Merge pull request #39 from gyrdym/coveralls-integration

Coveralls integration

.travis.yml

@@ -1,6 +1,8 @@
 language: dart
 dart:
-- "2.0.0"
+- "2.1.0"
 dart_task:
 - test: --platform vm
 - dartanalyzer: true
+- dartfmt: true
+script: ./tool/coverage.sh

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Changelog
 
+## 5.0.1
+- Travis integration added
+- `dartfmt` task added
+
 ## 5.0.0
 - MLVector and MLMatrix now don't have generic type parameters
 

README.md

@@ -1,4 +1,5 @@
 [![Build Status](https://travis-ci.com/gyrdym/ml_linalg.svg?branch=master)](https://travis-ci.com/gyrdym/ml_linalg)
+[![Coverage Status](https://coveralls.io/repos/github/gyrdym/ml_linalg/badge.svg)](https://coveralls.io/github/gyrdym/ml_linalg)
 [![pub package](https://img.shields.io/pub/v/ml_linalg.svg)](https://pub.dartlang.org/packages/ml_linalg)
 [![Gitter Chat](https://badges.gitter.im/gyrdym/gyrdym.svg)](https://gitter.im/gyrdym/)
 

benchmark/main.dart

@@ -8,4 +8,4 @@ void main() {
   VectorUniqueBenchmark.main();
   VectorMulBenchmark.main();
   VectorAdditionBenchmark.main();
-}
+}

benchmark/vector_initializing/float32x4_from_iterable.dart

@@ -9,7 +9,9 @@ const amountOfElements = 10000000;
 Float32x4Vector vector;
 
 class VectorInitializationBenchmark extends BenchmarkBase {
-  const VectorInitializationBenchmark() : super('Vector initialization (from simple iterable), $amountOfElements elements');
+  const VectorInitializationBenchmark()
+      : super(
+            'Vector initialization (from simple iterable), $amountOfElements elements');
 
   static void main() {
     const VectorInitializationBenchmark().report();

benchmark/vector_operations/float32x4_unique.dart

@@ -11,7 +11,8 @@ const amountOfElements = 10000;
 Float32x4Vector vector;
 
 class VectorUniqueBenchmark extends BenchmarkBase {
-  const VectorUniqueBenchmark() : super('Vector unnique elements obtaining, $amountOfElements elements');
+  const VectorUniqueBenchmark()
+      : super('Vector unnique elements obtaining, $amountOfElements elements');
 
   static void main() {
     const VectorUniqueBenchmark().report();
@@ -25,7 +26,8 @@ class VectorUniqueBenchmark extends BenchmarkBase {
   @override
   void setup() {
     final generator = math.Random(DateTime.now().millisecondsSinceEpoch);
-    vector = Float32x4Vector.from(List<double>.generate(amountOfElements, (int idx) => generator.nextDouble()));
+    vector = Float32x4Vector.from(List<double>.generate(
+        amountOfElements, (int idx) => generator.nextDouble()));
   }
 
   void tearDown() {
@@ -35,4 +37,4 @@ class VectorUniqueBenchmark extends BenchmarkBase {
 
 void main() {
   VectorUniqueBenchmark.main();
-}
+}

benchmark/vector_operations/float32x4_vectors_multiplication.dart

@@ -12,7 +12,8 @@ Float32x4Vector vector1;
 Float32x4Vector vector2;
 
 class VectorMulBenchmark extends BenchmarkBase {
-  const VectorMulBenchmark() : super('Vectors multiplication, $amountOfElements elements');
+  const VectorMulBenchmark()
+      : super('Vectors multiplication, $amountOfElements elements');
 
   static void main() {
     const VectorMulBenchmark().report();
@@ -27,8 +28,10 @@ class VectorMulBenchmark extends BenchmarkBase {
   @override
   void setup() {
     final generator = math.Random(DateTime.now().millisecondsSinceEpoch);
-    vector1 = Float32x4Vector.from(List<double>.generate(amountOfElements, (int idx) => generator.nextDouble()));
-    vector2 = Float32x4Vector.from(List<double>.generate(amountOfElements, (int idx) => generator.nextDouble()));
+    vector1 = Float32x4Vector.from(List<double>.generate(
+        amountOfElements, (int idx) => generator.nextDouble()));
+    vector2 = Float32x4Vector.from(List<double>.generate(
+        amountOfElements, (int idx) => generator.nextDouble()));
   }
 
   void tearDown() {
@@ -39,4 +42,4 @@ class VectorMulBenchmark extends BenchmarkBase {
 
