From 0c534da94a543b82f0dcb579b0f6e7ba265fd897 Mon Sep 17 00:00:00 2001 From: vinush-vignes Date: Thu, 18 Jan 2024 17:09:30 +0000 Subject: [PATCH] removed mesh_normals var --- openep/data_structures/surface.py | 7 ------- openep/io/writers.py | 2 -- 2 files changed, 9 deletions(-) diff --git a/openep/data_structures/surface.py b/openep/data_structures/surface.py index bb9988d1..77a05053 100644 --- a/openep/data_structures/surface.py +++ b/openep/data_structures/surface.py @@ -53,7 +53,6 @@ class Fields: pacing_site: np.ndarray = None conduction_velocity: np.ndarray = None cv_divergence: np.ndarray = None - mesh_normals : np.ndarray = None def __repr__(self): return f"fields: {tuple(self.__dict__.keys())}" @@ -204,11 +203,6 @@ def extract_surface_data(surface_data): except KeyError as e: cv_divergence = None - try: - mesh_normals = surface_data['mesh_normals'].astype(float) - except KeyError as e: - mesh_normals = None - fields = Fields( bipolar_voltage=bipolar_voltage, unipolar_voltage=unipolar_voltage, @@ -222,7 +216,6 @@ def extract_surface_data(surface_data): pacing_site=pacing_site, conduction_velocity=conduction_velocity, cv_divergence=cv_divergence, - mesh_normals=mesh_normals ) return points, indices, fields diff --git a/openep/io/writers.py b/openep/io/writers.py index 7b503371..854f2ff6 100644 --- a/openep/io/writers.py +++ b/openep/io/writers.py @@ -172,7 +172,6 @@ def export_openCARP( def export_openep_mat( case: Case, filename: str, - separate_regions: bool = False, ): """Export data in OpenEP format. @@ -366,7 +365,6 @@ def _extract_surface_data( surface_data['longitudinal'] = fields.longitudinal_fibres if fields.longitudinal_fibres is not None else empty_float_array surface_data['transverse'] = fields.transverse_fibres if fields.transverse_fibres is not None else empty_float_array surface_data['pacing_site'] = fields.pacing_site if fields.pacing_site is not None else empty_int_array - surface_data['mesh_normals'] = fields.mesh_normals if fields.mesh_normals is not None else empty_int_array # Remove arrays that are full of NaNs for field_name, field in surface_data.items():