def link(f, search_range, *args, **kw):
kw = dict(self.linker_opts, **kw)
size = 3
separation = kw['separation']
f = f.copy()
topleft = (f[['y', 'x']].min().values - 4 * separation).astype(
np.int)
f[['y', 'x']] -= topleft
shape = (f[['y', 'x']].max().values + 4 * separation).astype(
np.int)
reader = CoordinateReader(f, shape, size,
t=f['frame'].unique())
pred.pos_columns = kw.get('pos_columns', ['x', 'y'])
pred.t_column = kw.get('t_column', 'frame')
f = []
for i, frame in trackpy.find_link_iter(reader, predictor=pred.predict,
search_range=search_range,
*args, **kw):
f.append(frame)
f = pandas.concat(f)
f[['y', 'x']] += topleft
return f
def link_iter(f, search_range, *args, **kw):
kw = dict(self.linker_opts, **kw)
size = 3
separation = kw['separation']
# convert the iterable to a single DataFrame (OK for tests)
f = [_f for _f in f]
indices = [_f['frame'].iloc[0] for _f in f]
f = pandas.concat([_f for _f in f])
topleft = (f[['y', 'x']].min().values - 4 * separation).astype(
np.int)
f[['y', 'x']] -= topleft
shape = (f[['y', 'x']].max().values + 4 * separation).astype(
np.int)
reader = CoordinateReader(f, shape, size, t=indices)
pred.pos_columns = kw.get('pos_columns', ['x', 'y'])
pred.t_column = kw.get('t_column', 'frame')
for i, frame in trackpy.find_link_iter(reader, predictor=pred.predict,
search_range=search_range,
*args, **kw):
pred.observe(frame)
frame[['y', 'x']] += topleft
yield frame
def link(f, search_range, *args, **kw):
kw = dict(self.linker_opts, **kw)
size = 3
separation = kw['separation']
f = f.copy()
topleft = (f[['y', 'x']].min().values - 4 * separation).astype(
np.int)
f[['y', 'x']] -= topleft
shape = (f[['y', 'x']].max().values + 4 * separation).astype(
np.int)
reader = CoordinateReader(f, shape, size,
t=f['frame'].unique())
pred.pos_columns = kw.get('pos_columns', ['x', 'y'])
pred.t_column = kw.get('t_column', 'frame')
f = []
for i, frame in trackpy.find_link_iter(reader, predictor=pred.predict,
search_range=search_range,
*args, **kw):
f.append(frame)
f = pandas.concat(f)
f[['y', 'x']] += topleft
return f
def link_iter(f, search_range, *args, **kw):
kw = dict(self.linker_opts, **kw)
size = 3
separation = kw['separation']
# convert the iterable to a single DataFrame (OK for tests)
f = [_f for _f in f]
indices = [_f['frame'].iloc[0] for _f in f]
f = pandas.concat([_f for _f in f])
topleft = (f[['y', 'x']].min().values - 4 * separation).astype(
np.int)
f[['y', 'x']] -= topleft
shape = (f[['y', 'x']].max().values + 4 * separation).astype(
np.int)
reader = CoordinateReader(f, shape, size, t=indices)
pred.pos_columns = kw.get('pos_columns', ['x', 'y'])
pred.t_column = kw.get('t_column', 'frame')
for i, frame in trackpy.find_link_iter(reader, predictor=pred.predict,
search_range=search_range,
*args, **kw):
pred.observe(frame)
frame[['y', 'x']] += topleft
yield frame
def link_iter(f, search_range, *args, **kw):
kw = dict(self.linker_opts, **kw)
size = 3
separation = kw['separation']
# convert the iterable to a single DataFrame (OK for tests)
f = [_f for _f in f]
indices = [_f['frame'].iloc[0] for _f in f]
f = pandas.concat([_f for _f in f])
topleft = (f[['y', 'x']].min().values - 4 * separation).astype(int)
f[['y', 'x']] -= topleft
shape = (f[['y', 'x']].max().values + 4 * separation).astype(int)
reader = CoordinateReader(f, shape, size, t=indices)
for i, frame in trackpy.find_link_iter(reader,
search_range=search_range,
*args,
**kw):
frame[['y', 'x']] += topleft
yield frame
