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numpy-stl
==============================================================================
Simple library to make working with STL files (and 3D objects in general) fast
and easy.
Due to all operations heavily relying on `numpy` this is one of the fastest
STL editing libraries for Python available.
Links
-----
- The source: https://github.com/WoLpH/numpy-stl
- Project page: https://pypi.python.org/pypi/numpy-stl
- Reporting bugs: https://github.com/WoLpH/numpy-stl/issues
- Documentation: http://numpy-stl.readthedocs.org/en/latest/
- My blog: https://wol.ph/
Requirements for installing:
------------------------------------------------------------------------------
- `numpy`_ any recent version
- `python-utils`_ version 1.6 or greater
Installation:
------------------------------------------------------------------------------
`pip install numpy-stl`
Initial usage:
------------------------------------------------------------------------------
- `stl2bin your_ascii_stl_file.stl new_binary_stl_file.stl`
- `stl2ascii your_binary_stl_file.stl new_ascii_stl_file.stl`
- `stl your_ascii_stl_file.stl new_binary_stl_file.stl`
Contributing:
------------------------------------------------------------------------------
Contributions are always welcome. Please view the guidelines to get started:
https://github.com/WoLpH/numpy-stl/blob/develop/CONTRIBUTING.rst
Quickstart
------------------------------------------------------------------------------
.. code-block:: python
import numpy
from stl import mesh
# Using an existing stl file:
your_mesh = mesh.Mesh.from_file('some_file.stl')
# Or creating a new mesh (make sure not to overwrite the `mesh` import by
# naming it `mesh`):
VERTICE_COUNT = 100
data = numpy.zeros(VERTICE_COUNT, dtype=mesh.Mesh.dtype)
your_mesh = mesh.Mesh(data, remove_empty_areas=False)
# The mesh normals (calculated automatically)
your_mesh.normals
# The mesh vectors
your_mesh.v0, your_mesh.v1, your_mesh.v2
# Accessing individual points (concatenation of v0, v1 and v2 in triplets)
assert (your_mesh.points[0][0:3] == your_mesh.v0[0]).all()
assert (your_mesh.points[0][3:6] == your_mesh.v1[0]).all()
assert (your_mesh.points[0][6:9] == your_mesh.v2[0]).all()
assert (your_mesh.points[1][0:3] == your_mesh.v0[1]).all()
your_mesh.save('new_stl_file.stl')
Plotting using `matplotlib`_ is equally easy:
------------------------------------------------------------------------------
.. code-block:: python
from stl import mesh
from mpl_toolkits import mplot3d
from matplotlib import pyplot
# Create a new plot
figure = pyplot.figure()
axes = mplot3d.Axes3D(figure)
# Load the STL files and add the vectors to the plot
your_mesh = mesh.Mesh.from_file('tests/stl_binary/HalfDonut.stl')
axes.add_collection3d(mplot3d.art3d.Poly3DCollection(your_mesh.vectors))
# Auto scale to the mesh size
scale = your_mesh.points.flatten(-1)
axes.auto_scale_xyz(scale, scale, scale)
# Show the plot to the screen
pyplot.show()
.. _numpy: http://numpy.org/
.. _matplotlib: http://matplotlib.org/
.. _python-utils: https://github.com/WoLpH/python-utils
Modifying Mesh objects
------------------------------------------------------------------------------
.. code-block:: python
from stl import mesh
import math
import numpy
# Create 3 faces of a cube
data = numpy.zeros(6, dtype=mesh.Mesh.dtype)
# Top of the cube
data['vectors'][0] = numpy.array([[0, 1, 1],
[1, 0, 1],
[0, 0, 1]])
data['vectors'][1] = numpy.array([[1, 0, 1],
[0, 1, 1],
[1, 1, 1]])
# Right face
data['vectors'][2] = numpy.array([[1, 0, 0],
[1, 0, 1],
[1, 1, 0]])
data['vectors'][3] = numpy.array([[1, 1, 1],
[1, 0, 1],
[1, 1, 0]])
# Left face
data['vectors'][4] = numpy.array([[0, 0, 0],
[1, 0, 0],
[1, 0, 1]])
data['vectors'][5] = numpy.array([[0, 0, 0],
[0, 0, 1],
[1, 0, 1]])
# Since the cube faces are from 0 to 1 we can move it to the middle by
# substracting .5
data['vectors'] -= .5
# Generate 4 different meshes so we can rotate them later
meshes = [mesh.Mesh(data.copy()) for _ in range(4)]
