ahwillia

import numpy as np
from sklearn.utils.extmath import randomized_svd


def partial_whiten(X, alpha, eigval_tol=1e-7):
    """
    Return regularized whitening transform for a matrix X.

    Parameters
    ----------

ahwillia

import numpy as np
import matplotlib.pyplot as plt

import scipy.stats
normcdf = scipy.stats.norm.cdf
normpdf = scipy.stats.norm.pdf

from scipy.linalg import cho_factor, cho_solve
from sklearn.base import BaseEstimator

ahwillia

import numpy as np
import numpy.random as npr
from functools import reduce

# Goal
# ----
# Compute (As[0] kron As[1] kron ... As[-1]) @ v

# ==== HELPER FUNCTIONS ==== #

ahwillia

"""
References:

  - B. Plateau, On the stochastic structure of parallelism and synchronization models for distributed algorithms.
  Perform. Eval. Rev., 13 (1985), pp. 147–154.

  - Dayar, T., & Orhan, M. C. (2015). On vector-Kronecker product multiplication with rectangular factors.
  SIAM Journal on Scientific Computing, 37(5), S526-S543.
"""

ahwillia

import numpy as np
from scipy.linalg import solve_circulant, circulant
from numpy.testing import assert_array_almost_equal
import numba


@numba.jit(nopython=True, cache=True)
def rojo_method(c, a, f, x, z):
    """
    Solves symmetric, tridiagonal circulant system, assuming diagonal

ahwillia

def bandpass(x, lowcut, highcut, fs, order=5, axis=-1, kind='butter'):
    """
    Parameters
    ----------
    x : ndarray
        1d time series data
    lowcut : float
        Defines lower frequency cutoff (e.g. in Hz)
    highcut : float
        Defines upper frequency cutoff (e.g. in Hz)

ahwillia

"""
Computing hessian-vector products in tensorflow.

For simplicity, we demonstrate the idea on a Poisson regression model.
"""

import tensorflow as tf
import numpy as np
from scipy.optimize import minimize

ahwillia

"""
A simple implementation of Poisson regression.
"""

import numpy as np
from scipy.optimize import minimize

n = 1000   # number of datapoints
p = 5     # number of features

ahwillia

# coding: utf-8

# In[1]:

import numpy as np
import matplotlib.pyplot as plt
import scipy.linalg as sci

# In[2]:

ahwillia

import numpy as np
from tqdm import trange
import matplotlib.pyplot as plt


# TODO: subclass np.ndarray?
class ShiftMatrix(object):
    """
    Thin wrapper around a numpy matrix to support shifting along the second
    axis and padding with zeros.