Revert "Implementation of external Zernike3D distance"

src/cryo_challenge/_map_to_map/map_to_map_distance.py

@@ -1,5 +1,3 @@
-import os
-import subprocess
 import math
 import torch
 from typing import Optional, Sequence
@@ -57,7 +55,6 @@ def get_distance_matrix(self, maps1, maps2, global_store_of_running_results):
         """Compute the distance matrix between two sets of maps."""
         if self.config["data"]["mask"]["do"]:
             maps2 = maps2[:, self.mask]
-
         else:
             maps2 = maps2.reshape(len(maps2), -1)
 
@@ -90,8 +87,6 @@ def get_distance_matrix(self, maps1, maps2, global_store_of_running_results):
 
         else:
             maps1 = maps1.reshape(len(maps1), -1)
-            if self.config["data"]["mask"]["do"]:
-                maps1 = maps1.reshape(len(maps1), -1)[:, self.mask]
             maps2 = maps2.reshape(len(maps2), -1)
             distance_matrix = torch.vmap(
                 lambda maps1: torch.vmap(
@@ -403,80 +398,3 @@ def res_at_fsc_threshold(fscs, threshold=0.5):
         res_fsc_half, fraction_nyquist = res_at_fsc_threshold(fsc_matrix)
         self.stored_computed_assets = {"fraction_nyquist": fraction_nyquist}
         return units_Angstroms[res_fsc_half]
-
-
-class Zernike3DDistance(MapToMapDistance):
-    """Zernike3D based distance.
-
-    Zernike3D distance relies on the estimation of the non-linear transformation needed to align two different maps.
-    The RMSD of the associated non-linear alignment represented as a deformation field is then used as the distance
-    between two maps
-    """
-
-    @override
-    def get_distance_matrix(self, maps1, maps2, global_store_of_running_results):
-        gpuID = self.config["analysis"]["zernike3d_extra_params"]["gpuID"]
-        outputPath = self.config["analysis"]["zernike3d_extra_params"]["tmpDir"]
-        thr = self.config["analysis"]["zernike3d_extra_params"]["thr"]
-        numProjections = self.config["analysis"]["zernike3d_extra_params"][
-            "numProjections"
-        ]
-
-        # Create output directory
-        if not os.path.isdir(outputPath):
-            os.mkdir(outputPath)
-
-        # Prepare data to call external
-        targets_paths = os.path.join(outputPath, "target_maps.npy")
-        references_path = os.path.join(outputPath, "reference_maps.npy")
-        if not os.path.isfile(targets_paths):
-            np.save(targets_paths, maps1)
-        if not os.path.isfile(references_path):
-            np.save(references_path, maps2)
-
-        # Check conda is in PATH (otherwise abort as external software is not installed)
-        try:
-            subprocess.check_call("conda", shell=True, stdout=subprocess.PIPE)
-        except FileNotFoundError:
-            raise Exception("Conda not found in PATH... Aborting")
-
-        # Check if conda env is installed
-        env_installed = subprocess.run(
-            r"conda env list | grep 'flexutils-tensorflow '",
-            shell=True,
-            check=False,
-            stdout=subprocess.PIPE,
-        ).stdout
-        env_installed = bool(
-            env_installed.decode("utf-8").replace("\n", "").replace("*", "")
-        )
-        if not env_installed:
-            raise Exception("External software not found... Aborting")
-
-        # Find conda executable (needed to activate conda envs in a subprocess)
-        condabin_path = subprocess.run(
-            r"which conda | sed 's: ::g'",
-            shell=True,
-            check=False,
-            stdout=subprocess.PIPE,
-        ).stdout
-        condabin_path = condabin_path.decode("utf-8").replace("\n", "").replace("*", "")
-
-        # Call external program
-        subprocess.check_call(
-            f'eval "$({condabin_path} shell.bash hook)" &&'
-            f" conda activate flexutils-tensorflow && "
-            f"compute_distance_matrix_zernike3deep.py --references_file {references_path} "
-            f"--targets_file {targets_paths} --out_path {outputPath} --gpu {gpuID} --num_projections {numProjections} "
-            f"--thr {thr}",
-            shell=True,
-        )
-
-        # Read distance matrix
-        dists = np.load(os.path.join(outputPath, "dist_mat.npy")).T
-        self.stored_computed_assets = {"zernike3d": dists}
-        return dists
-
-    @override
-    def get_computed_assets(self, maps1, maps2, global_store_of_running_results):
-        return self.stored_computed_assets  # must run get_distance_matrix first

