Sensor sample_time affects reported CHO and Insulin

[PrangerStefan]

First of all, thanks a lot for the implementation of this simulation!

While inspecting and playing around with the implementation I have found that the sensors sample_time affects the reported CHO and Insulin.

Using the second scenario defined in advanced_scenario.py and comparing the Dexcom (sample_size = 3.0) and GuardianRT (sample_size = 5.0), I come to the following with the Dexcom sensor:

        mini_step: BG:  49.677, measured CGM:   48.167, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.004644444444444445
        mini_step: BG:  99.354, measured CGM:   96.334, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.00928888888888889
        mini_step: BG:  149.032, measured CGM:  144.882, carbo (CHO):   0.000 (tmp_CHO:0.000), insulin: 0.013933333333333336
BG:     149.032, measured CGM:  144.882, carbo (CHO):   0.000, insulin: 0.013933333333333336
        mini_step: BG:  49.677, measured CGM:   48.548, carbo (CHO):    15.000 (tmp_CHO:45.000), insulin:       0.004644444444444445
        mini_step: BG:  99.354, measured CGM:   97.096, carbo (CHO):    15.000 (tmp_CHO:0.000), insulin:        0.00928888888888889
        mini_step: BG:  149.032, measured CGM:  146.033, carbo (CHO):   15.000 (tmp_CHO:0.000), insulin:        0.013933333333333336
BG:     149.032, measured CGM:  146.033, carbo (CHO):   15.000, insulin:        0.013933333333333336
        mini_step: BG:  49.677, measured CGM:   48.937, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.42131111111111114
        mini_step: BG:  99.355, measured CGM:   97.874, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.8426222222222223
        mini_step: BG:  149.033, measured CGM:  147.163, carbo (CHO):   0.000 (tmp_CHO:0.000), insulin: 1.2639333333333334
BG:     149.033, measured CGM:  147.163, carbo (CHO):   0.000, insulin: 1.2639333333333334

Note, that these are three steps around 7am, when according to the scenario 45 units of CHO are to be consumed.

The same simulation using GuardianRT:

        mini_step: BG:  29.806, measured CGM:   29.051, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.002786666666666667
        mini_step: BG:  59.613, measured CGM:   58.101, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.005573333333333334
        mini_step: BG:  89.419, measured CGM:   87.152, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.008360000000000001
        mini_step: BG:  119.225, measured CGM:  116.202, carbo (CHO):   0.000 (tmp_CHO:0.000), insulin: 0.011146666666666668
        mini_step: BG:  149.032, measured CGM:  145.639, carbo (CHO):   0.000 (tmp_CHO:0.000), insulin: 0.013933333333333334
BG:     149.032, measured CGM:  145.639, carbo (CHO):   0.000, insulin: 0.013933333333333334
        mini_step: BG:  29.806, measured CGM:   29.436, carbo (CHO):    9.000 (tmp_CHO:45.000), insulin:        0.002786666666666667
        mini_step: BG:  59.613, measured CGM:   58.872, carbo (CHO):    9.000 (tmp_CHO:0.000), insulin: 0.005573333333333334
        mini_step: BG:  89.419, measured CGM:   88.309, carbo (CHO):    9.000 (tmp_CHO:0.000), insulin: 0.008360000000000001
        mini_step: BG:  119.225, measured CGM:  117.745, carbo (CHO):   9.000 (tmp_CHO:0.000), insulin: 0.011146666666666668
        mini_step: BG:  149.032, measured CGM:  147.478, carbo (CHO):   9.000 (tmp_CHO:0.000), insulin: 0.013933333333333334
BG:     149.032, measured CGM:  147.478, carbo (CHO):   9.000, insulin: 0.013933333333333334
        mini_step: BG:  29.807, measured CGM:   29.733, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.15278666666666668
        mini_step: BG:  59.614, measured CGM:   59.467, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.30557333333333336
        mini_step: BG:  89.422, measured CGM:   89.200, carbo (CHO):    0.000 (tmp_CHO:0.000), insulin: 0.45836000000000005
        mini_step: BG:  119.231, measured CGM:  118.933, carbo (CHO):   0.000 (tmp_CHO:0.000), insulin: 0.6111466666666667
        mini_step: BG:  149.043, measured CGM:  148.751, carbo (CHO):   0.000 (tmp_CHO:0.000), insulin: 0.7639333333333334
BG:     149.043, measured CGM:  148.751, carbo (CHO):   0.000, insulin: 0.7639333333333334

The comparison between these two sensors shows the difference in reported CHO and insulin:

It seems that this is only a cosmetic error (I am guessing this by comparing the trajectories of BG). I am happy to provide a PR...

The logs from above have been created with with:

diff --git i/examples/advanced_tutorial.py w/examples/advanced_tutorial.py
index 1249c88..f194ad9 100644
--- i/examples/advanced_tutorial.py
+++ w/examples/advanced_tutorial.py
@@ -29,8 +29,8 @@ controller = BBController()
 
 # Put them together to create a simulation object
 s1 = SimObj(env, controller, timedelta(days=1), animate=False, path=path)
-results1 = sim(s1)
-print(results1)
+#results1 = sim(s1)
+#print(results1)
 
 # --------- Create Custom Scenario --------------
 # Create a simulation environment
@@ -46,7 +46,7 @@ env = T1DSimEnv(patient, sensor, pump, scenario)
 controller = BBController()
 
 # Put them together to create a simulation object
-s2 = SimObj(env, controller, timedelta(days=1), animate=False, path=path)
+s2 = SimObj(env, controller, timedelta(days=1), animate=True, path=path)
 results2 = sim(s2)
 print(results2)
 
diff --git i/simglucose/simulation/env.py w/simglucose/simulation/env.py
index 45a43cb..c96a6b1 100644
--- i/simglucose/simulation/env.py
+++ w/simglucose/simulation/env.py
@@ -79,6 +79,8 @@ class T1DSimEnv(object):
             insulin += tmp_insulin / self.sample_time
             BG += tmp_BG / self.sample_time
             CGM += tmp_CGM / self.sample_time
+            print(f"\tmini_step: BG:\t{BG:4.3f}, measured CGM:\t{CGM:3.3f}, carbo (CHO):\t{CHO:3.3f} (tmp_CHO:{tmp_CHO:3.3f}), insulin:\t{insulin}")
+        print(f"BG:\t{BG:4.3f}, measured CGM:\t{CGM:3.3f}, carbo (CHO):\t{CHO:3.3f}, insulin:\t{insulin}")
 
         # Compute risk index
         horizon = 1