Use "N-dimensional" instead of "rank-N" in docstrings and error messages

crates/re_types/definitions/rerun/archetypes/bar_chart.fbs

@@ -18,7 +18,7 @@ table BarChart (
 ) {
   // --- Required ---
 
-  /// The values. Should always be a rank-1 tensor.
+  /// The values. Should always be a 1-dimensional tensor (i.e. a vector).
   values: rerun.components.TensorData ("attr.rerun.component_required", required, order: 1000);
 
   // --- Optional ---

crates/re_types/definitions/rerun/archetypes/depth_image.fbs

@@ -25,7 +25,7 @@ table DepthImage (
 ) {
   // --- Required ---
 
-  /// The depth-image data. Should always be a rank-2 tensor.
+  /// The depth-image data. Should always be a 2-dimensional tensor.
   data: rerun.components.TensorData ("attr.rerun.component_required", order: 1000);
 
   // --- Optional ---

crates/re_types/definitions/rerun/archetypes/image.fbs

@@ -40,7 +40,7 @@ table Image (
 ) {
   // --- Required ---
 
-  /// The image data. Should always be a rank-2 or rank-3 tensor.
+  /// The image data. Should always be a 2- or 3-dimensional tensor.
   data: rerun.components.TensorData ("attr.rerun.component_required", order: 1000);
 
   // --- Optional ---

crates/re_types/definitions/rerun/archetypes/segmentation_image.fbs

@@ -33,7 +33,7 @@ table SegmentationImage (
 ) {
   // --- Required ---
 
-  /// The image data. Should always be a rank-2 tensor.
+  /// The image data. Should always be a 2-dimensional tensor.
   data: rerun.components.TensorData ("attr.rerun.component_required", order: 1000);
 
   // --- Optional ---

rerun_cpp/src/rerun/archetypes/depth_image_ext.cpp

@@ -3,6 +3,8 @@
 
 #include "../collection_adapter_builtins.hpp"
 
+#include <sstream>
+
 namespace rerun::archetypes {
 
 #ifdef EDIT_EXTENSION
@@ -11,7 +13,7 @@ namespace rerun::archetypes {
     /// New depth image from height/width and tensor buffer.
     ///
     /// \param shape
-    /// Shape of the image. Calls `Error::handle()` if the shape is not rank 2.
+    /// Shape of the image. Calls `Error::handle()` if the tensor is not 2-dimensional
     /// Sets the dimension names to "height" and "width" if they are not specified.
     /// \param buffer
     /// The tensor buffer containing the depth image data.
@@ -23,14 +25,14 @@ namespace rerun::archetypes {
     /// \param data_
     /// The tensor buffer containing the depth image data.
     /// Sets the dimension names to "height" and "width" if they are not specified.
-    /// Calls `Error::handle()` if the shape is not rank 2.
+    /// Calls `Error::handle()` if the tensor is not 2-dimensional
     explicit DepthImage(components::TensorData data_);
 
     /// New depth image from dimensions and pointer to depth image data.
     ///
     /// Type must be one of the types supported by `rerun::datatypes::TensorData`.
     /// \param shape
-    /// Shape of the image. Calls `Error::handle()` if the shape is not rank 2.
+    /// Shape of the image. Calls `Error::handle()` if the tensor is not 2-dimensional
     /// Sets the dimension names to "height", "width" and "channel" if they are not specified.
     /// Determines the number of elements expected to be in `data`.
     /// \param data_
@@ -45,7 +47,9 @@ namespace rerun::archetypes {
     DepthImage::DepthImage(components::TensorData data_) : data(std::move(data_)) {
         auto& shape = data.data.shape;
         if (shape.size() != 2) {
-            Error(ErrorCode::InvalidTensorDimension, "Shape must be rank 2.").handle();
+            std::stringstream ss;
+            ss << "Expected 2-dimensional tensor, got " << shape.size() << " dimensions.";
+            Error(ErrorCode::InvalidTensorDimension, ss.str()).handle();
             return;
         }
 

rerun_cpp/src/rerun/archetypes/image_ext.cpp

@@ -3,6 +3,8 @@
 
 #include "../collection_adapter_builtins.hpp"
 
