Cardiopulmonary bstar (Integration Test)

.gitignore

@@ -28,6 +28,9 @@ test/integration/*.xprot
 test/integration/*.xml
 .atom-build.json
 #.vscode/
+test/nhlbi_integration_tests/test
+test/nhlbi_integration_tests/baselines
+*.seq
 dep-build/
 stats.csv
 junit.xml

apps/gadgetron/connection/HeaderConnection.cpp

@@ -41,7 +41,7 @@ namespace {
             std::string raw_header(read_string_from_stream<uint32_t>(stream));
 
             ISMRMRD::IsmrmrdHeader header{};
-            
+
             //GDEBUG_STREAM("HEADER" << raw_header.c_str());
             ISMRMRD::deserialize(raw_header.c_str(), header);
             //PD
@@ -57,10 +57,17 @@ namespace {
                     if (it->name == "tSequenceVariant") {
                         GDEBUG("Hash bstar found %s found\n", it->value.c_str());
                         std::string hash_bstar=it->value.c_str();
-                        std::string bstar_folder_traj="/opt/data/bstar_traj/";
-                        // Loop through all .seq files in bstar_folder_traj
-                        for (const auto& entry : std::filesystem::directory_iterator(bstar_folder_traj)) {
-
+                        // Search for .seq trajectory files in known locations
+                        std::vector<std::string> traj_search_paths = {
+                            "/opt/data/bstar_traj/",
+                            "/opt/nhlbi-integration-test/data/",
+                            "/opt/code/gadgetron_lit/test/nhlbi_integration_tests/data/",
+                        };
+                        bool seq_found = false;
+                        for (const auto& bstar_folder_traj : traj_search_paths) {
+                            if (!std::filesystem::exists(bstar_folder_traj)) continue;
+                            for (const auto& entry : std::filesystem::recursive_directory_iterator(bstar_folder_traj)) {
+
                             if (entry.path().extension()==".seq"){
                                 //Find the hash (Last line of the .seq file)
                                 std::ifstream fin;
@@ -85,48 +92,49 @@ namespace {
                                         }
                                     }
 
-                                    std::string lastLine;            
+                                    std::string lastLine;
                                     std::getline(fin,lastLine);                      // Read the current line
                                     fin.close();
 
