clatlan · clatlan · Jun 7, 2024 · May 22, 2024 · May 22, 2024 · May 22, 2024
diff --git a/cdiutils/__init__.py b/cdiutils/__init__.py
@@ -1,7 +1,11 @@
 from . import load, plot, process
+from .geometry import Geometry
+from .converter import SpaceConverter
 
 __all__ = [
     "load",
     "plot",
-    "process"
+    "process",
+    "Geometry",
+    "SpaceConverter"
 ]
diff --git a/cdiutils/converter.py b/cdiutils/converter.py
@@ -366,7 +366,7 @@ def _check_shape(self, shape: tuple) -> None:
     def init_interpolator(
             self,
             detector_data: np.ndarray,
-            direct_space_data_shape: tuple = None,
+            direct_space_data_shape: tuple | np.ndarray | list = None,
             direct_space_voxel_size: tuple | np.ndarray | list | float = None,
             space: str = "direct",
             shift_voxel: tuple = None
@@ -414,6 +414,7 @@ def init_interpolator(
                     "if space is 'direct' direct_space_data_shape must be "
                     "provided."
                 )
+            direct_space_data_shape = tuple(direct_space_data_shape)
             if shape != direct_space_data_shape:
                 raise ValueError(
                     "The cropped_raw_data should have the same shape as the "

diff --git a/cdiutils/geometry.py b/cdiutils/geometry.py
@@ -39,33 +39,50 @@ def from_setup(cls, beamline_setup: str) -> None:
         """Create a Geometry instance using a beamline name."""
 
         # Note that we use CXI convention here
-        if beamline_setup in ("ID01", "ID01SPEC", "ID01BLISS"):
+        if beamline_setup.lower() in ("id01", "id01spec", "id01bliss"):
             return cls(
                 sample_circles=["x-", "y-"],  # eta, phi
-                detector_circles=["y-", "x-"],  # delta, nu
+                detector_circles=["y-", "x-"],  # nu, delta
                 detector_vertical_orientation="y-",
                 detector_horizontal_orientation="x+",
                 beam_direction=[1, 0, 0]
             )
-        if "P10" in beamline_setup:
+        if "p10" in beamline_setup.lower():
             return cls(
                 sample_circles=["x-", "y-"],  # om (or samth), phi
-                detector_circles=["y+", "x-"],  # del (or e2_t02), gam
+                detector_circles=["y+", "x-"],  # gam, del (or e2_t02)
                 detector_vertical_orientation="y-",
                 detector_horizontal_orientation="x+",
                 beam_direction=[1, 0, 0]
             )
-        if beamline_setup == "SIXS2022":
+        if beamline_setup.lower() == "sixs2022":
             return cls(
                 sample_circles=["x-", "y+"],  # mu, omega
-                detector_circles=["y+", "x-"],  # gamma, delta
+                detector_circles=["y+", "x-"],  # gamma, delta  NOT SURE OF THE COMMENT
+                detector_vertical_orientation="y-",
+                detector_horizontal_orientation="x+",
+                beam_direction=[1, 0, 0]
+            )
+        if beamline_setup.lower() == "nanomax":
+            return cls(
+                sample_circles=["x-", "y-"],  # gontheta, gonphi
+                detector_circles=["y-", "x-"],  # gamma, delta
+                detector_vertical_orientation="y+",
+                detector_horizontal_orientation="x-",
+                beam_direction=[1, 0, 0]
+            )
+        if beamline_setup.lower() == "cristal":
+            return cls(
+                sample_circles=["x-", "y+"],  # omega, phi
+                detector_circles=["y+", "x-"],  # gamma, delta  OK FOR omega/delta but not for the two others
                 detector_vertical_orientation="y-",
                 detector_horizontal_orientation="x+",
                 beam_direction=[1, 0, 0]
             )
         raise NotImplementedError(
             f"The beamline_setup {beamline_setup} is not valid. Available:\n"
-            "'ID01', 'ID01SPEC', 'ID01BLISS', 'P10' , 'SIXS2022'"
+            "'ID01', 'ID01SPEC', 'ID01BLISS', 'P10', 'P10EH2', 'SIXS2022' "
+            "and NanoMAX."
         )
 
     def cxi_to_xu(self) -> None:

diff --git a/cdiutils/load/bliss.py b/cdiutils/load/bliss.py
@@ -4,7 +4,6 @@
 import hdf5plugin
 import silx.io.h5py_utils
 
