fixed conflict

.travis.yml

@@ -10,7 +10,7 @@ env:
   - TEST=API
   - TEST=E2E LANG="c_lang or python or java or go_lang or javascript or php"
   - TEST=E2E LANG="c_sharp or visual_basic or powershell"
-  - TEST=E2E LANG="r_lang"
+  - TEST=E2E LANG="r_lang or dart"
 
 before_install:
   - bash .travis/setup.sh

.travis/setup.sh

@@ -29,3 +29,11 @@ if [[ $LANG == *"php"* ]]; then
   sudo apt-get update
   sudo apt-get install --no-install-recommends -y php
 fi
+
+# Install Dart. (https://dart.dev/get-dart)
+if [[ $LANG == *"dart"* ]]; then
+  sudo sh -c 'wget -qO- https://dl-ssl.google.com/linux/linux_signing_key.pub | apt-key add -'
+  sudo sh -c 'wget -qO- https://storage.googleapis.com/download.dartlang.org/linux/debian/dart_stable.list > /etc/apt/sources.list.d/dart_stable.list'
+  sudo apt-get update
+  sudo apt-get install --no-install-recommends -y dart
+fi

Dockerfile

@@ -7,6 +7,8 @@ RUN apt-get update && \
     add-apt-repository ppa:deadsnakes/ppa && \
     wget -q https://packages.microsoft.com/config/ubuntu/$(lsb_release -rs)/packages-microsoft-prod.deb -O packages-microsoft-prod.deb && \
     dpkg -i packages-microsoft-prod.deb && \
+    wget -qO- https://dl-ssl.google.com/linux/linux_signing_key.pub | apt-key add - && \
+    wget -qO- https://storage.googleapis.com/download.dartlang.org/linux/debian/dart_stable.list > /etc/apt/sources.list.d/dart_stable.list && \
     apt-get update && \
     apt-get install --no-install-recommends -y \
         gcc \
@@ -20,7 +22,8 @@ RUN apt-get update && \
         dotnet-sdk-3.0 \
         powershell \
         r-base \
-        php && \
+        php \
+        dart && \
     rm -rf /var/lib/apt/lists/*
 
 WORKDIR /m2cgen

MANIFEST.in

@@ -1,5 +1,5 @@
 include LICENSE
 recursive-include m2cgen VERSION.txt
 recursive-include m2cgen linear_algebra.*
-recursive-include m2cgen tanh.bas
+recursive-include m2cgen tanh.*
 global-exclude *.py[cod]

README.md

@@ -7,7 +7,7 @@
 [![PyPI Version](https://img.shields.io/pypi/v/m2cgen.svg?logo=pypi&logoColor=white)](https://pypi.org/project/m2cgen)
 [![Downloads](https://pepy.tech/badge/m2cgen)](https://pepy.tech/project/m2cgen)
 
-**m2cgen** (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP).
+**m2cgen** (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart).
 
 * [Installation](#installation)
 * [Supported Languages](#supported-languages)
@@ -28,6 +28,7 @@ pip install m2cgen
 
 - C
 - C#
+- Dart
 - Go
 - Java
 - JavaScript
@@ -41,7 +42,7 @@ pip install m2cgen
 