                                     // Comparison hash of the data with hash of the .seq file
                                     if(lastLine.find(hash_bstar) != std::string::npos){
                                         GDEBUG_STREAM("Seq file found with hash"<< lastLine);
-                                        
-                                        std::string traj_h5=(bstar_folder_traj +std::string("traj_") + entry.path().stem().string() + std::string(".h5"));
+
+                                        std::string traj_h5=(entry.path().parent_path().string() + std::string("/traj_") + entry.path().stem().string() + std::string(".h5"));
                                         GDEBUG_STREAM("Pulseq trajectory filepath " << traj_h5);
-                                        
+
                                         std::string xml_config;
                                         std::string hdf5_in_group="/dataset";
                                         std::shared_ptr<ISMRMRD::Dataset> ismrmrd_dataset= std::shared_ptr<ISMRMRD::Dataset>(new ISMRMRD::Dataset(traj_h5.c_str(), hdf5_in_group.c_str(), false));
                                         ismrmrd_dataset->readHeader(xml_config);
                                         ISMRMRD::IsmrmrdHeader h_traj;
-                                        
+
                                         ISMRMRD::deserialize(xml_config.c_str(), h_traj);
                                         // MODIFying Header matrixSize and FOV : Only reconSpace.matrixSize/FOV are correct in the trajectory file
                                         auto factor_0r = float((size_t(round(float(h_traj.encoding.front().reconSpace.matrixSize.x) / 32.0))) * 32.0) / float(size_t(h_traj.encoding.front().reconSpace.matrixSize.x));
                                         auto factor_1r = float((size_t(round(float(h_traj.encoding.front().reconSpace.matrixSize.y) / 32.0))) * 32.0) / float(size_t(h_traj.encoding.front().reconSpace.matrixSize.y));
                                         auto factor_2r = float((size_t(round(float(h_traj.encoding.front().reconSpace.matrixSize.z) / 32.0))) * 32.0) / float(size_t(h_traj.encoding.front().reconSpace.matrixSize.z));
                                         GDEBUG_STREAM("Recon Matrix traj : X " << h_traj.encoding.front().reconSpace.matrixSize.x << " Y " << h_traj.encoding.front().reconSpace.matrixSize.y << " Z " << h_traj.encoding.front().reconSpace.matrixSize.z);
                                         GDEBUG_STREAM("Factor traj : X " << factor_0r << " Y " << factor_1r << " Z " << factor_2r);
-                                        
+
                                         factor_0r = factor_0r == 0 ? 1 : factor_0r;
                                         factor_1r = factor_1r == 0 ? 1 : factor_1r;
                                         factor_2r = factor_2r == 0 ? 1 : factor_2r;
+
                                         GDEBUG_STREAM("Raw Header information :");
                                         GDEBUG_STREAM("Encoded Matrix: X " << header.encoding.front().encodedSpace.matrixSize.x << " Y " << header.encoding.front().encodedSpace.matrixSize.y << " Z " << header.encoding.front().encodedSpace.matrixSize.z);
                                         GDEBUG_STREAM("Recon Matrix: X " << header.encoding.front().reconSpace.matrixSize.x << " Y " << header.encoding.front().reconSpace.matrixSize.y << " Z " << header.encoding.front().reconSpace.matrixSize.z);
                                         GDEBUG_STREAM("Encoded FOV: X " << header.encoding.front().encodedSpace.fieldOfView_mm.x << " Y " << header.encoding.front().encodedSpace.fieldOfView_mm.y << " Z " << header.encoding.front().encodedSpace.fieldOfView_mm.z);
                                         GDEBUG_STREAM("Recon FOV: X " << header.encoding.front().reconSpace.fieldOfView_mm.x << " Y " << header.encoding.front().reconSpace.fieldOfView_mm.y << " Z " << header.encoding.front().reconSpace.fieldOfView_mm.z);
                                         GDEBUG_STREAM("Encoding Limits: Encoded step 1 max " << header.encoding.at(0).encodingLimits.kspace_encoding_step_1.get().maximum  << " Encoded step 2 max " << header.encoding.at(0).encodingLimits.kspace_encoding_step_2.get().maximum  );
 
-                                        header.encoding.front().encodedSpace.matrixSize.x=size_t(h_traj.encoding.front().reconSpace.matrixSize.x* factor_0r);
-                                        header.encoding.front().encodedSpace.matrixSize.y=size_t(h_traj.encoding.front().reconSpace.matrixSize.y* factor_1r);
-                                        header.encoding.front().encodedSpace.matrixSize.z=size_t(h_traj.encoding.front().reconSpace.matrixSize.z* factor_2r);
+                                        header.encoding.front().encodedSpace.matrixSize.x=size_t(h_traj.encoding.front().reconSpace.matrixSize.x * factor_0r);
+                                        header.encoding.front().encodedSpace.matrixSize.y=size_t(h_traj.encoding.front().reconSpace.matrixSize.y * factor_1r);
+                                        header.encoding.front().encodedSpace.matrixSize.z=size_t(h_traj.encoding.front().reconSpace.matrixSize.z * factor_2r);
 
-                                        header.encoding.front().reconSpace.matrixSize.x=size_t(h_traj.encoding.front().reconSpace.matrixSize.x* factor_0r);
-                                        header.encoding.front().reconSpace.matrixSize.y=size_t(h_traj.encoding.front().reconSpace.matrixSize.y* factor_1r);
-                                        header.encoding.front().reconSpace.matrixSize.z=size_t(h_traj.encoding.front().reconSpace.matrixSize.z* factor_2r);
+                                        header.encoding.front().reconSpace.matrixSize.x=size_t(h_traj.encoding.front().reconSpace.matrixSize.x * factor_0r);
+                                        header.encoding.front().reconSpace.matrixSize.y=size_t(h_traj.encoding.front().reconSpace.matrixSize.y * factor_1r);
+                                        header.encoding.front().reconSpace.matrixSize.z=size_t(h_traj.encoding.front().reconSpace.matrixSize.z * factor_2r);
 
