from .kernel import Kernel2D, Kernel3D
from .cursor import LNUnitCursor, MultiLNUnitCursor, MultiLNUnitMultiMovieCursor, SeparableLNUnitCursor, \
SeparableMultiLNUnitCursor
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class LNUnit(object):
def __init__(self, linear_filter, transfer_function, amplitude=1.):
self.linear_filter = linear_filter
self.transfer_function = transfer_function
self.amplitude = amplitude
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def evaluate(self, movie, **kwargs):
return self.get_cursor(movie, separable=kwargs.pop('separable', False)).evaluate(**kwargs)
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def get_spatiotemporal_kernel(self, *args, **kwargs):
return self.linear_filter.get_spatiotemporal_kernel(*args, **kwargs)
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def get_spectrotemporal_kernel(self, *args, **kwargs):
return self.linear_filter.get_spectrotemporal_kernel(*args, **kwargs)
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def get_cursor(self, movie, threshold=0, separable=False):
if separable:
return SeparableLNUnitCursor(self, movie)
else:
return LNUnitCursor(self, movie, threshold=threshold)
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def show_temporal_filter(self, *args, **kwargs):
self.linear_filter.show_temporal_filter(*args, **kwargs)
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def show_spatial_filter(self, *args, **kwargs):
self.linear_filter.show_spatial_filter(*args, **kwargs)
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def to_dict(self):
return {
'class': (__name__, self.__class__.__name__),
'linear_filter': self.linear_filter.to_dict(),
'transfer_function': self.transfer_function.to_dict()
}
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class MultiLNUnit(object):
def __init__(self, lnunit_list, transfer_function):
self.lnunit_list = lnunit_list
self.transfer_function = transfer_function
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def get_spatiotemporal_kernel(self, *args, **kwargs):
k = Kernel3D([], [], [], [], [], [], [])
for unit in self.lnunit_list:
k = k+unit.get_spatiotemporal_kernel(*args, **kwargs)
return k
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def show_temporal_filter(self, *args, **kwargs):
import matplotlib.pyplot as plt
ax = kwargs.pop('ax', None)
show = kwargs.pop('show', None)
save_file_name = kwargs.pop('save_file_name', None)
if ax is None:
_, ax = plt.subplots(1, 1)
kwargs.update({'ax': ax, 'show': False, 'save_file_name': None})
for unit in self.lnunit_list:
if unit.linear_filter.amplitude < 0:
color = 'b'
else:
color = 'r'
unit.linear_filter.show_temporal_filter(color=color, **kwargs)
if save_file_name is not None:
plt.savefig(save_file_name, transparent=True)
if show:
plt.show()
return ax
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def show_spatial_filter(self, *args, **kwargs):
ax = kwargs.pop('ax', None)
show = kwargs.pop('show', True)
save_file_name = kwargs.pop('save_file_name', None)
colorbar = kwargs.pop('colorbar', True)
k = Kernel2D(args[0], args[1], [], [], [])
for lnunit in self.lnunit_list:
k = k + lnunit.linear_filter.spatial_filter.get_kernel(*args, **kwargs)
k.imshow(ax=ax, show=show, save_file_name=save_file_name, colorbar=colorbar)
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def get_cursor(self, *args, **kwargs):
threshold = kwargs.get('threshold', 0.)
separable = kwargs.get('separable', False)
if len(args) == 1:
movie = args[0]
if separable:
return SeparableMultiLNUnitCursor(self, movie)
else:
return MultiLNUnitCursor(self, movie, threshold=threshold)
elif len(args) > 1:
movie_list = args
if separable:
raise NotImplementedError
else:
return MultiLNUnitMultiMovieCursor(self, movie_list, threshold=threshold)
else:
assert ValueError
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def evaluate(self, movie, **kwargs):
seperable = kwargs.pop('separable', False)
return self.get_cursor(movie, separable=seperable).evaluate(**kwargs)
