def __init__(self):
app.Canvas.__init__(self, position=(50, 50), keys='interactive')
ps = self.pixel_scale
# Load the Iris dataset and normalize.
iris = load_iris()
position = iris['data'].astype(np.float32)
n, ndim = position.shape
position -= position.mean()
position /= np.abs(position).max()
v_position = position * .75
v_color = ColorArray(['orange', 'magenta', 'darkblue'])
v_color = v_color.rgb[iris['group'], :].astype(np.float32)
v_color *= np.random.uniform(.5, 1.5, (n, 3))
v_color = np.clip(v_color, 0, 1)
v_size = np.random.uniform(2 * ps, 12 * ps, (n, 1)).astype(np.float32)
self.program = gloo.Program(VERT_SHADER, FRAG_SHADER)
self.program['a_position'] = gloo.VertexBuffer(v_position)
self.program['a_color'] = gloo.VertexBuffer(v_color)
self.program['a_size'] = gloo.VertexBuffer(v_size)
self.program['u_pan'] = (0., 0.)
self.program['u_scale'] = (1., 1.)
self.program['u_vec1'] = (1., 0., 0., 0.)
self.program['u_vec2'] = (0., 1., 0., 0.)
# Circulant matrix.
circ = np.diagflat(np.ones(ndim - 1), 1)
circ[-1, 0] = -1 if ndim % 2 == 0 else 1
self.logcirc = logm(circ)
# We will solve the equation dX/dt = log(circ) * X in real time
# to compute the matrix exponential expm(t*log(circ)).
self.mat = np.eye(ndim)
self.dt = .001
gloo.set_state(clear_color=(1, 1, 1, 1),
blend=True,
blend_func=('src_alpha', 'one_minus_src_alpha'))
gloo.set_viewport(0, 0, *self.physical_size)
self._timer = app.Timer('auto', connect=self.on_timer, start=True)
self.show()
def __init__(self):
app.Canvas.__init__(self, position=(50, 50), keys='interactive')
ps = self.pixel_scale
# Load the Iris dataset and normalize.
iris = load_iris()
position = iris['data'].astype(np.float32)
n, ndim = position.shape
position -= position.mean()
position /= np.abs(position).max()
v_position = position*.75
v_color = ColorArray(['orange', 'magenta', 'darkblue'])
v_color = v_color.rgb[iris['group'], :].astype(np.float32)
v_color *= np.random.uniform(.5, 1.5, (n, 3))
v_color = np.clip(v_color, 0, 1)
v_size = np.random.uniform(2*ps, 12*ps, (n, 1)).astype(np.float32)
self.program = gloo.Program(VERT_SHADER, FRAG_SHADER)
self.program['a_position'] = gloo.VertexBuffer(v_position)
self.program['a_color'] = gloo.VertexBuffer(v_color)
self.program['a_size'] = gloo.VertexBuffer(v_size)
self.program['u_pan'] = (0., 0.)
self.program['u_scale'] = (1., 1.)
self.program['u_vec1'] = (1., 0., 0., 0.)
self.program['u_vec2'] = (0., 1., 0., 0.)
# Circulant matrix.
circ = np.diagflat(np.ones(ndim-1), 1)
circ[-1, 0] = -1 if ndim % 2 == 0 else 1
self.logcirc = logm(circ)
# We will solve the equation dX/dt = log(circ) * X in real time
# to compute the matrix exponential expm(t*log(circ)).
self.mat = np.eye(ndim)
self.dt = .001
gloo.set_state(clear_color=(1, 1, 1, 1), blend=True,
blend_func=('src_alpha', 'one_minus_src_alpha'))
gloo.set_viewport(0, 0, *self.physical_size)
self._timer = app.Timer('auto', connect=self.on_timer, start=True)
self.show()
# -*- coding: utf-8 -*- # vispy: gallery 2000 """N-dimensional scatter plot with GPU-based projections. The projection axes evolve smoothly over time, following a path on the Lie group SO(n). """ from vispy import gloo from vispy import app from vispy.color import ColorArray from vispy.io import load_iris import numpy as np from scipy.linalg import logm # Load the Iris dataset and normalize. iris = load_iris() position = iris['data'].astype(np.float32) n, ndim = position.shape position -= position.mean() position /= np.abs(position).max() v_position = position * .75 v_color = ColorArray(['orange', 'magenta', 'darkblue']) v_color = v_color.rgb[iris['group'], :].astype(np.float32) v_color *= np.random.uniform(.5, 1.5, (n, 3)) v_color = np.clip(v_color, 0, 1) v_size = np.random.uniform(2, 12, (n, 1)).astype(np.float32) VERT_SHADER = """ #version 120 attribute vec4 a_position;
>>> op = OrthogonalPath(mat1, mat2)
>>> mat = op(t)
"""
def __init__(self, mat, origin=None):
if origin is None:
origin = np.eye(len(mat))
self.a, self.b = np.matrix(origin), np.matrix(mat)
self._logainvb = logm(self.a.I * self.b)
def __call__(self, t):
return np.real(self.a * expm(t * self._logainvb))
# Load the Iris dataset and normalize.
iris = load_iris()
position = iris['data'].astype(np.float32)
n, ndim = position.shape
position -= position.mean()
position /= np.abs(position).max()
v_position = position*.75
v_color = ColorArray(['orange', 'magenta', 'darkblue'])
v_color = v_color.rgb[iris['group'], :].astype(np.float32)
v_color *= np.random.uniform(.5, 1.5, (n, 3))
v_color = np.clip(v_color, 0, 1)
v_size = np.random.uniform(2, 12, (n, 1)).astype(np.float32)
VERT_SHADER = """
#version 120
attribute vec4 a_position;
