def startup( self ) :
# super().startup()
# this will reduce the amount of data to roughly a grid of 15x15x15 vectors. can
# always change later in the gui.
self.mask_points = int( ( self.data[0].shape[0] / 15. ) ** 3 )
for i in range(3) :
if self.slices_to_add[i] :
self.add_slice( i )
self.set_orientation_axes( 1 )
self.set_outline( 1 )
mlab.vectorbar( orientation = 'vertical' )
mlab.vectorbar( orientation = 'vertical' )
# mlab.vectorbar()
self.needs_startup = 0
def vectorbar(*args, **kwargs):
"""Wraps mayavi.mlab.vectorbar and adjusts cmap if you so choose"""
cmap = kwargs.pop("cmap", False)
kwargs, cmap_kwargs = _extract_cmap_kwargs(kwargs)
cmap_kwargs.pop("cmap")
ret = mlab.vectorbar(*args, **kwargs)
apply_cmap(ret, cmap=cmap, **cmap_kwargs)
return ret
def mayavi_barchart():
"""
绘制barchart图
:return:
"""
mlab.figure(fgcolor=(0, 0, 0), bgcolor=(1, 1, 1)) # 更改背景色
# s = np.random.rand(3, 3)
# print(s)
# mlab.barchart(s)
# mlab.vectorbar()
# mlab.show()
x, y = np.mgrid[-5:5:20j, -5:5:20j]
# print(x, y)
s = peaks(x, y)
mlab.barchart(x, y, s)
mlab.vectorbar()
mlab.show()
def startup(self):
# super().startup()
# print( len( self.data ) )
src = mlab.pipeline.vector_field(*self.data, figure=self.mayavi_scene)
self.mayavi_plot = mlab.pipeline.vectors(src, figure=self.mayavi_scene)
mlab.vectorbar(self.mayavi_plot, orientation='vertical')
mlab.vectorbar(self.mayavi_plot, orientation='vertical')
# see https://docs.enthought.com/mayavi/mayavi/auto/example_magnetic_field.html
self.mayavi_plot.glyph.trait_set(mask_input_points=True)
self.mayavi_plot.glyph.mask_points.trait_set(on_ratio=2,
random_mode=False)
# print_info( self.mayavi_plot.glyph.mask_points )
self.set_mask_points(5)
self.set_orientation_axes(1)
self.set_outline(1)
self.needs_startup = 0
data.shape = shape
nx = shape[0]
ny = shape[1]
nz = shape[2]
dx = nx / 2 + 1
dy = ny / 2 + 1
dz = nz / 2 + 1
if hslice:
amp = np.sqrt(data[:, :, dz, 0]**2 + data[:, :, dz, 1]**2 +
data[:, :, dz, 2]**2)
mlab.imshow(amp, opacity=0.6, reset_zoom=False)
mlab.quiver3d(data[:, :, :, 0],
data[:, :, :, 1],
data[:, :, :, 2],
mask_points=mask_points,
scale_factor=scale_factor,
extent=[-dx, dx, -dy, dy, -dz, dz])
if axes:
mlab.axes()
if colorbar:
mlab.vectorbar()
mlab.show()
forceY = []
forceZ = []
originX = []
originY = []
originZ = []
i = 0
with open("forceOnObject.txt", "r") as f:
for line in f:
vect = line.split('[')[1].split(']')[0].split(',') # Parse list
forceX.append(float(vect[0]))
forceY.append(float(vect[1]))
forceZ.append(float(vect[2]))
originX.append(0.0)
originY.append(time[i])
originZ.append(0.0)
i += 1
m.quiver3d(originX, originY, originZ, forceX, forceY, forceZ)
# m.title('Force applied on the house over time')
m.vectorbar(orientation='vertical')
m.ylabel('time (s)')
m.axes()
m.show()
delimiter='\t',
newline='\n',
fmt='%s')
xx = np.arange(0, len(ef[0]), 1)
y = np.arange(0, len(ef[0]), 1)
z = np.arange(0, len(ef[0]), 1)
Xe, Ye, Ze = np.meshgrid(xx, y, z, indexing='ij')
norm = o.dimension**3
print(norm)
ef = ef / norm
m.figure()
m.quiver3d(Xe, Ye, Ze, ef[0], ef[1], ef[2], colormap='gnuplot')
m.title('E-field/potential - vector/scalar')
m.vectorbar()
m.axes(ranges=[0, n, 0, n, 0, n])
m.figure()
a = m.contour3d(X, Y, Z, o.potential / norm)
m.scalarbar()
m.axes(ranges=[0, n, 0, n, 0, n])
m.show()
d_values = []
p_values = []
half = int(n / 2)
for i in range(n):
for j in range(n):
for k in range(n):
distance = np.sqrt(((i - half)**2) + ((j - half)**2) +
#######################################################################################
# Calculating the magnetic field of a Current around Loop
#######################################################################################
elif prompt == "L":
"Endpoints of vector to rotate circle around"
x0, y0, z0, x1, y1, z1 = 0, 0, 0, 0, 0, 1
"Calculate field and graph the wire"
B_loop(n, x0, y0, z0, x1, y1, z1, 0, 10, 0)
"Scale and plot the vectors up so they can be seen graphically "
draw_vector(x_grid, y_grid, z_grid, Bx, By, Bz)
"Current around Solenoid"
#######################################################################################
"""Draw the x, y, z axes"""
axes = np.linspace(-20, 20, 100)
x_axis = mlab.plot3d(0*axes, 0*axes, axes, color=(0,0,0), tube_radius = .02)
y_axis = mlab.plot3d(axes, 0*axes, 0*axes, color=(0,0,0), tube_radius = .02)
z_axis = mlab.plot3d(0*axes, axes, 0*axes, color=(0,0,0), tube_radius = .02)
"Figure Functions"
mlab.title("Magnetic Field", height = .9, size = .45)
mlab.view(distance = 200)
"Vectorbar functions"
vb = mlab.vectorbar(title = "Field Strength (T)", nb_labels = 5)
vb.scalar_bar_representation.position = [0.006644735064188584, 0.016157157980456187]
vb.scalar_bar_representation.position2 = [0.5567139298716236, 0.11830171009771967]
mlab.show()
#!/usr/bin/env python # -*- coding: utf-8 -*- import numpy as np import mayavi.mlab as mlab mlab.figure(fgcolor=(0, 0, 0), bgcolor=(1, 1, 1)) #更改背景色 s = np.random.normal(size=(21, 21)) #mlab.barchart(s) #x,y为矩阵p的坐标,可以省略 #mlab.imshow(s) # the colormap x, y = np.mgrid[-10:10:21j, -10:10:21j] mlab.mesh(x, y, s) mlab.vectorbar() #颜色bar mlab.show()
from file_reading import read_file
from mayavi import mlab
import matplotlib.pyplot as plt
import numpy as np
import hexbin
t,x,y,z,u,vx,vy,vz,uvx,uvy,uvz = read_file("../Data/h_med_5")
mlab.quiver3d(x,y,z, vx, vy, vz)
mlab.vectorbar(title="Velocity (metres per second)", orientation='Vertical', nb_labels=4)
mlab.show()
