def draw_axes(settings):
GL.glMatrixMode(GL.GL_MODELVIEW)
GL.glLoadIdentity()
# GL.glTranslatef(0, 0, -2)
size_x = abs(settings.get("maxx"))
size_y = abs(settings.get("maxy"))
size_z = abs(settings.get("maxz"))
size = number(1.7) * max(size_x, size_y, size_z)
# the divider is just based on playing with numbers
scale = size / number(1500.0)
string_distance = number(1.1) * size
GL.glBegin(GL.GL_LINES)
GL.glColor3f(1, 0, 0)
GL.glVertex3f(0, 0, 0)
GL.glVertex3f(size, 0, 0)
GL.glEnd()
draw_string(string_distance, 0, 0, "xy", "X", scale=scale)
GL.glBegin(GL.GL_LINES)
GL.glColor3f(0, 1, 0)
GL.glVertex3f(0, 0, 0)
GL.glVertex3f(0, size, 0)
GL.glEnd()
draw_string(0, string_distance, 0, "yz", "Y", scale=scale)
GL.glBegin(GL.GL_LINES)
GL.glColor3f(0, 0, 1)
GL.glVertex3f(0, 0, 0)
GL.glVertex3f(0, 0, size)
GL.glEnd()
draw_string(0, 0, string_distance, "xz", "Z", scale=scale)
def get_rotation_matrix_axis_angle(rot_axis, rot_angle, use_radians=True):
""" calculate rotation matrix for a normalized vector and an angle
see http://mathworld.wolfram.com/RotationMatrix.html
@type rot_axis: tuple(float)
@value rot_axis: the vector describes the rotation axis. Its length should
be 1.0 (normalized).
@type rot_angle: float
@value rot_angle: rotation angle (radiant)
@rtype: tuple(tuple(float))
@return: the roation matrix (3x3)
"""
if not use_radians:
rot_angle *= math.pi / 180
sin = number(math.sin(rot_angle))
cos = number(math.cos(rot_angle))
return ((cos + rot_axis[0] * rot_axis[0] * (1 - cos),
rot_axis[0] * rot_axis[1] * (1 - cos) - rot_axis[2] * sin,
rot_axis[0] * rot_axis[2] * (1 - cos) + rot_axis[1] * sin),
(rot_axis[1] * rot_axis[0] * (1 - cos) + rot_axis[2] * sin,
cos + rot_axis[1] * rot_axis[1] * (1 - cos),
rot_axis[1] * rot_axis[2] * (1 - cos) - rot_axis[0] * sin),
(rot_axis[2] * rot_axis[0] * (1 - cos) - rot_axis[1] * sin,
rot_axis[2] * rot_axis[1] * (1 - cos) + rot_axis[0] * sin,
cos + rot_axis[2] * rot_axis[2] * (1 - cos)))
def draw_axes(settings):
GL.glMatrixMode(GL.GL_MODELVIEW)
GL.glLoadIdentity()
#GL.glTranslatef(0, 0, -2)
size_x = abs(settings.get("maxx"))
size_y = abs(settings.get("maxy"))
size_z = abs(settings.get("maxz"))
size = number(1.7) * max(size_x, size_y, size_z)
# the divider is just based on playing with numbers
scale = size / number(1500.0)
string_distance = number(1.1) * size
GL.glBegin(GL.GL_LINES)
GL.glColor3f(1, 0, 0)
GL.glVertex3f(0, 0, 0)
GL.glVertex3f(size, 0, 0)
GL.glEnd()
draw_string(string_distance, 0, 0, 'xy', "X", scale=scale)
GL.glBegin(GL.GL_LINES)
GL.glColor3f(0, 1, 0)
GL.glVertex3f(0, 0, 0)
GL.glVertex3f(0, size, 0)
GL.glEnd()
draw_string(0, string_distance, 0, 'yz', "Y", scale=scale)
GL.glBegin(GL.GL_LINES)
GL.glColor3f(0, 0, 1)
GL.glVertex3f(0, 0, 0)
GL.glVertex3f(0, 0, size)
GL.glEnd()
draw_string(0, 0, string_distance, 'xz', "Z", scale=scale)
def move_camera_by_screen(self, x_move, y_move, max_model_shift):
""" move the camera acoording to a mouse movement
@type x_move: int
@value x_move: movement of the mouse along the x axis
@type y_move: int
@value y_move: movement of the mouse along the y axis
@type max_model_shift: float
@value max_model_shift: maximum shifting of the model view (e.g. for
x_move == screen width)
"""
factors_x, factors_y = self._get_axes_vectors()
width, height = self._get_screen_dimensions()
# relation of x/y movement to the respective screen dimension
win_x_rel = (-2 * x_move) / float(width) / math.sin(self.view["fovy"])
win_y_rel = (-2 * y_move) / float(height) / math.sin(self.view["fovy"])
# This code is completely arbitrarily based on trial-and-error for
# finding a nice movement speed for all distances.
# Anyone with a better approach should just fix this.
distance_vector = self.get("distance")
distance = float(sqrt(sum([dim**2 for dim in distance_vector])))
win_x_rel *= math.cos(win_x_rel / distance)**20
win_y_rel *= math.cos(win_y_rel / distance)**20
# update the model position that should be centered on the screen
old_center = self.view["center"]
new_center = []
for i in range(3):
new_center.append(old_center[i] \
+ max_model_shift * (number(win_x_rel) * factors_x[i] \
+ number(win_y_rel) * factors_y[i]))
self.view["center"] = tuple(new_center)
def move_camera_by_screen(self, x_move, y_move, max_model_shift):
""" move the camera acoording to a mouse movement
@type x_move: int
@value x_move: movement of the mouse along the x axis
@type y_move: int
@value y_move: movement of the mouse along the y axis
@type max_model_shift: float
@value max_model_shift: maximum shifting of the model view (e.g. for
x_move == screen width)
"""
factors_x, factors_y = self._get_axes_vectors()
width, height = self._get_screen_dimensions()
# relation of x/y movement to the respective screen dimension
win_x_rel = (-2 * x_move) / float(width) / math.sin(self.view["fovy"])
win_y_rel = (-2 * y_move) / float(height) / math.sin(self.view["fovy"])
# This code is completely arbitrarily based on trial-and-error for
# finding a nice movement speed for all distances.
# Anyone with a better approach should just fix this.
distance_vector = self.get("distance")
distance = float(sqrt(sum([dim ** 2 for dim in distance_vector])))
win_x_rel *= math.cos(win_x_rel / distance) ** 20
win_y_rel *= math.cos(win_y_rel / distance) ** 20
# update the model position that should be centered on the screen
old_center = self.view["center"]
new_center = []
for i in range(3):
new_center.append(old_center[i] \
+ max_model_shift * (number(win_x_rel) * factors_x[i] \
+ number(win_y_rel) * factors_y[i]))
self.view["center"] = tuple(new_center)
def __init__(self, x, y, z):
self.id = Point.id
Point.id += 1
self.x = number(x)
self.y = number(y)
self.z = number(z)
self.reset_cache()
def get_rotation_matrix_axis_angle(rot_axis, rot_angle, use_radians=True):
""" calculate rotation matrix for a normalized vector and an angle
see http://mathworld.wolfram.com/RotationMatrix.html
@type rot_axis: tuple(float)
@value rot_axis: the vector describes the rotation axis. Its length should
be 1.0 (normalized).
