diff options
Diffstat (limited to 'pyspike/function.py')
| -rw-r--r-- | pyspike/function.py | 165 |
1 files changed, 156 insertions, 9 deletions
diff --git a/pyspike/function.py b/pyspike/function.py index 662606c..e0dadf6 100644 --- a/pyspike/function.py +++ b/pyspike/function.py @@ -136,15 +136,6 @@ class PieceWiseConstFunc(object): a /= int_length return a - def avrg_function_value(self): - """ Computes the average function value of the piece-wise const - function: :math:`a = 1/N sum_i f_i` where N is the number of intervals. - - :returns: the average a. - :rtype: float - """ - return sum(self.y)/(len(self.y)) - def add(self, f): """ Adds another PieceWiseConst function to this function. Note: only functions defined on the same interval can be summed. @@ -364,6 +355,162 @@ that PySpike is installed by running\n 'python setup.py build_ext --inplace'! \ self.y2 *= fac +############################################################## +# DiscreteFunction +############################################################## +class DiscreteFunction(object): + """ A class representing values defined on a discrete set of points. + """ + + def __init__(self, x, y, multiplicity): + """ Constructs the discrete function. + + :param x: array of length N defining the points at which the values are + defined. + :param y: array of length N degining the values at the points x. + :param multiplicity: array of length N defining the multiplicity of the + values. + """ + # convert parameters to arrays, also ensures copying + self.x = np.array(x) + self.y = np.array(y) + self.mp = np.array(multiplicity) + + def copy(self): + """ Returns a copy of itself + + :rtype: :class:`DiscreteFunction` + """ + return DiscreteFunction(self.x, self.y, self.mp) + + def almost_equal(self, other, decimal=14): + """ Checks if the function is equal to another function up to `decimal` + precision. + + :param other: another :class:`DiscreteFunction` + :returns: True if the two functions are equal up to `decimal` decimals, + False otherwise + :rtype: bool + """ + eps = 10.0**(-decimal) + return np.allclose(self.x, other.x, atol=eps, rtol=0.0) and \ + np.allclose(self.y, other.y, atol=eps, rtol=0.0) and \ + np.allclose(self.mp, other.mp, atol=eps, rtol=0.0) + + def get_plottable_data(self, k=0): + """ Returns two arrays containing x- and y-coordinates for immeditate + plotting of the interval sequence. + + :returns: (x_plot, y_plot) containing plottable data + :rtype: pair of np.array + + Example:: + + x, y = f.get_plottable_data() + plt.plot(x, y, '-o', label="Discrete function") + """ + + if k > 0: + raise NotImplementedError() + + return 1.0*self.x, 1.0*self.y/self.mp + + def integral(self, interval=None): + """ Returns the integral over the given interval. For the discrete + function, this amounts to the sum over all values divided by the total + multiplicity. + + :param interval: integration interval given as a pair of floats, or a + sequence of pairs in case of multiple intervals, if + None the integral over the whole function is computed. + :type interval: Pair, sequence of pairs, or None. + :returns: the integral + :rtype: float + """ + + def get_indices(ival): + """ Retuns the indeces surrounding the given interval""" + start_ind = np.searchsorted(self.x, ival[0], side='right') + end_ind = np.searchsorted(self.x, ival[1], side='left') + assert start_ind > 0 and end_ind < len(self.x), \ + "Invalid averaging interval" + return start_ind, end_ind + + if interval is None: + # no interval given, integrate over the whole spike train + # don't count the first value, which is zero by definition + return 1.0 * np.sum(self.y[1:-1]) / np.sum(self.mp[1:-1]) + + # check if interval is as sequence + assert isinstance(interval, collections.Sequence), \ + "Invalid value for `interval`. None, Sequence or Tuple expected." + # check if interval is a sequence of intervals + if not isinstance(interval[0], collections.Sequence): + # find the indices corresponding to the interval + start_ind, end_ind = get_indices(interval) + return (np.sum(self.y[start_ind:end_ind]) / + np.sum(self.mp[start_ind:end_ind])) + else: + value = 0.0 + multiplicity = 0.0 + for ival in interval: + # find the indices corresponding to the interval + start_ind, end_ind = get_indices(ival) + value += np.sum(self.y[start_ind:end_ind]) + multiplicity += np.sum(self.mp[start_ind:end_ind]) + return value/multiplicity + + def avrg(self, interval=None): + """ Computes the average of the interval sequence: + :math:`a = 1/N sum f_n ` where N is the number of intervals. + + :param interval: averaging interval given as a pair of floats, a + sequence of pairs for averaging multiple intervals, or + None, if None the average over the whole function is + computed. + :type interval: Pair, sequence of pairs, or None. + :returns: the average a. + :rtype: float + """ + return self.integral(interval) + + def add(self, f): + """ Adds another `DiscreteFunction` function to this function. + Note: only functions defined on the same interval can be summed. + + :param f: :class:`DiscreteFunction` function to be added. + :rtype: None + """ + assert self.x[0] == f.x[0], "The functions have different intervals" + assert self.x[-1] == f.x[-1], "The functions have different intervals" + + # cython version + try: + from cython_add import add_discrete_function_cython as \ + add_discrete_function_impl + except ImportError: + print("Warning: add_discrete_function_cython not found. Make \ +sure that PySpike is installed by running\n\ +'python setup.py build_ext --inplace'! \ +\n Falling back to slow python backend.") + # use python backend + from python_backend import add_discrete_function_python as \ + add_discrete_function_impl + + self.x, self.y, self.mp = \ + add_discrete_function_impl(self.x, self.y, self.mp, + f.x, f.y, f.mp) + + def mul_scalar(self, fac): + """ Multiplies the function with a scalar value + + :param fac: Value to multiply + :type fac: double + :rtype: None + """ + self.y *= fac + + def average_profile(profiles): """ Computes the average profile from the given ISI- or SPIKE-profiles. |