From 977ffc4c119c08bf296f000f10e5b76e62ef6d97 Mon Sep 17 00:00:00 2001
From: pswain <peter.swain@ed.ac.uk>
Date: Fri, 17 May 2024 14:11:05 +0100
Subject: [PATCH] fix(kymograph): error in using sort_order
---
src/wela/plotting.py | 4 ++--
src/wela/sorting.py | 21 +++++++++++----------
2 files changed, 13 insertions(+), 12 deletions(-)
diff --git a/src/wela/plotting.py b/src/wela/plotting.py
index 4e47b06..f7fa0c2 100644
--- a/src/wela/plotting.py
+++ b/src/wela/plotting.py
@@ -105,7 +105,7 @@ def kymograph(
dt = np.min(np.diff(np.sort(df.time.unique())))
data = wdf.to_numpy()
if sort_order is not None:
- data = data[np.argsort(sort_order), :]
+ data = data[sort_order, :]
if filterfunc is not None:
data = filterfunc(data)
if standardscale:
@@ -146,7 +146,7 @@ def kymograph(
if buddings:
buddings = df.pivot(index=y, columns=x, values="buddings").to_numpy()
if sort_order is not None:
- buddings = buddings[np.argsort(sort_order), :]
+ buddings = buddings[sort_order, :]
bud_mask = np.ma.masked_where(buddings == 0, buddings)
ax.imshow(bud_mask, interpolation="none")
ax.figure.colorbar(
diff --git a/src/wela/sorting.py b/src/wela/sorting.py
index 31616c1..11694aa 100644
--- a/src/wela/sorting.py
+++ b/src/wela/sorting.py
@@ -11,20 +11,21 @@ def sort_by_budding(buddings, bud_number=0):
sort_order.append(cell_buds[bud_number][1])
else:
sort_order.append(np.nan)
- sort_order = np.array(sort_order)
+ sort_order = np.argsort(sort_order)
return sort_order
-def sort_by_maximum(data, byfunction=None):
- """Return indices of cells sorted by largest value."""
- sort_order = np.nan * np.ones(data.shape[0])
- sdata = data[not_all_nan(data), :]
- if byfunction is not None:
- sorted_indices = np.argsort(byfunction(sdata, axis=1))
+def sort_by_maximum(data, byfunction, reverse=False):
+ """
+ Return indices of cells sorted by largest value.
+
+ Any cells that have all NaN values are placed last.
+ """
+ sort_order = np.argsort(byfunction(data, axis=1))
+ if reverse:
+ return sort_order[::-1]
else:
- sorted_indices = np.nanargmax(sdata, axis=1)
- sort_order[not_all_nan(data)] = sorted_indices
- return sort_order
+ return sort_order
def not_all_nan(data):
--
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