@type rot_angle: float
@value rot_angle: rotation angle (radiant)
@rtype: tuple(tuple(float))
@return: the roation matrix (3x3)
"""
if not use_radians:
rot_angle *= math.pi / 180
sin = number(math.sin(rot_angle))
cos = number(math.cos(rot_angle))
return ((cos + rot_axis[0]*rot_axis[0]*(1-cos),
rot_axis[0]*rot_axis[1]*(1-cos) - rot_axis[2]*sin,
rot_axis[0]*rot_axis[2]*(1-cos) + rot_axis[1]*sin),
(rot_axis[1]*rot_axis[0]*(1-cos) + rot_axis[2]*sin,
cos + rot_axis[1]*rot_axis[1]*(1-cos),
rot_axis[1]*rot_axis[2]*(1-cos) - rot_axis[0]*sin),
(rot_axis[2]*rot_axis[0]*(1-cos) - rot_axis[1]*sin,
rot_axis[2]*rot_axis[1]*(1-cos) + rot_axis[0]*sin,
cos + rot_axis[2]*rot_axis[2]*(1-cos)))
def _get_axes_vectors(self):
"""calculate the model vectors along the screen's x and y axes"""
# The "up" vector defines, in what proportion each axis of the model is
# in line with the screen's y axis.
v_up = self.view["up"]
factors_y = (number(v_up[0]), number(v_up[1]), number(v_up[2]))
# Calculate the proportion of each model axis according to the x axis of
# the screen.
distv = self.view["distance"]
distv = pnormalized((distv[0], distv[1], distv[2]))
factors_x = pnormalized(pcross(distv, (v_up[0], v_up[1], v_up[2])))
return (factors_x, factors_y)
def _get_axes_vectors(self):
"""calculate the model vectors along the screen's x and y axes"""
# The "up" vector defines, in what proportion each axis of the model is
# in line with the screen's y axis.
v_up = self.view["up"]
factors_y = (number(v_up[0]), number(v_up[1]), number(v_up[2]))
# Calculate the proportion of each model axis according to the x axis of
# the screen.
distv = self.view["distance"]
distv = pnormalized((distv[0], distv[1], distv[2]))
factors_x = pnormalized(pcross(distv, (v_up[0], v_up[1], v_up[2])))
return (factors_x, factors_y)
def set_bounds(self, low=None, high=None):
if not low is None:
if len(low) != 3:
raise ValueError, "lower bounds should be supplied as a " \
+ "tuple/list of 3 items - but %d were given" % len(low)
else:
self.bounds_low = [number(value) for value in low]
if not high is None:
if len(high) != 3:
raise ValueError, "upper bounds should be supplied as a " \
+ "tuple/list of 3 items - but %d were given" \
% len(high)
else:
self.bounds_high = [number(value) for value in high]
def set_bounds(self, low=None, high=None):
if not low is None:
if len(low) != 3:
raise ValueError, "lower bounds should be supplied as a " \
+ "tuple/list of 3 items - but %d were given" % len(low)
else:
self.bounds_low = [number(value) for value in low]
if not high is None:
if len(high) != 3:
raise ValueError, "upper bounds should be supplied as a " \
+ "tuple/list of 3 items - but %d were given" \
% len(high)
else:
self.bounds_high = [number(value) for value in high]
def get_absolute_limits(self, reference=None):
""" calculate the current absolute limits of the Bounds instance
@value reference: a reference object described by a tuple (or list) of
three item. These three values describe only the lower boundary of
this object (for the x, y and z axes). Each item must be a float
value. This argument is ignored for the boundary type "TYPE_CUSTOM".
@type reference: (tuple|list) of float
@returns: a tuple of two lists containg the low and high limits
@rvalue: tuple(list)
"""
# use the default reference if none was given
if reference is None:
reference = self.reference
# check if a reference is given (if necessary)
if self.bounds_type \
in (Bounds.TYPE_RELATIVE_MARGIN, Bounds.TYPE_FIXED_MARGIN):
if reference is None:
raise ValueError, "any non-custom boundary definition " \
+ "requires a reference object for caluclating " \
+ "absolute limits"
else:
ref_low, ref_high = reference.get_absolute_limits()
low = [None] * 3
high = [None] * 3
# calculate the absolute limits
if self.bounds_type == Bounds.TYPE_RELATIVE_MARGIN:
for index in range(3):
dim_width = ref_high[index] - ref_low[index]
low[index] = ref_low[index] \
- self.bounds_low[index] * dim_width
high[index] = ref_high[index] \
+ self.bounds_high[index] * dim_width
elif self.bounds_type == Bounds.TYPE_FIXED_MARGIN:
for index in range(3):
low[index] = ref_low[index] - self.bounds_low[index]
high[index] = ref_high[index] + self.bounds_high[index]
elif self.bounds_type == Bounds.TYPE_CUSTOM:
for index in range(3):
low[index] = number(self.bounds_low[index])
high[index] = number(self.bounds_high[index])
else:
# this should not happen
raise NotImplementedError, "the function 'get_absolute_limits' is" \
+ " currently not implemented for the bounds_type " \
+ "'%s'" % str(self.bounds_type)
return low, high
def get_absolute_limits(self, reference=None):
""" calculate the current absolute limits of the Bounds instance
@value reference: a reference object described by a tuple (or list) of
three item. These three values describe only the lower boundary of
this object (for the x, y and z axes). Each item must be a float
value. This argument is ignored for the boundary type "TYPE_CUSTOM".
