def __init__(self,
mechanism: Dict[str, Any],
path: Sequence[Sequence[_Coord]],
vpoints: List[VPoint] = None,
vlinks: List[VLink] = None,
parent: QWidget = None):
"""Input link and path data."""
super(_DynamicCanvas, self).__init__(parent)
self.mechanism = mechanism
self.vpoints = vpoints or []
self.vlinks = vlinks or []
self.no_mechanism = not self.vpoints or not self.vlinks
use_norm = self.no_mechanism and self.mechanism.get(
'shape_only', False)
# Target path
same: Dict[int, int] = self.mechanism['same']
target_path: _TargetPath = self.mechanism['target']
for i, p in target_path.items():
for j in range(i):
if j in same:
i -= 1
if use_norm:
self.target_path[i] = [(x, y) for x, y in norm_path(p)]
else:
self.target_path[i] = p
self.path.path = []
for i, p in enumerate(path):
if i in self.target_path and use_norm:
self.path.path.append([(x, y)
for x, y in norm_path(efd_fitting(p))])
else:
self.path.path.append(p)
self.__index = 0
self.__interval = 1
self.__path_count = max(len(path) for path in self.path.path) - 1
self.pos = []
# Error
self.error = False
self.__no_error = 0
if self.no_mechanism:
return
# Ranges
ranges: Dict[int, _Range] = self.mechanism['placement']
self.ranges.update({
f"P{i}":
QRectF(QPointF(values[0] - values[2], values[1] + values[2]),
QSizeF(values[2] * 2, values[2] * 2))
for i, values in ranges.items()
})
# Timer
self.__timer = QTimer()
self.__timer.timeout.connect(self.__change_index)
self.__timer.start(18)
def __efd_path(self) -> None:
"""Elliptical Fourier Descriptors."""
path = self.current_path()
n, ok = QInputDialog.getInt(self, "Elliptical Fourier Descriptors",
"The number of points:", len(path), 3)
if not ok:
return
dlg = QProgressDialog("Path transform.", "Cancel", 0, 1, self)
dlg.setWindowTitle("Elliptical Fourier Descriptors")
dlg.show()
self.set_path(efd_fitting(path, n))
dlg.setValue(1)
dlg.deleteLater()
def __gen_fitting(self) -> ndarray:
"""Generate the fitted curve."""
num = self.num_points.value()
is_close = self.close_path_option.isChecked()
if is_close:
num += 1
if self.bspline_option.isChecked():
if is_close:
path = concatenate((self.path, self.path[:1, :]))
else:
path = self.path
tck = splprep((path[:, 0], path[:, 1]), per=is_close)
path = array(splev(linspace(0, 1, num, endpoint=True), tck[0])).T
else:
path = efd_fitting(self.path, num)
if is_close:
path = path[:-1]
return path
def test_fitting(self):
ans = efd_fitting(PATH, 20)
self.assertTrue(isclose(ans, TARGET).all())
