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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,62 @@ | ||
| // Include Statistal Library | ||
| #include <Statistical.h> | ||
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| // Set Data | ||
| float Data[5]; | ||
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| // Construct Object | ||
| Array_Stats<float> Data_Array(Data, sizeof(Data) / sizeof(Data[0])); | ||
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| void setup() { | ||
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| // Start Serial | ||
| Serial.begin(115200); | ||
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| // Set Data | ||
| Serial.println(F("Learning Data...")); | ||
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| // Set FILO | ||
| Data_Array.Set_FILO_Size(4); | ||
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| // Add Data to FILO Array | ||
| Data_Array.FILO_Add_Data(220.12); | ||
| Data_Array.FILO_Add_Data(214.35); | ||
| Data_Array.FILO_Add_Data(200.14); | ||
| Data_Array.FILO_Add_Data(212.80); | ||
| Data_Array.FILO_Add_Data(242.33); | ||
| Data_Array.FILO_Add_Data(215.99); | ||
| Data_Array.FILO_Add_Data(220.12); | ||
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| // Print Stats | ||
| Serial.println(F("------------------------------------------------")); | ||
| Serial.print(F("Array Size : ")); Serial.println(Data_Array.Size()); | ||
| Serial.println(F("------------------------------------------------")); | ||
| Serial.print(F("Data Array : ")); Data_Array.Array(); | ||
| Serial.print(F("Array Sum : ")); Serial.println(Data_Array.Sum()); | ||
| Serial.print(F("Array Min : ")); Serial.println(Data_Array.Min()); | ||
| Serial.print(F("Array Max : ")); Serial.println(Data_Array.Max()); | ||
| Serial.print(F("Array Square Sum : ")); Serial.println(Data_Array.Sq_Sum()); | ||
| Serial.print(F("Array Arithmetic Average : ")); Serial.println(Data_Array.Average(Data_Array.Arithmetic_Avg)); | ||
| Serial.print(F("Array Geometric Average : ")); Serial.println(Data_Array.Average(Data_Array.Geometric_Avg)); | ||
| Serial.print(F("Array RMS Average : ")); Serial.println(Data_Array.Average(Data_Array.RMS_Avg)); | ||
| Serial.print(F("Array Extended RMS Average : ")); Serial.println(Data_Array.Average(Data_Array.Ext_RMS_Avg)); | ||
| Serial.print(F("Array Q1 : ")); Serial.println(Data_Array.Quartile(1)); | ||
| Serial.print(F("Array Q2 (Median) : ")); Serial.println(Data_Array.Quartile(2)); | ||
| Serial.print(F("Array Q3 : ")); Serial.println(Data_Array.Quartile(3)); | ||
| Serial.print(F("Array IQR : ")); Serial.println(Data_Array.IQR()); | ||
| Serial.print(F("Array Standard Deviation : ")); Serial.println(Data_Array.Standard_Deviation()); | ||
| Serial.print(F("Array Standard Deviation Error : ")); Serial.println(Data_Array.Standard_Deviation_Error()); | ||
| Serial.print(F("Array Coefficient Factor : ")); Serial.println(Data_Array.Coefficient_Factor()); | ||
| Serial.print(F("Array Variance : ")); Serial.println(Data_Array.Variance()); | ||
| Serial.println(F("------------------------------------------------")); | ||
| Serial.print(F("Sorted Data Array : ")); Data_Array.Array(); | ||
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| } | ||
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| void loop() { | ||
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| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,53 +1,48 @@ | ||
| #include <Statistical.h> | ||
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| Statistical DataSet; | ||
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| void setup() { | ||
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| // Start Serial | ||
| Serial.begin(115200); | ||
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| // Set Data | ||
| Serial.println("Learning Data..."); | ||
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| } | ||
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| void loop() { | ||
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| // Set Data | ||
| Serial.println("Learning Data..."); | ||
| uint8_t Data_X[] = {1, 2, 3, 4, 5, 6, 7}; | ||
| float Data_Y[] = {2, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7}; | ||
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| // Declare Object | ||
| Linear_Regression<uint8_t, float> Regression(Data_X, Data_Y, sizeof(Data_X) / sizeof(Data_X[0])); | ||
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| // Print Array X | ||
| Serial.print("Data X Array : "); | ||
| for (size_t i = 0; i < sizeof(Data_X) / sizeof(Data_X[0]); i++) {Serial.print(F("[")); Serial.print(Data_X[i]); Serial.print(F("] "));} | ||
| Serial.println(""); | ||
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| // Print Array X | ||
| Serial.print("Data Y Array : "); | ||
| for (size_t i = 0; i < sizeof(Data_X) / sizeof(Data_X[0]); i++) {Serial.print(F("[")); Serial.print(Data_Y[i]); Serial.print(F("] "));} | ||
| Serial.println(""); | ||
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| // Print Regression Slope | ||
| Serial.print("Slope : "); Serial.println(Regression.Slope(),5); | ||
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| // Print Regression Offset | ||
| Serial.print("Offset : "); Serial.println(Regression.Offset(),5); | ||
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| // Print Regression R2 | ||
| Serial.print("R2 : "); Serial.println(Regression.R2(),5); | ||
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| // Print Divider | ||
| Serial.println("--------------------------"); | ||
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| // Set Precision | ||
| uint8_t Linear_Regression_Precision = 5; | ||
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| // Set Array | ||
| float Data[Linear_Regression_Precision][2]; | ||
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| // Learn Data | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 1, 220.14); | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 2, 221.36); | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 3, 218.21); | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 4, 217.06); | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 5, 220.14); | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 6, 222.14); | ||
| DataSet.Array_FILO(Data, Linear_Regression_Precision, 7, 225.14); | ||
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| // Print FILO Array | ||
| Serial.print("Regression Data Array : "); | ||
| for (uint8_t i = 0; i < Linear_Regression_Precision; i++) { | ||
| Serial.print("["); | ||
| Serial.print(Data[i][0]); | ||
| Serial.print(","); | ||
| Serial.print(Data[i][1]); | ||
| Serial.print("] "); | ||
| } | ||
| Serial.println(""); | ||
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| // Print Calculated Data | ||
| Serial.print("Regression Data Count : "); Serial.println(Linear_Regression_Precision); | ||
| Serial.print("Regression Slope : "); Serial.println(DataSet.Linear_Regression_Slope(Data, Linear_Regression_Precision), 4); | ||
| Serial.print("Regression Offset : "); Serial.println(DataSet.Linear_Regression_Offset(Data, Linear_Regression_Precision), 4); | ||
| Serial.print("Regression R2 : "); Serial.println(DataSet.Linear_Regression_R2(Data, Linear_Regression_Precision), 4); | ||
| Serial.println("------------------------"); | ||
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| delay(10000); | ||
| // Delay | ||
| delay(1000); | ||
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| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,5 +1,5 @@ | ||
| name=Statistical | ||
| version=1.4.15 | ||
| version=2.0.2 | ||
| author=Gunce Akkoyun <[email protected]> | ||
| maintainer=Gunce Akkoyun <[email protected]> | ||
| sentence=Statistic, Sum, Max, Min, Sq_Sum, Arithmetic Average, Geometric Average, RMS Average, Ext RMS Average, Bubble Sort, Median, Standard Deviation, Standard Deviation Error, Coefficient Factor, Average, Stream, Regression, Slope, Data, Analyse | ||
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