@type reference: (tuple|list) of float
@returns: a tuple of two lists containg the low and high limits
@rvalue: tuple(list)
"""
# use the default reference if none was given
if reference is None:
reference = self.reference
# check if a reference is given (if necessary)
if self.bounds_type \
in (Bounds.TYPE_RELATIVE_MARGIN, Bounds.TYPE_FIXED_MARGIN):
if reference is None:
raise ValueError, "any non-custom boundary definition " \
+ "requires a reference object for caluclating " \
+ "absolute limits"
else:
ref_low, ref_high = reference.get_absolute_limits()
low = [None] * 3
high = [None] * 3
# calculate the absolute limits
if self.bounds_type == Bounds.TYPE_RELATIVE_MARGIN:
for index in range(3):
dim_width = ref_high[index] - ref_low[index]
low[index] = ref_low[index] \
- self.bounds_low[index] * dim_width
high[index] = ref_high[index] \
+ self.bounds_high[index] * dim_width
elif self.bounds_type == Bounds.TYPE_FIXED_MARGIN:
for index in range(3):
low[index] = ref_low[index] - self.bounds_low[index]
high[index] = ref_high[index] + self.bounds_high[index]
elif self.bounds_type == Bounds.TYPE_CUSTOM:
for index in range(3):
low[index] = number(self.bounds_low[index])
high[index] = number(self.bounds_high[index])
else:
# this should not happen
raise NotImplementedError, "the function 'get_absolute_limits' is" \
+ " currently not implemented for the bounds_type " \
+ "'%s'" % str(self.bounds_type)
return low, high
def __init__(self, radius, location=None, height=None):
super(BaseCutter, self).__init__()
if location is None:
location = (0, 0, 0)
if height is None:
height = 10
radius = number(radius)
self.height = number(height)
self.radius = radius
self.radiussq = radius**2
self.required_distance = 0
self.distance_radius = self.radius
self.distance_radiussq = self.distance_radius**2
self.shape = {}
self.location = location
self.moveto(self.location)
self.uuid = None
self.update_uuid()
def __init__(self, radius, location=None, height=None):
super(BaseCutter, self).__init__()
if location is None:
location = Point(0, 0, 0)
if height is None:
height = 10
radius = number(radius)
self.height = number(height)
self.radius = radius
self.radiussq = radius ** 2
self.required_distance = 0
self.distance_radius = self.radius
self.distance_radiussq = self.distance_radius ** 2
self.shape = {}
self.location = location
self.moveto(self.location)
self.uuid = None
self.update_uuid()
def get_machine_movement_distance(self, safety_height=0.0):
result = 0
safety_height = number(safety_height)
current_position = None
# go through all points of the path
for new_pos, rapid in self.get_moves(safety_height):
if not current_position is None:
result += new_pos.sub(current_position).norm
current_position = new_pos
return result
def get_machine_movement_distance(self, safety_height=0.0):
result = 0
safety_height = number(safety_height)
current_position = None
# go through all points of the path
for new_pos, rapid in self.get_moves(safety_height):
if not current_position is None:
result += new_pos.sub(current_position).norm
current_position = new_pos
return result
def get_machine_time(self, safety_height=0.0):
""" calculate an estimation of the time required for processing the
toolpath with the machine
@value safety_height: the safety height configured for this toolpath
@type safety_height: float
@rtype: float
@returns: the machine time used for processing the toolpath in minutes
"""
result = 0
feedrate = self.toolpath_settings.get_tool_settings()["feedrate"]
feedrate = number(feedrate)
safety_height = number(safety_height)
current_position = None
# go through all points of the path
for new_pos, rapid in self.get_moves(safety_height):
if not current_position is None:
result += new_pos.sub(current_position).norm / feedrate
current_position = new_pos
return result
def multiply_vector_matrix(v, m):
""" Multiply a 3d vector with a 3x3 matrix. The result is a 3d vector.
@type v: tuple(float) | list(float)
@value v: a 3d vector as tuple or list containing three floats
@type m: tuple(tuple(float)) | list(list(float))
@value m: a 3x3 list/tuple of floats
@rtype: tuple(float)
@return: a tuple of 3 floats as the matrix product
"""
if len(m) == 9:
m = [number(value) for value in m]
m = ((m[0], m[1], m[2]), (m[3], m[4], m[5]), (m[6], m[7], m[8]))
else:
new_m = []
for column in m:
new_m.append([number(value) for value in column])
v = [number(value) for value in v]
return (v[0] * m[0][0] + v[1] * m[0][1] + v[2] * m[0][2],
v[0] * m[1][0] + v[1] * m[1][1] + v[2] * m[1][2],
v[0] * m[2][0] + v[1] * m[2][1] + v[2] * m[2][2])
def multiply_vector_matrix(v, m):
""" Multiply a 3d vector with a 3x3 matrix. The result is a 3d vector.
@type v: tuple(float) | list(float)
@value v: a 3d vector as tuple or list containing three floats
@type m: tuple(tuple(float)) | list(list(float))
@value m: a 3x3 list/tuple of floats
@rtype: tuple(float)
@return: a tuple of 3 floats as the matrix product
"""
if len(m) == 9:
m = [number(value) for value in m]
m = ((m[0], m[1], m[2]), (m[3], m[4], m[5]), (m[6], m[7], m[8]))
else:
new_m = []
for column in m:
new_m.append([number(value) for value in column])
v = [number(value) for value in v]
return (v[0] * m[0][0] + v[1] * m[0][1] + v[2] * m[0][2],
v[0] * m[1][0] + v[1] * m[1][1] + v[2] * m[1][2],
v[0] * m[2][0] + v[1] * m[2][1] + v[2] * m[2][2])
def get_support_grid(minx,
maxx,
miny,
maxy,
z_plane,
dist_x,
dist_y,
thickness,
height,
offset_x=0.0,
offset_y=0.0,
adjustments_x=None,
adjustments_y=None):
lines_x, lines_y = get_support_grid_locations(minx, maxx, miny, maxy,
dist_x, dist_y, offset_x,
offset_y, adjustments_x,
adjustments_y)
# create all x grid lines
grid_model = Model()
# convert all inputs to "number"
thickness = number(thickness)
height = number(height)
# helper variables
thick_half = thickness / 2
length_extension = max(thickness, height)
for line_x in lines_x:
# we make the grid slightly longer (by thickness) than necessary
grid_model += _add_aligned_cuboid_to_model(line_x - thick_half,
line_x + thick_half,
miny - length_extension,
maxy + length_extension,
z_plane, z_plane + height)
for line_y in lines_y:
# we make the grid slightly longer (by thickness) than necessary
grid_model += _add_aligned_cuboid_to_model(minx - length_extension,
