Update validation statistics and remove double entries for image processing functions

Author: PierreRaybaut

doc/validation_statistics.csv

@@ -1,3 +1,3 @@
-Number of compute functions,72,198,270
-Number of validated compute functions,56,130,186
-Percentage of validated compute functions,77%,65%,68%
+Number of compute functions,72,99,171
+Number of validated compute functions,56,86,142
+Percentage of validated compute functions,77%,86%,83%

doc/validation_status_image.csv

@@ -97,102 +97,3 @@
 :py:func:`white_tophat <sigima.proc.image.white_tophat>`,Compute White Top-Hat,`test_white_tophat <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L411>`_
 :py:func:`wiener <sigima.proc.image.wiener>`,Compute Wiener filter,`test_image_wiener <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L181>`_
 :py:func:`zero_padding <sigima.proc.image.zero_padding>`,,`test_image_zero_padding <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/fft2d_unit_test.py#L52>`_
-:py:func:`addition <sigima.proc.image.arithmetic.addition>`,Add images in the list and return the result image object,N/A
-:py:func:`addition_constant <sigima.proc.image.arithmetic.addition_constant>`,Add **dst** and a constant value and return the new result image object,N/A
-:py:func:`arithmetic <sigima.proc.image.arithmetic.arithmetic>`,Compute arithmetic operation on two images,N/A
-:py:func:`average <sigima.proc.image.arithmetic.average>`,Compute the average of images in the list and return the result image object,N/A
-:py:func:`difference <sigima.proc.image.arithmetic.difference>`,Compute difference between two images,N/A
-:py:func:`difference_constant <sigima.proc.image.arithmetic.difference_constant>`,Subtract a constant value from an image and return the new result image object,N/A
-:py:func:`division <sigima.proc.image.arithmetic.division>`,Compute division between two images,N/A
-:py:func:`division_constant <sigima.proc.image.arithmetic.division_constant>`,Divide an image by a constant value and return the new result image object,N/A
-:py:func:`product <sigima.proc.image.arithmetic.product>`,Multiply images in the list and return the result image object,N/A
-:py:func:`product_constant <sigima.proc.image.arithmetic.product_constant>`,Multiply **dst** by a constant value and return the new result image object,N/A
-:py:func:`quadratic_difference <sigima.proc.image.arithmetic.quadratic_difference>`,Compute quadratic difference between two images,N/A
-:py:func:`blob_dog <sigima.proc.image.detection.blob_dog>`,Compute blobs using Difference of Gaussian method,N/A
-:py:func:`blob_doh <sigima.proc.image.detection.blob_doh>`,Compute blobs using Determinant of Hessian method,N/A
-:py:func:`blob_log <sigima.proc.image.detection.blob_log>`,Compute blobs using Laplacian of Gaussian method,N/A
-:py:func:`blob_opencv <sigima.proc.image.detection.blob_opencv>`,Compute blobs using OpenCV,N/A
-:py:func:`contour_shape <sigima.proc.image.detection.contour_shape>`,Compute contour shape fit,N/A
-:py:func:`hough_circle_peaks <sigima.proc.image.detection.hough_circle_peaks>`,Compute Hough circles,N/A
-:py:func:`peak_detection <sigima.proc.image.detection.peak_detection>`,Compute 2D peak detection,N/A
-:py:func:`canny <sigima.proc.image.edges.canny>`,Compute Canny filter,`test_canny <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L447>`_
-:py:func:`farid <sigima.proc.image.edges.farid>`,Compute Farid filter,`test_farid <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L544>`_
-:py:func:`farid_h <sigima.proc.image.edges.farid_h>`,Compute horizontal Farid filter,`test_farid_h <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L550>`_
-:py:func:`farid_v <sigima.proc.image.edges.farid_v>`,Compute vertical Farid filter,`test_farid_v <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L556>`_
-:py:func:`laplace <sigima.proc.image.edges.laplace>`,Compute Laplace filter,`test_laplace <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L562>`_
-:py:func:`prewitt <sigima.proc.image.edges.prewitt>`,Compute Prewitt filter,`test_prewitt <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L490>`_
-:py:func:`prewitt_h <sigima.proc.image.edges.prewitt_h>`,Compute horizontal Prewitt filter,`test_prewitt_h <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L496>`_
-:py:func:`prewitt_v <sigima.proc.image.edges.prewitt_v>`,Compute vertical Prewitt filter,`test_prewitt_v <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L502>`_
-:py:func:`roberts <sigima.proc.image.edges.roberts>`,Compute Roberts filter,`test_roberts <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L484>`_
-:py:func:`scharr <sigima.proc.image.edges.scharr>`,Compute Scharr filter,`test_scharr <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L526>`_
-:py:func:`scharr_h <sigima.proc.image.edges.scharr_h>`,Compute horizontal Scharr filter,`test_scharr_h <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L532>`_
