From 5749932e5d8dc0b6c02904c8d912a65bda2f7f3f Mon Sep 17 00:00:00 2001
From: yoshoku <yoshoku@outlook.com>
Date: Tue, 4 May 2021 00:28:53 +0900
Subject: [PATCH] :art: Refactor Tree estimator specs

---
 .../tree/decision_tree_classifier_spec.rb     | 19 ++++++++++------
 .../tree/decision_tree_regressor_spec.rb      | 22 ++++++++++++-------
 .../rumale/tree/extra_tree_classifier_spec.rb | 19 ++++++++++------
 spec/rumale/tree/extra_tree_regressor_spec.rb | 19 ++++++++++------
 .../tree/gradient_tree_regressor_spec.rb      |  8 ++++---
 5 files changed, 55 insertions(+), 32 deletions(-)

diff --git a/spec/rumale/tree/decision_tree_classifier_spec.rb b/spec/rumale/tree/decision_tree_classifier_spec.rb
index 01fabf4..26743c5 100644
--- a/spec/rumale/tree/decision_tree_classifier_spec.rb
+++ b/spec/rumale/tree/decision_tree_classifier_spec.rb
@@ -27,11 +27,13 @@ RSpec.describe Rumale::Tree::DecisionTreeClassifier do
     let(:dataset) { two_clusters_dataset }
 
     it 'classifies two clusters data.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.classes.class).to eq(Numo::Int32)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.classes).to be_a(Numo::Int32)
+      expect(estimator.classes).to be_contiguous
       expect(estimator.classes.ndim).to eq(1)
       expect(estimator.classes.shape[0]).to eq(n_classes)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
       expect(score).to eq(1.0)
@@ -42,18 +44,21 @@ RSpec.describe Rumale::Tree::DecisionTreeClassifier do
     let(:dataset) { three_clusters_dataset }
 
     it 'classifies three clusters data.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.classes.class).to eq(Numo::Int32)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.classes).to be_a(Numo::Int32)
+      expect(estimator.classes).to be_contiguous
       expect(estimator.classes.ndim).to eq(1)
       expect(estimator.classes.shape[0]).to eq(n_classes)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
       expect(score).to eq(1.0)
     end
 
     it 'estimates class probabilities with three clusters dataset.', :aggregate_failures do
-      expect(probs.class).to eq(Numo::DFloat)
+      expect(probs).to be_a(Numo::DFloat)
+      expect(probs).to be_contiguous
       expect(probs.ndim).to eq(2)
       expect(probs.shape[0]).to eq(n_samples)
       expect(probs.shape[1]).to eq(n_classes)
diff --git a/spec/rumale/tree/decision_tree_regressor_spec.rb b/spec/rumale/tree/decision_tree_regressor_spec.rb
index 8a693c5..81e014c 100644
--- a/spec/rumale/tree/decision_tree_regressor_spec.rb
+++ b/spec/rumale/tree/decision_tree_regressor_spec.rb
@@ -26,14 +26,17 @@ RSpec.describe Rumale::Tree::DecisionTreeRegressor do
     let(:y) { single_target }
 
     it 'learns the model for single regression problem.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
-      expect(estimator.leaf_values.class).to eq(Numo::DFloat)
+      expect(estimator.leaf_values).to be_a(Numo::DFloat)
+      expect(estimator.leaf_values).to be_contiguous
       expect(estimator.leaf_values.ndim).to eq(1)
       expect(estimator.leaf_values.shape[0]).not_to be_zero
-      expect(predicted.class).to eq(Numo::DFloat)
+      expect(predicted).to be_a(Numo::DFloat)
+      expect(predicted).to be_contiguous
       expect(predicted.ndim).to eq(1)
       expect(predicted.shape[0]).to eq(n_samples)
       expect(score).to be_within(0.01).of(1.0)
@@ -112,15 +115,18 @@ RSpec.describe Rumale::Tree::DecisionTreeRegressor do
     let(:y) { multi_target }
 
     it 'learns the model for multiple regression problem.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
-      expect(estimator.leaf_values.class).to eq(Numo::DFloat)
+      expect(estimator.leaf_values).to be_a(Numo::DFloat)
+      expect(estimator.leaf_values).to be_contiguous
       expect(estimator.leaf_values.ndim).to eq(2)
       expect(estimator.leaf_values.shape[0]).not_to be_zero
       expect(estimator.leaf_values.shape[1]).to eq(n_outputs)
-      expect(predicted.class).to eq(Numo::DFloat)
+      expect(predicted).to be_a(Numo::DFloat)
+      expect(predicted).to be_contiguous
       expect(predicted.ndim).to eq(2)
       expect(predicted.shape[0]).to eq(n_samples)
       expect(predicted.shape[1]).to eq(n_outputs)
diff --git a/spec/rumale/tree/extra_tree_classifier_spec.rb b/spec/rumale/tree/extra_tree_classifier_spec.rb
index 176e10c..0f3f041 100644
--- a/spec/rumale/tree/extra_tree_classifier_spec.rb
+++ b/spec/rumale/tree/extra_tree_classifier_spec.rb
@@ -27,11 +27,13 @@ RSpec.describe Rumale::Tree::ExtraTreeClassifier do
     let(:dataset) { two_clusters_dataset }
 