maxx + length_extension,
line_y - thick_half,
line_y + thick_half,
z_plane, z_plane + height)
return grid_model
def set_drill(self, shape, position):
#geom = ode.GeomTransform(self._space)
#geom.setOffset(position)
#geom.setGeom(shape)
#shape.setOffset(position)
self._space.add(shape)
# sadly PyODE forgets to update the "space" attribute that we need in
# the cutters' "extend" functions
shape.space = self._space
self._add_geom(shape, position, append=False)
self._drill_offset = [number(value) for value in position]
self._drill = shape
self.reset_drill()
self._dirty = True
def set_drill(self, shape, position):
#geom = ode.GeomTransform(self._space)
#geom.setOffset(position)
#geom.setGeom(shape)
#shape.setOffset(position)
self._space.add(shape)
# sadly PyODE forgets to update the "space" attribute that we need in
# the cutters' "extend" functions
shape.space = self._space
self._add_geom(shape, position, append=False)
self._drill_offset = [number(value) for value in position]
self._drill = shape
self.reset_drill()
self._dirty = True
def __init__(self, radius, minorradius, **kwargs):
minorradius = number(minorradius)
self.minorradius = minorradius
# we need "minorradius" for "moveto" - thus set it before parent's init
BaseCutter.__init__(self, radius, **kwargs)
self.majorradius = self.radius - minorradius
self.axis = (0, 0, 1)
self.majorradiussq = self.majorradius**2
self.minorradiussq = self.minorradius**2
self.distance_majorradius = self.majorradius \
+ self.get_required_distance()
self.distance_minorradius = self.minorradius \
+ self.get_required_distance()
self.distance_majorradiussq = self.distance_majorradius**2
self.distance_minorradiussq = self.distance_minorradius**2
def __init__(self, radius, minorradius, **kwargs):
minorradius = number(minorradius)
self.minorradius = minorradius
# we need "minorradius" for "moveto" - thus set it before parent's init
BaseCutter.__init__(self, radius, **kwargs)
self.majorradius = self.radius - minorradius
self.axis = (0, 0, 1)
self.majorradiussq = self.majorradius ** 2
self.minorradiussq = self.minorradius ** 2
self.distance_majorradius = self.majorradius \
+ self.get_required_distance()
self.distance_minorradius = self.minorradius \
+ self.get_required_distance()
self.distance_majorradiussq = self.distance_majorradius ** 2
self.distance_minorradiussq = self.distance_minorradius ** 2
def get_support_grid(minx, maxx, miny, maxy, z_plane, dist_x, dist_y, thickness,
height, offset_x=0.0, offset_y=0.0, adjustments_x=None,
adjustments_y=None):
lines_x, lines_y = get_support_grid_locations(minx, maxx, miny, maxy,
dist_x, dist_y, offset_x, offset_y, adjustments_x, adjustments_y)
# create all x grid lines
grid_model = Model()
# convert all inputs to "number"
thickness = number(thickness)
height = number(height)
# helper variables
thick_half = thickness / 2
length_extension = max(thickness, height)
for line_x in lines_x:
# we make the grid slightly longer (by thickness) than necessary
grid_model += _add_aligned_cuboid_to_model(line_x - thick_half,
line_x + thick_half, miny - length_extension,
maxy + length_extension, z_plane, z_plane + height)
for line_y in lines_y:
# we make the grid slightly longer (by thickness) than necessary
grid_model += _add_aligned_cuboid_to_model(minx - length_extension,
maxx + length_extension, line_y - thick_half,
line_y + thick_half, z_plane, z_plane + height)
return grid_model
def auto_adjust_distance(self):
s = self.core
v = self.view
# adjust the distance to get a view of the whole object
low_high = zip(*self._get_low_high_dims())
if (None, None) in low_high:
return
max_dim = max([high - low for low, high in low_high])
distv = pnormalized((v["distance"][0], v["distance"][1], v["distance"][2]))
# The multiplier "1.25" is based on experiments. 1.414 (sqrt(2)) should
# be roughly sufficient for showing the diagonal of any model.
distv = pmul(distv, (max_dim * 1.25) / number(math.sin(v["fovy"] / 2)))
self.view["distance"] = distv
# Adjust the "far" distance for the camera to make sure, that huge
# models (e.g. x=1000) are still visible.
self.view["zfar"] = 100 * max_dim
def auto_adjust_distance(self):
s = self.settings
v = self.view
# adjust the distance to get a view of the whole object
dimx = s.get("maxx") - s.get("minx")
dimy = s.get("maxy") - s.get("miny")
dimz = s.get("maxz") - s.get("minz")
max_dim = max(max(dimx, dimy), dimz)
distv = Point(v["distance"][0], v["distance"][1], v["distance"][2]).normalized()
# The multiplier "1.25" is based on experiments. 1.414 (sqrt(2)) should
# be roughly sufficient for showing the diagonal of any model.
distv = distv.mul((max_dim * 1.25) / number(math.sin(v["fovy"] / 2)))
self.view["distance"] = (distv.x, distv.y, distv.z)
# Adjust the "far" distance for the camera to make sure, that huge
# models (e.g. x=1000) are still visible.
self.view["zfar"] = 100 * max_dim
def auto_adjust_distance(self):
s = self.settings
v = self.view
# adjust the distance to get a view of the whole object
dimx = s.get("maxx") - s.get("minx")
dimy = s.get("maxy") - s.get("miny")
dimz = s.get("maxz") - s.get("minz")
max_dim = max(max(dimx, dimy), dimz)
distv = Point(v["distance"][0], v["distance"][1],
v["distance"][2]).normalized()
# The multiplier "1.25" is based on experiments. 1.414 (sqrt(2)) should
# be roughly sufficient for showing the diagonal of any model.
distv = distv.mul((max_dim * 1.25) / number(math.sin(v["fovy"] / 2)))
self.view["distance"] = (distv.x, distv.y, distv.z)
# Adjust the "far" distance for the camera to make sure, that huge
# models (e.g. x=1000) are still visible.
self.view["zfar"] = 100 * max_dim
def auto_adjust_distance(self):
s = self.core
v = self.view
# adjust the distance to get a view of the whole object
low_high = zip(*self._get_low_high_dims())
if (None, None) in low_high:
return
max_dim = max([high - low for low, high in low_high])
distv = pnormalized(
(v["distance"][0], v["distance"][1], v["distance"][2]))
# The multiplier "1.25" is based on experiments. 1.414 (sqrt(2)) should
# be roughly sufficient for showing the diagonal of any model.
distv = pmul(distv, (max_dim * 1.25) / number(math.sin(v["fovy"] / 2)))