-from cdiutils.utils import CroppingHandler
 from cdiutils.load import Loader
 
 
@@ -23,10 +22,10 @@ class BlissLoader(Loader):
     """
 
     angle_names = {
-            "sample_outofplane_angle": "eta",
-            "sample_inplane_angle": "phi",
-            "detector_outofplane_angle": "delta",
-            "detector_inplane_angle": "nu"
+        "sample_outofplane_angle": "eta",
+        "sample_inplane_angle": "phi",
+        "detector_outofplane_angle": "delta",
+        "detector_inplane_angle": "nu"
     }
 
     def __init__(
@@ -79,12 +78,7 @@ def load_detector_data(
             + f".1/measurement/{self.detector_name}"
         )
 
-        if roi is None:
-            roi = tuple(slice(None) for i in range(3))
-        elif len(roi) == 2:
-            roi = tuple([slice(None), roi[0], roi[1]])
-        elif all(isinstance(e, int) for e in roi):
-            roi = CroppingHandler.roi_list_to_slices(roi)
+        roi = self._check_roi(roi)
 
         try:
             if binning_along_axis0:

diff --git a/cdiutils/load/loader.py b/cdiutils/load/loader.py
@@ -2,6 +2,8 @@
 
 import numpy as np
 
+from cdiutils.utils import CroppingHandler
+
 
 class Loader:
     """A generic class for loaders."""
@@ -86,6 +88,39 @@ def _check_load(data_or_path: np.ndarray | str) -> np.ndarray:
             "parameter provide a path, np.ndarray or leave it to None"
         )
 
+    @staticmethod
+    def _check_roi(roi: tuple = None) -> tuple[slice]:
+        """
+        Utility function to check if a region of interest (roi) was
+        parsed correctly.
+
+        Args:
+            roi (tuple, optional): the roi, a tuple of slices.
+                len = 2 or len = 3 if tuple of slices. len = 4 or
+                len = 6 if tuple of int. Defaults to None.
+
+        Raises:
+            ValueError: if roi does not correspond to tuple of slices
+                with len 2 or 3 or tuple of int wit len 4 or 6.
+
+        Returns:
+            tuple[slice]: the prepared roi.
+        """
+        usage_text = (
+            "Wrong value for roi (roi={}), roi should be:\n"
+            "\t - either a tuple of slices with len = 2 or len = 3"
+            "\t - either a tuple of int with len = 4 or len = 6"
+        )
+        if roi is None:
+            return tuple(slice(None) for _ in range(3))
+        if len(roi) == 2 or len(roi) == 3:
+            if all(isinstance(e, slice) for e in roi):
+                return (slice(None), roi[0], roi[1])
+        if len(roi) == 4 or len(roi) == 6:
+            if all(isinstance(e, int) for e in roi):
+                return CroppingHandler.roi_list_to_slices(roi)
+        raise ValueError(usage_text.format(roi))
+
     @staticmethod
     def get_mask(
             channel: int = None,

diff --git a/cdiutils/load/nanomax.py b/cdiutils/load/nanomax.py
@@ -0,0 +1,106 @@
+"""
+Loader for the Nanomax beamlien at MAXIV.
+See:
+https://www.maxiv.lu.se/beamlines-accelerators/beamlines/nanomax/
+"""
+
+import numpy as np
+
+from cdiutils.load import Loader
+from cdiutils.load.bliss import safe
+
+
+class NanoMaxLoader(Loader):
+    """
+    A class to handle loading/reading .h5 files that were created at the
+    NanoMax beamline.
+
+    Args:
+        experiment_file_path (str): path to the master file
+            used for the experiment.
+        detector_name (str): name of the detector.
+        sample_name (str, optional): name of the sample. Defaults
+            to None.
+        flat_field (np.ndarray | str, optional): flat field to
+            account for the non homogeneous counting of the
+            detector. Defaults to None.
+        alien_mask (np.ndarray | str, optional): array to mask the
+            aliens. Defaults to None.
+    """
+
+    angle_names = {
+        "sample_outofplane_angle": "gontheta",
+        "sample_inplane_angle": "gonphi",
+        "detector_outofplane_angle": "delta",
+        "detector_inplane_angle": "nu"
+    }
+
+    def __init__(
+            self,
+            experiment_file_path: str,
+            detector_name: str = "eiger500k",
+            sample_name: str = None,
+            flat_field: np.ndarray | str = None,
+            alien_mask: np.ndarray | str = None,
+            **kwargs
+    ) -> None:
+        """
+        Initialise NanoMaxLoader with experiment data file path and
+        detector information.
+
+        Args:
+            experiment_file_path (str): path to the master file
+                used for the experiment.
+            detector_name (str): name of the detector.
+            sample_name (str, optional): name of the sample. Defaults
+                to None.
+            flat_field (np.ndarray | str, optional): flat field to
+                account for the non homogeneous counting of the
+                detector. Defaults to None.
+            alien_mask (np.ndarray | str, optional): array to mask the
+                aliens. Defaults to None.
+        """
+        super(NanoMaxLoader, self).__init__(flat_field, alien_mask)
+        self.experiment_file_path = experiment_file_path
+        self.detector_name = detector_name
+        self.sample_name = sample_name
+
+    @safe
+    def load_detector_data(
+            self,
+            scan: int,
+            sample_name: str = None,
+            roi: tuple[slice] = None,
+            binning_along_axis0: int = None,
+            binnig_method: str = "sum"
+    ) -> np.ndarray:
+        """
+        Main method to load the detector data (collected intensity).
+
+        Args:
+            scan (int): the scan number you want to load the data from.
+            sample_name (str, optional): the sample name for this scan.
+                Only used if self.sample_name is None. Defaults to None.
+            roi (tuple[slice], optional): the region of interest of the
+                detector to load. Defaults to None.
+            binning_along_axis0 (int, optional): whether to bin the data
+                along the rocking curve axis. Defaults to None.
+            binnig_method (str, optional): the method employed for the
+                binning. It can be sum or "mean". Defaults to "sum".
+
+        Returns:
+            np.ndarray: the detector data.
+        """
+        # # The self.h5file is initialised by the @safe decorator.
+        # h5file = self.h5file
+        # if sample_name is None:
+        #     sample_name = self.sample_name
+
+        # # Where to find the data.
+        # key_path = (
+        #     "_".join((sample_name, str(scan)))
+        #     + f"/entry/measurement/{self.detector_name}"
+        # )
+
+        # roi = self._check_roi(roi)
+        pass
diff --git a/cdiutils/load/p10.py b/cdiutils/load/p10.py
@@ -127,10 +127,7 @@ def load_detector_data(
         path = self._get_file_path(scan, sample_name)
         key_path = "entry/data/data_000001"
 