     it 'classifies two clusters data.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.classes.class).to eq(Numo::Int32)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.classes).to be_a(Numo::Int32)
+      expect(estimator.classes).to be_contiguous
       expect(estimator.classes.ndim).to eq(1)
       expect(estimator.classes.shape[0]).to eq(n_classes)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
       expect(score).to eq(1.0)
@@ -42,18 +44,21 @@ RSpec.describe Rumale::Tree::ExtraTreeClassifier do
     let(:dataset) { three_clusters_dataset }
 
     it 'classifies three clusters data.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.classes.class).to eq(Numo::Int32)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.classes).to be_a(Numo::Int32)
+      expect(estimator.classes).to be_contiguous
       expect(estimator.classes.ndim).to eq(1)
       expect(estimator.classes.shape[0]).to eq(n_classes)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
       expect(score).to eq(1.0)
     end
 
     it 'estimates class probabilities with three clusters dataset.', :aggregate_failures do
-      expect(probs.class).to eq(Numo::DFloat)
+      expect(probs).to be_a(Numo::DFloat)
+      expect(probs).to be_contiguous
       expect(probs.ndim).to eq(2)
       expect(probs.shape[0]).to eq(n_samples)
       expect(probs.shape[1]).to eq(n_classes)
diff --git a/spec/rumale/tree/extra_tree_regressor_spec.rb b/spec/rumale/tree/extra_tree_regressor_spec.rb
index c067117..357cfb8 100644
--- a/spec/rumale/tree/extra_tree_regressor_spec.rb
+++ b/spec/rumale/tree/extra_tree_regressor_spec.rb
@@ -26,14 +26,17 @@ RSpec.describe Rumale::Tree::ExtraTreeRegressor do
     let(:y) { single_target }
 
     it 'learns the model for single regression problem.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
-      expect(estimator.leaf_values.class).to eq(Numo::DFloat)
+      expect(estimator.leaf_values).to be_a(Numo::DFloat)
+      expect(estimator.leaf_values).to be_contiguous
       expect(estimator.leaf_values.ndim).to eq(1)
       expect(estimator.leaf_values.shape[0]).not_to be_zero
-      expect(predicted.class).to eq(Numo::DFloat)
+      expect(predicted).to be_a(Numo::DFloat)
+      expect(predicted).to be_contiguous
       expect(predicted.ndim).to eq(1)
       expect(predicted.shape[0]).to eq(n_samples)
       expect(score).to be_within(0.01).of(1.0)
@@ -111,11 +114,13 @@ RSpec.describe Rumale::Tree::ExtraTreeRegressor do
     let(:y) { multi_target }
 
     it 'learns the model for multiple regression problem.', :aggregate_failures do
-      expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-      expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+      expect(estimator.tree).to be_a(Rumale::Tree::Node)
+      expect(estimator.feature_importances).to be_a(Numo::DFloat)
+      expect(estimator.feature_importances).to be_contiguous
       expect(estimator.feature_importances.ndim).to eq(1)
       expect(estimator.feature_importances.shape[0]).to eq(n_features)
-      expect(estimator.leaf_values.class).to eq(Numo::DFloat)
+      expect(estimator.leaf_values).to be_a(Numo::DFloat)
+      expect(estimator.leaf_values).to be_contiguous
       expect(estimator.leaf_values.ndim).to eq(2)
       expect(estimator.leaf_values.shape[0]).not_to be_zero
       expect(estimator.leaf_values.shape[1]).to eq(n_outputs)
diff --git a/spec/rumale/tree/gradient_tree_regressor_spec.rb b/spec/rumale/tree/gradient_tree_regressor_spec.rb
index bb34783..fa81752 100644
--- a/spec/rumale/tree/gradient_tree_regressor_spec.rb
+++ b/spec/rumale/tree/gradient_tree_regressor_spec.rb
@@ -23,11 +23,13 @@ RSpec.describe Rumale::Tree::GradientTreeRegressor do
 
   it 'classifies two clusters data.' do
     estimator.fit(x_bin, y_bin, grad, hess)
-    expect(estimator.tree.class).to eq(Rumale::Tree::Node)
-    expect(estimator.leaf_weights.class).to eq(Numo::DFloat)
+    expect(estimator.tree).to be_a(Rumale::Tree::Node)
+    expect(estimator.leaf_weights).to be_a(Numo::DFloat)
+    expect(estimator.leaf_weights).to be_contiguous
     expect(estimator.leaf_weights.shape[0]).to eq(2)
     expect(estimator.leaf_weights.shape[1]).to be_nil
-    expect(estimator.feature_importances.class).to eq(Numo::DFloat)
+    expect(estimator.feature_importances).to be_a(Numo::DFloat)
+    expect(estimator.feature_importances).to be_contiguous
     expect(estimator.feature_importances.shape[0]).to eq(n_features)
     expect(estimator.feature_importances.shape[1]).to be_nil
     expect(estimator.score(x_bin, Numo::DFloat.cast(y_bin))).to be > 0.95