-:py:func:`scharr_v <sigima.proc.image.edges.scharr_v>`,Compute vertical Scharr filter,`test_scharr_v <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L538>`_
-:py:func:`sobel <sigima.proc.image.edges.sobel>`,Compute Sobel filter,`test_sobel <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L508>`_
-:py:func:`sobel_h <sigima.proc.image.edges.sobel_h>`,Compute horizontal Sobel filter,`test_sobel_h <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L514>`_
-:py:func:`sobel_v <sigima.proc.image.edges.sobel_v>`,Compute vertical Sobel filter,`test_sobel_v <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L520>`_
-:py:func:`adjust_gamma <sigima.proc.image.exposure.adjust_gamma>`,Gamma correction,`test_adjust_gamma <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L255>`_
-:py:func:`adjust_log <sigima.proc.image.exposure.adjust_log>`,Compute log correction,`test_adjust_log <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L267>`_
-:py:func:`adjust_sigmoid <sigima.proc.image.exposure.adjust_sigmoid>`,Compute sigmoid correction,`test_adjust_sigmoid <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L279>`_
-:py:func:`calibration <sigima.proc.image.exposure.calibration>`,Compute linear calibration,N/A
-:py:func:`clip <sigima.proc.image.exposure.clip>`,Apply clipping,N/A
-:py:func:`equalize_adapthist <sigima.proc.image.exposure.equalize_adapthist>`,Adaptive histogram equalization,`test_equalize_adapthist <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L318>`_
-:py:func:`equalize_hist <sigima.proc.image.exposure.equalize_hist>`,Histogram equalization,`test_equalize_hist <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L306>`_
-:py:func:`flatfield <sigima.proc.image.exposure.flatfield>`,Compute flat field correction,N/A
-:py:func:`histogram <sigima.proc.image.exposure.histogram>`,"Compute histogram of the image data,",N/A
-:py:func:`normalize <sigima.proc.image.exposure.normalize>`,,N/A
-:py:func:`offset_correction <sigima.proc.image.exposure.offset_correction>`,Apply offset correction,N/A
-:py:func:`rescale_intensity <sigima.proc.image.exposure.rescale_intensity>`,Rescale image intensity levels,`test_rescale_intensity <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L293>`_
-:py:func:`average_profile <sigima.proc.image.extraction.average_profile>`,Compute horizontal or vertical average profile,`test_average_profile <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/profile_unit_test.py#L70>`_
-:py:func:`extract_roi <sigima.proc.image.extraction.extract_roi>`,Extract single ROI,N/A
-:py:func:`extract_rois <sigima.proc.image.extraction.extract_rois>`,Extract multiple regions of interest from data,N/A
-:py:func:`line_profile <sigima.proc.image.extraction.line_profile>`,Compute horizontal or vertical profile,`test_line_profile <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/profile_unit_test.py#L19>`_
-:py:func:`radial_profile <sigima.proc.image.extraction.radial_profile>`,Compute radial profile around the centroid,N/A
-:py:func:`segment_profile <sigima.proc.image.extraction.segment_profile>`,Compute segment profile,`test_segment_profile <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/profile_unit_test.py#L48>`_
-:py:func:`butterworth <sigima.proc.image.filtering.butterworth>`,Compute Butterworth filter,`test_butterworth <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L568>`_
-:py:func:`gaussian_filter <sigima.proc.image.filtering.gaussian_filter>`,Compute gaussian filter,N/A
-:py:func:`moving_average <sigima.proc.image.filtering.moving_average>`,Compute moving average,N/A
-:py:func:`moving_median <sigima.proc.image.filtering.moving_median>`,Compute moving median,N/A
-:py:func:`wiener <sigima.proc.image.filtering.wiener>`,Compute Wiener filter,N/A
-:py:func:`fft <sigima.proc.image.fourier.fft>`,Compute FFT,N/A
-:py:func:`ifft <sigima.proc.image.fourier.ifft>`,Compute inverse FFT,N/A
-:py:func:`magnitude_spectrum <sigima.proc.image.fourier.magnitude_spectrum>`,Compute magnitude spectrum,N/A
-:py:func:`phase_spectrum <sigima.proc.image.fourier.phase_spectrum>`,Compute phase spectrum,N/A
-:py:func:`psd <sigima.proc.image.fourier.psd>`,Compute power spectral density,N/A
-:py:func:`zero_padding <sigima.proc.image.fourier.zero_padding>`,,N/A
-:py:func:`binning <sigima.proc.image.geometry.binning>`,Binning function on data,`test_binning <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/binning_unit_test.py#L75>`_
-:py:func:`fliph <sigima.proc.image.geometry.fliph>`,Flip data horizontally,N/A
-:py:func:`flipv <sigima.proc.image.geometry.flipv>`,Flip data vertically,N/A
-:py:func:`resize <sigima.proc.image.geometry.resize>`,Zooming function,N/A
-:py:func:`rotate <sigima.proc.image.geometry.rotate>`,Rotate data,N/A