                                         header.encoding.front().encodedSpace.fieldOfView_mm.x=h_traj.encoding.front().reconSpace.fieldOfView_mm.x;
                                         header.encoding.front().encodedSpace.fieldOfView_mm.y=h_traj.encoding.front().reconSpace.fieldOfView_mm.y;
@@ -138,7 +146,7 @@ namespace {
 
 
                                         // Modifying the header encodingLimits :
-                                        
+
                                         header.encoding.at(0).encodingLimits.kspace_encoding_step_1.get().maximum =h_traj.encoding.front().encodingLimits.kspace_encoding_step_1.get().maximum;
                                         header.encoding.at(0).encodingLimits.kspace_encoding_step_2.get().maximum =h_traj.encoding.front().encodingLimits.segment.get().maximum;
 
@@ -149,13 +157,20 @@ namespace {
                                         GDEBUG_STREAM("Recon FOV: X " << header.encoding.front().reconSpace.fieldOfView_mm.x << " Y " << header.encoding.front().reconSpace.fieldOfView_mm.y << " Z " << header.encoding.front().reconSpace.fieldOfView_mm.z);
                                         GDEBUG_STREAM("Encoding Limits: Encoded step 1 max " << header.encoding.at(0).encodingLimits.kspace_encoding_step_1.get().maximum  << " Encoded step 2 max " << header.encoding.at(0).encodingLimits.kspace_encoding_step_2.get().maximum  );
 
+                                        seq_found = true;
                                         break;
                                     }
                                 }
-                                
+
                             }
+                            if (seq_found) break;
 
                         }
+                        if (seq_found) break;
+                        }
+                        if (!seq_found) {
+                            GDEBUG_STREAM("Seq file not found in any search path for hash " << hash_bstar);
+                        }
                     }
                 }
             }

test/nhlbi_integration_tests/cases/imoco_vds.cfg

@@ -0,0 +1,36 @@
+[dependency.siemens]
+data_file = imoco_vds/noise_data.h5
+measurement = 0
+additional_arguments = skip_converstion
+
+[dependency.client]
+configuration = default_measurement_dependencies.xml
+
+[reconstruction.siemens]
+data_file = imoco_vds/recon_data.h5
+measurement = 0
+additional_arguments = skip_converstion
+
+[reconstruction.client]
+configuration = imoco_recon_vds.xml
+
+[reconstruction.test]
+reference_file = imoco_vds/baseline_output.h5
+reference_images = imoco_recon_vds.xml/image_0
+output_images = imoco_recon_vds.xml/image_0
+value_comparison_threshold = 0.01
+scale_comparison_threshold = 0.01
+
+[requirements]
+system_memory = 8192
+gpu_support = 1
+gpu_memory = 8192
+
+[tags]
+tags = nhlbi,imoco
+
+[nhlbi]
+description = iMOCO VDS 3D lung reconstruction
+noise_file = imoco_vds/noise_data.h5
+baseline_recon_time = 386.0
+

test/nhlbi_integration_tests/cases/mocolr_bSTAR.cfg

@@ -0,0 +1,44 @@
+[dependency.siemens]
+data_file = mocolr_bSTAR/noise_data.h5
+measurement = 0
+additional_arguments = skip_converstion
+
+[dependency.client]
+configuration = default_measurement_dependencies.xml
+
+[reconstruction.siemens]
+data_file = mocolr_bSTAR/recon_data.h5
+measurement = 0
+additional_arguments = skip_converstion
+
+[reconstruction.client]
+configuration = pulmonary_echo0.xml
+
+[reconstruction.test.1]
+reference_file = mocolr_bSTAR/baseline_output.h5
+reference_images = pulmonary_echo0.xml/image_6
+output_images = pulmonary_echo0.xml/image_6
+value_comparison_threshold = 0.01
+scale_comparison_threshold = 0.01
+
+[reconstruction.test.2]
+reference_file = mocolr_bSTAR/baseline_output.h5
+reference_images = pulmonary_echo0.xml/image_7
+output_images = pulmonary_echo0.xml/image_7
+value_comparison_threshold = 0.01
+scale_comparison_threshold = 0.01
+
+[requirements]
+system_memory = 8192
+gpu_support = 1
+gpu_memory = 8192
+
+[tags]
+tags = nhlbi,mocolr,bSTAR,lung
+
+[nhlbi]
+description = MOCO Low Rank respiratory resolved pulmonary reconstruction
+noise_file = mocolr_bSTAR/noise_data.h5
+additional_dataset_0 = mocolr_bSTAR/bstar_450mm_1.20mm_true0_TR2.32ms_rf200_i110_67k_FA40_WASP_self0_fid0_noise0.seq
+additional_dataset_1 = mocolr_bSTAR/traj_bstar_450mm_1.20mm_true0_TR2.32ms_rf200_i110_67k_FA40_WASP_self0_fid0_noise0.h5
+baseline_recon_time = 179.6

