备注

This section is only a reference describing the function, please see the chapter on mlab：用Python脚本进行3D绘图 for an introduction to mlab and how to interact with and assemble the functions of mlab.

Please see the section on 运行mlab脚本 for instructions on running the examples.

Plotting functions¶

barchart¶

mayavi.mlab.barchart(*args, **kwargs)¶

Plots vertical glyphs (like bars) scaled vertical, to do histogram-like plots.

This functions accepts a wide variety of inputs, with positions given in 2-D or in 3-D.

Function signatures:

barchart(s, ...)
barchart(x, y, s, ...)
barchart(x, y, f, ...)
barchart(x, y, z, s, ...)
barchart(x, y, z, f, ...)

If only one positional argument is passed, it can be a 1-D, 2-D, or 3-D array giving the length of the vectors. The positions of the data points are deducted from the indices of array, and an uniformly-spaced data set is created.

If 3 positional arguments (x, y, s) are passed the last one must be an array s, or a callable, f, that returns an array. x and y give the 2D coordinates of positions corresponding to the s values.

If 4 positional arguments (x, y, z, s) are passed, the 3 first are arrays giving the 3D coordinates of the data points, and the last one is an array s, or a callable, f, that returns an array giving the data value.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_barchart():
    """ Demo the bar chart plot with a 2D array.
    """
    s = np.abs(np.random.random((3, 3)))
    return barchart(s)

contour3d¶

mayavi.mlab.contour3d(*args, **kwargs)¶

Plots iso-surfaces for a 3D volume of data supplied as arguments.

Function signatures:

contour3d(scalars, ...)
contour3d(x, y, z, scalars, ...)

scalars is a 3D numpy arrays giving the data on a grid.

If 4 arrays, (x, y, z, scalars) are passed, the 3 first arrays give the position, and the last the scalar value. The x, y and z arrays are then supposed to have been generated by numpy.mgrid, in other words, they are 3D arrays, with positions lying on a 3D orthogonal and regularly spaced grid with nearest neighbor in space matching nearest neighbor in the array. The function builds a scalar field assuming the points are regularly spaced.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_contour3d():
    x, y, z = np.ogrid[-5:5:64j, -5:5:64j, -5:5:64j]

    scalars = x * x * 0.5 + y * y + z * z * 2.0

    obj = contour3d(scalars, contours=4, transparent=True)
    return obj

contour_surf¶

mayavi.mlab.contour_surf(*args, **kwargs)¶

Plots a the contours of a surface using grid-spaced data for elevation supplied as a 2D array.

Function signatures:

contour_surf(s, ...)
contour_surf(x, y, s, ...)
contour_surf(x, y, f, ...)

s is the elevation matrix, a 2D array. The contour lines plotted are lines of equal s value.

x and y can be 1D or 2D arrays (such as returned by numpy.ogrid or numpy.mgrid), but the points should be located on an orthogonal grid (possibly non-uniform). In other words, all the points sharing a same index in the s array need to have the same x or y value. For arbitrary-shaped position arrays (non-orthogonal grids), see the mesh function.

If only 1 array s is passed, the x and y arrays are assumed to be made from the indices of arrays, and an uniformly-spaced data set is created.

If 3 positional arguments are passed the last one must be an array s, or a callable, f, that returns an array. x and y give the coordinates of positions corresponding to the s values.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_contour_surf():
    """Test contour_surf on regularly spaced co-ordinates like MayaVi."""
    def f(x, y):
        sin, cos = np.sin, np.cos
        return sin(x + y) + sin(2 * x - y) + cos(3 * x + 4 * y)

    x, y = np.mgrid[-7.:7.05:0.1, -5.:5.05:0.05]
    s = contour_surf(x, y, f)
    return s

flow¶

mayavi.mlab.flow(*args, **kwargs)¶

Creates a trajectory of particles following the flow of a vector field.

Function signatures:

flow(u, v, w, ...)
flow(x, y, z, u, v, w, ...)
flow(x, y, z, f, ...)

u, v, w are numpy arrays giving the components of the vectors.

If only 3 arrays, u, v, and w are passed, they must be 3D arrays, and the positions of the arrows are assumed to be the indices of the corresponding points in the (u, v, w) arrays.

If 6 arrays, (x, y, z, u, v, w) are passed, the 3 first arrays give the position of the arrows, and the 3 last the components. The x, y and z arrays are then supposed to have been generated by numpy.mgrid, in other words, they are 3D arrays, with positions lying on a 3D orthogonal and regularly spaced grid with nearest neighbor in space matching nearest neighbor in the array. The function builds a vector field assuming the points are regularly spaced.

If 4 positional arguments, (x, y, z, f) are passed, the last one must be a callable, f, that returns vectors components (u, v, w) given the positions (x, y, z).

