finishing library migration

.gitignore

@@ -176,4 +176,7 @@ build
 
 librir/libs/*
 
-plugins/*
+plugins/*
+
+
+.vscode/*

librir/video_io/IRMovie.py

@@ -9,6 +9,13 @@
 import numpy as np
 from librir.tools.utils import init_thermavip, unbind_thermavip_shared_mem
 from librir.tools.FileAttributes import FileAttributes
+from typing import List, Dict, Union
+
+from librir.low_level.rir_video_io import (
+    enable_motion_correction,
+    load_motion_correction_file,
+    motion_correction_enabled,
+)
 from typing import List, Dict
 
 from librir.low_level.rir_video_io import (
@@ -52,6 +59,10 @@ class IncoherentMetadata(Exception):
     pass
 
 
+class CalibrationNotFound(Exception):
+    pass
+
+
 def create_pcr_header(rows, columns, frequency=50, bits=16):
     pcr_header = np.zeros((256,), dtype=np.uint32)
     pcr_header[2] = columns
@@ -68,7 +79,7 @@ class IRMovie(object):
     _header_offset = 1024
     __tempfile__ = None
     handle = -1
-
+    _calibration_nickname_mapper = {"DL": "Digital Level"}
     _roi_result_line = {"CEDIP": 240, "WEST": 512, "NIT": 256}
 
     _SHAPES = {
@@ -151,17 +162,40 @@ def __init__(self, handle):
 
         try:
             self.calibration = "T"
-        except (IndexError, ValueError):
+        except (IndexError, ValueError, CalibrationNotFound):
             logger.debug(
-                f"There is no temperature calibration. Switching back to Digital Level"
+                "There is no temperature calibration. Switching back to Digital Level"
             )
+            self.calibration = "DL"
 
-        # if not ('Type' in self.attributes):
-        #     d = self.attributes
-        #     # inv_shapes = {v: k for k, v in self._SHAPES.items()}
-        #     d['Type'] = self._SHAPES[self.image_size].encode('utf8')
-        #     self.attributes = d
-        #     # self._file_attributes.flush()
+    @property
+    def calibration(self):
+        return list(self._calibration_nickname_mapper.keys())[self._calibration_index]
+
+    @calibration.setter
+    def calibration(self, value: Union[str, int]):
+        searching_keys = self.calibrations + list(
+            self._calibration_nickname_mapper.keys()
+        )
+        _calibrations = self.calibrations
+        if isinstance(value, int):
+            if value >= len(_calibrations):
+                raise CalibrationNotFound(
+                    f"Available calibrations : {self.calibrations}."
+                    "Calibration index out of range"
+                )
+
+            self._calibration_index = value
+            return
+
+        if value not in searching_keys:
+            raise CalibrationNotFound(f"Available calibrations : {self.calibrations}")
+        try:
+            self._calibration_index = list(self._calibration_nickname_mapper).index(
+                value
+            )
+        except ValueError as e:
+            raise CalibrationNotFound(f"calibration {value} is not registered")
 
     def __enter__(self):
         """
@@ -195,12 +229,11 @@ def close(self):
                 logger.warning(p_exc)
 
             self.__tempfile__ = None
-
-
+
     @property
     def registration_file(self) -> Path:
         """
-        Returns the registration file name for this camera, and tries to download it 
+        Returns the registration file name for this camera, and tries to download it
         from ARCADE if not already done.
         """
 
@@ -283,7 +316,9 @@ def load_pos(self, pos, calibration=None):
         """Returns the image at given position using given calibration index (integer)"""
         if calibration is None:
             calibration = 0
-        res = load_image(self.handle, pos, calibration)
+
+        self.calibration = calibration
+        res = load_image(self.handle, pos, self._calibration_index)
         self._frame_attributes_d[pos] = get_attributes(self.handle)
         # self.frame_attributes = get_attributes(self.handle)
         return res

pytest.ini

@@ -0,0 +1,8 @@
+[pytest]
+markers =
+    slow: marks tests as slow (deselect with '-m "not slow"')
+    concurrent: Concurrent and parallel jobs
+    h264
+    thermavip
+    io
+    needs_improvement

tests/python/conftest.py

@@ -1,5 +1,5 @@
 import logging
-import os
+
 import sys
 from pathlib import Path
 
