if label_motifs_side == "right":
@@ -129,7 +130,7 @@ def __init__(
                     xycoords="axes fraction",
                     xytext=xytext,
                     textcoords="offset points",
-                    color=group_motifs["color"][0],
+                    color=group_motifs["color"].iloc[0] if group_motifs.shape[0] == 1 else "black",
                     va="center",
                     fontsize=9,
                     ha=ha,
@@ -228,9 +229,11 @@ def __init__(self, motifscan, gene, motifs_oi, breaking, group_info=None, panel_
             panel, ax = broken[0, -1]
             _setup_group(ax, group_info_oi, group_motifs)
 
+            color = group_motifs["color"].iloc[0] if group_motifs.shape[0] == 1 else "black"
+
             for panel, ax in broken:
                 ax.axis("off")
-                ax.axhspan(0, 1, color=group_motifs["color"].iloc[0], zorder=0, alpha=0.1, transform=ax.transAxes, lw=0)
+                ax.axhspan(0, 1, color=color, zorder=0, alpha=0.1, transform=ax.transAxes, lw=0)
 
             # plot the motifs
             for motif in group_motifs.itertuples():
@@ -260,7 +263,8 @@ def _setup_group(ax, group_info_oi, group_motifs):
     ax.set_yticks([])
 
     if "label" in group_info_oi.keys():
-        ax.text(s=group_info_oi["label"], color=group_motifs["color"].tolist()[0], x=1.0, y=0.0, transform=ax.transAxes)
+        color = group_motifs["color"].tolist()[0] if group_motifs.shape[0] == 1 else "black"
+        ax.text(s=group_info_oi["label"], color=color, x=1.0, y=0.0, transform=ax.transAxes)
     else:
         rainbow_text(
             ax=ax,

src/chromatinhd/models/diff/interpret/regionpositional.py

@@ -360,7 +360,7 @@ def get_plotdata(self, region: str, clusters=None, relative_to=None) -> (pd.Data
         plotdata["prob"] = plotdata["prob"]
 
         if relative_to is not None:
-            plotdata_mean = plotdata[["prob"]].query("cluster in @relative_to").groupby("coord").mean()
+            plotdata_mean = plotdata[["prob"]].query("cluster in @relative_to").groupby("coord", observed=False).mean()
         else:
             plotdata_mean = plotdata[["prob"]].groupby("coord", observed=True).mean()
 

src/chromatinhd/models/diff/plot/differential.py

@@ -471,8 +471,9 @@ def _process_plotdata(plotdata, plotdata_mean, cluster_info, order, relative_to,
             plotdata.index.get_level_values("coord").min(),
             plotdata.index.get_level_values("coord").max(),
         )
-
-    if window is not None:
+    else:
+        if isinstance(window, pd.Series):
+            window = window.values.tolist()
         plotdata = plotdata.loc[
             (plotdata.index.get_level_values("coord") >= window[0])
             & (plotdata.index.get_level_values("coord") <= window[1])