def iter_neurites(obj, mapfun=None, filt=None, neurite_order=NeuriteIter.FileOrder):
"""Iterator to a neurite, neuron or neuron population.
Applies optional neurite filter and mapping functions.
Arguments:
obj: a neurite, neuron or neuron population.
mapfun: optional neurite mapping function.
filt: optional neurite filter function.
neurite_order (NeuriteIter): order upon which neurites should be iterated
- NeuriteIter.FileOrder: order of appearance in the file
- NeuriteIter.NRN: NRN simulator order: soma -> axon -> basal -> apical
Examples:
Get the number of points in each neurite in a neuron population
>>> from neurom.core import iter_neurites
>>> n_points = [n for n in iter_neurites(pop, lambda x : len(x.points))]
Get the number of points in each axon in a neuron population
>>> import neurom as nm
>>> from neurom.core import iter_neurites
>>> filter = lambda n : n.type == nm.AXON
>>> mapping = lambda n : len(n.points)
>>> n_points = [n for n in iter_neurites(pop, mapping, filter)]
"""
neurites = ((obj,) if isinstance(obj, Neurite) else
obj.neurites if hasattr(obj, 'neurites') else obj)
if neurite_order == NeuriteIter.NRN:
last_position = max(NRN_ORDER.values()) + 1
neurites = sorted(neurites, key=lambda neurite: NRN_ORDER.get(neurite.type, last_position))
neurite_iter = iter(neurites) if filt is None else filter(filt, neurites)
return neurite_iter if mapfun is None else map(mapfun, neurite_iter)
def iter_neurites(obj, mapfun=None, filt=None):
'''Iterator to a neurite, neuron or neuron population
Applies optional neurite filter and mapping functions.
Parameters:
obj: a neurite, neuron or neuron population.
mapfun: optional neurite mapping function.
filt: optional neurite filter function.
Examples:
Get the number of points in each neurite in a neuron population
>>> from neurom.core import iter_neurites
>>> n_points = [n for n in iter_neurites(pop, lambda x : len(x.points))]
Get the number of points in each axon in a neuron population
>>> import neurom as nm
>>> from neurom.core import iter_neurites
>>> filter = lambda n : n.type == nm.AXON
>>> mapping = lambda n : len(n.points)
>>> n_points = [n for n in iter_neurites(pop, mapping, filter)]
'''
neurites = ((obj,) if isinstance(obj, Neurite) else
obj.neurites if hasattr(obj, 'neurites') else obj)
neurite_iter = iter(neurites) if filt is None else filter(filt, neurites)
return neurite_iter if mapfun is None else map(mapfun, neurite_iter)
def update_plot_limits(ax, white_space):
"""Sets the limit options of a matplotlib plot.
Args:
ax: matplotlib axes
white_space(float): whitespace added to surround the tight limit of the data
Note: This relies on ax.dataLim (in 2d) and ax.[xy, zz]_dataLim being set in 3d
"""
if hasattr(ax, 'zz_dataLim'):
bounds = ax.xy_dataLim.bounds
ax.set_xlim(bounds[0] - white_space,
bounds[0] + bounds[2] + white_space)
ax.set_ylim(bounds[1] - white_space,
bounds[1] + bounds[3] + white_space)
bounds = ax.zz_dataLim.bounds
ax.set_zlim(bounds[0] - white_space,
bounds[0] + bounds[2] + white_space)
else:
bounds = ax.dataLim.bounds
assert not any(
map(np.isinf,
bounds)), 'Cannot set bounds if dataLim has infinite elements'
ax.set_xlim(bounds[0] - white_space,
bounds[0] + bounds[2] + white_space)
ax.set_ylim(bounds[1] - white_space,
bounds[1] + bounds[3] + white_space)
def iter_neurites(obj, mapfun=None, filt=None):
'''Iterator to a neurite, neuron or neuron population
Applies optional neurite filter and mapping functions.
Parameters:
obj: a neurite, neuron or neuron population.
mapfun: optional neurite mapping function.
filt: optional neurite filter function.
Examples:
Get the number of points in each neurite in a neuron population
>>> from neurom.core import iter_neurites
>>> n_points = [n for n in iter_neurites(pop, lambda x : len(x.points))]
Get the number of points in each axon in a neuron population
>>> import neurom as nm
>>> from neurom.core import iter_neurites
>>> filter = lambda n : n.type == nm.AXON
>>> mapping = lambda n : len(n.points)
>>> n_points = [n for n in iter_neurites(pop, mapping, filter)]
'''
neurites = ((obj, ) if isinstance(obj, Neurite) else
obj.neurites if hasattr(obj, 'neurites') else obj)
neurite_iter = iter(neurites) if filt is None else filter(filt, neurites)
return neurite_iter if mapfun is None else map(mapfun, neurite_iter)
def update_plot_limits(ax, white_space):
"""Sets the limit options of a matplotlib plot.
Args:
ax: matplotlib axes
white_space(float): whitespace added to surround the tight limit of the data
Note: This relies on ax.dataLim (in 2d) and ax.[xy, zz]_dataLim being set in 3d
"""
if hasattr(ax, 'zz_dataLim'):
bounds = ax.xy_dataLim.bounds
ax.set_xlim(bounds[0] - white_space, bounds[0] + bounds[2] + white_space)
ax.set_ylim(bounds[1] - white_space, bounds[1] + bounds[3] + white_space)
bounds = ax.zz_dataLim.bounds
ax.set_zlim(bounds[0] - white_space, bounds[0] + bounds[2] + white_space)
else:
bounds = ax.dataLim.bounds
assert not any(map(np.isinf, bounds)), 'Cannot set bounds if dataLim has infinite elements'
ax.set_xlim(bounds[0] - white_space, bounds[0] + bounds[2] + white_space)
ax.set_ylim(bounds[1] - white_space, bounds[1] + bounds[3] + white_space)
def iter_neurites(obj, mapfun=None, filt=None, neurite_order=NeuriteIter.FileOrder):
'''Iterator to a neurite, neuron or neuron population
Applies optional neurite filter and mapping functions.
Parameters:
obj: a neurite, neuron or neuron population.
mapfun: optional neurite mapping function.
filt: optional neurite filter function.
neurite_order (NeuriteIter): order upon which neurites should be iterated
- NeuriteIter.FileOrder: order of appearance in the file
- NeuriteIter.NRN: NRN simulator order: soma -> axon -> basal -> apical
Examples:
Get the number of points in each neurite in a neuron population
>>> from neurom.core import iter_neurites
>>> n_points = [n for n in iter_neurites(pop, lambda x : len(x.points))]
Get the number of points in each axon in a neuron population
>>> import neurom as nm
>>> from neurom.core import iter_neurites
>>> filter = lambda n : n.type == nm.AXON
>>> mapping = lambda n : len(n.points)
>>> n_points = [n for n in iter_neurites(pop, mapping, filter)]
'''
neurites = ((obj,) if isinstance(obj, Neurite) else
obj.neurites if hasattr(obj, 'neurites') else obj)
if neurite_order == NeuriteIter.NRN:
last_position = max(NRN_ORDER.values()) + 1
neurites = sorted(neurites, key=lambda neurite: NRN_ORDER.get(neurite.type, last_position))
neurite_iter = iter(neurites) if filt is None else filter(filt, neurites)
return neurite_iter if mapfun is None else map(mapfun, neurite_iter)
