def update(self, i):
i = int(i)
self.parent.matrix = np.array(
(self.parent.i_vector, self.parent.j_vector,
self.parent.k_vector)).T
self.parent.plus_matrix = np.array(
(self.parent.i_plus_vector, self.parent.j_plus_vector,
self.parent.k_plus_vector)).T
if self.canvasFigure != None:
try:
self.parent.quiver.remove()
self.parent.plus_quiver.remove()
except:
print("do nothing")
self.parent.matrix = (1 - self.parent.sigmoid(i)) * np.array(
(self.parent.i_origin, self.parent.j_origin, self.parent.
k_origin)) + self.parent.sigmoid(i) * self.parent.matrix
self.parent.plus_matrix = (1 - self.parent.sigmoid(i)) * np.array(
(self.parent.i_origin, self.parent.j_origin, self.parent.
k_origin)) + self.parent.sigmoid(i) * self.parent.plus_matrix
else:
self.parent.matrix = np.array(
(self.parent.i_origin, self.parent.j_origin,
self.parent.k_origin)) + self.parent.matrix
self.parent.plus_matrix = np.array(
(self.parent.i_origin, self.parent.j_origin,
self.parent.k_origin)) + self.parent.plus_matrix
# Compute a matrix that is in the middle between the full transformation matrix and the identity
self.parent.vector_location = np.array(
(self.parent.matrix.dot(self.parent.i_origin),
self.parent.matrix.dot(self.parent.j_origin),
self.parent.matrix.dot(self.parent.k_origin))).T
self.parent.quiver = self.parent.ax.quiver(
0,
0,
0,
self.parent.vector_location[0],
self.parent.vector_location[1],
self.parent.vector_location[2],
length=1,
color='r',
arrow_length_ratio=0.1)
self.parent.plus_vector_location = np.array(
(self.parent.plus_matrix.dot(self.parent.i_origin),
self.parent.plus_matrix.dot(self.parent.j_origin),
self.parent.plus_matrix.dot(self.parent.k_origin))).T
self.parent.plus_quiver = self.parent.ax.quiver(
0,
0,
0,
self.parent.plus_vector_location[0],
self.parent.plus_vector_location[1],
self.parent.plus_vector_location[2],
length=1,
color='y',
arrow_length_ratio=0.1)
# Set vector location - must transpose since we need U and V representing x and y components
# of each vector respectively (without transposing, e ach column represents each unit vector)
self.parent.transform = np.array(
[self.parent.matrix.dot(k) for k in self.parent.x])
#ax.view_init((1 - self.parent.sigmoid(i)) * elevation, (1 - self.parent.sigmoid(i)) * angle)
if self.canvasFigure != None:
self.parent.scat._offsets3d = [
self.parent.transform[:, 0], self.parent.transform[:, 1],
self.parent.transform[:, 2]
]
self.canvasFigure.draw()
a = self.parent.plus_vector_location
#with pylatex.config.active.change(indent=False):
doc = Document()
doc.packages.append(
Package('geometry',
options=['paperwidth=6in', 'paperheight=2.5in']))
section = Section('Linear Combination')
subsection = Subsection('Using the dot product')
V1 = np.transpose(np.array([[1, 1]]))
M1 = np.array((self.parent.i_vector, self.parent.j_vector)).T
math = Math(data=[
Matrix(M1), 'dot',
Matrix(V1), '=',
Matrix(np.dot(M1, V1))
])
subsection.append(math)
section.append(subsection)
subsection = Subsection('Using vector addition')
V1 = np.array([self.parent.i_vector])
V2 = np.array([self.parent.j_vector])
math = Math(
data=[Matrix(V1), '+',
Matrix(V2), '=',
Matrix(V1 + V2)])
subsection.append(math)
section.append(subsection)
#doc.append(section)
'''
subsection = Subsection('Product')
math = Math(data=['M', vec_name, '=', Matrix(M * a)])
subsection.append(math)
section.append(subsection)
doc.append(section)
'''
doc.append(section)
latex = doc.dumps_as_content()
print(latex)
self.strvar.set(latex)
#self.strvar.set("\prod_{p\,\mathrm{prime}}\\frac1{1-p^{-s}} = \sum_{n=1}^\infty \\frac1{n^s}")
self.on_latex()