@@ -13,11 +13,8 @@
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.DEBUG)
 
-pulse = 56927
 base = Path(thismodule.__file__).parent
 
-ROWS = 512
-COLUMNS = 640
 IMAGES = 10
 N_TIS = 7
 DL_MAX_VALUE = 8192
@@ -33,7 +30,7 @@ def generate_mock_movie_data_uniform(*shape):
     tis = np.zeros(shape, dtype=np.uint16)
     step = 2**13
     if n_images > 1:
-        step /= n_images - 1
+        step /= n_images - 2
 
     for i in range(n_images):
         tis[i] = i % N_TIS
@@ -67,14 +64,15 @@ def generate_random_movie_data(n_rows, n_columns, n_images):
 VALID_3D_SHAPES = [
     (1, 512, 640),
     (10, 512, 640),
-    (10, 515, 640),
+    (10, 515, 640),  # pb
     (10, 240, 320),
-    (10, 243, 320),
+    (10, 243, 320),  # pb
     (10, 256, 320),
     (10, 259, 320),
 ]
 VALID_2D_SHAPES = [
     (512, 640),
+    (515, 640),
 ]
 
 VALID_SHAPES = VALID_2D_SHAPES + VALID_3D_SHAPES
@@ -85,8 +83,6 @@ def generate_random_movie_data(n_rows, n_columns, n_images):
 ]
 
 
-
-
 VALID_UNIFORM_2D_NUMPY_ARRAYS = [
     generate_mock_movie_data_uniform(*shape) for shape in VALID_2D_SHAPES
 ]
@@ -106,41 +102,41 @@ def generate_random_movie_data(n_rows, n_columns, n_images):
 VALID_MASKS = [generate_constant_mask_array(*shape) for shape in VALID_3D_SHAPES]
 
 
-
 # @pytest.fixture(scope="module")
 # def uniform_movies():
 #     return [IRMovie.from_numpy_array(arr) for arr in VALID_UNIFORM_NUMPY_ARRAYS]
 
 
-
 @pytest.fixture(scope="session", params=VALID_SHAPES)
 def array(request):
     shape = request.param
     yield generate_mock_movie_data_uniform(*shape)
-
+
+
 @pytest.fixture(scope="session", params=VALID_3D_SHAPES)
 def valid_3d_array(request):
     shape = request.param
     yield generate_mock_movie_data_uniform(*shape)
-    
-    
+
+
 @pytest.fixture(scope="session", params=INVALID_SHAPES)
 def bad_array(request):
     shape = request.param
     yield generate_mock_movie_data_uniform(*shape)
-    
+
 
 @pytest.fixture(scope="session", params=VALID_2D_SHAPES)
 def valid_2D_array(request):
     shape = request.param
     yield generate_mock_movie_data_uniform(*shape)
 
+
 @pytest.fixture(scope="session")
 def movie(array):
-    return IRMovie.from_numpy_array(array)
+    with IRMovie.from_numpy_array(array) as mov:
+        yield mov
+
 
 @pytest.fixture(scope="session")
 def filename(movie):
     return movie.filename
-
-# filenames = pytest.mark.parametrize("filenames", [mov.filename for mov in uniform_movies])

tests/python/create_file_for_tests.py

@@ -31,7 +31,7 @@ def generate_mock_movie_data_uniform(*shape):
 
     dl = np.zeros(shape, dtype=np.uint16)
     tis = np.zeros(shape, dtype=np.uint16)
-    step = 2 ** 13
+    step = 2**13
     if n_images > 1:
         step /= n_images - 1
 
@@ -66,10 +66,10 @@ def generate_constant_mask_array(*shape):
 
 def generate_random_movie_data(n_rows, n_columns, n_images):
     dl = np.random.randint(
-        0, (2 ** 13), size=(n_images, n_rows, n_columns), dtype=np.uint16
+        0, (2**13), size=(n_images, n_rows, n_columns), dtype=np.uint16
     )  # >> 16  & (2**13)-1
     tis = np.random.randint(
-        0, (2 ** 3) - 1, size=(n_images, n_rows, n_columns), dtype=np.uint16
+        0, (2**3) - 1, size=(n_images, n_rows, n_columns), dtype=np.uint16
     )  # >> 29 & (2**3)-1
 
     data = dl | (tis << 13)