def extract_line(data, ofs, vec, mid=True):
'''extracts intensity values from a volume at points
at unit length intervals along a line
Usage: (vals, coords) = extract_line(data, ofs, vec)
Inputs:
data = volume to extract from
ofs = point on line
vec = direction of line
Outputs:
vals = returned values from volume
coords = co-ordinates of extracted points'''
if mid:
mid_ = 0.5
else:
mid_ = 0.
maxval = n.array( data.shape ) - 1
# ensure inputs are numpy arrays
ofs = n.asarray( ofs )
vec = unitvec( vec )
if n.alltrue( ofs <= maxval + mid_ ) and n.alltrue( ofs >= mid_ ):
max_cnr = n.where(vec > 0, maxval, zeros(data.ndim)) + mid_
min_cnr = n.where(vec < 0, maxval, zeros(data.ndim)) + mid_
#print max_cnr
#print min_cnr
# work out how many steps before ofs
presteps = (n.abs( min_cnr - ofs ) / n.abs( vec ) \
).min().astype(int)
# ... and how many after ofs
poststeps = (n.abs( max_cnr - ofs ) / n.abs( vec ) \
).min().astype(int)
# construct list of steps ( in delta vecs )
if presteps > 0:
steps = [(presteps - i) * -1 \
for i in range( presteps + 1)]
# +1 to add 0 pt (at ofs)
else:
steps = [0]
if poststeps > 0:
steps += [(i + 1) for i in range( poststeps )]
steps = n.array(steps)[newaxis,...]
# construct array of actual pts
pts = ofs[...,newaxis] + steps * vec[...,newaxis]
#print pts
val = ninterpol( data, pts, mid=mid )
return val, pts
else:
raise ValueError("[extract_line] Offset must be within bounds of data.")
return None
def test_glm_any_model():
nbin = 10
align = 'hold'
lag = 0.1 # s
ds = datasets['small']
dc = DataCollection(ds.get_files())
dc.add_unit(ds.get_units()[0], lag)
bnd = dc.make_binned(nbin=nbin, align=align)
ntask, nrep, nunit, nbin = bnd.shape
# make perfect test counts
# direction-only model
tp = radians([20, 10]) # degrees
b0 = log(10) # log(Hz)
pd = pol2cart(tp)
drn = kinematics.get_idir(bnd.pos, axis=2)
rate = exp(dot(drn, pd) + b0)
window_size = diff(bnd.bin_edges, axis=2)
count_mean = rate * window_size
count = poisson(count_mean)
count = count[:,:,None]
bnd.set_PSTHs(count)
# now fit data for pd
count, pos, time = bnd.get_for_regress()
bnom, bse_nom = glm_any_model(count, pos, time, model='kd')
pd_exp = unitvec(bnom['d'])
tp_exp = cart2pol(pd_exp)
acceptable_err = 0.05 # about 3 degrees absolute error
err = abs(tp - tp_exp)
assert_array_less(err, acceptable_err)
def get_dir(pos, tax=-2, spax=-1):
'''Get instantaneous direction
Parameters
----------
pos : array_like
tax : int, optional
time axis, defaults to 0
'''
dp = np.diff(pos, axis=tax)
return unitvec(dp, axis=spax)
def test_get_dir():
pos = np.array([[ 0, 0, 0],
[ 1, 2, -1],
[ 2, 4, -2],
[ 3, 6, -3]]) # shape (4,3)
dir = kin.get_dir(pos, tax=0, spax=-1)
correct_dir = unitvec(np.array([[1,2,-1], [1,2,-1], [1,2,-1]]), axis=1)
# default case
assert_array_equal(dir, correct_dir)
# switched axes case
dir = kin.get_dir(pos.T, tax=1, spax=0)
assert_array_equal(dir, correct_dir.T)
# additional axes case
pos = np.tile(pos[None], (2,1,1))
dir = kin.get_dir(pos, tax=1, spax=-1)
correct_dir = np.tile(correct_dir[None], (2,1,1))
assert_array_equal(dir, correct_dir)
def __init__(self,
parent=None,
length=1.,
attachment=None,
ref_vec=array([0,1,0])):
'''
Parameters
----------
parent : Bone
bone to which this one is attached
length : scalar
length of bone
attachment : function
callable to get attachment point of bone
ref_vec : ndarray
vector describing reference orientation of bone
(that occurring at all zero angles)
'''
self.get_pta = attachment
self.vec = unitvec(ref_vec) * length
self.child = None
self.parent = parent
