From a0d8ed87a3e9b90c5b7264e7a9dbb1fb1a04555e Mon Sep 17 00:00:00 2001
From: Wirawan Purwanto <wirawan0@gmail.com>
Date: Mon, 7 Apr 2014 12:27:08 -0400
Subject: [PATCH] * New module: wpylib.array_tools for convenient array
 manipulations.

---
 array_tools.py | 40 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 40 insertions(+)
 create mode 100644 array_tools.py

diff --git a/array_tools.py b/array_tools.py
new file mode 100644
index 0000000..31f0438
--- /dev/null
+++ b/array_tools.py
@@ -0,0 +1,40 @@
+#
+# Created: 20140207
+# Wirawan Purwanto
+#
+
+"""
+wpylib.array_tools
+
+Various tools for arrays (mainly, numpy array objects).
+
+"""
+
+
+def array_indices_cond_1d(arr, cond):
+  """Get the odered list of array indices whose corresponding elements satisfy
+  a given condition.
+  Useful for conditional assignment or evaluation.
+
+  The input `cond' argument can be an ufunc-like function that evaluates
+  a logical expression in bulk for each of the arr's element.
+  Or it can be an array of logical values that has the same length as arr.
+
+  Example use case:
+
+     r = numpy.linspace(1.97, 3.5, num=150)
+     i_select = cond_indices_1d(r, r <= 2.5)
+     # ... then we can do something with r[i_select]
+     # for conditional assignment or value extraction.
+  """
+  arr = numpy.asarray(arr)
+  assert len(arr.shape) == 1
+
+  if callable(cond):
+    cond = cond(arr)
+  # otherwise, assume cond is already a good array
+  return numpy.array(xrange(len(arr)))[ cond ]
+
+
+
+