self.view["distance"] = distv
# Adjust the "far" distance for the camera to make sure, that huge
# models (e.g. x=1000) are still visible.
self.view["zfar"] = 100 * max_dim
def get_support_grid_locations(minx,
maxx,
miny,
maxy,
dist_x,
dist_y,
offset_x=0.0,
offset_y=0.0,
adjustments_x=None,
adjustments_y=None):
def get_lines(center, dist, min_value, max_value):
""" generate a list of positions starting from the middle going up and
and down
"""
if dist > 0:
lines = [center]
current = center
while current - dist > min_value:
current -= dist
lines.insert(0, current)
current = center
while current + dist < max_value:
current += dist
lines.append(current)
else:
lines = []
# remove lines that are out of range (e.g. due to a huge offset)
lines = [line for line in lines if min_value < line < max_value]
return lines
# convert all inputs to the type defined in "number"
dist_x = number(dist_x)
dist_y = number(dist_y)
offset_x = number(offset_x)
offset_y = number(offset_y)
center_x = (maxx + minx) / 2 + offset_x
center_y = (maxy + miny) / 2 + offset_y
lines_x = get_lines(center_x, dist_x, minx, maxx)
lines_y = get_lines(center_y, dist_y, miny, maxy)
if adjustments_x:
for index in range(min(len(lines_x), len(adjustments_x))):
lines_x[index] += number(adjustments_x[index])
if adjustments_y:
for index in range(min(len(lines_y), len(adjustments_y))):
lines_y[index] += number(adjustments_y[index])
return lines_x, lines_y
def get_support_grid_locations(minx, maxx, miny, maxy, dist_x, dist_y,
offset_x=0.0, offset_y=0.0, adjustments_x=None, adjustments_y=None):
def get_lines(center, dist, min_value, max_value):
""" generate a list of positions starting from the middle going up and
and down
"""
if dist > 0:
lines = [center]
current = center
while current - dist > min_value:
current -= dist
lines.insert(0, current)
current = center
while current + dist < max_value:
current += dist
lines.append(current)
else:
lines = []
# remove lines that are out of range (e.g. due to a huge offset)
lines = [line for line in lines if min_value < line < max_value]
return lines
# convert all inputs to the type defined in "number"
dist_x = number(dist_x)
dist_y = number(dist_y)
offset_x = number(offset_x)
offset_y = number(offset_y)
center_x = (maxx + minx) / 2 + offset_x
center_y = (maxy + miny) / 2 + offset_y
lines_x = get_lines(center_x, dist_x, minx, maxx)
lines_y = get_lines(center_y, dist_y, miny, maxy)
if adjustments_x:
for index in range(min(len(lines_x), len(adjustments_x))):
lines_x[index] += number(adjustments_x[index])
if adjustments_y:
for index in range(min(len(lines_y), len(adjustments_y))):
lines_y[index] += number(adjustments_y[index])
return lines_x, lines_y
def pdiv(a, c):
c = number(c)
return (a[0] / c, a[1] / c, a[2] / c)
def mul(self, c):
c = number(c)
return Point(self.x * c, self.y * c, self.z * c)
def scale_distance(self, scale):
if scale != 0:
scale = number(scale)
dist = self.view["distance"]
self.view["distance"] = (scale * dist[0], scale * dist[1],
scale * dist[2])
def generate_toolpath(model, tool_settings=None,
bounds=None, direction="x",
path_generator="DropCutter", path_postprocessor="ZigZagCutter",
material_allowance=0, overlap_percent=0, step_down=0, engrave_offset=0,
milling_style="ignore", pocketing_type="none",
support_grid_type=None, support_grid_distance_x=None,
support_grid_distance_y=None, support_grid_thickness=None,
support_grid_height=None, support_grid_offset_x=None,
support_grid_offset_y=None, support_grid_adjustments_x=None,
support_grid_adjustments_y=None, support_grid_average_distance=None,
support_grid_minimum_bridges=None, support_grid_length=None,
calculation_backend=None, callback=None):
""" abstract interface for generating a toolpath
@type model: pycam.Geometry.Model.Model
@value model: a model contains surface triangles or a contour
@type tool_settings: dict
@value tool_settings: contains at least the following keys (depending on
the tool type):
"shape": any of possible cutter shape (see "pycam.Cutters")
"tool_radius": main radius of the tools
"torus_radius": (only for ToroidalCutter) second toroidal radius
@type bounds_low: tuple(float) | list(float)
@value bounds_low: the lower processing boundary (used for the center of
the tool) (order: minx, miny, minz)
@type bounds_high: tuple(float) | list(float)
@value bounds_high: the lower processing boundary (used for the center of
the tool) (order: maxx, maxy, maxz)
@type direction: str
@value direction: any member of the DIRECTIONS set (e.g. "x", "y" or "xy")
@type path_generator: str
@value path_generator: any member of the PATH_GENERATORS set
@type path_postprocessor: str
@value path_postprocessor: any member of the PATH_POSTPROCESSORS set
@type material_allowance: float
@value material_allowance: the minimum distance between the tool and the model
@type overlap_percent: int
@value overlap_percent: the overlap between two adjacent tool paths (0..100) given in percent
@type step_down: float
@value step_down: maximum height of each layer (for PushCutter)
@type engrave_offset: float
@value engrave_offset: toolpath distance to the contour model
@type support_grid_distance_x: float
@value support_grid_distance_x: distance between support grid lines along x
@type support_grid_distance_y: float
@value support_grid_distance_y: distance between support grid lines along y
@type support_grid_thickness: float
@value support_grid_thickness: thickness of the support grid
@type support_grid_height: float
@value support_grid_height: height of the support grid
@type support_grid_offset_x: float
@value support_grid_offset_x: shift the support grid by this value along x
@type support_grid_offset_y: float
@value support_grid_offset_y: shift the support grid by this value along y
@type support_grid_adjustments_x: list(float)
@value support_grid_adjustments_x: manual adjustment of each x-grid bar
@type support_grid_adjustments_y: list(float)
@value support_grid_adjustments_y: manual adjustment of each y-grid bar
@type calculation_backend: str | None
@value calculation_backend: any member of the CALCULATION_BACKENDS set
The default is the triangular collision detection.