test/nhlbi_integration_tests/delete_test.py

@@ -0,0 +1,105 @@
+#!/usr/bin/env python3
+"""Remove an NHLBI integration test case.
+
+Deletes the .cfg file, removes manifest entries, and optionally deletes
+the associated Azure Blob Storage data.
+
+Usage:
+    python delete_test.py imoco_vds
+    python delete_test.py imoco_vds --keep-data
+"""
+
+import argparse
+import sys
+from pathlib import Path
+
+from get_nhlbi_data import get_container_client, load_manifest, save_manifest
+
+CASES_DIR = Path(__file__).parent / "cases"
+BASELINES_DIR = Path(__file__).parent / "baselines"
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Remove an NHLBI integration test",
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+    )
+    parser.add_argument('name', help="Test case name to delete")
+    parser.add_argument('--keep-data', action='store_true',
+                        help="Keep Azure blobs; only remove local .cfg and manifest entries")
+    parser.add_argument('--yes', '-y', action='store_true',
+                        help="Skip confirmation prompt")
+
+    args = parser.parse_args()
+    name = args.name
+
+    cfg_path = CASES_DIR / f"{name}.cfg"
+    manifest = load_manifest()
+    test_entries = [e for e in manifest if e.get('test') == name]
+
+    if not cfg_path.exists() and not test_entries:
+        print(f"Error: Test '{name}' not found")
+        sys.exit(1)
+
+    # Show what will be deleted
+    print(f"Test: {name}")
+    if cfg_path.exists():
+        print(f"  Config: {cfg_path}")
+    if test_entries:
+        print(f"  Manifest entries: {len(test_entries)}")
+        for entry in test_entries:
+            print(f"    - {entry['file']} ({entry.get('type', 'unknown')})")
+    if not args.keep_data and test_entries:
+        print(f"  Azure blobs: {len(test_entries)} will be deleted")
+    else:
+        print(f"  Azure blobs: kept")
+
+    baseline_dir = BASELINES_DIR / name
+    if baseline_dir.exists():
+        print(f"  Local baselines: {baseline_dir}")
+
+    # Confirm
+    if not args.yes:
+        action = "and Azure blobs" if not args.keep_data else "(keeping Azure data)"
+        response = input(f"\nDelete test '{name}' {action}? [y/N] ").strip().lower()
+        if response not in ('y', 'yes'):
+            print("Cancelled.")
+            sys.exit(0)
+
+    # Delete Azure blobs
+    if not args.keep_data and test_entries:
+        try:
+            container_client = get_container_client()
+            for entry in test_entries:
+                blob_name = entry['file']
+                try:
+                    blob_client = container_client.get_blob_client(blob_name)
+                    blob_client.delete_blob()
+                    print(f"  Deleted blob: {blob_name}")
+                except Exception as e:
+                    print(f"  Warning: Could not delete blob {blob_name}: {e}")
+        except Exception as e:
+            print(f"  Warning: Could not connect to Azure: {e}")
+            print("  Local files will still be removed.")
+
+    # Remove from manifest
+    remaining = [e for e in manifest if e.get('test') != name]
+    save_manifest(remaining)
+    print(f"  Removed {len(test_entries)} manifest entries")
+
+    # Delete .cfg
+    if cfg_path.exists():
+        cfg_path.unlink()
+        print(f"  Deleted {cfg_path}")
+
+    # Delete local baseline directory
+    if baseline_dir.exists():
+        import shutil
+        shutil.rmtree(baseline_dir)
+        print(f"  Deleted {baseline_dir}")
+
+    print(f"\nTest '{name}' removed successfully.")
+
+
+if __name__ == '__main__':
+    main()