bnaul

y = [0.1 0.2 0.1 0.2 0.5 0.4 0.6 0.7 0.8]';
p = length(y);
a = 0.2; b = 0.6;
A = tril(toeplitz([-1 1 zeros(1,p-2)]));
cvx_begin
variable x(p, 1)
minimize norm(x - y)
subject to
A * x <= 0
x(1) >= a

bnaul

import numpy as np


class Point:
    def __init__(self,x,y):
        self.x = x
        self.y = y

    def __repr__(self):
        return "Point({}, {})".format(self.x, self.y)

bnaul

bnaul

cesium: Open-Source Inference Platform for Time-Series Data

Brett Naul

bnaul@berkeley.edu

https://github.com/cesium-ml

---

General intro

bnaul

bnaul

bnaul

import imp
from os.path import expanduser
import dask
import numpy as np

from cesium import featurize, time_series


imp.reload(dask.async)
execute_task_old = dask.async.execute_task

bnaul

bnaul

bnaul