@rtype: pycam.Toolpath.Toolpath | str
@return: the resulting toolpath object or an error string in case of invalid
arguments
"""
log.debug("Starting toolpath generation")
step_down = number(step_down)
engrave_offset = number(engrave_offset)
if bounds is None:
# no bounds were given - we use the boundaries of the model
bounds = pycam.Toolpath.Bounds(pycam.Toolpath.Bounds.TYPE_CUSTOM,
(model.minx, model.miny, model.minz),
(model.maxx, model.maxy, model.maxz))
bounds_low, bounds_high = bounds.get_absolute_limits()
minx, miny, minz = [number(value) for value in bounds_low]
maxx, maxy, maxz = [number(value) for value in bounds_high]
# trimesh model or contour model?
if isinstance(model, pycam.Geometry.Model.ContourModel):
# contour model
trimesh_models = []
contour_model = model
else:
# trimesh model
trimesh_models = [model]
contour_model = None
# Due to some weirdness the height of the drill must be bigger than the
# object's size. Otherwise some collisions are not detected.
cutter_height = 4 * abs(maxz - minz)
cutter = pycam.Cutters.get_tool_from_settings(tool_settings, cutter_height)
if isinstance(cutter, basestring):
return cutter
if not path_generator in ("EngraveCutter", "ContourFollow"):
# material allowance is not available for these two strategies
cutter.set_required_distance(material_allowance)
# create the grid model if requested
if (support_grid_type == "grid") \
and (((not support_grid_distance_x is None) \
or (not support_grid_distance_y is None)) \
and (not support_grid_thickness is None)):
# grid height defaults to the thickness
if support_grid_height is None:
support_grid_height = support_grid_thickness
if (support_grid_distance_x < 0) or (support_grid_distance_y < 0):
return "The distance of the support grid must be a positive value"
if not ((support_grid_distance_x > 0) or (support_grid_distance_y > 0)):
return "Both distance values for the support grid may not be " \
+ "zero at the same time"
if support_grid_thickness <= 0:
return "The thickness of the support grid must be a positive value"
if support_grid_height <= 0:
return "The height of the support grid must be a positive value"
if not callback is None:
callback(text="Preparing support grid model ...")
support_grid_model = pycam.Toolpath.SupportGrid.get_support_grid(
minx, maxx, miny, maxy, minz, support_grid_distance_x,
support_grid_distance_y, support_grid_thickness,
support_grid_height, offset_x=support_grid_offset_x,
offset_y=support_grid_offset_y,
adjustments_x=support_grid_adjustments_x,
adjustments_y=support_grid_adjustments_y)
trimesh_models.append(support_grid_model)
elif (support_grid_type in ("distributed_edges", "distributed_corners")) \
and (not support_grid_average_distance is None) \
and (not support_grid_thickness is None) \
and (not support_grid_length is None):
if support_grid_height is None:
support_grid_height = support_grid_thickness
if support_grid_minimum_bridges is None:
support_grid_minimum_bridges = 2
if support_grid_average_distance <= 0:
return "The average support grid distance must be a positive value"
if support_grid_minimum_bridges <= 0:
return "The minimum number of bridged per polygon must be a " \
+ "positive value"
if support_grid_thickness <= 0:
return "The thickness of the support grid must be a positive value"
if support_grid_height <= 0:
return "The height of the support grid must be a positive value"
if not callback is None:
callback(text="Preparing support grid model ...")
# check which model to choose
if contour_model:
model = contour_model
else:
model = trimesh_models[0]
start_at_corners = (support_grid_type == "distributed_corners")
support_grid_model = pycam.Toolpath.SupportGrid.get_support_distributed(
model, minz, support_grid_average_distance,
support_grid_minimum_bridges, support_grid_thickness,
support_grid_height, support_grid_length,
bounds, start_at_corners=start_at_corners)
trimesh_models.append(support_grid_model)
elif (not support_grid_type) or (support_grid_type == "none"):
pass
else:
return "Invalid support grid type selected: %s" % support_grid_type
# Adapt the contour_model to the engraving offset. This offset is
# considered to be part of the material_allowance.
if contour_model and (engrave_offset != 0):
if not callback is None:
callback(text="Preparing contour model with offset ...")
contour_model = contour_model.get_offset_model(engrave_offset,
callback=callback)
if not contour_model:
return "Failed to calculate offset polygons"
if not callback is None:
# reset percentage counter after the contour model calculation
callback(percent=0)
if callback(text="Checking contour model with offset for " \
+ "collisions ..."):
# quit requested
return None
progress_callback = ProgressCounter(
len(contour_model.get_polygons()), callback).increment
else:
progress_callback = None
result = contour_model.check_for_collisions(callback=progress_callback)
if result is None:
return None
elif result:
warning = "The contour model contains colliding line groups. " + \
"This can cause problems with an engraving offset.\n" + \
"A collision was detected at (%.2f, %.2f, %.2f)." % \
(result.x, result.y, result.z)
log.warning(warning)
else:
# no collisions and no user interruption
pass
# check the pocketing type
if contour_model and (pocketing_type != "none"):
if not callback is None:
callback(text="Generating pocketing polygons ...")
pocketing_offset = cutter.radius * 1.8
# TODO: this is an arbitrary limit to avoid infinite loops
pocketing_limit = 1000
base_polygons = []
other_polygons = []
if pocketing_type == "holes":
# fill polygons with negative area
for poly in contour_model.get_polygons():
if poly.is_closed and not poly.is_outer():
base_polygons.append(poly)
else:
other_polygons.append(poly)
elif pocketing_type == "enclosed":
# fill polygons with positive area
pocketing_offset *= -1
for poly in contour_model.get_polygons():
if poly.is_closed and poly.is_outer():
base_polygons.append(poly)
else:
other_polygons.append(poly)
else:
return "Unknown pocketing type given (not one of 'none', " + \
"'holes', 'enclosed'): %s" % str(pocketing_type)
# For now we use only the polygons that do not surround eny other
# polygons. Sorry - the pocketing is currently very simple ...
base_filtered_polygons = []
for candidate in base_polygons:
if callback and callback():
return "Interrupted"
for other in other_polygons:
if candidate.is_polygon_inside(other):
break
else:
base_filtered_polygons.append(candidate)
# start the pocketing for all remaining polygons
pocket_polygons = []
for base_polygon in base_filtered_polygons:
current_queue = [base_polygon]
next_queue = []
pocket_depth = 0
while current_queue and (pocket_depth < pocketing_limit):
if callback and callback():
return "Interrupted"
for poly in current_queue:
result = poly.get_offset_polygons(pocketing_offset)
pocket_polygons.extend(result)
next_queue.extend(result)
pocket_depth += 1
current_queue = next_queue
next_queue = []
# use a copy instead of the original
contour_model = contour_model.get_copy()
for pocket in pocket_polygons:
contour_model.append(pocket)
# limit the contour model to the bounding box
if contour_model:
# use minz/maxz of the contour model (in other words: ignore z)
contour_model = contour_model.get_cropped_model(minx, maxx, miny, maxy,
contour_model.minz, contour_model.maxz)
if not contour_model:
return "No part of the contour model is within the bounding box."