# Rotate 90 degrees over the Y axis
meshes[0].rotate([0.0, 0.5, 0.0], math.radians(90))
# Translate 2 points over the X axis
meshes[1].x += 2
# Rotate 90 degrees over the X axis
meshes[2].rotate([0.5, 0.0, 0.0], math.radians(90))
# Translate 2 points over the X and Y points
meshes[2].x += 2
meshes[2].y += 2
# Rotate 90 degrees over the X and Y axis
meshes[3].rotate([0.5, 0.0, 0.0], math.radians(90))
meshes[3].rotate([0.0, 0.5, 0.0], math.radians(90))
# Translate 2 points over the Y axis
meshes[3].y += 2
# Optionally render the rotated cube faces
from matplotlib import pyplot
from mpl_toolkits import mplot3d
# Create a new plot
figure = pyplot.figure()
axes = mplot3d.Axes3D(figure)
# Render the cube faces
for m in meshes:
axes.add_collection3d(mplot3d.art3d.Poly3DCollection(m.vectors))
# Auto scale to the mesh size
scale = numpy.concatenate([m.points for m in meshes]).flatten(-1)
axes.auto_scale_xyz(scale, scale, scale)
# Show the plot to the screen
pyplot.show()
Extending Mesh objects
------------------------------------------------------------------------------
.. code-block:: python
from stl import mesh
import math
import numpy
# Create 3 faces of a cube
data = numpy.zeros(6, dtype=mesh.Mesh.dtype)
# Top of the cube
data['vectors'][0] = numpy.array([[0, 1, 1],
[1, 0, 1],
[0, 0, 1]])
data['vectors'][1] = numpy.array([[1, 0, 1],
[0, 1, 1],
[1, 1, 1]])
# Right face
data['vectors'][2] = numpy.array([[1, 0, 0],
[1, 0, 1],
[1, 1, 0]])
data['vectors'][3] = numpy.array([[1, 1, 1],
[1, 0, 1],
[1, 1, 0]])
# Left face
data['vectors'][4] = numpy.array([[0, 0, 0],
[1, 0, 0],
[1, 0, 1]])
data['vectors'][5] = numpy.array([[0, 0, 0],
[0, 0, 1],
[1, 0, 1]])
# Since the cube faces are from 0 to 1 we can move it to the middle by
# substracting .5
data['vectors'] -= .5
cube_back = mesh.Mesh(data.copy())
cube_front = mesh.Mesh(data.copy())
# Rotate 90 degrees over the X axis followed by the Y axis followed by the
# X axis
cube_back.rotate([0.5, 0.0, 0.0], math.radians(90))
cube_back.rotate([0.0, 0.5, 0.0], math.radians(90))
cube_back.rotate([0.5, 0.0, 0.0], math.radians(90))
cube = mesh.Mesh(numpy.concatenate([
cube_back.data.copy(),
cube_front.data.copy(),
]))
# Optionally render the rotated cube faces
from matplotlib import pyplot
from mpl_toolkits import mplot3d
# Create a new plot
figure = pyplot.figure()
axes = mplot3d.Axes3D(figure)
# Render the cube
axes.add_collection3d(mplot3d.art3d.Poly3DCollection(cube.vectors))
# Auto scale to the mesh size
scale = cube_back.points.flatten(-1)
axes.auto_scale_xyz(scale, scale, scale)
# Show the plot to the screen
pyplot.show()
Creating Mesh objects from a list of vertices and faces
------------------------------------------------------------------------------
.. code-block:: python
import numpy as np
from stl import mesh
# Define the 8 vertices of the cube
vertices = np.array([\
[-1, -1, -1],
[+1, -1, -1],
[+1, +1, -1],
[-1, +1, -1],
[-1, -1, +1],
[+1, -1, +1],
[+1, +1, +1],
[-1, +1, +1]])
# Define the 12 triangles composing the cube
faces = np.array([\
[0,3,1],
[1,3,2],
[0,4,7],
[0,7,3],
[4,5,6],
[4,6,7],
[5,1,2],
[5,2,6],
[2,3,6],
[3,7,6],
[0,1,5],
[0,5,4]])
# Create the mesh
cube = mesh.Mesh(np.zeros(faces.shape[0], dtype=mesh.Mesh.dtype))
for i, f in enumerate(faces):
for j in range(3):
cube.vectors[i][j] = vertices[f[j],:]
# Write the mesh to file "cube.stl"
cube.save('cube.stl')
Evaluating Mesh properties (Volume, Center of gravity, Inertia)
------------------------------------------------------------------------------
.. code-block:: python
import numpy as np
from stl import mesh
# Using an existing closed stl file:
your_mesh = mesh.Mesh.from_file('some_file.stl')
volume, cog, inertia = your_mesh.get_mass_properties()
print("Volume = {0}".format(volume))
print("Position of the center of gravity (COG) = {0}".format(cog))
print("Inertia matrix at expressed at the COG = {0}".format(inertia[0,:]))
print(" {0}".format(inertia[1,:]))
print(" {0}".format(inertia[2,:]))