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_flow():
    x, y, z = np.mgrid[-4:4:40j, -4:4:40j, 0:4:20j]
    r = np.sqrt(x ** 2 + y ** 2 + z ** 2 + 0.1)
    u = y * np.sin(r) / r
    v = -x * np.sin(r) / r
    w = np.ones_like(z)*0.05
    obj = flow(u, v, w)
    return obj

imshow¶

mayavi.mlab.imshow(*args, **kwargs)¶

View a 2D array as an image.

Function signatures:

imshow(s, ...)

s is a 2 dimension array. The values of s are mapped to a color using the colormap.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_imshow():
    """ Use imshow to visualize a 2D 10x10 random array.
    """
    s = np.random.random((10, 10))
    return imshow(s, colormap='gist_earth')

mesh¶

mayavi.mlab.mesh(*args, **kwargs)¶

Plots a surface using grid-spaced data supplied as 2D arrays.

Function signatures:

mesh(x, y, z, ...)

x, y, z are 2D arrays, all of the same shape, giving the positions of the vertices of the surface. The connectivity between these points is implied by the connectivity on the arrays.

For simple structures (such as orthogonal grids) prefer the surf function, as it will create more efficient data structures. For mesh defined by triangles rather than regular implicit connectivity, see the triangular_mesh function.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_mesh():
    """A very pretty picture of spherical harmonics translated from
    the octaviz example."""
    pi = np.pi
    cos = np.cos
    sin = np.sin
    dphi, dtheta = pi / 250.0, pi / 250.0
    [phi, theta] = np.mgrid[0:pi + dphi * 1.5:dphi,
                            0:2 * pi + dtheta * 1.5:dtheta]
    m0 = 4
    m1 = 3
    m2 = 2
    m3 = 3
    m4 = 6
    m5 = 2
    m6 = 6
    m7 = 4
    r = sin(m0 * phi) ** m1 + cos(m2 * phi) ** m3 + \
        sin(m4 * theta) ** m5 + cos(m6 * theta) ** m7
    x = r * sin(phi) * cos(theta)
    y = r * cos(phi)
    z = r * sin(phi) * sin(theta)

    return mesh(x, y, z, colormap="bone")

plot3d¶

mayavi.mlab.plot3d(*args, **kwargs)¶

Draws lines between points.

Function signatures:

plot3d(x, y, z, ...)
plot3d(x, y, z, s, ...)

x, y, z and s are numpy arrays or lists of the same shape. x, y and z give the positions of the successive points of the line. s is an optional scalar value associated with each point.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_plot3d():
    """Generates a pretty set of lines."""
    n_mer, n_long = 6, 11
    dphi = np.pi / 1000.0
    phi = np.arange(0.0, 2 * np.pi + 0.5 * dphi, dphi)
    mu = phi * n_mer
    x = np.cos(mu) * (1 + np.cos(n_long * mu / n_mer) * 0.5)
    y = np.sin(mu) * (1 + np.cos(n_long * mu / n_mer) * 0.5)
    z = np.sin(n_long * mu / n_mer) * 0.5

    l = plot3d(x, y, z, np.sin(mu), tube_radius=0.025, colormap='Spectral')
    return l

points3d¶

mayavi.mlab.points3d(*args, **kwargs)¶

Plots glyphs (like points) at the position of the supplied data.

Function signatures:

points3d(x, y, z...)
points3d(x, y, z, s, ...)
points3d(x, y, z, f, ...)

x, y and z are numpy arrays, or lists, all of the same shape, giving the positions of the points.

If only 3 arrays x, y, z are given, all the points are drawn with the same size and color.

In addition, you can pass a fourth array s of the same shape as x, y, and z giving an associated scalar value for each point, or a function f(x, y, z) returning the scalar value. This scalar value can be used to modulate the color and the size of the points.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_points3d():
    t = np.linspace(0, 4 * np.pi, 20)

    x = np.sin(2 * t)
    y = np.cos(t)
    z = np.cos(2 * t)
    s = 2 + np.sin(t)

    return points3d(x, y, z, s, colormap="copper", scale_factor=.25)

quiver3d¶

mayavi.mlab.quiver3d(*args, **kwargs)¶

Plots glyphs (like arrows) indicating the direction of the vectors at the positions supplied.

Function signatures:

quiver3d(u, v, w, ...)
quiver3d(x, y, z, u, v, w, ...)
quiver3d(x, y, z, f, ...)

u, v, w are numpy arrays giving the components of the vectors.

If only 3 arrays, u, v, and w are passed, they must be 3D arrays, and the positions of the arrows are assumed to be the indices of the corresponding points in the (u, v, w) arrays.

If 6 arrays, (x, y, z, u, v, w) are passed, the 3 first arrays give the position of the arrows, and the 3 last the components. They can be of any shape.

