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import numpy as np
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from nengo.base import Process
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from nengo.exceptions import ValidationError
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from nengo.utils.stdlib import checked_call
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__all__ = ['Callable']
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class Callable(Process):
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"""Adapter to convert any callable into a :class:`nengo.Process`.
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Parameters
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----------
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func : ``callable``
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A function that can be called with a single float argument (time).
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default_dt : ``float``, optional
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Default time-step for the process. Defaults to ``0.001`` seconds.
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seed : ``integer``, optional
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Seed for the process.
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See Also
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--------
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:class:`nengo.Process`
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Examples
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--------
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Making a sine wave process using a lambda:
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>>> from nengolib.processes import Callable
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>>> process = Callable(lambda t: np.sin(2*np.pi*t))
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>>> import matplotlib.pyplot as plt
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>>> plt.plot(process.ntrange(1000), process.run_steps(1000))
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>>> plt.xlabel("Time (s)")
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>>> plt.show()
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"""
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def __init__(self, func, default_dt=0.001, seed=None):
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if not callable(func):
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raise ValidationError("func (%s) must be callable" % func,
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attr='func', obj=self)
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self.func = func
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value, invoked = checked_call(func, 0.)
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if not invoked:
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raise ValidationError(
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"func (%s) must only take single float argument" % func,
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attr='func', obj=self)
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default_size_out = np.asarray(value).size
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super(Callable, self).__init__(
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default_size_in=0,
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default_size_out=default_size_out,
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default_dt=default_dt,
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seed=seed)
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def __repr__(self):
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return "%s(func=%r, default_dt=%r, seed=%r)" % (
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type(self).__name__, self.func, self.default_dt, self.seed)
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def make_step(self, shape_in, shape_out, dt, rng):
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if shape_in != (0,):
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raise ValidationError("shape_in must be (0,), got %s" % (
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shape_in,), attr='func', obj=self)
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if shape_out != (self.default_size_out,):
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raise ValidationError("shape_out must be (%s,), got %s" % (
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self.default_size_out, shape_out), attr='func', obj=self)
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def step(t):
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return self.func(t)
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return step
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arvoelke