 |  | Classification | Regression |
 | --- | --- | --- |
-| **Linear** | <ul><li>scikit-learn<ul><li>LogisticRegression</li><li>LogisticRegressionCV</li><li>PassiveAggressiveClassifier</li><li>Perceptron</li><li>RidgeClassifier</li><li>RidgeClassifierCV</li><li>SGDClassifier</li></ul></li><li>lightning<ul><li>AdaGradClassifier</li><li>CDClassifier</li><li>FistaClassifier</li><li>SAGAClassifier</li><li>SAGClassifier</li><li>SDCAClassifier</li><li>SGDClassifier</li></ul></li></ul> | <ul><li>scikit-learn<ul><li>ARDRegression</li><li>BayesianRidge</li><li>ElasticNet</li><li>ElasticNetCV</li><li>HuberRegressor</li><li>Lars</li><li>LarsCV</li><li>Lasso</li><li>LassoCV</li><li>LassoLars</li><li>LassoLarsCV</li><li>LassoLarsIC</li><li>LinearRegression</li><li>OrthogonalMatchingPursuit</li><li>OrthogonalMatchingPursuitCV</li><li>PassiveAggressiveRegressor</li><li>RANSACRegressor(only supported regression estimators can be used as a base estimator)</li><li>Ridge</li><li>RidgeCV</li><li>SGDRegressor</li><li>TheilSenRegressor</li></ul><li>StatsModels<ul><li>Generalized Least Squares (GLS)</li><li>Ordinary Least Squares (OLS)</li><li>Weighted Least Squares (WLS)</li></ul><li>lightning<ul><li>AdaGradRegressor</li><li>CDRegressor</li><li>FistaRegressor</li><li>SAGARegressor</li><li>SAGRegressor</li><li>SDCARegressor</li></ul></li></ul> |
+| **Linear** | <ul><li>scikit-learn<ul><li>LogisticRegression</li><li>LogisticRegressionCV</li><li>PassiveAggressiveClassifier</li><li>Perceptron</li><li>RidgeClassifier</li><li>RidgeClassifierCV</li><li>SGDClassifier</li></ul></li><li>lightning<ul><li>AdaGradClassifier</li><li>CDClassifier</li><li>FistaClassifier</li><li>SAGAClassifier</li><li>SAGClassifier</li><li>SDCAClassifier</li><li>SGDClassifier</li></ul></li></ul> | <ul><li>scikit-learn<ul><li>ARDRegression</li><li>BayesianRidge</li><li>ElasticNet</li><li>ElasticNetCV</li><li>HuberRegressor</li><li>Lars</li><li>LarsCV</li><li>Lasso</li><li>LassoCV</li><li>LassoLars</li><li>LassoLarsCV</li><li>LassoLarsIC</li><li>LinearRegression</li><li>OrthogonalMatchingPursuit</li><li>OrthogonalMatchingPursuitCV</li><li>PassiveAggressiveRegressor</li><li>RANSACRegressor(only supported regression estimators can be used as a base estimator)</li><li>Ridge</li><li>RidgeCV</li><li>SGDRegressor</li><li>TheilSenRegressor</li></ul><li>StatsModels<ul><li>Generalized Least Squares (GLS)</li><li>Generalized Least Squares with AR Errors (GLSAR)</li><li>Ordinary Least Squares (OLS)</li><li>Weighted Least Squares (WLS)</li></ul><li>lightning<ul><li>AdaGradRegressor</li><li>CDRegressor</li><li>FistaRegressor</li><li>SAGARegressor</li><li>SAGRegressor</li><li>SDCARegressor</li></ul></li></ul> |
 | **SVM** | <ul><li>scikit-learn<ul><li>LinearSVC</li><li>NuSVC</li><li>SVC</li></ul></li><li>lightning<ul><li>LinearSVC</li></ul></li></ul> | <ul><li>scikit-learn<ul><li>LinearSVR</li><li>NuSVR</li><li>SVR</li></ul></li><li>lightning<ul><li>LinearSVR</li></ul></li></ul> |
 | **Tree** | <ul><li>DecisionTreeClassifier</li><li>ExtraTreeClassifier</li></ul> | <ul><li>DecisionTreeRegressor</li><li>ExtraTreeRegressor</li></ul> |
 | **Random Forest** | <ul><li>ExtraTreesClassifier</li><li>LGBMClassifier(rf booster only)</li><li>RandomForestClassifier</li><li>XGBRFClassifier(binary only, multiclass is not supported yet)</li></ul> | <ul><li>ExtraTreesRegressor</li><li>LGBMRegressor(rf booster only)</li><li>RandomForestRegressor</li><li>XGBRFRegressor</li></ul> |

generated_code_examples/php/classification/random_forest.php

@@ -1,12 +1,12 @@
 <?php
-function add_vectors(array $v1, array $v2) {
+function addVectors(array $v1, array $v2) {
     $result = array();
     for ($i = 0; $i < count($v1); ++$i) {
         $result[] = $v1[$i] + $v2[$i];
     }
     return $result;
 }
-function mul_vector_number(array $v1, $num) {
+function mulVectorNumber(array $v1, $num) {
     $result = array();
     for ($i = 0; $i < count($v1); ++$i) {
         $result[] = $v1[$i] * $num;
@@ -50,5 +50,5 @@ function score(array $input) {
             }
         }
     }
-    return add_vectors(mul_vector_number($var0, 0.5), mul_vector_number($var1, 0.5));
+    return addVectors(mulVectorNumber($var0, 0.5), mulVectorNumber($var1, 0.5));
 }

