# -*- coding: utf-8 -*-
import numpy as np
from scipy.signal import fftconvolve


def energy(traces, duration, dt=1):
    """
    Compute an mean-squared energy measurement for each point of a
    seismic section.

    :param traces: The data array to use for calculating MS energy.
                   Must be 1D or 2D numpy array.
    :param duration: the time duration of the window (in seconds), or
                     samples if dt=1.
    :param dt: the sample interval of the data (in seconds). Defaults
               to 1 so duration can be in samples.
    :returns: An array the same dimensions as the input array.
    """

    energy_data = np.zeros(traces.shape)
    signal = traces * traces
    n_samples = int(duration / dt)

    window = np.ones(n_samples)

    if np.ndim(signal) == 1:
        # Compute the sliding average using a convolution
        energy_data = fftconvolve(signal, window, mode='same') \
                     / n_samples

    elif np.ndim(signal) == 2:
        for trace in range(signal.shape[1]):
            energy_data[:, trace] = (fftconvolve(signal[:, trace],
                                                 window,
                                                 mode='same'))

    else:
        raise ValueError('Array must be 1D or 2D')

    return energy_data

# -*- coding: utf-8 -*-
import numpy as np
from scipy.signal import fftconvolve


def energy(traces, duration, dt=1):
    """
    Compute an mean-squared energy measurement for each point of a
    seismic section.

    :param traces: The data array to use for calculating MS energy.
                   Must be 1D or 2D numpy array.
    :param duration: the time duration of the window (in seconds), or
                     samples if dt=1.
    :param dt: the sample interval of the data (in seconds). Defaults
               to 1 so duration can be in samples.
    :returns: An array the same dimensions as the input array.
    """

    energy_data = np.zeros(traces.shape)
    signal = traces * traces
    n_samples = int(duration / dt)

    window = np.ones(n_samples)

    if np.ndim(signal) == 1:
        # Compute the sliding average using a convolution
        energy_data = fftconvolve(signal, window, mode='same') \
                     / n_samples

    elif np.ndim(signal) == 2:
        for trace in range(signal.shape[1]):
            energy_data[:, trace] = (fftconvolve(signal[:, trace],
                                                 window,
                                                 mode='same'))

    else:
        raise ValueError('Array must be 1D or 2D')

    return energy_data

# -*- coding: utf-8 -*- Compute an mean-squared energy measurement for each point of a     seismic section.      :param traces: The data array to use for calculating MS energy.                    Must be 1D or 2D numpy array.     :param duration: the time duration of the window (in seconds), or                      samples if dt=1.     :param dt: the sample interval of the data (in seconds). Defaults                to 1 so duration can be in samples.     :returns: An array the same dimensions as the input array. # Compute the sliding average using a convolution