Python maximum_deviation Exemples

Exemple #1

Fichier : calculate_divergence.py Projet : dials/dials_scratch

def calculate_threshold(sweep, trusted_range):
  from scipy.ndimage.measurements import histogram
  from thresholding import maximum_deviation
  import numpy

  threshold_list = []
  for i, flex_image in enumerate(sweep):

    # Get image as numpy array
    image = flex_image.as_numpy_array()

    # Cap pixels to within trusted range
    image.shape = -1
    ind = numpy.where(image < trusted_range[0])
    image[ind] = trusted_range[0]
    ind = numpy.where(image > trusted_range[1])
    image[ind] = trusted_range[1]

    # Histogram the pixels
    histo = histogram(image, trusted_range[0], trusted_range[1], trusted_range[1])
    histo = histo / numpy.sum(histo)

    # Calculate the threshold and add to list
    threshold = maximum_deviation(histo)
    threshold_list.append(threshold)

  # Return mean threshold
  return numpy.mean(threshold_list)

Exemple #2

Fichier : calculate_divergence2.py Projet : dials/dials_scratch

def calculate_threshold(sweep, trusted_range):
    from scipy.ndimage.measurements import histogram
    from thresholding import maximum_deviation
    import numpy

    threshold_list = []
    for i, flex_image in enumerate(sweep):

        # Get image as numpy array
        image = flex_image.as_numpy_array()

        # Cap pixels to within trusted range
        image.shape = -1
        ind = numpy.where(image < trusted_range[0])
        image[ind] = trusted_range[0]
        ind = numpy.where(image > trusted_range[1])
        image[ind] = trusted_range[1]

        # Histogram the pixels
        histo = histogram(image, trusted_range[0], trusted_range[1],
                          trusted_range[1])
        histo = histo / numpy.sum(histo)

        # Calculate the threshold and add to list
        threshold = maximum_deviation(histo)
        threshold_list.append(threshold)

    # Return mean threshold
    return numpy.mean(threshold_list)

Exemple #3

Fichier : calculate_divergence3.py Projet : dials/dials_scratch

def calculate_threshold(image, trusted_range):
  from scipy.ndimage.measurements import histogram
  from thresholding import maximum_deviation
  import numpy

  # Cap pixels to within trusted range
  image.shape = -1
  ind = numpy.where(image < trusted_range[0])
  image[ind] = trusted_range[0]
  ind = numpy.where(image > trusted_range[1])
  image[ind] = trusted_range[1]

  # Histogram the pixels
  histo = histogram(image, trusted_range[0], trusted_range[1], trusted_range[1])
  histo = histo / numpy.sum(histo)

  # Calculate the threshold and add to list
  return maximum_deviation(histo)

Exemple #4

def calculate_threshold(image, trusted_range):
    from scipy.ndimage.measurements import histogram
    from thresholding import maximum_deviation
    import numpy

    # Cap pixels to within trusted range
    image.shape = -1
    ind = numpy.where(image < trusted_range[0])
    image[ind] = trusted_range[0]
    ind = numpy.where(image > trusted_range[1])
    image[ind] = trusted_range[1]

    # Histogram the pixels
    histo = histogram(image, trusted_range[0], trusted_range[1],
                      trusted_range[1])
    histo = histo / numpy.sum(histo)

    # Calculate the threshold and add to list
    return maximum_deviation(histo)

Exemple #5

        image.shape = -1
        ind = numpy.where(image < trusted_range[0])
        image[ind] = trusted_range[0]
        ind = numpy.where(image > trusted_range[1])
        image[ind] = trusted_range[1]

        mean = numpy.mean(image)
        sdev = numpy.std(image)
        var = sdev ** 2

        temp = histogram(image, trusted_range[0], trusted_range[1], trusted_range[1])
        temp = temp / numpy.sum(temp)
        histo.append(temp)

        # threshold = bhthreshold(temp)
        threshold = maximum_deviation(temp)
        # threshold = percentage_threshold(temp)
        #        threshold = normal_threshold(temp)
        threshold_list.append(threshold)

        print(
            "{0} - Mean: {1}, Sdev: {2}, Var: {3}, Thres: {4}".format(
                i, mean, sdev, var, threshold
            )
        )

    print(
        "Threshold - Mean: {0}, Sdev: {1}".format(
            numpy.mean(threshold_list), numpy.std(threshold_list)
        )
    )

Exemple #6

Fichier : histogram_pixels.py Projet : dials/dials_scratch

    image.shape = -1
    ind = numpy.where(image < trusted_range[0])
    image[ind] = trusted_range[0]
    ind = numpy.where(image > trusted_range[1])
    image[ind] = trusted_range[1]

    mean = numpy.mean(image)
    sdev = numpy.std(image)
    var = sdev **2

    temp = histogram(image, trusted_range[0], trusted_range[1], trusted_range[1])
    temp = temp / numpy.sum(temp)
    histo.append(temp)

    #threshold = bhthreshold(temp)
    threshold = maximum_deviation(temp)
    #threshold = percentage_threshold(temp)
#        threshold = normal_threshold(temp)
    threshold_list.append(threshold)


    print "{0} - Mean: {1}, Sdev: {2}, Var: {3}, Thres: {4}".format(
        i, mean, sdev, var, threshold)

  print "Threshold - Mean: {0}, Sdev: {1}".format(
      numpy.mean(threshold_list), numpy.std(threshold_list))

  mean_thresh = numpy.mean(threshold_list)

  image = sweep[start:stop].to_array().as_numpy_array()
  mask = image > mean_thresh