Merge remote-tracking branch 'origin/master'

Author: jlwalke2

examples/Fleet_Management_DecisionTree.ipynb

@@ -0,0 +1,263 @@
+import math
+import pickle
+import pandas as pd
+import numpy as np
+import settings
+
+def scoreFleetDecisionTree(Speed_sensor, Vibration, Engine_Load, Coolant_Temp, Intake_Pressure, Engine_RPM, Speed_OBD, Intake_Air, Flow_Rate, Throttle_Pos, Voltage, Ambient, Accel, Engine_Oil_Temp, Speed_GPS, GPS_Longitude, GPS_Latitude, GPS_Bearing, GPS_Altitude, Turbo_Boost, Trip_Distance, Litres_Per_km, Accel_Ssor_Total, CO2, Trip_Time, CO_emission, HC_emission, PM_emission, NOx_emission, CO2_emission, Fuel_level, Oil_life, Vibration_alert, VibrationAlert_Total, Vibration_Recent, Turbo_alert, Emission_alert, Fog_control, Engine_control):
+    "Output: EM_EVENTPROBABILITY, EM_CLASSIFICATION"
+
+    try:
+        _thisModelFit
+    except NameError:
+        with open(settings.pickle_path + 'FleetDecisionTree.pickle', 'rb') as _pFile:
+            _thisModelFit = pickle.load(_pFile)
+
+    try:
+        if math.isnan(Speed_sensor):
+            Speed_sensor = 75.06777416636571
+    except TypeError:
+        Speed_sensor = 75.06777416636571
+
+    try:
+        if math.isnan(Vibration):
+            Vibration = 246.95994479089921
+    except TypeError:
+        Vibration = 246.95994479089921
+
+    try:
+        if math.isnan(Engine_Load):
+            Engine_Load = 36.06875427988444
+    except TypeError:
+        Engine_Load = 36.06875427988444
+
+    try:
+        if math.isnan(Coolant_Temp):
+            Coolant_Temp = 87.7360057782593
+    except TypeError:
+        Coolant_Temp = 87.7360057782593
+
+    try:
+        if math.isnan(Intake_Pressure):
+            Intake_Pressure = 119.41133983387505
+    except TypeError:
+        Intake_Pressure = 119.41133983387505
+
+    try:
+        if math.isnan(Engine_RPM):
+            Engine_RPM = 1263.593956903816
+    except TypeError:
+        Engine_RPM = 1263.593956903816
+
+    try:
+        if math.isnan(Speed_OBD):
+            Speed_OBD = 75.06777416636571
+    except TypeError:
+        Speed_OBD = 75.06777416636571
+
+    try:
+        if math.isnan(Intake_Air):
+            Intake_Air = 10.664138678223186
+    except TypeError:
+        Intake_Air = 10.664138678223186
+
+    try:
+        if math.isnan(Flow_Rate):
+            Flow_Rate = 23.769685807150594
+    except TypeError:
+        Flow_Rate = 23.769685807150594
+
+    try:
+        if math.isnan(Throttle_Pos):
+            Throttle_Pos = 75.25847583170821
+    except TypeError:
+        Throttle_Pos = 75.25847583170821
+
+    try:
+        if math.isnan(Voltage):
+            Voltage = 14.171672083784758
+    except TypeError:
+        Voltage = 14.171672083784758
+
+    try:
+        if math.isnan(Ambient):
+            Ambient = 7.309738774527507
+    except TypeError:
+        Ambient = 7.309738774527507
+
+    try:
+        if math.isnan(Accel):
+            Accel = 22.004593668231607
+    except TypeError:
+        Accel = 22.004593668231607
+
+    try:
+        if math.isnan(Engine_Oil_Temp):
+            Engine_Oil_Temp = 84.52690501986277
+    except TypeError:
+        Engine_Oil_Temp = 84.52690501986277
+
+    try:
+        if math.isnan(Speed_GPS):
+            Speed_GPS = 77.28586848607259
+    except TypeError:
+        Speed_GPS = 77.28586848607259
+
+    try:
+        if math.isnan(GPS_Longitude):
+            GPS_Longitude = 8.569920139091247
+    except TypeError:
+        GPS_Longitude = 8.569920139091247
+
+    try:
+        if math.isnan(GPS_Latitude):
+            GPS_Latitude = 48.54705087261828
+    except TypeError:
+        GPS_Latitude = 48.54705087261828
+
+    try:
+        if math.isnan(GPS_Bearing):
+            GPS_Bearing = 195.5093294811605
+    except TypeError:
+        GPS_Bearing = 195.5093294811605
+
+    try:
+        if math.isnan(GPS_Altitude):
+            GPS_Altitude = 326.22607439508846
+    except TypeError:
+        GPS_Altitude = 326.22607439508846
+
+    try:
+        if math.isnan(Turbo_Boost):
+            Turbo_Boost = 3.2505074667148186
+    except TypeError:
+        Turbo_Boost = 3.2505074667148186
+
+    try:
+        if math.isnan(Trip_Distance):
