def OnGenShiftmapQuad(self, event):
from PYME.Analysis.points import twoColour, twoColourPlot
from PYME.IO.MetaDataHandler import get_camera_roi_origin
pipeline = self.visFr.pipeline
vs = pipeline.mdh.voxelsize_nm
roi_x0, roi_y0 = get_camera_roi_origin(pipeline.mdh)
x0 = (roi_x0)*vs[0]
y0 = (roi_y0)*vs[1]
lx = len(pipeline.filter['x'])
bbox = None#[0,(pipeline.mdh['Camera.ROIWidth'] + 1)*vs[0], 0,(pipeline.mdh['Camera.ROIHeight'] + 1)*vs[1]]
dx, dy, spx, spy, good = twoColour.genShiftVectorFieldQ(pipeline.filter['x']+.1*np.random.randn(lx) + x0, pipeline.filter['y']+.1*np.random.randn(lx) + y0, pipeline.filter['fitResults_dx'], pipeline.filter['fitResults_dy'], pipeline.filter['fitError_dx'], pipeline.filter['fitError_dy'], bbox=bbox)
#twoColourPlot.PlotShiftField(dx, dy, spx, spy)
twoColourPlot.PlotShiftField2(spx, spy, pipeline.mdh['Splitter.Channel0ROI'][2:], voxelsize=vs)
twoColourPlot.PlotShiftResiduals(pipeline['x'][good] + x0, pipeline['y'][good] + y0, pipeline['fitResults_dx'][good], pipeline['fitResults_dy'][good], spx, spy)
from six.moves import cPickle
defFile = os.path.splitext(os.path.split(self.visFr.GetTitle())[-1])[0] + '.sf'
fdialog = wx.FileDialog(None, 'Save shift field as ...',
wildcard='Shift Field file (*.sf)|*.sf', style=wx.FD_SAVE, defaultDir = nameUtils.genShiftFieldDirectoryPath(), defaultFile=defFile)
succ = fdialog.ShowModal()
if (succ == wx.ID_OK):
fpath = fdialog.GetPath()
#save as a pickle containing the data and voxelsize
fid = open(fpath, 'wb')
cPickle.dump((spx, spy), fid, 2)
fid.close()
def execute(self, namespace):
from PYME.Analysis.points import twoColour
from PYME.Analysis.points import multiview
from PYME.IO.MetaDataHandler import NestedClassMDHandler
inp = namespace[self.input_name]
try: # make sure we're looking at multiview data
n_chan = inp.mdh['Multiview.NumROIs']
except AttributeError:
raise AttributeError('multiview metadata is missing or incomplete')
# sort in frame order
I = inp['tIndex'].argsort()
x_sort, y_sort = inp['x'][I], inp['y'][I]
chan_sort = inp['multiviewChannel'][I]
clump_id, keep = multiview.pair_molecules(
inp['tIndex'][I],
x_sort,
y_sort,
chan_sort,
self.search_radius_nm * np.ones_like(x_sort),
appear_in=np.arange(n_chan),
n_frame_sep=inp['tIndex'].max(),
pix_size_nm=1e3 * inp.mdh['voxelsize.x'])
# only look at the clumps which showed up in all channels
x = x_sort[keep]
y = y_sort[keep]
chan = chan_sort[keep]
clump_id = clump_id[keep]
# Generate raw shift vectors (map of displacements between channels) for each channel
mol_list = np.unique(clump_id)
n_mols = len(mol_list)
dx = np.zeros((n_chan - 1, n_mols))
dy = np.zeros_like(dx)
dx_err = np.zeros_like(dx)
dy_err = np.zeros_like(dx)
x_clump, y_clump, x_std, y_std, x_shifted, y_shifted = [], [], [], [], [], []
shift_map_dtype = [
('mx', '<f4'),
('mx2', '<f4'),
('mx3', '<f4'), # x terms
('my', '<f4'),
('my2', '<f4'),
('my3', '<f4'), # y terms
('mxy', '<f4'),
('mx2y', '<f4'),
('mxy2', '<f4'), # cross terms
('x0', '<f4')
] # 0th order shift
shift_maps = np.zeros(2 * (n_chan - 1), dtype=shift_map_dtype)
mdh = NestedClassMDHandler(inp.mdh)
mdh['Multiview.shift_map.legend'] = {}
for ii in range(n_chan):
chan_mask = (chan == ii)
x_chan = np.zeros(n_mols)
y_chan = np.zeros(n_mols)
x_chan_std = np.zeros(n_mols)
y_chan_std = np.zeros(n_mols)
for ind in range(n_mols):
# merge clumps within channels
clump_mask = np.where(
np.logical_and(chan_mask, clump_id == mol_list[ind]))
x_chan[ind] = x[clump_mask].mean()
y_chan[ind] = y[clump_mask].mean()
x_chan_std[ind] = x[clump_mask].std()
y_chan_std[ind] = y[clump_mask].std()
x_clump.append(x_chan)
y_clump.append(y_chan)
x_std.append(x_chan_std)
y_std.append(y_chan_std)
if ii > 0:
dx[ii - 1, :] = x_clump[0] - x_clump[ii]
dy[ii - 1, :] = y_clump[0] - y_clump[ii]
dx_err[ii - 1, :] = np.sqrt(x_std[ii]**2 + x_std[0]**2)
dy_err[ii - 1, :] = np.sqrt(y_std[ii]**2 + y_std[0]**2)
# generate shiftmap between ii-th channel and the 0th channel
dxx, dyy, spx, spy, good = twoColour.genShiftVectorFieldQ(
x_clump[0], y_clump[0], dx[ii - 1, :], dy[ii - 1, :],
dx_err[ii - 1, :], dy_err[ii - 1, :])
# store shiftmaps in structured array
mdh['Multiview.shift_map.legend']['Chan0%s.X' %
ii] = 2 * (ii - 1)
mdh['Multiview.shift_map.legend']['Chan0%s.Y' %
ii] = 2 * (ii - 1) + 1
for ki in range(len(shift_map_dtype)):
k = shift_map_dtype[ki][0]
shift_maps[2 * (ii - 1)][k] = spx.__getattribute__(k)
shift_maps[2 * (ii - 1) + 1][k] = spy.__getattribute__(k)
# shift_maps['Chan0%s.X' % ii], shift_maps['Chan0%s.Y' % ii] = spx.__dict__, spy.__dict__
mdh['Multiview.shift_map.model'] = '.'.join(
[spx.__class__.__module__, spx.__class__.__name__])
namespace[self.output_name] = tabular.RecArraySource(shift_maps)
namespace[self.output_name].mdh = mdh