From 400756db7c31f73b604dbb39184ad0acea88cfa5 Mon Sep 17 00:00:00 2001
From: Peter Teuben <teuben@gmail.com>
Date: Thu, 28 Jul 2016 11:45:37 -0400
Subject: [PATCH] notes from focus session

---
 timing/README.md  | 43 +++++++++++++++++++++++++++++++++++++++++++
 timing/timing1.py | 45 +++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 88 insertions(+)
 create mode 100644 timing/README.md
 create mode 100644 timing/timing1.py

diff --git a/timing/README.md b/timing/README.md
new file mode 100644
index 0000000..e9927c8
--- /dev/null
+++ b/timing/README.md
@@ -0,0 +1,43 @@
+Timing your codes:
+
+python examples:
+       % ipython
+       run -i timing1.py
+       %time a=make1(1000,0)
+       %time a=make1(1000,1)
+       %time a=make1(1000,2)
+       %time amake1(1000,3)
+       %timeit make1(1000,3)
+
+       %time d=delta1(a)
+       %time d=delta2(a)
+
+       %timeit d=delta1(a)
+       %timeit d=delta2(a)
+
+
+C example:
+       taken from NEMO http://carma.astro.umd.edu/nemo/
+       cd $NEMO/src/nbody/evolve/hackcode/hackcode1
+       make hackcode1 CC="gcc -pg"
+       hackcode1 nbody=1000
+       gprof hackcode1
+
+       # -> not so great, but this is the classic  profiler
+
+       # on mac, Xcode has a good profiler
+       
+       # intel compiler has a good profiler
+       
+       # linux has valgrid and kcachegrind
+       valgrind --tool=callgrind  hackcode1 nbody=1000
+       kcachegrind callgrind.out.16241
+
+       # note valgrind has lots of other useful option (finding memory leaks etc.)
+       # and also note the profiler doesn't need the -pg compile flag
+       make hackcode1_qp
+       valgrind --tool=callgrind  hackcode1_qp nbody=1000	
+       kcachegrind callgrind.out.16301
+
+       # note that the gravity routine now has twice as much CPU overhead.(25 -> 50%)
+
diff --git a/timing/timing1.py b/timing/timing1.py
new file mode 100644
index 0000000..0bedfe8
--- /dev/null
+++ b/timing/timing1.py
@@ -0,0 +1,45 @@
+#! /usr/bin/env python
+#
+#
+#  demo:   using "run -i timing1.py"
+
+import numpy as np
+
+
+def make1(n, mode=0):
+    if mode==0:
+        return np.zeros(n, dtype=np.float64)         # zeros
+    elif mode==1:   
+        return np.arange(float(n))                   # ordinals
+    elif mode==2:
+        return np.random.uniform(0.0,1.0,int(n))     # random, uniform
+    elif mode==3:
+        return np.random.normal(0.0,1.0,int(n))      # random, normal
+
+
+def make2(n, mode=0):
+    if mode==0:
+        a=[]
+        for i in range(n):
+            a.append(0)
+        return a
+    elif mode==1:
+        a=[]
+        for i in range(n):
+            a.append(i)
+        return a
+    elif mode==2:
+        return list(range(n))       # for python3 , otherwise this is a constant independant of n !!
+
+def delta1(a):
+    n = len(a)
+    d = np.zeros(n-1)
+    for i in range(1,n):
+        d[i-1] = a[i]-a[i-1]
+    return d
+
+
+def delta2(a):
+    return a[1:] - a[:-1]
+
+