+            Trip_Distance = 230.49551875887803
+    except TypeError:
+        Trip_Distance = 230.49551875887803
+
+    try:
+        if math.isnan(Litres_Per_km):
+            Litres_Per_km = 4.316090813719474
+    except TypeError:
+        Litres_Per_km = 4.316090813719474
+
+    try:
+        if math.isnan(Accel_Ssor_Total):
+            Accel_Ssor_Total = -0.0031587095220898037
+    except TypeError:
+        Accel_Ssor_Total = -0.0031587095220898037
+
+    try:
+        if math.isnan(CO2):
+            CO2 = 93.42142250399041
+    except TypeError:
+        CO2 = 93.42142250399041
+
+    try:
+        if math.isnan(Trip_Time):
+            Trip_Time = 7512.937041049717
+    except TypeError:
+        Trip_Time = 7512.937041049717
+
+    try:
+        if math.isnan(CO_emission):
+            CO_emission = 0.0
+    except TypeError:
+        CO_emission = 0.0
+
+    try:
+        if math.isnan(HC_emission):
+            HC_emission = 0.0
+    except TypeError:
+        HC_emission = 0.0
+
+    try:
+        if math.isnan(PM_emission):
+            PM_emission = 0.0
+    except TypeError:
+        PM_emission = 0.0
+
+    try:
+        if math.isnan(NOx_emission):
+            NOx_emission = 0.0
+    except TypeError:
+        NOx_emission = 0.0
+
+    try:
+        if math.isnan(CO2_emission):
+            CO2_emission = 0.0
+    except TypeError:
+        CO2_emission = 0.0
+
+    try:
+        if math.isnan(Fuel_level):
+            Fuel_level = 0.0
+    except TypeError:
+        Fuel_level = 0.0
+
+    try:
+        if math.isnan(Oil_life):
+            Oil_life = 0.0
+    except TypeError:
+        Oil_life = 0.0
+
+    try:
+        if math.isnan(Vibration_alert):
+            Vibration_alert = 1.0
+    except TypeError:
+        Vibration_alert = 1.0
+
+    try:
+        if math.isnan(VibrationAlert_Total):
+            VibrationAlert_Total = 123.0
+    except TypeError:
+        VibrationAlert_Total = 123.0
+
+    try:
+        if math.isnan(Vibration_Recent):
+            Vibration_Recent = 12.0
+    except TypeError:
+        Vibration_Recent = 12.0
+
+    try:
+        if math.isnan(Turbo_alert):
+            Turbo_alert = 1.0
+    except TypeError:
+        Turbo_alert = 1.0
+
+    try:
+        if math.isnan(Emission_alert):
+            Emission_alert = 1.0
+    except TypeError:
+        Emission_alert = 1.0
+
+    try:
+        if math.isnan(Fog_control):
+            Fog_control = 1.0
+    except TypeError:
+        Fog_control = 1.0
+
+    try:
+        if math.isnan(Engine_control):
+            Engine_control = 1.0
+    except TypeError:
+        Engine_control = 1.0
+
+    inputArray = pd.DataFrame([[1.0, Speed_sensor, Vibration, Engine_Load, Coolant_Temp, Intake_Pressure, Engine_RPM, Speed_OBD, Intake_Air, Flow_Rate, Throttle_Pos, Voltage, Ambient, Accel, Engine_Oil_Temp, Speed_GPS, GPS_Longitude, GPS_Latitude, GPS_Bearing, GPS_Altitude, Turbo_Boost, Trip_Distance, Litres_Per_km, Accel_Ssor_Total, CO2, Trip_Time, CO_emission, HC_emission, PM_emission, NOx_emission, CO2_emission, Fuel_level, Oil_life, Vibration_alert, VibrationAlert_Total, Vibration_Recent, Turbo_alert, Emission_alert, Fog_control, Engine_control]],
+                              columns = ['const', 'Speed_sensor', 'Vibration', 'Engine_Load', 'Coolant_Temp', 'Intake_Pressure', 'Engine_RPM', 'Speed_OBD', 'Intake_Air', 'Flow_Rate', 'Throttle_Pos', 'Voltage', 'Ambient', 'Accel', 'Engine_Oil_Temp', 'Speed_GPS', 'GPS_Longitude', 'GPS_Latitude', 'GPS_Bearing', 'GPS_Altitude', 'Turbo_Boost', 'Trip_Distance', 'Litres_Per_km', 'Accel_Ssor_Total', 'CO2', 'Trip_Time', 'CO_emission', 'HC_emission', 'PM_emission', 'NOx_emission', 'CO2_emission', 'Fuel_level', 'Oil_life', 'Vibration_alert', 'VibrationAlert_Total', 'Vibration_Recent', 'Turbo_alert', 'Emission_alert', 'Fog_control', 'Engine_control'],
+                              dtype = float)
+
+    prediction = _thisModelFit.predict(inputArray)
+
+    EM_EVENTPROBABILITY = float(prediction)
+
+    if (EM_EVENTPROBABILITY >= 0.2269170579029734):
+        EM_CLASSIFICATION = '1'
+    else:
+        EM_CLASSIFICATION = '0' 
+
+    return(EM_EVENTPROBABILITY, EM_CLASSIFICATION)

