dcnum.feat.feat_brightness.bright_all
=====================================

.. py:module:: dcnum.feat.feat_brightness.bright_all


Functions
---------

.. autoapisummary::

   dcnum.feat.feat_brightness.bright_all.brightness_features
   dcnum.feat.feat_brightness.bright_all.compute_avg_sd_masked_uint8
   dcnum.feat.feat_brightness.bright_all.compute_avg_sd_masked_int16
   dcnum.feat.feat_brightness.bright_all.compute_median
   dcnum.feat.feat_brightness.bright_all.compute_percentiles_10_90


Module Contents
---------------

.. py:function:: brightness_features(image: numpy.typing.NDArray[numpy.uint8], mask: numpy.typing.NDArray[numpy.bool_], image_bg: numpy.typing.NDArray[numpy.uint8] | None = None, image_corr: numpy.typing.NDArray[numpy.int16] | None = None, bg_off: float | None = None)

   Compute brightness features

   :param image: 2D array of "image" of shape (H, W)
   :type image: np.ndarray
   :param mask: 3D array containing the N masks of shape (N, H, W)
   :type mask: np.ndarray
   :param image_bg: 2D array of "image_bg" of shape (H, W), required for computing
                    the "bg_med" feature.
   :type image_bg: np.ndarray
   :param image_corr: 2D array of (image - image_bg), which can be optionally passed
                      to this method. If not given, will be computed.
   :type image_corr: np.ndarray
   :param bg_off: Systematic offset value for correcting the brightness of the
                  background data which has an effect on "bright_bc_avg",
                  "bright_perc_10", "bright_perc_90", and "bg_med" (`bg_off` is
                  generated by sparsemed background correction).
   :type bg_off: float


.. py:function:: compute_avg_sd_masked_uint8(image, mask)

.. py:function:: compute_avg_sd_masked_int16(image, mask)

.. py:function:: compute_median(image)

.. py:function:: compute_percentiles_10_90(image, mask)