If 4 positional arguments, (x, y, z, f) are passed, the last one must be a callable, f, that returns vectors components (u, v, w) given the positions (x, y, z).

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_quiver3d():
    x, y, z = np.mgrid[-2:3, -2:3, -2:3]
    r = np.sqrt(x ** 2 + y ** 2 + z ** 4)
    u = y * np.sin(r) / (r + 0.001)
    v = -x * np.sin(r) / (r + 0.001)
    w = np.zeros_like(z)
    obj = quiver3d(x, y, z, u, v, w, line_width=3, scale_factor=1)
    return obj

set_picker_props¶

mayavi.mlab.set_picker_props(figure=None, pick_type='point_picker', tolerance=0.025, text_color=None)¶

surf¶

mayavi.mlab.surf(*args, **kwargs)¶

Plots a surface using regularly-spaced elevation data supplied as a 2D array.

Function signatures:

surf(s, ...)
surf(x, y, s, ...)
surf(x, y, f, ...)

s is the elevation matrix, a 2D array, where indices along the first array axis represent x locations, and indices along the second array axis represent y locations.

x and y can be 1D or 2D arrays such as returned by numpy.ogrid or numpy.mgrid. Arrays returned by numpy.meshgrid require a transpose first to obtain correct indexing order. The points should be located on an orthogonal grid (possibly non-uniform). In other words, all the points sharing a same index in the s array need to have the same x or y value. For arbitrary-shaped position arrays (non-orthogonal grids), see the mesh function.

If only 1 array s is passed, the x and y arrays are assumed to be made from the indices of arrays, and an uniformly-spaced data set is created.

If 3 positional arguments are passed the last one must be an array s, or a callable, f, that returns an array. x and y give the coordinates of positions corresponding to the s values.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_surf():
    """Test surf on regularly spaced co-ordinates like MayaVi."""
    def f(x, y):
        sin, cos = np.sin, np.cos
        return sin(x + y) + sin(2 * x - y) + cos(3 * x + 4 * y)

    x, y = np.mgrid[-7.:7.05:0.1, -5.:5.05:0.05]
    s = surf(x, y, f)
    #cs = contour_surf(x, y, f, contour_z=0)
    return s

triangular_mesh¶

mayavi.mlab.triangular_mesh(*args, **kwargs)¶

Plots a surface using a mesh defined by the position of its vertices and the triangles connecting them.

Function signatures:

triangular_mesh(x, y, z, triangles ...)

x, y, z are arrays giving the positions of the vertices of the surface. triangles is a list of triplets (or an array) list the vertices in each triangle. Vertices are indexes by their appearance number in the position arrays.

For simple structures (such as rectangular grids) prefer the surf or mesh functions, as they will create more efficient data structures.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_triangular_mesh():
    """An example of a cone, ie a non-regular mesh defined by its
        triangles.
    """
    n = 8
    t = np.linspace(-np.pi, np.pi, n)
    z = np.exp(1j * t)
    x = z.real.copy()
    y = z.imag.copy()
    z = np.zeros_like(x)

    triangles = [(0, i, i + 1) for i in range(1, n)]
    x = np.r_[0, x]
    y = np.r_[0, y]
    z = np.r_[1, z]
    t = np.r_[0, t]

    return triangular_mesh(x, y, z, triangles, scalars=t)

volume_slice¶

mayavi.mlab.volume_slice(*args, **kwargs)¶

Plots an interactive image plane sliced through a 3D volume of data supplied as argument.

Function signatures:

volume_slice(scalars, ...)
volume_slice(x, y, z, scalars, ...)

scalars is a 3D numpy arrays giving the data on a grid.

If 4 arrays, (x, y, z, scalars) are passed, the 3 first arrays give the position, and the last the scalar value. The x, y and z arrays are then supposed to have been generated by numpy.mgrid, in other words, they are 3D arrays, with positions lying on a 3D orthogonal and regularly spaced grid with nearest neighbor in space matching nearest neighbor in the array. The function builds a scalar field assuming the points are regularly spaced.

关键字：

Example (run in ipython --gui=qt, or in the mayavi2 interactive shell, see 运行mlab脚本 for more info):

import numpy
from mayavi.mlab import *

def test_volume_slice():
    x, y, z = np.ogrid[-5:5:64j, -5:5:64j, -5:5:64j]

    scalars = x * x * 0.5 + y * y + z * z * 2.0

    obj = volume_slice(scalars, plane_orientation='x_axes')
    return obj

Plotting functions¶

barchart¶

contour3d¶

contour_surf¶

flow¶

imshow¶

mesh¶

plot3d¶

points3d¶

quiver3d¶

set_picker_props¶

surf¶

triangular_mesh¶

volume_slice¶

目录

上一主题

下一主题

本页