jcorrius

Origin: Bluekiri Demo
Label: bluekiri
Codename: bionic
Architectures: amd64
Components: main
Description: Personal repository
SignWith: B501DE17DA19A16F

jcorrius

[Unit]
Description=Demo Api Service
After=network.target

[Service]
Type=simple
ExecStart=/opt/bluekiri/demoapi/demoapi
ExecReload=/bin/kill -HUP $MAINPID

[Install]

jcorrius

#!/usr/bin/make -f
#export DH_VERBOSE = 1

%:
	dh $@ --with=systemd

override_dh_auto_build:
	dotnet publish -c Release --self-contained -r ubuntu.18.04-x64
	# auto-build disabled

jcorrius

Source: demoapi
Section: net
Priority: optional
Maintainer: Bluekiri Demo <[email protected]>
Build-Depends: debhelper (>= 10), dh-systemd
Standards-Version: 4.1.2
Homepage: https://github.com/bluekiri/demoapi

Package: demoapi
Architecture: any

jcorrius

demoapi (1.0-0ubuntu1) bionic; urgency=medium

  * Initial Release.

 -- Bluekiri Demo <[email protected]>  Tue, 13 Nov 2018 08:23:08 +0000

jcorrius

<Project Sdk="Microsoft.NET.Sdk.Web">

  <PropertyGroup>
    <TargetFramework>netcoreapp2.1</TargetFramework>
    <RuntimeIdentifiers>ubuntu.18.04-x64</RuntimeIdentifiers>
  </PropertyGroup>

  <ItemGroup>
    <Folder Include="wwwroot\" />
  </ItemGroup>

jcorrius

import numpy as np
from statsmodels.tsa.tsatools import lagmat
 
 
def johansen(ts, lags):
    """
    Calculate the Johansen Test for the given time series
    """
    # Make sure we are working with arrays, convert if necessary
    ts = np.asarray(ts)

jcorrius

import numpy as np
from statsmodels.regression.linear_model import OLS
from statsmodels.tsa.tsatools import lagmat, add_trend
from statsmodels.tsa.adfvalues import mackinnonp
 
def adf(ts, maxlag=1):
    """
    Augmented Dickey-Fuller unit root test
    """
    # make sure we are working with an array, convert if necessary

jcorrius

import numpy as np

def half_life(ts):  
    """ 
    Calculates the half life of a mean reversion
    """
    # make sure we are working with an array, convert if necessary
    ts = np.asarray(ts)
    
    # delta = p(t) - p(t-1)

jcorrius

import numpy as np

def variance_ratio(ts, lag = 2):
    """
    Returns the variance ratio test result
    """
    # make sure we are working with an array, convert if necessary
    ts = np.asarray(ts)
    
    # Apply the formula to calculate the test