def evaluate(self, t):
t = _np.ascontiguousarray(t, dtype='float32')
output = _np.empty(t.shape + (3, ), dtype='float32')
_lib.asdf_asdfspline_evaluate(self._ptr,
_ffi.from_buffer('float[]', t), t.size,
_ffi.from_buffer('float[]', output))
return output
def _evaluate(t, extra_dim, func, ptr):
t = _np.ascontiguousarray(t, dtype='float32')
t_ptr = _ffi.from_buffer('float[]', t)
output = _np.empty(t.shape + extra_dim, dtype='float32')
output_ptr = _ffi.from_buffer('float[]', output)
func(ptr, t_ptr, t.size, output_ptr)
return output
def evaluate(self, t):
t = _np.ascontiguousarray(t, dtype='float32')
output = _np.empty_like(t)
_lib.asdf_cubiccurve1_evaluate(self._ptr,
_ffi.from_buffer('float[]', t), t.size,
_ffi.from_buffer('float[]', output))
return output
def __init__(self, positions, tcb=None, closed=False):
positions = _np.ascontiguousarray(positions, dtype='float32')
if positions.ndim != 2:
raise ValueError(
"Positions must be two-dimensional (list of coordinate pairs)")
if positions.shape[1] != 2:
raise ValueError("Positions must be a list of coordinate pairs")
if tcb is None:
tcb = 0, 0, 0
tcb = _np.ascontiguousarray(tcb, dtype='float32')
if tcb.ndim == 1:
N = len(positions) if closed else len(positions) - 2
tcb = _np.tile(tcb, (N, 1))
if tcb.ndim != 2:
raise ValueError(
"TCB values must be two-dimensional (list of triples)")
if tcb.shape[1] != 3:
raise ValueError("TCB values must be a list of triples")
ptr = _ffi.gc(
_lib.asdf_centripetalkochanekbartelsspline2(
_ffi.from_buffer('float[]', positions),
len(positions),
_ffi.from_buffer('float[]', tcb),
len(tcb),
closed,
), _lib.asdf_cubiccurve2_free)
super().__init__(ptr)
def get_time(self, values):
values = _np.ascontiguousarray(values, dtype='float32')
output = _np.empty_like(values)
_lib.asdf_monotonecubic_get_time(self._monotone_ptr,
_ffi.from_buffer('float[]', values),
values.size,
_ffi.from_buffer('float[]', output))
return output
def __init__(self, values, slopes=None, grid=None):
# TODO: code re-use?
values = _np.ascontiguousarray(values, dtype='float32')
if values.ndim != 1:
raise ValueError("Values must be one-dimensional")
if grid is None:
grid = _np.arange(len(values), dtype='float32')
grid = _np.ascontiguousarray(grid, dtype='float32')
if grid.ndim != 1:
raise ValueError("Grid must be one-dimensional")
values_ptr = _ffi.from_buffer('float[]', values)
grid_ptr = _ffi.from_buffer('float[]', grid)
if slopes is None:
ptr = _ffi.gc(
_lib.asdf_monotonecubic(
values_ptr,
len(values),
grid_ptr,
len(grid),
), _lib.asdf_monotonecubic_free)
else:
# TODO: code re-use?
slopes = _np.ascontiguousarray(slopes, dtype='float32')
if slopes.ndim != 1:
raise ValueError("Slopes must be one-dimensional")
slopes_ptr = _ffi.from_buffer('float[]', slopes)
ptr = _ffi.gc(
_lib.asdf_monotonecubic_with_slopes(
values_ptr,
len(values),
slopes_ptr,
len(slopes),
grid_ptr,
len(grid),
), _lib.asdf_monotonecubic_free)
if ptr == _ffi.NULL:
raise ValueError(_ffi.string(_lib.asdf_last_error()).decode())
self._monotone_ptr = ptr
super().__init__(_lib.asdf_monotonecubic_inner(ptr))
def _check_tcb(tcb, closed, N):
if tcb is None:
tcb = 0, 0, 0
tcb = _np.ascontiguousarray(tcb, dtype='float32')
if tcb.ndim == 1:
if not closed:
N = max(N - 2, 0)
tcb = _np.tile(tcb, (N, 1))
if tcb.ndim != 2:
raise ValueError(
'TCB values must be two-dimensional (list of triples)')
if tcb.shape[1] != 3:
raise ValueError('TCB values must be a list of triples')
tcb_ptr = _ffi.from_buffer('float[]', tcb)
return tcb, tcb_ptr
def __init__(self, values, slopes=None, grid=None, closed=False):
values = _np.ascontiguousarray(values, dtype='float32')
if values.ndim != 1:
raise ValueError("Values must be one-dimensional")
if grid is None:
grid = _np.arange(len(values) + closed, dtype='float32')
grid = _np.ascontiguousarray(grid, dtype='float32')
if grid.ndim != 1:
raise ValueError("Grid must be one-dimensional")
values_ptr = _ffi.from_buffer('float[]', values)
grid_ptr = _ffi.from_buffer('float[]', grid)
if slopes is None:
ptr = _ffi.gc(
_lib.asdf_shapepreservingcubicspline(
values_ptr,
len(values),
grid_ptr,
len(grid),
closed,
), _lib.asdf_cubiccurve1_free)
else:
slopes = _np.ascontiguousarray(slopes, dtype='float32')
if slopes.ndim != 1:
raise ValueError("Slopes must be one-dimensional")
slopes_ptr = _ffi.from_buffer('float[]', slopes)
ptr = _ffi.gc(
_lib.asdf_shapepreservingcubicspline_with_slopes(
values_ptr,
len(values),
slopes_ptr,
len(slopes),
grid_ptr,
len(grid),
closed,
), _lib.asdf_cubiccurve1_free)
super().__init__(ptr)
def _make_buffer(dim, numbers, name=None):
# NB: If name is None, this is supposed to never fail
numbers = _np.ascontiguousarray(numbers, dtype='float32')
if dim > 1:
if numbers.ndim != 2:
raise ValueError(
name + ' must be two-dimensional (list of coordinate pairs)')
if numbers.shape[1] != dim:
raise ValueError(
'{} must be a list of {}D coordinate pairs'.format(name, dim))
elif dim == 1:
if numbers.ndim != 1:
raise ValueError(name + ' must be one-dimensional')
else:
assert False
numbers_ptr = _ffi.from_buffer('float[]', numbers)
return numbers, numbers_ptr
def __init__(self, data):
positions = []
times = []
speeds = []
tcb = []
closed = False
for vertex in data:
vertex = dict(vertex) # Make a copy
position = vertex.pop('position', None)
if position is None:
raise ValueError('every vertex must have a position')
time = vertex.pop('time', _np.nan)
if not _np.isscalar(time):
raise TypeError('time values must be scalars')
times.append(time)
if position == 'closed':
if vertex:
raise ValueError(
'when position is "closed", only time is allowed')
closed = True
break
position = _np.asarray(position, dtype='float32')
if position.ndim != 1:
raise ValueError('positions must be one-dimensional')
if len(position) == 2:
position = _np.append(position, 0)
if len(position) != 3:
raise ValueError('positions must be 2- or 3-dimensional')
positions.append(position)
speed = vertex.pop('speed', _np.nan)
if not _np.isscalar(speed):
raise TypeError('speed values must be scalars')
speeds.append(speed)
tension = vertex.pop('tension', 0)
if not _np.isscalar(tension):
raise TypeError('tension values must be scalars')
continuity = vertex.pop('continuity', 0)
if not _np.isscalar(continuity):
raise TypeError('continuity values must be scalars')
