def exec_oneshot(self, *args):
keyframes = self.global_extractor.get_n_keyframes(self.n_globals)
n_keyframes = len(keyframes)
interps = []
for name in self.curves.keys():
for dim in self.dimensions[name].keys():
if not self.dimensions[name][dim]:
continue
index = -1
if dim == "rx": index = 1
if dim == "ry": index = 2
if dim == "rz": index = 3
curve = []
for i in range(len(Motion.mocap["single"][name])):
curve.append([Motion.mocap["single"][name].item(i, 0), Motion.mocap["single"][name].item(i, index)])
curve = np.array(curve)
for i in range(1, n_keyframes):
k1 = keyframes[i-1]
k2 = keyframes[i]
seg_curve = curve[k1:k2+1]
interp = interp_f.unconstrained(seg_curve, 100)
interps.append(interp)
for i in range(len(interps)):
seg = interps[i]
if len(seg.curve) <= 3:
interps[i] = interp_f.line(seg.curve, 100)
self.interps = interps
self.app.update()
return interps
def create_zerotable(self):
n = self.n_data
self.zero_table = [[-1 for i in range(n)] for j in range(n)]
curve_tangents = segment_fitting.tangents_of_curve(self.curve)
if self.verbose:
print "Creating zerostop table"
print "-" * (n-1)
for i in range(n - 1):
if self.verbose:
sys.stdout.write("#")
for j in range(i, n):
if i == j:
continue
if abs(i - j) == 1:
self.zero_table[i][j] = 0
else:
seg = make_seg.true_tangents( self.curve[i:j+1]
, curve_tangents[i:j+1]
, self.res )
cost, cost_index = self.cost_fn(seg)
self.zero_table[i][j] = cost
if self.verbose: print ""
def per_segment_solve(self, curve, keyframes):
interps = []
res = Algorithm.interp_res
curve_tangents = segment_fitting.tangents_of_curve(curve)
# Do initial fit using true tangents and
# iterating-constrainted-salient-points
n_keyframes = len(keyframes)
for i in range(1, n_keyframes):
k1 = keyframes[i-1]
k2 = keyframes[i]
seg_curve = curve[k1:k2+1]
seg_tangents = curve_tangents[k1:k2+1]
# if len(seg_curve) > 3:
interp = interp_f.true_tangents( seg_curve
, seg_tangents
, res)
# for j in range(5):
# nts = interp.ts_nearest()
# interp = interp_f.true_tangents( interp.curve
# , curve_tangents
# , res
# , nts)
interps.append(interp)
return interps
def exec_coupledsolve(self, *args):
keyframes = self.global_extractor.get_n_keyframes(self.n_globals)
n_keyframes = len(keyframes)
interps = []
for name in self.curves.keys():
for dim in self.dimensions[name].keys():
if not self.dimensions[name][dim]:
continue
index = -1
if dim == "rx": index = 1
if dim == "ry": index = 2
if dim == "rz": index = 3
curve = []
for i in range(len(Motion.mocap["single"][name])):
curve.append([Motion.mocap["single"][name].item(i, 0), Motion.mocap["single"][name].item(i, index)])
curve = np.array(curve)
interps += global_fitting.coupled_solve( curve
, keyframes
, self.alpha
, self.beta
, 100)
for i in range(len(interps)):
seg = interps[i]
if len(seg.curve) <= 3:
interps[i] = interp_f.line(seg.curve, 100)
self.interps = interps
self.app.update()
return interps
def coupled_solve(self, curve, keyframes):
interps = global_fitting.coupled_solve( curve
, keyframes
, self.r_straight_tangents
, self.r_small_tangents
, Algorithm.interp_res)
for i in range(len(interps)):
seg = interps[i]
if len(seg.curve) <= 3:
interps[i] = interp_f.line(seg.curve, Algorithm.interp_res)
return interps
def create_zerostop_truetangents_cl(self):
tmp_table = [[[0] for i in range(self.n_data)] for j in range(self.n_data)]
curve_tangents = segment_fitting.tangents_of_curve(self.curve)
cols = []
col_index = 0
n_i, n_j = self.curve.shape
n = n_j
inds_a = []
inds_b = []
inds_c = []
fill_cell = []
if self.verbose: print "-" * (self.n_data - 1)
for s in range(self.n_data - 1):
if self.verbose:
sys.stdout.write("#")
for e in range(s + 1, self.n_data):
if s == e:
continue
if abs(e - s) == 1:
continue
else:
seg = make_seg.true_tangents( self.curve[s:e+1]
, curve_tangents[s:e+1]
, self.res )
a_p = seg.n_curve_interps(30)
b_p = seg.n_sampling(30)
# print a_p[:10]
# print a_b[:10]
# raise "hi"
for i in range(len(a_p)):
cols += a_p[i].tolist()
inds_a.append(col_index); col_index += 1
cols += b_p[i].tolist()
inds_b.append(col_index); col_index += 1
inds_c.append(0)
fill_cell.append((s, e))
if self.verbose: print ""
results = gg.gogo("dist_many.cl", n, cols, inds_a, inds_b, inds_c)
for i in range(len(fill_cell)):
s, e = fill_cell[i]
tmp_table[s][e].append(results[i])
self.zero_table = [[-1 for i in range(self.n_data)] for j in range(self.n_data)]
for i in range(self.n_data):
for j in range(self.n_data):
self.zero_table[i][j] = sum(tmp_table[i][j])
def tighten_fitting_with_breaking(self, interps):
for i in range(len(interps)):
interp = interps[i]
refit = interp_f.unconstrained( interp.curve
, Algorithm.interp_res )
cost_org = Algorithm.eval_method_refit(interp)[0]
cost_new = Algorithm.eval_method_refit(refit)[0]
if cost_org == 0:
continue
# print "%s %s %d improved = before:%2.3f after:%2.3f" % i, cost_org, cost_new)
if 1 - (cost_new / float(cost_org)) > Algorithm.refit_cost:
interps[i] = refit
return interps
def eval_errors(self):
def keyframe_of_worst(cases):
max_cost = 0
keyframe = -1
for (cost, index) in cases:
if cost > max_cost:
max_cost = cost
keyframe = index
return keyframe
def combine_costs(cases):
return max([case[0] for c in cases])
worst_cases = []
for i in range(1, n_keyframes):
k1 = keyframes[i-1]
k2 = keyframes[i]
seg = make_seg.unconstrained(self.curve[k1:k2+1], self.res)
cost, index = self.cost_fn(seg)
worst_cases.append([cost, k1 + index])
return combine_costs(cases)
def coupled_solve(curve, keyframes, alpha, t_lambda, res):
# Break the motion curve into a list of segments
segments = []
for i in range(1, len(keyframes)):
start = keyframes[i - 1]
finish = keyframes[i]
segments.append(curve[start:finish + 1])
# Run least-sqaures solve, and format
solved = solve_constrained(segments, keyframes, alpha, t_lambda)
output = [solved[i] for i in range(len(solved))]
# Format results into a chain of interpolation functions.
interps = []
for i in range(len(segments)):
seg = segments[i]
hB = np.array([output[i * 4 + 0], output[i * 4 + 2]])
hC = np.array([output[i * 4 + 1], output[i * 4 + 3]])
interp = InterpolationFactory.from_coordinates(seg, res, seg[0], hB, hC, seg[-1])
interps.append(interp)
return interps