physics = _get_physics(trimesh_models, cutter, calculation_backend)
if isinstance(physics, basestring):
return physics
generator = _get_pathgenerator_instance(trimesh_models, contour_model,
cutter, path_generator, path_postprocessor, physics,
milling_style)
if isinstance(generator, basestring):
return generator
overlap = overlap_percent / 100.0
if (overlap < 0) or (overlap >= 1):
return "Invalid overlap value (%f): should be greater or equal 0 " \
+ "and lower than 1"
# factor "2" since we are based on radius instead of diameter
line_stepping = 2 * number(tool_settings["tool_radius"]) * (1 - overlap)
if path_generator == "PushCutter":
step_width = None
else:
# the step_width is only used for the DropCutter
step_width = tool_settings["tool_radius"] / 4
if path_generator == "DropCutter":
layer_distance = None
else:
layer_distance = step_down
direction_dict = {"x": pycam.Toolpath.MotionGrid.GRID_DIRECTION_X,
"y": pycam.Toolpath.MotionGrid.GRID_DIRECTION_Y,
"xy": pycam.Toolpath.MotionGrid.GRID_DIRECTION_XY}
milling_style_grid = {
"ignore": pycam.Toolpath.MotionGrid.MILLING_STYLE_IGNORE,
"conventional": pycam.Toolpath.MotionGrid.MILLING_STYLE_CONVENTIONAL,
"climb": pycam.Toolpath.MotionGrid.MILLING_STYLE_CLIMB}
if path_generator in ("DropCutter", "PushCutter"):
motion_grid = pycam.Toolpath.MotionGrid.get_fixed_grid(bounds,
layer_distance, line_stepping, step_width=step_width,
grid_direction=direction_dict[direction],
milling_style=milling_style_grid[milling_style])
if path_generator == "DropCutter":
toolpath = generator.GenerateToolPath(motion_grid, minz, maxz,
callback)
else:
toolpath = generator.GenerateToolPath(motion_grid, callback)
elif path_generator == "EngraveCutter":
if step_down > 0:
dz = step_down
else:
dz = maxz - minz
toolpath = generator.GenerateToolPath(minz, maxz, step_width, dz,
callback)
elif path_generator == "ContourFollow":
if step_down > 0:
dz = step_down
else:
dz = maxz - minz
if dz <= 0:
dz = 1
toolpath = generator.GenerateToolPath(minx, maxx, miny, maxy, minz,
maxz, dz, callback)
elif path_generator == "Contour2dCutter": # JULIEN
toolpath = generator.GenerateToolPath(callback)
else:
return "Invalid path generator (%s): not one of %s" \
% (path_generator, PATH_GENERATORS)
return toolpath
def pmul(a, c):
c = number(c)
return (a[0] * c, a[1] * c, a[2] * c)
def pmul(a, c):
c = number(c)
return (a[0] * c, a[1] * c, a[2] * c)
def div(self, c):
c = number(c)
return Point(self.x / c, self.y / c, self.z / c)
def div(self, c):
c = number(c)
return Point(self.x / c, self.y / c, self.z / c)
def set_required_distance(self, value):
if value >= 0:
self.required_distance = number(value)
self.distance_radius = self.radius + self.get_required_distance()
self.distance_radiussq = self.distance_radius * self.distance_radius
self.update_uuid()
def generate_toolpath(model,
tool_settings=None,
bounds=None,
direction="x",
path_generator="DropCutter",
path_postprocessor="ZigZagCutter",
material_allowance=0,
overlap_percent=0,
step_down=0,
engrave_offset=0,
milling_style="ignore",
pocketing_type="none",
support_model=None,
calculation_backend=None,
callback=None):
""" abstract interface for generating a toolpath
@type model: pycam.Geometry.Model.Model
@value model: a model contains surface triangles or a contour
@type tool_settings: dict
@value tool_settings: contains at least the following keys (depending on
the tool type):
"shape": any of possible cutter shape (see "pycam.Cutters")
"tool_radius": main radius of the tools
"torus_radius": (only for ToroidalCutter) second toroidal radius
@type bounds_low: tuple(float) | list(float)
@value bounds_low: the lower processing boundary (used for the center of
the tool) (order: minx, miny, minz)
@type bounds_high: tuple(float) | list(float)
@value bounds_high: the lower processing boundary (used for the center of
the tool) (order: maxx, maxy, maxz)
@type direction: str
@value direction: any member of the DIRECTIONS set (e.g. "x", "y" or "xy")
@type path_generator: str
@value path_generator: any member of the PATH_GENERATORS set
@type path_postprocessor: str
@value path_postprocessor: any member of the PATH_POSTPROCESSORS set
@type material_allowance: float
@value material_allowance: the minimum distance between the tool and the model
@type overlap_percent: int
@value overlap_percent: the overlap between two adjacent tool paths (0..100) given in percent
@type step_down: float
@value step_down: maximum height of each layer (for PushCutter)
@type engrave_offset: float
@value engrave_offset: toolpath distance to the contour model
@type calculation_backend: str | None
@value calculation_backend: any member of the CALCULATION_BACKENDS set
The default is the triangular collision detection.
@rtype: pycam.Toolpath.Toolpath | str
@return: the resulting toolpath object or an error string in case of invalid
arguments
"""
log.debug("Starting toolpath generation")
step_down = number(step_down)
engrave_offset = number(engrave_offset)
if bounds is None:
# no bounds were given - we use the boundaries of the model
bounds = pycam.Toolpath.Bounds(pycam.Toolpath.Bounds.TYPE_CUSTOM,
(model.minx, model.miny, model.minz),
(model.maxx, model.maxy, model.maxz))
bounds_low, bounds_high = bounds.get_absolute_limits()
minx, miny, minz = [number(value) for value in bounds_low]
maxx, maxy, maxz = [number(value) for value in bounds_high]
# trimesh model or contour model?
if isinstance(model, pycam.Geometry.Model.ContourModel):
# contour model
trimesh_models = []
contour_model = model
else:
# trimesh model
trimesh_models = [model]
contour_model = None
# Due to some weirdness the height of the drill must be bigger than the
# object's size. Otherwise some collisions are not detected.
cutter_height = 4 * abs(maxz - minz)
cutter = pycam.Cutters.get_tool_from_settings(tool_settings, cutter_height)
if isinstance(cutter, basestring):
return cutter
if not path_generator in ("EngraveCutter", "ContourFollow"):
# material allowance is not available for these two strategies
cutter.set_required_distance(material_allowance)
# create the grid model if requested
if support_model:
trimesh_models.append(support_model)
# Adapt the contour_model to the engraving offset. This offset is
# considered to be part of the material_allowance.
if contour_model and (engrave_offset != 0):
if not callback is None:
callback(text="Preparing contour model with offset ...")