generated_code_examples/visual_basic/classification/decision_tree.vb

@@ -1,15 +1,15 @@
 Module Model
-Function score(ByRef input_vector() As Double) As Double()
+Function Score(ByRef inputVector() As Double) As Double()
     Dim var0() As Double
-    If (input_vector(2)) <= (2.6) Then
+    If (inputVector(2)) <= (2.6) Then
         Dim var1(2) As Double
         var1(0) = 1.0
         var1(1) = 0.0
         var1(2) = 0.0
         var0 = var1
     Else
-        If (input_vector(2)) <= (4.8500004) Then
-            If (input_vector(3)) <= (1.6500001) Then
+        If (inputVector(2)) <= (4.8500004) Then
+            If (inputVector(3)) <= (1.6500001) Then
                 Dim var2(2) As Double
                 var2(0) = 0.0
                 var2(1) = 1.0
@@ -23,7 +23,7 @@ Function score(ByRef input_vector() As Double) As Double()
                 var0 = var3
             End If
         Else
-            If (input_vector(3)) <= (1.75) Then
+            If (inputVector(3)) <= (1.75) Then
                 Dim var4(2) As Double
                 var4(0) = 0.0
                 var4(1) = 0.42857142857142855
@@ -38,6 +38,6 @@ Function score(ByRef input_vector() As Double) As Double()
             End If
         End If
     End If
-    score = var0
+    Score = var0
 End Function
 End Module

generated_code_examples/visual_basic/classification/lightgbm.vb

@@ -1,8 +1,8 @@
 Module Model
-Function score(ByRef input_vector() As Double) As Double()
+Function Score(ByRef inputVector() As Double) As Double()
     Dim var0 As Double
-    If (input_vector(2)) > (1.8) Then
-        If (input_vector(2)) > (4.250000000000001) Then
+    If (inputVector(2)) > (1.8) Then
+        If (inputVector(2)) > (4.250000000000001) Then
             var0 = -1.1736122903444903
         Else
             var0 = -1.1633850173886202
@@ -11,8 +11,8 @@ Function score(ByRef input_vector() As Double) As Double()
         var0 = -0.9486122853153485
     End If
     Dim var1 As Double
-    If (input_vector(2)) > (1.8) Then
-        If (input_vector(1)) > (3.0500000000000003) Then
+    If (inputVector(2)) > (1.8) Then
+        If (inputVector(1)) > (3.0500000000000003) Then
             var1 = -0.06193194743580539
         Else
             var1 = -0.07237070828653688
@@ -23,8 +23,8 @@ Function score(ByRef input_vector() As Double) As Double()
     Dim var2 As Double
     var2 = Math.Exp(((0) + (var0)) + (var1))
     Dim var3 As Double
-    If (input_vector(2)) > (1.8) Then
-        If (input_vector(2)) > (4.8500000000000005) Then
+    If (inputVector(2)) > (1.8) Then
+        If (inputVector(2)) > (4.8500000000000005) Then
             var3 = -1.1807342692411888
         Else
             var3 = -0.9831932134295853
@@ -33,8 +33,8 @@ Function score(ByRef input_vector() As Double) As Double()
         var3 = -1.1952609652674462
     End If
     Dim var4 As Double
-    If (input_vector(2)) > (1.8) Then
-        If (input_vector(2)) > (4.8500000000000005) Then
+    If (inputVector(2)) > (1.8) Then
+        If (inputVector(2)) > (4.8500000000000005) Then
             var4 = -0.05694282927518771
         Else
             var4 = 0.11960489254350348
@@ -45,28 +45,28 @@ Function score(ByRef input_vector() As Double) As Double()
     Dim var5 As Double
     var5 = Math.Exp(((0) + (var3)) + (var4))
     Dim var6 As Double
-    If (input_vector(2)) > (4.8500000000000005) Then
-        If (input_vector(3)) > (1.9500000000000002) Then
+    If (inputVector(2)) > (4.8500000000000005) Then
+        If (inputVector(3)) > (1.9500000000000002) Then
             var6 = -0.9298942558407184
         Else
             var6 = -0.9632815288936335
         End If
     Else
-        If (input_vector(2)) > (4.250000000000001) Then
+        If (inputVector(2)) > (4.250000000000001) Then
             var6 = -1.1322413652523249
         Else
             var6 = -1.1524760761934856
         End If
     End If
     Dim var7 As Double
-    If (input_vector(2)) > (4.8500000000000005) Then
-        If (input_vector(3)) > (1.9500000000000002) Then
+    If (inputVector(2)) > (4.8500000000000005) Then
+        If (inputVector(3)) > (1.9500000000000002) Then
             var7 = 0.12809276954555665
         Else
             var7 = 0.09898817876916756
         End If
     Else
-        If (input_vector(2)) > (4.250000000000001) Then
+        If (inputVector(2)) > (4.250000000000001) Then
             var7 = -0.052710589717642864
         Else
             var7 = -0.07292857712854424
@@ -80,6 +80,6 @@ Function score(ByRef input_vector() As Double) As Double()
     var10(0) = (var2) / (var9)
     var10(1) = (var5) / (var9)
     var10(2) = (var8) / (var9)
-    score = var10
+    Score = var10
 End Function
 End Module

