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def cpcv_generator(t_span, n, k, verbose=True):
    # split data into N groups, with N << T
    # this will assign each index position to a group position
    group_num = np.arange(t_span) // (t_span // n)
    group_num[group_num == n] = n-1
    
    # generate the combinations 
    test_groups = np.array(list(itt.combinations(np.arange(n), k))).reshape(-1, k)
    C_nk = len(test_groups)
    n_paths = C_nk * k // n 

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#!/usr/bin/env python3
'''2021-03-26: Reverse-engineer by searching for the following terms in features*.js:
    - bracketMaintenanceMarginRate
    - cumFastMaintenanceAmount
    - bracketNotionalFloor
    - bracketNotionalCap'''


# (max) position, maintenance margin, maintenance amount
maint_lookup_table = [

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    # Store the short term moving average in a new column 'window_ST'
    prices.loc[:, 'window_ST'] = prices['close'].rolling(
                                            context.short_term_window).mean()

    # Store the long term moving average in a new column 'window_LT'
    prices.loc[:, 'window_LT'] = prices['close'].rolling(
                                            context.long_term_window).mean()

    # Get the latest signal, 1 for golden cross, -1 for death cross
    prices.loc[:, 'signal'] = np.where(

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Date	Open	High	Low	Close	Volume
2020-05-06 18:15:00-04:00	2832	2838.5	2832	2838	3750
2020-05-06 18:30:00-04:00	2838	2838.5	2826	2827.75	6864
2020-05-06 18:45:00-04:00	2827.75	2830.5	2827	2829.5	2937
2020-05-06 19:00:00-04:00	2829.5	2830.5	2823	2826.5	4619
2020-05-06 19:15:00-04:00	2826.75	2829.5	2825.25	2827.75	3610
2020-05-06 19:30:00-04:00	2827.75	2829.5	2825.5	2826.75	2460
2020-05-06 19:45:00-04:00	2826.75	2830.75	2826.25	2830.5	2531
2020-05-06 20:00:00-04:00	2830.5	2833.5	2830.25	2833.5	2361

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import select
import datetime

import psycopg2
import psycopg2.extensions

conn = psycopg2.connect(database="postgres", user="vagrant")
#conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)

curs = conn.cursor()

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import select
import datetime

import psycopg2
import psycopg2.extensions

from sqlalchemy import create_engine, text

engine = create_engine("postgresql+psycopg2://vagrant@/postgres")

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import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import tensorflow.keras.layers as layers
import tensorflow.keras.losses as loss
import tensorflow_datasets.public_api as tfds

from sys import argv
from random import Random
from os import walk

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#!/usr/bin/python2.7
"""Quick hack of 'modern' OpenGL example using pysdl2 and pyopengl
that shows a textured triangle; assumes there is a 'hazard.png' image
file in working directory.

Based on:

pysdl2 OpenGL example
http://www.tomdalling.com/blog/modern-opengl/02-textures/
http://www.arcsynthesis.org/gltut/Basics/Tut02%20Vertex%20Attributes.html