examples/data/FleetMaintenanceModels/Sklearn_DecisionTree/FleetDecisionTree.pickle

@@ -0,0 +1,16 @@
+{
+    "name": "Truck Fleet",
+    "description": " : Maintenance_flag = Speed_sensor + Vibration + Engine_Load + Coolant_Temp + Intake_Pressure + Engine_RPM + Speed_OBD + Intake_Air + Flow_Rate + Throttle_Pos + Voltage + Ambient + Accel + Engine_Oil_Temp + Speed_GPS + GPS_Longitude + GPS_Latitude + GPS_Bearing + GPS_Altitude + Turbo_Boost + Trip_Distance + Litres_Per_km + Accel_Ssor_Total + CO2 + Trip_Time + CO_emission + HC_emission + PM_emission + NOx_emission + CO2_emission + Fuel_level + Oil_life + Vibration_alert + VibrationAlert_Total + Vibration_Recent + Turbo_alert + Emission_alert + Fog_control + Engine_control",
+    "function": "classification",
+    "scoreCodeType": "python",
+    "trainTable": " ",
+    "trainCodeType": "Python",
+    "algorithm": "Classification Decision Tree",
+    "targetVariable": "Maintenance_flag",
+    "targetEvent": 1,
+    "targetLevel": "BINARY",
+    "eventProbVar": "EM_EVENTPROBABILITY",
+    "modeler": "sasdemo",
+    "tool": "Python 3",
+    "toolVersion": "3.8.3"
+}