contour_model = contour_model.get_offset_model(engrave_offset,
callback=callback)
if contour_model:
return "Failed to calculate offset polygons"
if not callback is None:
# reset percentage counter after the contour model calculation
callback(percent=0)
if callback(text="Checking contour model with offset for " \
+ "collisions ..."):
# quit requested
return None
progress_callback = ProgressCounter(
len(contour_model.get_polygons()), callback).increment
else:
progress_callback = None
result = contour_model.check_for_collisions(callback=progress_callback)
if result is None:
return None
elif result:
warning = "The contour model contains colliding line groups. " + \
"This can cause problems with an engraving offset.\n" + \
"A collision was detected at (%.2f, %.2f, %.2f)." % \
(result.x, result.y, result.z)
log.warning(warning)
else:
# no collisions and no user interruption
pass
# check the pocketing type
if contour_model and (pocketing_type != "none"):
if not callback is None:
callback(text="Generating pocketing polygons ...")
pocketing_offset = cutter.radius * 1.8
# TODO: this is an arbitrary limit to avoid infinite loops
pocketing_limit = 1000
base_polygons = []
other_polygons = []
if pocketing_type == "holes":
# fill polygons with negative area
for poly in contour_model.get_polygons():
if poly.is_closed and not poly.is_outer():
base_polygons.append(poly)
else:
other_polygons.append(poly)
elif pocketing_type == "enclosed":
# fill polygons with positive area
pocketing_offset *= -1
for poly in contour_model.get_polygons():
if poly.is_closed and poly.is_outer():
base_polygons.append(poly)
else:
other_polygons.append(poly)
else:
return "Unknown pocketing type given (not one of 'none', " + \
"'holes', 'enclosed'): %s" % str(pocketing_type)
# For now we use only the polygons that do not surround eny other
# polygons. Sorry - the pocketing is currently very simple ...
base_filtered_polygons = []
for candidate in base_polygons:
if callback and callback():
return "Interrupted"
for other in other_polygons:
if candidate.is_polygon_inside(other):
break
else:
base_filtered_polygons.append(candidate)
# start the pocketing for all remaining polygons
pocket_polygons = []
for base_polygon in base_filtered_polygons:
current_queue = [base_polygon]
next_queue = []
pocket_depth = 0
while current_queue and (pocket_depth < pocketing_limit):
if callback and callback():
return "Interrupted"
for poly in current_queue:
result = poly.get_offset_polygons(pocketing_offset)
pocket_polygons.extend(result)
next_queue.extend(result)
pocket_depth += 1
current_queue = next_queue
next_queue = []
# use a copy instead of the original
contour_model = contour_model.get_copy()
for pocket in pocket_polygons:
contour_model.append(pocket)
# limit the contour model to the bounding box
if contour_model:
# use minz/maxz of the contour model (in other words: ignore z)
contour_model = contour_model.get_cropped_model(
minx, maxx, miny, maxy, contour_model.minz, contour_model.maxz)
if contour_model:
return "No part of the contour model is within the bounding box."
physics = _get_physics(trimesh_models, cutter, calculation_backend)
if isinstance(physics, basestring):
return physics
generator = _get_pathgenerator_instance(trimesh_models, contour_model,
cutter, path_generator,
path_postprocessor, physics,
milling_style)
if isinstance(generator, basestring):
return generator
overlap = overlap_percent / 100.0
if (overlap < 0) or (overlap >= 1):
return "Invalid overlap value (%f): should be greater or equal 0 " \
+ "and lower than 1"
# factor "2" since we are based on radius instead of diameter
line_stepping = 2 * number(tool_settings["tool_radius"]) * (1 - overlap)
if path_generator == "PushCutter":
step_width = None
else:
# the step_width is only used for the DropCutter
step_width = tool_settings["tool_radius"] / 4
if path_generator == "DropCutter":
layer_distance = None
else:
layer_distance = step_down
direction_dict = {
"x": pycam.Toolpath.MotionGrid.GRID_DIRECTION_X,
"y": pycam.Toolpath.MotionGrid.GRID_DIRECTION_Y,
"xy": pycam.Toolpath.MotionGrid.GRID_DIRECTION_XY
}
milling_style_grid = {
"ignore": pycam.Toolpath.MotionGrid.MILLING_STYLE_IGNORE,
"conventional": pycam.Toolpath.MotionGrid.MILLING_STYLE_CONVENTIONAL,
"climb": pycam.Toolpath.MotionGrid.MILLING_STYLE_CLIMB
}
if path_generator in ("DropCutter", "PushCutter"):
motion_grid = pycam.Toolpath.MotionGrid.get_fixed_grid(
(bounds_low, bounds_high),
layer_distance,
line_stepping,
step_width=step_width,
grid_direction=direction_dict[direction],
milling_style=milling_style_grid[milling_style])
if path_generator == "DropCutter":
toolpath = generator.GenerateToolPath(motion_grid, minz, maxz,
callback)
else:
toolpath = generator.GenerateToolPath(motion_grid, callback)
elif path_generator == "EngraveCutter":
if step_down > 0:
dz = step_down
else:
dz = maxz - minz
toolpath = generator.GenerateToolPath(minz, maxz, step_width, dz,
callback)
elif path_generator == "ContourFollow":
if step_down > 0:
dz = step_down
else:
dz = maxz - minz
if dz <= 0:
dz = 1
toolpath = generator.GenerateToolPath(minx, maxx, miny, maxy, minz,
maxz, dz, callback)
else:
return "Invalid path generator (%s): not one of %s" \
% (path_generator, PATH_GENERATORS)
return toolpath
def __init__(self, x, y, z):
super(Point, self).__init__()
self.x = number(x)
self.y = number(y)
self.z = number(z)
self.reset_cache()
def scale_distance(self, scale):
if scale != 0:
scale = number(scale)
dist = self.view["distance"]
self.view["distance"] = (scale * dist[0], scale * dist[1],
scale * dist[2])
def mul(self, c):
c = number(c)
return Point(self.x * c, self.y * c, self.z * c)
def set_required_distance(self, value):
if value >= 0:
self.required_distance = number(value)
self.distance_radius = self.radius + self.get_required_distance()
self.distance_radiussq = self.distance_radius * self.distance_radius
self.update_uuid()
def __init__(self, x, y, z):
super(Point, self).__init__()
self.x = number(x)
self.y = number(y)
self.z = number(z)
self.reset_cache()
def pdiv(a, c):
c = number(c)
return (a[0] / c, a[1] / c, a[2] / c)