bias = vertex.pop('bias', 0)
if not _np.isscalar(bias):
raise TypeError('bias values must be scalars')
tcb.append((tension, continuity, bias))
if vertex:
raise ValueError('invalid key(s): {}'.format(set(vertex)))
if len(positions) < 2:
raise ValueError('at least two vertices are needed')
if not closed:
assert len(tcb) >= 2
if tcb.pop(0) != (0, 0, 0):
raise ValueError(
'first vertex cannot have tension/continuity/bias '
'(except for closed curves')
if tcb.pop(-1) != (0, 0, 0):
raise ValueError(
'last vertex cannot have tension/continuity/bias '
'(except for closed curves)')
positions, positions_ptr = _make_buffer(3, positions)
if _np.isnan(times[0]):
# NB: NaN <= 0 returns False
if any(t <= 0 for t in times):
raise ValueError('first time defaults to 0 if other times > 0')
times[0] = 0
times, times_ptr = _make_buffer(1, times)
speeds, speeds_ptr = _make_buffer(1, speeds)
tcb = _np.ascontiguousarray(tcb, dtype='float32')
tcb_ptr = _ffi.from_buffer('float[]', tcb)
ptr = _ffi.gc(
_lib.asdf_asdfposspline3(
positions_ptr,
len(positions),
times_ptr,
len(times),
speeds_ptr,
len(speeds),
tcb_ptr,
len(tcb),
closed,
), _lib.asdf_asdfposspline3_free)
super().__init__(ptr)
def __init__(self, data):
positions = []
times = []
speeds = []
tcb = []
closed = False
for vertex in data:
vertex = dict(vertex) # Make a copy
position = vertex.pop('position', None)
if position is None:
raise ValueError('Every vertex must have a position')
time = vertex.pop('time', _np.nan)
if not _np.isscalar(time):
raise TypeError('Time values must be scalars')
times.append(time)
if position == 'closed':
if vertex:
raise ValueError(
'When position is "closed", only time is allowed')
closed = True
break
position = _np.asarray(position, dtype='float32')
if position.ndim != 1:
raise ValueError("Positions must be one-dimensional")
if len(position) == 2:
position = _np.append(position, 0)
if len(position) != 3:
raise ValueError("Positions must be 2- or 3-dimensional")
positions.append(position)
speed = vertex.pop('speed', _np.nan)
if not _np.isscalar(speed):
raise TypeError('Speed values must be scalars')
speeds.append(speed)
tension = vertex.pop('tension', 0)
if not _np.isscalar(tension):
raise TypeError('Tension values must be scalars')
continuity = vertex.pop('continuity', 0)
if not _np.isscalar(continuity):
raise TypeError('Continuity values must be scalars')
bias = vertex.pop('bias', 0)
if not _np.isscalar(bias):
raise TypeError('Bias values must be scalars')
tcb.append((tension, continuity, bias))
if vertex:
raise ValueError('Invalid key(s): {}'.format(set(vertex)))
if len(positions) < 2:
raise ValueError('At least two vertices are needed')
if not closed:
assert len(tcb) >= 2
if tcb.pop(0) != (0, 0, 0):
raise ValueError(
'First vertex cannot have tension/continuity/bias (except for closed curves'
)
if tcb.pop(-1) != (0, 0, 0):
raise ValueError(
'Last vertex cannot have tension/continuity/bias (except for closed curves)'
)
positions = _np.ascontiguousarray(positions, dtype='float32')
assert positions.ndim == 2
assert positions.shape[1] == 3
positions_ptr = _ffi.from_buffer('float[]', positions)
times = _np.ascontiguousarray(times, dtype='float32')
assert times.ndim == 1
times_ptr = _ffi.from_buffer('float[]', times)
speeds = _np.ascontiguousarray(speeds, dtype='float32')
assert speeds.ndim == 1
speeds_ptr = _ffi.from_buffer('float[]', speeds)
tcb = _np.ascontiguousarray(tcb, dtype='float32')
tcb_ptr = _ffi.from_buffer('float[]', tcb)
ptr = _ffi.gc(
_lib.asdf_asdfspline(
positions_ptr,
len(positions),
times_ptr,
len(times),
speeds_ptr,
len(speeds),
tcb_ptr,
len(tcb),
closed,
), _lib.asdf_asdfspline_free)
if ptr == _ffi.NULL:
raise ValueError(_ffi.string(_lib.asdf_last_error()).decode())
self._ptr = ptr
