More strict analyser options added (#171)

Author: gyrdym

CHANGELOG.md

@@ -1,5 +1,8 @@
 # Changelog
 
+## 15.6.2
+- More strict analyser options added
+
 ## 15.6.1
 - README.md: example for flutter developers added
 

analysis_options.yaml

@@ -1 +1,10 @@
 include: package:pedantic/analysis_options.yaml
+
+analyzer:
+  strong-mode:
+    implicit-casts: false
+    implicit-dynamic: true
+  errors:
+    missing_return: error
+    dead_code: error
+    duplicate_import: error

lib/src/classifier/logistic_regressor/logistic_regressor_impl.dart

@@ -255,13 +255,13 @@ class LogisticRegressorImpl
       iterationsLimit: iterationsLimit,
       initialLearningRate: initialLearningRate,
       minCoefficientsUpdate: minCoefficientsUpdate,
-      probabilityThreshold: probabilityThreshold,
+      probabilityThreshold: probabilityThreshold?.toDouble(),
       lambda: lambda,
       regularizationType: regularizationType,
       randomSeed: randomSeed,
       batchSize: batchSize,
       fitIntercept: fitIntercept,
-      interceptScale: interceptScale,
+      interceptScale: interceptScale?.toDouble(),
       isFittingDataNormalized: isFittingDataNormalized,
       learningRateType: learningRateType,
       initialCoefficientsType: initialCoefficientsType,

lib/src/classifier/softmax_regressor/softmax_regressor_factory.dart

@@ -10,7 +10,7 @@ import 'package:ml_linalg/matrix.dart';
 abstract class SoftmaxRegressorFactory {
   SoftmaxRegressor create({
     DataFrame trainData,
-    List<String> targetNames,
+    Iterable<String> targetNames,
     LinearOptimizerType optimizerType,
     int iterationsLimit,
     double initialLearningRate,

lib/src/classifier/softmax_regressor/softmax_regressor_factory_impl.dart

@@ -22,7 +22,7 @@ class SoftmaxRegressorFactoryImpl implements SoftmaxRegressorFactory {
   @override
   SoftmaxRegressor create({
     DataFrame trainData,
-    List<String> targetNames,
+    Iterable<String> targetNames,
     LinearOptimizerType optimizerType = LinearOptimizerType.gradient,
     int iterationsLimit = 100,
     double initialLearningRate = 1e-3,

lib/src/classifier/softmax_regressor/softmax_regressor_impl.dart

@@ -251,7 +251,7 @@ class SoftmaxRegressorImpl
       randomSeed: randomSeed,
       batchSize: batchSize,
       fitIntercept: fitIntercept,
-      interceptScale: interceptScale,
+      interceptScale: interceptScale?.toDouble(),
       learningRateType: learningRateType,
       isFittingDataNormalized: isFittingDataNormalized,
       initialCoefficientsType: initialCoefficientsType,

lib/src/regressor/linear_regressor/linear_regressor_impl.dart

@@ -203,9 +203,9 @@ class LinearRegressorImpl
       iterationsLimit: iterationsLimit,
       learningRateType: learningRateType,
       initialCoefficientsType: initialCoefficientsType,
-      initialLearningRate: initialLearningRate,
-      minCoefficientsUpdate: minCoefficientsUpdate,
-      lambda: lambda,
+      initialLearningRate: initialLearningRate?.toDouble(),
+      minCoefficientsUpdate: minCoefficientsUpdate?.toDouble(),
+      lambda: lambda?.toDouble(),
       regularizationType: regularizationType,
       fitIntercept: fitIntercept,
       interceptScale: interceptScale,

pubspec.yaml

@@ -1,6 +1,6 @@
 name: ml_algo
 description: Machine learning algorithms, Machine learning models performance evaluation functionality
-version: 15.6.1
+version: 15.6.2
 homepage: https://github.com/gyrdym/ml_algo
 
 environment:

test/classifier/logistic_regressor/integration_test/logistic_regressor_serialization_integration_test.dart

@@ -59,7 +59,7 @@ void main() {
     int iterationsLimit = 2,
     double minCoefficientsUpdate = 1e-12,
     double initialLearningRate = 1.0,
-    num lambda,
+    double lambda,
     RegularizationType regularizationType,
     int randomSeed,
     int batchSize = 5,