-:py:func:`rotate270 <sigima.proc.image.geometry.rotate270>`,Rotate data 270°,N/A
-:py:func:`rotate90 <sigima.proc.image.geometry.rotate90>`,Rotate data 90°,N/A
-:py:func:`swap_axes <sigima.proc.image.geometry.swap_axes>`,Swap image axes,N/A
-:py:func:`absolute <sigima.proc.image.mathops.absolute>`,Compute absolute value with :py:data:`numpy.absolute`,N/A
-:py:func:`astype <sigima.proc.image.mathops.astype>`,Convert image data type,N/A
-:py:func:`exp <sigima.proc.image.mathops.exp>`,Compute exponential with :py:data:`numpy.exp`,N/A
-:py:func:`imag <sigima.proc.image.mathops.imag>`,Compute imaginary part,N/A
-:py:func:`inverse <sigima.proc.image.mathops.inverse>`,Compute the inverse of an image and return the new result image object,N/A
-:py:func:`log10 <sigima.proc.image.mathops.log10>`,Compute log10 with :py:data:`numpy.log10`,N/A
-:py:func:`logp1 <sigima.proc.image.mathops.logp1>`,Compute log10(z+n) with :py:data:`numpy.log10`,N/A
-:py:func:`real <sigima.proc.image.mathops.real>`,Compute real part,N/A
-:py:func:`centroid <sigima.proc.image.measurement.centroid>`,Compute centroid,N/A
-:py:func:`enclosing_circle <sigima.proc.image.measurement.enclosing_circle>`,Compute minimum enclosing circle,N/A
-:py:func:`stats <sigima.proc.image.measurement.stats>`,Compute statistics on an image,N/A
-:py:func:`black_tophat <sigima.proc.image.morphology.black_tophat>`,Compute Black Top-Hat,`test_black_tophat <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L417>`_
-:py:func:`closing <sigima.proc.image.morphology.closing>`,Compute morphological closing,`test_closing <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L441>`_
-:py:func:`dilation <sigima.proc.image.morphology.dilation>`,Compute Dilation,`test_dilation <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L429>`_
-:py:func:`erosion <sigima.proc.image.morphology.erosion>`,Compute Erosion,`test_erosion <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L423>`_
-:py:func:`opening <sigima.proc.image.morphology.opening>`,Compute morphological opening,`test_opening <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L435>`_
-:py:func:`white_tophat <sigima.proc.image.morphology.white_tophat>`,Compute White Top-Hat,`test_white_tophat <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L411>`_
-:py:func:`denoise_bilateral <sigima.proc.image.restoration.denoise_bilateral>`,Compute bilateral filter denoising,`test_denoise_bilateral <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L349>`_
-:py:func:`denoise_tophat <sigima.proc.image.restoration.denoise_tophat>`,Denoise using White Top-Hat,`test_denoise_tophat <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L389>`_
-:py:func:`denoise_tv <sigima.proc.image.restoration.denoise_tv>`,Compute Total Variation denoising,`test_denoise_tv <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L330>`_
-:py:func:`denoise_wavelet <sigima.proc.image.restoration.denoise_wavelet>`,Compute Wavelet denoising,`test_denoise_wavelet <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L366>`_
-:py:func:`threshold <sigima.proc.image.threshold.threshold>`,"Compute the threshold, using one of the available algorithms",`test_threshold <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L190>`_
-:py:func:`threshold_isodata <sigima.proc.image.threshold.threshold_isodata>`,Compute the threshold using the Isodata algorithm with default parameters,`test_threshold_isodata <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L213>`_
-:py:func:`threshold_li <sigima.proc.image.threshold.threshold_li>`,Compute the threshold using the Li algorithm with default parameters,`test_threshold_li <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L219>`_
-:py:func:`threshold_mean <sigima.proc.image.threshold.threshold_mean>`,Compute the threshold using the Mean algorithm,`test_threshold_mean <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L225>`_
-:py:func:`threshold_minimum <sigima.proc.image.threshold.threshold_minimum>`,Compute the threshold using the Minimum algorithm with default parameters,`test_threshold_minimum <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L231>`_
-:py:func:`threshold_otsu <sigima.proc.image.threshold.threshold_otsu>`,Compute the threshold using the Otsu algorithm with default parameters,`test_threshold_otsu <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L237>`_
-:py:func:`threshold_triangle <sigima.proc.image.threshold.threshold_triangle>`,Compute the threshold using the Triangle algorithm with default parameters,`test_threshold_triangle <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L243>`_
-:py:func:`threshold_yen <sigima.proc.image.threshold.threshold_yen>`,Compute the threshold using the Yen algorithm with default parameters,`test_threshold_yen <https://github.com/DataLab-Platform/Sigima/blob/v0.2.0/sigima/tests/images/processing_unit_test.py#L249>`_