Combining multiple STL files
------------------------------------------------------------------------------
.. code-block:: python
import math
import stl
from stl import mesh
import numpy
# find the max dimensions, so we can know the bounding box, getting the height,
# width, length (because these are the step size)...
def find_mins_maxs(obj):
minx = maxx = miny = maxy = minz = maxz = None
for p in obj.points:
# p contains (x, y, z)
if minx is None:
minx = p[stl.Dimension.X]
maxx = p[stl.Dimension.X]
miny = p[stl.Dimension.Y]
maxy = p[stl.Dimension.Y]
minz = p[stl.Dimension.Z]
maxz = p[stl.Dimension.Z]
else:
maxx = max(p[stl.Dimension.X], maxx)
minx = min(p[stl.Dimension.X], minx)
maxy = max(p[stl.Dimension.Y], maxy)
miny = min(p[stl.Dimension.Y], miny)
maxz = max(p[stl.Dimension.Z], maxz)
minz = min(p[stl.Dimension.Z], minz)
return minx, maxx, miny, maxy, minz, maxz
def translate(_solid, step, padding, multiplier, axis):
if 'x' == axis:
items = 0, 3, 6
elif 'y' == axis:
items = 1, 4, 7
elif 'z' == axis:
items = 2, 5, 8
else:
raise RuntimeError('Unknown axis %r, expected x, y or z' % axis)
# _solid.points.shape == [:, ((x, y, z), (x, y, z), (x, y, z))]
_solid.points[:, items] += (step * multiplier) + (padding * multiplier)
def copy_obj(obj, dims, num_rows, num_cols, num_layers):
w, l, h = dims
copies = []
for layer in range(num_layers):
for row in range(num_rows):
for col in range(num_cols):
# skip the position where original being copied is
if row == 0 and col == 0 and layer == 0:
continue
_copy = mesh.Mesh(obj.data.copy())
# pad the space between objects by 10% of the dimension being
# translated
if col != 0:
translate(_copy, w, w / 10., col, 'x')
if row != 0:
translate(_copy, l, l / 10., row, 'y')
if layer != 0:
translate(_copy, h, h / 10., layer, 'z')
copies.append(_copy)
return copies
# Using an existing stl file:
main_body = mesh.Mesh.from_file('ball_and_socket_simplified_-_main_body.stl')
# rotate along Y
main_body.rotate([0.0, 0.5, 0.0], math.radians(90))
minx, maxx, miny, maxy, minz, maxz = find_mins_maxs(main_body)
w1 = maxx - minx
l1 = maxy - miny
h1 = maxz - minz
copies = copy_obj(main_body, (w1, l1, h1), 2, 2, 1)
# I wanted to add another related STL to the final STL
twist_lock = mesh.Mesh.from_file('ball_and_socket_simplified_-_twist_lock.stl')
minx, maxx, miny, maxy, minz, maxz = find_mins_maxs(twist_lock)
w2 = maxx - minx
l2 = maxy - miny
h2 = maxz - minz
translate(twist_lock, w1, w1 / 10., 3, 'x')
copies2 = copy_obj(twist_lock, (w2, l2, h2), 2, 2, 1)
combined = mesh.Mesh(numpy.concatenate([main_body.data, twist_lock.data] +
[copy.data for copy in copies] +
[copy.data for copy in copies2]))
combined.save('combined.stl', mode=stl.Mode.ASCII) # save as ASCII
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