 void main() {
   VectorMulBenchmark.main();
-}
+}

benchmark/vector_operations/float32x4_vectors_sum.dart

@@ -10,7 +10,8 @@ Float32x4Vector vector1;
 Float32x4Vector vector2;
 
 class VectorAdditionBenchmark extends BenchmarkBase {
-  const VectorAdditionBenchmark() : super('Vectors addition, $amountOfElements elements');
+  const VectorAdditionBenchmark()
+      : super('Vectors addition, $amountOfElements elements');
 
   static void main() {
     const VectorAdditionBenchmark().report();
@@ -36,4 +37,4 @@ class VectorAdditionBenchmark extends BenchmarkBase {
 
 void main() {
   VectorAdditionBenchmark.main();
-}
+}

example/main.dart

@@ -74,7 +74,8 @@ void dot() {
   final vector1 = Float32x4Vector.from([1.0, 2.0, 3.0, 4.0, 5.0]);
   final vector2 = Float32x4Vector.from([2.0, 3.0, 4.0, 5.0, 6.0]);
   final result = vector1.dot(vector2);
-  print(result); // 1.0 * 2.0 + 2.0 * 3.0 + 3.0 * 4.0 + 4.0 * 5.0 + 5.0 * 6.0 = 70.0
+  print(
+      result); // 1.0 * 2.0 + 2.0 * 3.0 + 3.0 * 4.0 + 4.0 * 5.0 + 5.0 * 6.0 = 70.0
 }
 
 void scalarAddition() {

lib/matrix.dart

@@ -70,10 +70,12 @@ abstract class MLMatrix {
   MLVector getRow(int index, {bool tryCache = true, bool mutable = false});
 
   /// Reduces all the matrix columns to only column, using [combiner] function
-  MLVector reduceColumns(MLVector combiner(MLVector combine, MLVector vector), {MLVector initValue});
+  MLVector reduceColumns(MLVector combiner(MLVector combine, MLVector vector),
+      {MLVector initValue});
 
   /// Reduces all the matrix rows to only row, using [combiner] function
-  MLVector reduceRows(MLVector combiner(MLVector combine, MLVector vector), {MLVector initValue});
+  MLVector reduceRows(MLVector combiner(MLVector combine, MLVector vector),
+      {MLVector initValue});
 
   /// Creates a new matrix, efficiently iterating through all the matrix elements (several floating point elements in a
   /// time) and applying the [mapper] function

lib/src/matrix/float32x4/float32_matrix_iterator.dart

@@ -18,10 +18,12 @@ class Float32MatrixIterator implements Iterator<Iterable<double>> {
     if (byteOffset >= _data.buffer.lengthInBytes) {
       _current = null;
     } else {
-      final totalSizeInBytes = byteOffset + (_columns * Float32List.bytesPerElement);
+      final totalSizeInBytes =
+          byteOffset + (_columns * Float32List.bytesPerElement);
       final length = _data.buffer.lengthInBytes >= totalSizeInBytes
           ? _columns
-          : (totalSizeInBytes - _data.buffer.lengthInBytes) ~/ Float32List.bytesPerElement;
+          : (totalSizeInBytes - _data.buffer.lengthInBytes) ~/
+              Float32List.bytesPerElement;
       _current = _data.buffer.asFloat32List(byteOffset, length);
     }
     _currentRow++;

lib/src/matrix/float32x4/float32x4_matrix.dart

@@ -12,15 +12,15 @@ import 'package:ml_linalg/src/matrix/ml_matrix_validator_mixin.dart';
 import 'package:ml_linalg/src/vector/float32x4/float32x4_vector_factory_mixin.dart';
 import 'package:ml_linalg/vector.dart';
 
-class Float32x4Matrix extends Object with
-    IterableMixin<Iterable<double>>,
-    MLMatrixValidatorMixin<Float32x4>,
-    Float32x4MatrixFactoryMixin,
-    Float32x4VectorFactoryMixin,
-    MLMatrixFastIterableMixin,
-    MLMatrixMixin<Float32x4, Float32x4List>
+class Float32x4Matrix extends Object
+    with
+        IterableMixin<Iterable<double>>,
+        MLMatrixValidatorMixin<Float32x4>,
+        Float32x4MatrixFactoryMixin,
+        Float32x4VectorFactoryMixin,
+        MLMatrixFastIterableMixin,
+        MLMatrixMixin<Float32x4, Float32x4List>
     implements MLMatrixDataStore, MLMatrix {
-
   @override
   final int rowsNum;
 
