crnlib: fix CodeQL report cpp/*-multiplication-cast-to-*

crnlib/crn_clusterizer.h

@@ -53,7 +53,7 @@ class clusterizer {
       root.m_total_weight += weight;
       root.m_vectors.push_back(i);
 
-      ttsum += v.dot(v) * weight;
+      ttsum += (double)v.dot(v) * (double)weight;
     }
 
     root.m_variance = (float)(ttsum - (root.m_centroid.dot(root.m_centroid) / root.m_total_weight));
@@ -409,7 +409,7 @@ class clusterizer {
         double sum = 0;
 
         for (uint j = 0; j < N; j++)
-          sum += axis[j] * covar[i][j];
+          sum += static_cast<double>(axis[j]) * static_cast<double>(covar[i][j]);
 
         x[i] = static_cast<float>(sum);
 
@@ -629,14 +629,14 @@ class clusterizer {
           new_left_child += (v * (float)weight);
           left_weight += weight;
 
-          left_ttsum += v.dot(v) * weight;
+          left_ttsum += (double)v.dot(v) * (double)weight;
         } else {
           m_right_children.push_back(parent_node.m_vectors[i]);
 
           new_right_child += (v * (float)weight);
           right_weight += weight;
 
-          right_ttsum += v.dot(v) * weight;
+          right_ttsum += (double)v.dot(v) * (double)weight;
         }
       }
 

crnlib/crn_dxt1.cpp

@@ -151,9 +151,9 @@ void dxt1_endpoint_optimizer::compute_pca(vec3F& axis, const vec3F_array& norm_c
   double cov[6] = {0, 0, 0, 0, 0, 0};
   for (uint i = 0; i < norm_colors.size(); i++) {
     const vec3F& v = norm_colors[i];
-    float r = v[0];
-    float g = v[1];
-    float b = v[2];
+    double r = (double)v[0];
+    double g = (double)v[1];
+    double b = (double)v[2];
     if (m_unique_colors[i].m_weight > 1) {
       const double weight = m_unique_colors[i].m_weight;
       cov[0] += r * r * weight;

crnlib/crn_dxt_fast.cpp

@@ -411,7 +411,7 @@ static bool refine_endpoints(uint n, const color_quad_u8* pBlock, uint& low16, u
           for (uint i = 0; i < n; i++) {
             const color_quad_u8& p = pBlock[i];
 
-            int e = v[pSelectors[i]] - p[axis];
+            uint64 e = v[pSelectors[i]] - p[axis];
 
             axis_error += e * e;
 

crnlib/crn_image_utils.cpp

@@ -570,9 +570,9 @@ bool resample_multithreaded(const image_u8& src, image_u8& dst, const resample_p
     return false;
 
   p.m_pSrc_pixels = src_samples.get_ptr();
-  p.m_src_pitch = src_width * resampler_comps * sizeof(float);
+  p.m_src_pitch = (size_t)src_width * (size_t)resampler_comps * sizeof(float);
   p.m_pDst_pixels = dst_samples.get_ptr();
-  p.m_dst_pitch = dst_width * resampler_comps * sizeof(float);
+  p.m_dst_pitch = (size_t)dst_width * (size_t)resampler_comps * sizeof(float);
 
   for (uint src_y = 0; src_y < src_height; src_y++) {
     const color_quad_u8* pSrc = src.get_scanline(src_y);

crnlib/crn_jpgd.cpp

@@ -2441,7 +2441,7 @@ jpeg_decoder::coeff_buf* jpeg_decoder::coeff_buf_open(int block_num_x, int block
   cb->block_len_x = block_len_x;
   cb->block_len_y = block_len_y;
   cb->block_size = (block_len_x * block_len_y) * sizeof(jpgd_block_t);
-  cb->pData = (uint8*)alloc(cb->block_size * block_num_x * block_num_y, true);
+  cb->pData = (uint8*)alloc((size_t)cb->block_size * (size_t)block_num_x * (size_t)block_num_y, true);
   return cb;
 }
 
@@ -2870,7 +2870,7 @@ unsigned char* decompress_jpeg_image_from_stream(jpeg_decoder_stream* pStream, i
 
   const int dst_bpl = image_width * req_comps;
 
-  uint8* pImage_data = (uint8*)jpgd_malloc(dst_bpl * image_height);
+  uint8* pImage_data = (uint8*)jpgd_malloc((size_t)dst_bpl * (size_t)image_height);
   if (!pImage_data)
     return NULL;
 

crnlib/crn_jpge.cpp

@@ -576,7 +576,7 @@ bool jpeg_encoder::jpg_open(int p_x_res, int p_y_res, int src_channels) {
   m_image_bpl_mcu = m_image_x_mcu * m_num_components;
   m_mcus_per_row = m_image_x_mcu / m_mcu_x;
 