-        if roi is None:
-            roi = tuple(slice(None) for i in range(3))
-        elif len(roi) == 2:
-            roi = tuple([slice(None), roi[0], roi[1]])
+        roi = self._check_roi(roi)
 
         with silx.io.h5py_utils.File(path) as h5file:
             if binning_along_axis0:

diff --git a/cdiutils/load/sixs.py b/cdiutils/load/sixs.py
@@ -107,10 +107,7 @@ def load_detector_data(
         path = self._get_file_path(scan, sample_name)
         key_path = "com/scan_data/test_image"
 
-        if roi is None:
-            roi = tuple(slice(None) for i in range(3))
-        elif len(roi) == 2:
-            roi = tuple([slice(None), roi[0], roi[1]])
+        roi = self._check_roi(roi)
 
         with silx.io.h5py_utils.File(path) as h5file:
             if binning_along_axis0:

diff --git a/cdiutils/load/spec.py b/cdiutils/load/spec.py
@@ -66,10 +66,7 @@ def load_detector_data(
             roi: tuple[slice] = None,
             binning_along_axis0=None
     ):
-        if roi is None:
-            roi = tuple(slice(None) for i in range(3))
-        elif len(roi) == 2:
-            roi = tuple([slice(None), roi[0], roi[1]])
+        roi = self._check_roi(roi)
 
         # TODO: implement flat_field consideration and binning_along_axis0
         frame_ids = specfile[f"{scan}.1/measurement/{self.detector_name}"][...]

diff --git a/cdiutils/plot/formatting.py b/cdiutils/plot/formatting.py
@@ -38,7 +38,7 @@ def get_extents(
             to the y-axis extent in the matshow/imshow plot.
     """
     absolute_extents = [
-        voxel_size[i] * shape[i] // (2 if zero_centered else 1)
+        voxel_size[i] * shape[i] / (2 if zero_centered else 1)
         for i in range(3)
     ]
     return (

diff --git a/cdiutils/process/parameters.py b/cdiutils/process/parameters.py
@@ -62,7 +62,7 @@
         "support_update_period": 20,
         "support_smooth_width_begin": 2,
         "support_smooth_width_end": 1,
-        "support_post_expand": None,
+        "support_post_expand": None,  # (-1, 1)
         "psf": "pseudo-voigt,0.5,0.1,10",
         "nb_raar": 500,
         "nb_hio": 300,

diff --git a/cdiutils/process/phaser.py b/cdiutils/process/phaser.py
@@ -47,8 +47,8 @@
     # support-related params
     "support_threshold": (0.15, 0.40),
     "smooth_width": (2, 0.5, 600),
+    "post_expand": None,  # (-1, 1)
     "support_update_period": 50,
-    "post_expand": (1, -2, 1),
     "method": "rms",
     "force_shrink": False,
     "update_border_n": 0,