generated_code_examples/visual_basic/classification/linear.vb

@@ -1,9 +1,9 @@
 Module Model
-Function score(ByRef input_vector() As Double) As Double()
+Function Score(ByRef inputVector() As Double) As Double()
     Dim var0(2) As Double
-    var0(0) = ((((0.2614587435880605) + ((input_vector(0)) * (0.42474116053569605))) + ((input_vector(1)) * (1.3963906033045026))) + ((input_vector(2)) * (-2.215054318516674))) + ((input_vector(3)) * (-0.9587396176450289))
-    var0(1) = ((((1.1348839223808307) + ((input_vector(0)) * (0.2567965976997648))) + ((input_vector(1)) * (-1.3904789369836008))) + ((input_vector(2)) * (0.596683023311173))) + ((input_vector(3)) * (-1.2690022726388828))
-    var0(2) = ((((-1.2162802012560197) + ((input_vector(0)) * (-1.6357766989177105))) + ((input_vector(1)) * (-1.5040638728422817))) + ((input_vector(2)) * (2.427835933129272))) + ((input_vector(3)) * (2.3469310693367276))
-    score = var0
+    var0(0) = ((((0.2614587435880605) + ((inputVector(0)) * (0.42474116053569605))) + ((inputVector(1)) * (1.3963906033045026))) + ((inputVector(2)) * (-2.215054318516674))) + ((inputVector(3)) * (-0.9587396176450289))
+    var0(1) = ((((1.1348839223808307) + ((inputVector(0)) * (0.2567965976997648))) + ((inputVector(1)) * (-1.3904789369836008))) + ((inputVector(2)) * (0.596683023311173))) + ((inputVector(3)) * (-1.2690022726388828))
+    var0(2) = ((((-1.2162802012560197) + ((inputVector(0)) * (-1.6357766989177105))) + ((inputVector(1)) * (-1.5040638728422817))) + ((inputVector(2)) * (2.427835933129272))) + ((inputVector(3)) * (2.3469310693367276))
+    Score = var0
 End Function
 End Module

generated_code_examples/visual_basic/classification/random_forest.vb

@@ -25,24 +25,24 @@ Function mulVectorNumber(ByRef v1() As Double, ByVal num As Double) As Double()
 
     mulVectorNumber = result
 End Function
-Function score(ByRef input_vector() As Double) As Double()
+Function Score(ByRef inputVector() As Double) As Double()
     Dim var0() As Double
-    If (input_vector(3)) <= (0.8) Then
+    If (inputVector(3)) <= (0.8) Then
         Dim var1(2) As Double
         var1(0) = 1.0
         var1(1) = 0.0
         var1(2) = 0.0
         var0 = var1
     Else
-        If (input_vector(2)) <= (4.8500004) Then
+        If (inputVector(2)) <= (4.8500004) Then
             Dim var2(2) As Double
             var2(0) = 0.0
             var2(1) = 0.9795918367346939
             var2(2) = 0.02040816326530612
             var0 = var2
         Else
-            If (input_vector(3)) <= (1.75) Then
-                If (input_vector(3)) <= (1.6500001) Then
+            If (inputVector(3)) <= (1.75) Then
+                If (inputVector(3)) <= (1.6500001) Then
                     Dim var3(2) As Double
                     var3(0) = 0.0
                     var3(1) = 0.25
@@ -65,15 +65,15 @@ Function score(ByRef input_vector() As Double) As Double()
         End If
     End If
     Dim var6() As Double
-    If (input_vector(3)) <= (0.8) Then
+    If (inputVector(3)) <= (0.8) Then
         Dim var7(2) As Double
         var7(0) = 1.0
         var7(1) = 0.0
         var7(2) = 0.0
         var6 = var7
     Else
-        If (input_vector(0)) <= (6.05) Then
-            If (input_vector(2)) <= (4.9) Then
+        If (inputVector(0)) <= (6.05) Then
+            If (inputVector(2)) <= (4.9) Then
                 Dim var8(2) As Double
                 var8(0) = 0.0
                 var8(1) = 0.9032258064516129
@@ -87,7 +87,7 @@ Function score(ByRef input_vector() As Double) As Double()
                 var6 = var9
             End If
         Else
-            If (input_vector(3)) <= (1.75) Then
+            If (inputVector(3)) <= (1.75) Then
                 Dim var10(2) As Double
                 var10(0) = 0.0
                 var10(1) = 0.8
@@ -102,6 +102,6 @@ Function score(ByRef input_vector() As Double) As Double()
             End If
         End If
     End If
-    score = addVectors(mulVectorNumber(var0, 0.5), mulVectorNumber(var6, 0.5))
+    Score = addVectors(mulVectorNumber(var0, 0.5), mulVectorNumber(var6, 0.5))
 End Function
 End Module