analysis.py v 1.1.12.006

analysis pkg v 1.0.0.003

analysis-master/analysis.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: analysis
-Version: 1.0.0.2
+Version: 1.0.0.3
 Summary: analysis package developed by Titan Scouting for The Red Alliance
 Home-page: https://github.com/titanscout2022/tr2022-strategy
 Author: The Titan Scouting Team

analysis-master/analysis/analysis.py

@@ -7,10 +7,12 @@
 #    current benchmark of optimization: 1.33 times faster
 # setup:
 
-__version__ = "1.1.12.005"
+__version__ = "1.1.12.006"
 
 # changelog should be viewed using print(analysis.__changelog__)
 __changelog__ = """changelog:
+    1.1.12.006:
+        - fixed bg with a division by zero in histo_analysis
     1.1.12.005:
         - fixed numba issues by removing numba  from elo, glicko2 and trueskill
     1.1.12.004:
@@ -323,6 +325,8 @@ def z_normalize(array, *args):
 # expects 2d array of [x,y]
 def histo_analysis(hist_data):
 
+    if(len(hist_data[0]) > 2):
+
         hist_data = np.array(hist_data)
         derivative = np.array(len(hist_data) - 1, dtype = float)
         t = np.diff(hist_data)
@@ -331,6 +335,10 @@ def histo_analysis(hist_data):
 
         return basic_stats(derivative)[0], basic_stats(derivative)[3]
 
+    else:
+
+        return None
+
 def regression(ndevice, inputs, outputs, args, loss = torch.nn.MSELoss(), _iterations = 10000, lr = 0.01, _iterations_ply = 10000, lr_ply = 0.01): # inputs, outputs expects N-D array 
 
     regressions = []

analysis-master/build/lib/analysis/analysis.py

@@ -7,10 +7,12 @@
 #    current benchmark of optimization: 1.33 times faster
 # setup:
 
-__version__ = "1.1.12.005"
+__version__ = "1.1.12.006"
 
 # changelog should be viewed using print(analysis.__changelog__)
 __changelog__ = """changelog:
+    1.1.12.006:
+        - fixed bg with a division by zero in histo_analysis
     1.1.12.005:
         - fixed numba issues by removing numba  from elo, glicko2 and trueskill
     1.1.12.004:
@@ -323,6 +325,8 @@ def z_normalize(array, *args):
 # expects 2d array of [x,y]
 def histo_analysis(hist_data):
 
+    if(len(hist_data[0]) > 2):
+
         hist_data = np.array(hist_data)
         derivative = np.array(len(hist_data) - 1, dtype = float)
         t = np.diff(hist_data)
@@ -331,6 +335,10 @@ def histo_analysis(hist_data):
 
         return basic_stats(derivative)[0], basic_stats(derivative)[3]
 
+    else:
+
+        return None
+
 def regression(ndevice, inputs, outputs, args, loss = torch.nn.MSELoss(), _iterations = 10000, lr = 0.01, _iterations_ply = 10000, lr_ply = 0.01): # inputs, outputs expects N-D array 
 
     regressions = []

analysis-master/setup.py

@@ -2,7 +2,7 @@ import setuptools
 
 setuptools.setup(
     name="analysis", # Replace with your own username
-    version="1.0.0.002",
+    version="1.0.0.003",
     author="The Titan Scouting Team",
     author_email="titanscout2022@gmail.com",
     description="analysis package developed by Titan Scouting for The Red Alliance",