+#include <sstream>
+
 // Uncomment for better auto-complete while editing the extension.
 // #define EDIT_EXTENSION
 
@@ -14,7 +16,7 @@ namespace rerun::archetypes {
     /// New Image from height/width/channel and tensor buffer.
     ///
     /// \param shape
-    /// Shape of the image. Calls `Error::handle()` if the shape is not rank 2 or 3.
+    /// Shape of the image. Calls `Error::handle()` if the tensor is not 2- or 3-dimensional.
     /// Sets the dimension names to "height", "width" and "channel" if they are not specified.
     /// \param buffer
     /// The tensor buffer containing the image data.
@@ -26,14 +28,14 @@ namespace rerun::archetypes {
     /// \param data_
     /// The tensor buffer containing the image data.
     /// Sets the dimension names to "height",  "width" and "channel" if they are not specified.
-    /// Calls `Error::handle()` if the shape is not rank 2 or 3.
+    /// Calls `Error::handle()` if the tensor is not 2- or 3-dimensional.
     explicit Image(rerun::components::TensorData data_);
 
     /// New image from dimensions and pointer to image data.
     ///
     /// Type must be one of the types supported by `rerun::datatypes::TensorData`.
     /// \param shape
-    /// Shape of the image. Calls `Error::handle()` if the shape is not rank 2 or 3.
+    /// Shape of the image. Calls `Error::handle()` if the tensor is not 2- or 3-dimensional.
     /// Sets the dimension names to "height", "width" and "channel" if they are not specified.
     /// Determines the number of elements expected to be in `data`.
     /// \param data_
@@ -48,11 +50,9 @@ namespace rerun::archetypes {
     Image::Image(rerun::components::TensorData data_) : data(std::move(data_)) {
         auto& shape = data.data.shape;
         if (shape.size() != 2 && shape.size() != 3) {
-            Error(
-                ErrorCode::InvalidTensorDimension,
-                "Image shape is expected to be either rank 2 or 3."
-            )
-                .handle();
+            std::stringstream ss;
+            ss << "Expected 2- or 3-dimensional tensor, got " << shape.size() << " dimensions.";
+            Error(ErrorCode::InvalidTensorDimension, ss.str()).handle();
             return;
         }
         if (shape.size() == 3 && shape[2].size != 1 && shape[2].size != 3 && shape[2].size != 4) {

rerun_cpp/src/rerun/archetypes/segmentation_image_ext.cpp

@@ -3,6 +3,8 @@
 #include "../collection_adapter_builtins.hpp"
 #include "../error.hpp"
 
+#include <sstream>
+
 namespace rerun::archetypes {
 
 #if 0
@@ -11,7 +13,7 @@ namespace rerun::archetypes {
     /// New segmentation image from height/width and tensor buffer.
     ///
     /// \param shape
-    /// Shape of the image. Calls `Error::handle()` if the shape is not rank 2.
+    /// Shape of the image. Calls `Error::handle()` if the tensor is not 2-dimensional
     /// Sets the dimension names to "height" and "width" if they are not specified.
     /// \param buffer
     /// The tensor buffer containing the segmentation image data.
@@ -23,14 +25,14 @@ namespace rerun::archetypes {
     /// \param data_
     /// The tensor buffer containing the segmentation image data.
     /// Sets the dimension names to "height" and "width" if they are not specified.
-    /// Calls `Error::handle()` if the shape is not rank 2.
+    /// Calls `Error::handle()` if the tensor is not 2-dimensional
     explicit SegmentationImage(components::TensorData data_);
 
