Much more scripting

Author: Matthew Daws

examples/Monte Carlo Integration.ipynb

@@ -11,8 +11,8 @@
 import open_cp.sources.chicago
 import lzma
 
-datadir = os.path.join("..", "..", "..", "..", "..", "Data")
-#datadir = os.path.join("/media", "disk", "Data")
+#datadir = os.path.join("..", "..", "..", "..", "..", "Data")
+datadir = os.path.join("/media", "disk", "Data")
 
 def load_points():
     """Load Chicago data for 2016"""

examples/Scripts/KDE.ipynb

@@ -0,0 +1,18 @@
+from common import *
+
+import datetime, itertools
+import open_cp.kde
+
+with scripted.Data(load_points, load_geometry,
+        start=datetime.datetime(2016,1,1)) as state:
+    
+    time_range = scripted.TimeRange(datetime.datetime(2016,10,1),
+            datetime.datetime(2017,1,1), datetime.timedelta(days=1))
+
+    for bw in [30, 40, 50, 60, 70, 100]:
+        tk = open_cp.kde.ExponentialTimeKernel(10)
+        sk = open_cp.kde.GaussianFixedBandwidthProvider(bw)
+        state.add_prediction(scripted.KDEProvider(tk, sk), time_range)
+
+    state.score(scripted.HitCountEvaluator)
+    state.process(scripted.HitCountSave("kde_opt.csv"))

examples/Scripts/ProHotspot.ipynb

@@ -19,7 +19,7 @@
 import lzma
 
 datadir = os.path.join("..", "..", "..", "..", "..", "Data")
-#datadir = os.path.join("/media", "disk", "Data")
+datadir = os.path.join("/media", "disk", "Data")
 
 def load_points():
     """Load Chicago data for 2016"""

examples/Scripts/Reload naive predictions.ipynb

@@ -0,0 +1,17 @@
+from common import *
+
+import datetime, itertools
+import open_cp.prohotspot
+
+with scripted.Data(load_points, load_geometry,
+        start=datetime.datetime(2016,1,1)) as state:
+    
+    time_range = scripted.TimeRange(datetime.datetime(2016,10,1),
+            datetime.datetime(2017,1,1), datetime.timedelta(days=1))
+    for tb, sb in itertools.product([6,7,8,9], [2,3,4]):
+        weight = open_cp.prohotspot.ClassicWeight(time_bandwidth=tb, space_bandwidth=sb)
+        distance = open_cp.prohotspot.DistanceCircle()
+        state.add_prediction(scripted.ProHotspotProvider(weight, distance), time_range)
+
+    state.score(scripted.HitCountEvaluator)
+    state.process(scripted.HitCountSave("pro_grid_opt.csv"))

examples/Scripts/Retro Hotspot.ipynb

@@ -0,0 +1,16 @@
+from common import *
+
+import datetime, itertools
+import open_cp.prohotspot
+
+with scripted.Data(load_points, load_geometry,
+        start=datetime.datetime(2016,1,1)) as state:
+    
+    time_range = scripted.TimeRange(datetime.datetime(2016,10,1),
+            datetime.datetime(2017,1,1), datetime.timedelta(days=1))
+    for tb, sb in itertools.product([6,7,8,9], [2,3,4]):
+        weight = open_cp.prohotspot.ClassicWeight(time_bandwidth=tb, space_bandwidth=sb)
+        state.add_prediction(scripted.ProHotspotCtsProvider(weight, 150), time_range)
+
+    state.score(scripted.HitCountEvaluator)
+    state.process(scripted.HitCountSave("pro_opt.csv"))