-  if ((m_mcu_lines[0] = static_cast<uint8*>(jpge_malloc(m_image_bpl_mcu * m_mcu_y))) == NULL)
+  if ((m_mcu_lines[0] = static_cast<uint8*>(jpge_malloc((size_t)m_image_bpl_mcu * (size_t)m_mcu_y))) == NULL)
     return false;
   for (int i = 1; i < m_mcu_y; i++)
     m_mcu_lines[i] = m_mcu_lines[i - 1] + m_image_bpl_mcu;

crnlib/crn_mipmapped_texture.cpp

@@ -2763,7 +2763,7 @@ bool mipmapped_texture::read_crn_from_memory(const void* pData, uint data_size,
 
       if (!pDXT_image->init(
               dxt_fmt, level_width, level_height,
-              num_blocks_x * num_blocks_y * (tex_info.m_bytes_per_block / sizeof(dxt_image::element)),
+              (size_t)num_blocks_x * (size_t)num_blocks_y * (tex_info.m_bytes_per_block / sizeof(dxt_image::element)),
               reinterpret_cast<dxt_image::element*>(pFaces[f]), true)) {
         crnlib_delete(pDXT_image);
 

crnlib/crn_threaded_clusterizer.h

@@ -219,7 +219,7 @@ class threaded_clusterizer {
         double sum = 0;
 
         for (uint j = 0; j < N; j++)
-          sum += axis[j] * covar[i][j];
+          sum += static_cast<double>(axis[j]) * static_cast<double>(covar[i][j]);
 
         x[i] = static_cast<float>(sum);
 

crnlib/crn_tree_clusterizer.h

@@ -72,7 +72,7 @@ class tree_clusterizer {
       m_weightedVectors[i] = v * (float)weight;
       root.m_centroid += m_weightedVectors[i];
       root.m_total_weight += weight;
-      m_weightedDotProducts[i] = v.dot(v) * weight;
+      m_weightedDotProducts[i] = (double)v.dot(v) * (double)weight;
       ttsum += m_weightedDotProducts[i];
     }
     root.m_variance = (float)(ttsum - (root.m_centroid.dot(root.m_centroid) / root.m_total_weight));
@@ -289,7 +289,7 @@ class tree_clusterizer {
           double sum = 0;
 
           for (uint j = 0; j < N; j++)
-            sum += axis[j] * covar[i][j];
+            sum += (double)axis[j] * (double)covar[i][j];
 
           x[i] = (float)sum;
 
@@ -464,7 +464,7 @@ void split_vectors(VectorType (&vectors)[64], uint (&weights)[64], uint size, Ve
     weightedVectors[i] = v * (float)weight;
     centroid += weightedVectors[i];
     total_weight += weight;
-    weightedDotProducts[i] = v.dot(v) * weight;
+    weightedDotProducts[i] = (double)v.dot(v) * (double)weight;
     ttsum += weightedDotProducts[i];
   }
   float variance = (float)(ttsum - (centroid.dot(centroid) / total_weight));
@@ -520,7 +520,7 @@ void split_vectors(VectorType (&vectors)[64], uint (&weights)[64], uint size, Ve
       for (uint i = 0; i < N; i++) {
         double sum = 0;
         for (uint j = 0; j < N; j++)
-          sum += axis[j] * covar[i][j];
+          sum += (double)axis[j] * (double)covar[i][j];
         x[i] = (float)sum;
         max_sum = i ? math::maximum(max_sum, sum) : sum;
       }

crnlib/crn_vec.h

@@ -475,9 +475,9 @@ class vec : public helpers::rel_ops<vec<N, T> > {
   }
 
   inline double normalize(const vec* pDefaultVec = NULL) {
-    double n = m_s[0] * m_s[0];
+    double n = (double)m_s[0] * (double)m_s[0];
     for (uint i = 1; i < N; i++)
-      n += m_s[i] * m_s[i];
+      n += (double)m_s[i] * (double)m_s[i];
 
     if (n != 0)
       *this *= static_cast<T>((1.0f / sqrt(n)));
@@ -489,7 +489,7 @@ class vec : public helpers::rel_ops<vec<N, T> > {
   inline double normalize3(const vec* pDefaultVec = NULL) {
     CRNLIB_ASSUME(N >= 3);
 
-    double n = m_s[0] * m_s[0] + m_s[1] * m_s[1] + m_s[2] * m_s[2];
+    double n = (double)m_s[0] * (double)m_s[0] + (double)m_s[1] * (double)m_s[1] + (double)m_s[2] * (double)m_s[2];
 
     if (n != 0)
       *this *= static_cast<T>((1.0f / sqrt(n)));