src/cryo_challenge/_map_to_map/map_to_map_pipeline.py

@@ -9,7 +9,6 @@
     L2DistanceNorm,
     BioEM3dDistance,
     FSCResDistance,
-    Zernike3DDistance,
 )
 
 
@@ -19,7 +18,6 @@
     "l2": L2DistanceNorm,
     "bioem": BioEM3dDistance,
     "res": FSCResDistance,
-    "zernike3d": Zernike3DDistance,
 }
 
 
@@ -53,7 +51,6 @@ def run(config):
     maps_user_flat = submission[submission_volume_key].reshape(
         len(submission["volumes"]), -1
     )
-
     maps_gt_flat = torch.load(
         config["data"]["ground_truth"]["volumes"], mmap=do_low_memory_mode
     )

src/cryo_challenge/data/_validation/output_validators.py

@@ -31,7 +31,6 @@ class MapToMapResultsValidator:
     bioem: Optional[dict] = None
     fsc: Optional[dict] = None
     res: Optional[dict] = None
-    zernike3d: Optional[dict] = None
 
     def __post_init__(self):
         validate_input_config_mtm(self.config)
@@ -152,7 +151,6 @@ class DistributionToDistributionResultsValidator:
     res: Optional[dict] = None
     l2: Optional[dict] = None
     corr: Optional[dict] = None
-    zernike3d: Optional[dict] = None
 
     def __post_init__(self):
         validate_input_config_disttodist(self.config)

tests/config_files/test_config_map_to_map.yaml

@@ -11,7 +11,7 @@ data:
     metadata: tests/data/Ground_truth/test_metadata_10.csv
   mask:
     do: true
-    volume: tests/data/Ground_truth/test_mask_bool.mrc
+    volume: tests/data/Ground_truth/test_mask_dilated_wide.mrc
 analysis:
   metrics:
     - l2

tests/config_files/test_config_map_to_map_low_memory_subbatch.yaml

@@ -11,7 +11,7 @@ data:
     metadata: tests/data/Ground_truth/test_metadata_10.csv
   mask:
     do: true
-    volume: tests/data/Ground_truth/test_mask_bool.mrc
+    volume: tests/data/Ground_truth/test_mask_dilated_wide.mrc
 analysis:
   metrics:
     - l2

tests/config_files/test_config_map_to_map_nomask_nonormalize.yaml

@@ -11,7 +11,7 @@ data:
     metadata: tests/data/Ground_truth/test_metadata_10.csv
   mask:
     do: false
-    volume: tests/data/Ground_truth/test_mask_bool.mrc
+    volume: tests/data/Ground_truth/test_mask_dilated_wide.mrc
 analysis:
   metrics:
     - l2

tests/test_map_to_map.py

@@ -4,18 +4,6 @@
 
 
 def test_run_map2map_pipeline():
-    try:
-        args = OmegaConf.create(
-            {"config": "tests/config_files/test_config_map_to_map_external.yaml"}
-        )
-        results_dict = run_map2map_pipeline.main(args)
-        assert "zernike3d" in results_dict.keys()
-    except Exception as e:
-        print(e)
-        print(
-            "External test failed. Skipping test. Fails when running in CI if external dependencies are not installed."
-        )
-
     for config_fname, config_fname_low_memory in zip(
         [
             "tests/config_files/test_config_map_to_map.yaml",