More fixes to get it to compile.

SingleR-inc · May 21, 2024 · db2ba1b · db2ba1b
1 parent af644cb
commit db2ba1b
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Showing 3 changed files with 13 additions and 13 deletions.
diff --git a/tests/src/IntegratedBuilder.cpp b/tests/src/IntegratedBuilder.cpp
@@ -125,7 +125,7 @@ TEST_P(IntegratedBuilderBasicTest, SimpleCombine) {
         // Checking the ranked values.
         std::vector<int> offsets(nlabels);
         auto wrk = matrices[r]->dense_column();
-        std::vector<double> buffer(matrices[r]->ncol());
+        std::vector<double> buffer(matrices[r]->nrow());
 
         for (size_t s = 0; s < nsamples; ++s) {
             int lab = labels[r][s]; 
@@ -289,7 +289,7 @@ TEST_P(IntegratedBuilderMoreTest, IntersectedCombine) {
         // Checking rankings for consistency with the availabilities.
         std::vector<int> offsets(nlabels);
         auto wrk = matrices[r]->dense_column();
-        std::vector<double> buffer(matrices[r]->ncol());
+        std::vector<double> buffer(matrices[r]->nrow());
 
         for (size_t s = 0; s < nsamples; ++s) {
             int lab = labels[r][s]; 

diff --git a/tests/src/fine_tune.cpp b/tests/src/fine_tune.cpp
@@ -86,9 +86,9 @@ TEST(FineTuneTest, Basic) {
 
     // Check early exit conditions.
     {
-        std::vector<double> buffer(refs->ncol());
+        std::vector<double> buffer(ngenes);
         auto vec = refs->dense_column()->fetch(0, buffer.data()); // doesn't really matter what we pick here.
-        auto ranked = fill_ranks(refs->ncol(), vec);
+        auto ranked = fill_ranks(ngenes, vec);
 
         std::vector<double> scores { 0.2, 0.5, 0.1 };
         auto output = ft.run(ranked, references, markers, scores, 0.8, 0.05);
@@ -105,9 +105,9 @@ TEST(FineTuneTest, Basic) {
     // Check edge case when there is only a single label, 
     // based on the length of 'scores'.
     {
-        std::vector<double> buffer(refs->ncol());
+        std::vector<double> buffer(ngenes);
         auto vec = refs->dense_column()->fetch(1, buffer.data()); // doesn't really matter which one we pick.
-        auto ranked = fill_ranks(refs->ncol(), vec);
+        auto ranked = fill_ranks(ngenes, vec);
 
         std::vector<double> scores { 0.5 };
         auto output = ft.run(ranked, references, markers, scores, 0.8, 0.05);
@@ -119,10 +119,10 @@ TEST(FineTuneTest, Basic) {
     // is identical to one of the references. We set the quantile to 1 to
     // guarantee a score of 1 from a correlation of 1.
     auto wrk = refs->dense_column();
-    std::vector<double> buffer(refs->ncol());
+    std::vector<double> buffer(ngenes);
     for (size_t r = 0; r < nrefs; ++r) {
         auto vec = wrk->fetch(r, buffer.data());
-        auto ranked = fill_ranks(refs->ncol(), buffer.data());
+        auto ranked = fill_ranks(ngenes, vec);
 
         // Setting the template parameter test = true to force it to do
         // calculations; otherwise it would exit early with the top score.
@@ -168,7 +168,7 @@ TEST(FineTuneTest, Comparison) {
     );
 
     auto wrk = mat->dense_column(subset);
-    std::vector<double> buffer(refs->ncol());
+    std::vector<double> buffer(subset.size());
     for (size_t c = 0; c < mat->ncol(); ++c) {
         auto vec = wrk->fetch(c, buffer.data()); 
         auto ranked = fill_ranks(refs->ncol(), vec);
@@ -224,10 +224,10 @@ TEST(FineTuneTest, Diagonal) {
     singlepp::FineTuner ft;
 
     auto wrk = refs->dense_column();
-    std::vector<double> buffer(refs->ncol());
+    std::vector<double> buffer(ngenes);
     for (size_t r = 0; r < nrefs; ++r) {
         auto vec = wrk->fetch(r, buffer.data()); 
-        auto ranked = fill_ranks(refs->ncol(), vec);
+        auto ranked = fill_ranks(ngenes, vec);
         std::vector<double> scores { 0.49, 0.5, 0.48 };
         auto output = ft.run<true>(ranked, references, markers, scores, 1, 0.05);
 

diff --git a/tests/src/naive_method.h b/tests/src/naive_method.h
@@ -19,7 +19,7 @@ template<class RefMatrix>
 double naive_score(const std::vector<double>& scaled_test, const std::vector<int>& in_label, const RefMatrix& refs, const std::vector<int>& subset, double quantile) {
     std::vector<double> correlations;
     auto wrk = refs->dense_column(subset);
-    std::vector<double> buffer(refs->nrow());
+    std::vector<double> buffer(subset.size());
 
     for (auto l : in_label) {
         auto col = wrk->fetch(l, buffer.data());
@@ -37,7 +37,7 @@ auto naive_method(size_t nlabels, const Labels& labels, const RefMatrix& refs, c
 
     auto by_labels = split_by_label(nlabels, labels);
     auto wrk = mat->dense_column(subset);
-    std::vector<typename Matrix::element_type::value_type> buffer(mat->nrow());
+    std::vector<double> buffer(subset.size());
 
     for (size_t c = 0; c < mat->ncol(); ++c) {
         auto col = wrk->fetch(c, buffer.data());