Beispiel #1
0
    def publish(self, pub):
        diffeo = self.summarize()

        pub.array_as_image('mle', diffeomorphism_to_rgb(diffeo.d))
        pub.array_as_image('angle', diffeo_to_rgb_angle(diffeo.d))
        pub.array_as_image('norm', diffeo_to_rgb_norm(diffeo.d, max_value=10))
        pub.array_as_image('curv', diffeo_to_rgb_curv(diffeo.d))
        pub.array_as_image('variance', diffeo.variance, filter='scale')

        pub.text('num_samples', self.num_samples)
        pub.text('statistics', diffeo_text_stats(diffeo.d))
        pub.array_as_image('legend', angle_legend((50, 50)))

        n = 20
        M = None
        for i in range(n):  # @UnusedVariable
            c = self.flattening.random_coords()
            Mc = self.get_similarity(c)
            if M is None:
                M = np.zeros(Mc.shape)
                M.fill(np.nan)

            ok = np.isfinite(Mc)
            Mmax = np.nanmax(Mc)
            if Mmax < 0:
                Mc = -Mc
                Mmax = -Mmax
            if Mmax > 0:
                M[ok] = Mc[ok] / Mmax

        pub.array_as_image('coords', M, filter='scale')

        if self.last_y0 is not None:
            y0 = self.last_y0
            y1 = self.last_y1
            none = np.logical_and(y0 == 0, y1 == 0)
            x = y0 - y1
            x[none] = np.nan
            pub.array_as_image('motion', x, filter='posneg')
    def publish(self, pub):
        diffeo = self.summarize() 
        
        pub.array_as_image('mle', diffeomorphism_to_rgb(diffeo.d))
        pub.array_as_image('angle', diffeo_to_rgb_angle(diffeo.d))
        pub.array_as_image('norm', diffeo_to_rgb_norm(diffeo.d, max_value=10))
        pub.array_as_image('curv', diffeo_to_rgb_curv(diffeo.d))
        pub.array_as_image('variance', diffeo.variance, filter='scale')

        pub.text('num_samples', self.num_samples)
        pub.text('statistics', diffeo_text_stats(diffeo.d))
        pub.array_as_image('legend', angle_legend((50, 50)))

        n = 20
        M = None
        for i in range(n):  # @UnusedVariable
            c = self.flattening.random_coords()
            Mc = self.get_similarity(c)
            if M is None:
                M = np.zeros(Mc.shape)
                M.fill(np.nan)

            ok = np.isfinite(Mc)
            Mmax = np.nanmax(Mc)
            if Mmax < 0:
                Mc = -Mc
                Mmax = -Mmax
            if Mmax > 0:
                M[ok] = Mc[ok] / Mmax

        pub.array_as_image('coords', M, filter='scale')

        if self.last_y0 is not None:
            y0 = self.last_y0
            y1 = self.last_y1
            none = np.logical_and(y0 == 0, y1 == 0)
            x = y0 - y1
            x[none] = np.nan
            pub.array_as_image('motion', x, filter='posneg')
Beispiel #3
0
 def get_rgb_angle(self):
     from diffeo2d import diffeo_to_rgb_angle   
     return diffeo_to_rgb_angle(self.get_discretized_diffeo())
Beispiel #4
0
 def get_rgb_angle(self):
     from diffeo2d import diffeo_to_rgb_angle
     return diffeo_to_rgb_angle(self.get_discretized_diffeo())