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42 lines
1.5 KiB
42 lines
1.5 KiB
import scipy.stats |
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import numpy as np |
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from .population import Population |
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from .. import cells |
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class DStellate(Population): |
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type = "dstellate" |
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def __init__(self, species="mouse", **kwds): |
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# Note that `cf` is the mean value used when selecting SGCs to connect; |
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# it is NOT the measured CF of the cell (although it should be close). |
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freqs = self._get_cf_array(species) |
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fields = [ |
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("cf", float), |
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("input_sr", list), # distribution probability of SGC SR groups |
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] |
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super(DStellate, self).__init__(species, len(freqs), fields=fields, **kwds) |
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self._cells["cf"] = freqs |
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self._cells["input_sr"] = [np.tile([1.0, 1.0, 1.0], len(freqs))] |
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def create_cell(self, cell_rec): |
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""" Return a single new cell to be used in this population. The |
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*cell_rec* argument is the row from self.cells that describes the cell |
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to be created. |
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""" |
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return cells.DStellate.create(species=self.species, **self._cell_args) |
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def connection_stats(self, pop, cell_rec): |
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""" The population *pop* is being connected to the cell described in |
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*cell_rec*. Return the number of presynaptic cells that should be |
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connected and a dictionary of distributions used to select cells |
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from *pop*. |
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""" |
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size, dist = Population.connection_stats(self, pop, cell_rec) |
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from .. import populations |
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if isinstance(pop, populations.SGC): |
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dist["sr"] = (pop.cells["sr"] < 2).astype(float) |
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return size, dist
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