     /// New segmentation image from dimensions and pointer to segmentation image data.
     ///
     /// Type must be one of the types supported by `rerun::datatypes::TensorData`.
     /// \param shape
-    /// Shape of the image. Calls `Error::handle()` if the shape is not rank 2.
+    /// Shape of the image. Calls `Error::handle()` if the tensor is not 2-dimensional
     /// Sets the dimension names to "height", "width" and "channel" if they are not specified.
     /// Determines the number of elements expected to be in `data`.
     /// \param data_
@@ -45,7 +47,9 @@ namespace rerun::archetypes {
     SegmentationImage::SegmentationImage(components::TensorData data_) : data(std::move(data_)) {
         auto& shape = data.data.shape;
         if (shape.size() != 2) {
-            Error(ErrorCode::InvalidTensorDimension, "Shape must be rank 2.").handle();
+            std::stringstream ss;
+            ss << "Expected 2-dimensional tensor, got " << shape.size() << " dimensions.";
+            Error(ErrorCode::InvalidTensorDimension, ss.str()).handle();
             return;
         }
 

rerun_cpp/tests/archetypes/image.cpp

@@ -7,7 +7,7 @@ using namespace rerun::archetypes;
 #define TEST_TAG "[image][archetypes]"
 
 SCENARIO("Image archetype can be created from tensor data." TEST_TAG) {
-    GIVEN("tensor data with correct rank 2 shape") {
+    GIVEN("tensor data with correct 2-dimensional shape") {
         rerun::datatypes::TensorData data({3, 7}, std::vector<uint8_t>(3 * 7, 0));
         THEN("no error occurs on image construction") {
             auto image = check_logged_error([&] { return Image(std::move(data)); });
@@ -22,7 +22,7 @@ SCENARIO("Image archetype can be created from tensor data." TEST_TAG) {
             }
         }
     }
-    GIVEN("tensor data with correct rank 3 shape") {
+    GIVEN("tensor data with correct 3-dimensional shape") {
         rerun::datatypes::TensorData data({3, 7, 3}, std::vector<uint8_t>(3 * 7 * 3, 0));
         THEN("no error occurs on image construction") {
             auto image = check_logged_error([&] { return Image(std::move(data)); });
@@ -38,7 +38,7 @@ SCENARIO("Image archetype can be created from tensor data." TEST_TAG) {
             }
         }
     }
-    GIVEN("tensor data with incorrect rank 3 shape") {
+    GIVEN("tensor data with incorrect 3-dimensional shape") {
         rerun::datatypes::TensorData data({3, 7, 2}, std::vector<uint8_t>(3 * 7 * 2, 0));
         THEN("a warning occurs on image construction") {
             auto image = check_logged_error(
@@ -72,7 +72,7 @@ SCENARIO("Image archetype can be created from tensor data." TEST_TAG) {
         }
     }
 
-    GIVEN("tensor data with too high rank") {
+    GIVEN("tensor data with too high dimensionality") {
         rerun::datatypes::TensorData data(
             {
                 {
@@ -103,7 +103,7 @@ SCENARIO("Image archetype can be created from tensor data." TEST_TAG) {
         }
     }
 
-    GIVEN("tensor data with too low rank") {
+    GIVEN("tensor data with too low dimensionality") {
         rerun::datatypes::TensorData data(
             {
                 rerun::datatypes::TensorDimension(1, "dr robotnik"),

rerun_cpp/tests/archetypes/segmentation_and_depth_image.cpp

@@ -46,7 +46,7 @@ void run_image_tests() {
         }
     }
 
-    GIVEN("tensor data with too high rank") {
+    GIVEN("tensor data with too high dimensionality") {
         rerun::datatypes::TensorData data(
             {
                 {
@@ -75,7 +75,7 @@ void run_image_tests() {
         }
     }
 
-    GIVEN("tensor data with too low rank") {
+    GIVEN("tensor data with too low dimensionality") {
         rerun::datatypes::TensorData data(
             {
                 rerun::datatypes::TensorDimension(1, "dr robotnik"),