@@ -39,7 +39,8 @@ class Float32x4Matrix extends Object with
   Float32x4Matrix.from(Iterable<Iterable<double>> source)
       : rowsNum = source.length,
         columnsNum = source.first.length,
-        data = ByteData(source.length * source.first.length * Float32List.bytesPerElement),
+        data = ByteData(
+            source.length * source.first.length * Float32List.bytesPerElement),
         rowsCache = List<MLVector>(source.length),
         columnsCache = List<MLVector>(source.first.length) {
     final flattened = flatten2dimList(source, (i, j) => i * columnsNum + j);
@@ -61,7 +62,8 @@ class Float32x4Matrix extends Object with
   Float32x4Matrix.columns(Iterable<MLVector> source)
       : rowsNum = source.first.length,
         columnsNum = source.length,
-        data = ByteData(source.length * source.first.length * Float32List.bytesPerElement),
+        data = ByteData(
+            source.length * source.first.length * Float32List.bytesPerElement),
         rowsCache = List<MLVector>(source.first.length),
         columnsCache = source.toList(growable: false) {
     final flattened = flatten2dimList(source, (i, j) => j * columnsNum + i);
@@ -72,14 +74,16 @@ class Float32x4Matrix extends Object with
   Float32x4Matrix.rows(Iterable<MLVector> source)
       : rowsNum = source.length,
         columnsNum = source.first.length,
-        data = ByteData(source.length * source.first.length * Float32List.bytesPerElement),
+        data = ByteData(
+            source.length * source.first.length * Float32List.bytesPerElement),
         rowsCache = source.toList(growable: false),
         columnsCache = List<MLVector>(source.first.length) {
     final flattened = flatten2dimList(source, (i, j) => i * columnsNum + j);
     data.buffer.asFloat32List().setAll(0, flattened);
   }
 
-  Float32x4Matrix.flattened(Iterable<double> source, this.rowsNum, this.columnsNum)
+  Float32x4Matrix.flattened(
+      Iterable<double> source, this.rowsNum, this.columnsNum)
       : data = ByteData(rowsNum * columnsNum * Float32List.bytesPerElement),
         rowsCache = List<MLVector>(rowsNum),
         columnsCache = List<MLVector>(columnsNum) {
@@ -90,5 +94,6 @@ class Float32x4Matrix extends Object with
   }
 
   @override
-  Iterator<Iterable<double>> get iterator => Float32MatrixIterator(data, columnsNum);
+  Iterator<Iterable<double>> get iterator =>
+      Float32MatrixIterator(data, columnsNum);
 }

lib/src/matrix/float32x4/float32x4_matrix_factory_mixin.dart

@@ -9,7 +9,8 @@ abstract class Float32x4MatrixFactoryMixin implements MLMatrixFactory {
       Float32x4Matrix.from(source);
 
   @override
-  MLMatrix createMatrixFromFlattened(Iterable<double> source, int rowsNum, int columnsNum) =>
+  MLMatrix createMatrixFromFlattened(
+          Iterable<double> source, int rowsNum, int columnsNum) =>
       Float32x4Matrix.flattened(source, rowsNum, columnsNum);
 
   @override
@@ -19,4 +20,4 @@ abstract class Float32x4MatrixFactoryMixin implements MLMatrixFactory {
   @override
   MLMatrix createMatrixFromColumns(Iterable<MLVector> source) =>
       Float32x4Matrix.columns(source);
-}
+}

lib/src/matrix/ml_matrix_factory.dart

@@ -3,7 +3,8 @@ import 'package:ml_linalg/vector.dart';
 
 abstract class MLMatrixFactory {
   MLMatrix createMatrixFrom(Iterable<Iterable<double>> source);
-  MLMatrix createMatrixFromFlattened(Iterable<double> source, int rowsNum, int columnsNum);
+  MLMatrix createMatrixFromFlattened(
+      Iterable<double> source, int rowsNum, int columnsNum);
   MLMatrix createMatrixFromRows(Iterable<MLVector> source);
   MLMatrix createMatrixFromColumns(Iterable<MLVector> source);
-}
+}

lib/src/matrix/ml_matrix_fast_iterable_mixin.dart

@@ -5,8 +5,10 @@ import 'package:ml_linalg/vector.dart';
 abstract class MLMatrixFastIterableMixin implements MLMatrixFactory, MLMatrix {
   @override
   MLMatrix fastMap<T>(T mapper(T element)) {
-    final source = List<MLVector>.generate(rowsNum, (int i) => (getRow(i))
-        .fastMap((T element, int startOffset, int endOffset) => mapper(element)));
+    final source = List<MLVector>.generate(
+        rowsNum,
+        (int i) => (getRow(i)).fastMap(
+            (T element, int startOffset, int endOffset) => mapper(element)));
     return createMatrixFromRows(source);
   }
-}
+}