anielsen001

from numpy import *
from scipy.signal import cubic

def cspline1d_eval(cj, newx, dx=1.0, x0=0):
    """Evaluate a spline at the new set of points.

    `dx` is the old sample-spacing while `x0` was the old origin.  In
    other-words the old-sample points (knot-points) for which the `cj`
    represent spline coefficients were at equally-spaced points of:

anielsen001

import matplotlib.pylab as plt
import seaborn as sns
import pandas as pd

nosoi = pd.read_csv('roc3.txt', names = ['file','name','score'],na_values = ['None','no_persons_found']  )
nosoi.assign(truth=False) # create a column of "false"

soi = pd.read_csv('roc_known.txt', names = ['file','name','score'], na_values = ['None','no_persons_found'] )
soi.assign(truth=True) # create a column of Truth = True

anielsen001

from __future__ import print_function
from ofxparse import OfxParser
import os
import re
import sys

if len(sys.argv) != 1:
    print ('This utility does not take command-line arguments')
    exit()

anielsen001

Building and installing opencv with python bindings

dependencies

sudo apt install ffmpeg
sudo apt install libgtk-3-dev
sudo apt install libv4l-dev
sudo apt install libtiff-dev
sudo apt install libwebp-dev

anielsen001

try:
    # python 3
    from io import StringIO
except:
    # python 2
    from StringIO import StringIO

 # some examples from
# https://stackoverflow.com/questions/17978092/combine-date-and-time-columns-using-python-pandas   

anielsen001

Target Ubunutu 16.04

Dependencies

cython

pip3 install cython

proj

anielsen001

# Example code for parsing sensor log files from Andriod apps

import pandas as pd

# SensorDataLogger
# https://play.google.com/store/apps/details?id=es.terrik.SensorLogger
# 'a' and 'b' are empty colums

date_parser = lambda x: pd.datetime.strptime( x, "%Y-%m-%d_%H-%M-%S.%f" )

anielsen001

# this is a python version of the wideband ambiguity function. A matlab version that it was ported from is below.
# https://dsp.stackexchange.com/questions/51372/how-to-calculate-the-ambiguity-function

import numpy as np
from scipy.interpolate import interp1d
from matplotlib import pylab as plt

tb = -1
tend = 1
dilation = 0.8

anielsen001

"""
Permeabilities can be found here:
https://www.engineeringtoolbox.com/permeability-d_1923.html

Resistivity can be found here:
http://hyperphysics.phy-astr.gsu.edu/hbase/Tables/rstiv.html

"""

import numpy as np

anielsen001

#!/usr/bin/env python3

import multiprocessing as mp

SENTINEL = None

dat = range(10)
rets = []

def function( *args ):