William Matthews WillMatthews

## haskell-conceals-to-add.txt
Arrows:
Dash, Equals


Greek
Superscripts
Type formatting - Mathbb and Bold
Mathcal P for powersets
Scientific Constants
Sum, Integral, Product, Sqrt, Not, cdot for multiply

## detect_interference.m
function [interference_present] = detect_interference(dataRX)
% takes a structure `dataRX` which has fields `x` and `y` which is an
% oscilloscope capture.
% Returns a boolean if interference is detected
% tested bands are defined in this function, below.

% use this function to determine if the capture has interference.
% this can be used to cause an error and then place capture code in a 'try catch' block.


## eyediagram_dense.m
function [screen, yscale] = eyediagram_dense(signal, time, rep)
% EYEDIAGRAM_DENSE Creates a very pretty eyediagram compared to MATLAB's default rubbish.
% uses the same arguments as matlab's eyediagram function


scr = 500;
num2delete = rep*mod(numel(signal)/rep,1);
num2delete = round(num2delete);

signal = signal((num2delete + 1):end);

## yoctolight.py
import os, sys
from yoctopuce.yocto_api import *
from yoctopuce.yocto_lightsensor import *
import datetime
import csv

errmsg = YRefParam()

# Setup the API to use local USB devices
if YAPI.RegisterHub("usb", errmsg) != YAPI.SUCCESS:

## multi-detector-dot-prod.py
import matplotlib.pyplot as plt
import numpy as np
import math as m

def Rx(theta):
  return np.matrix([[ 1, 0           , 0           ],
                   [ 0, m.cos(theta),-m.sin(theta)],
                   [ 0, m.sin(theta), m.cos(theta)]])

def Ry(theta):

## playground.m
clear all; close all; clc;

% 3B13c Q1 Tutorial Exploration Sandbox
% Written by William Matthews 25/02/2021
% Q2, Q3, Q4, Q6 can be applied here,
% but is left as an exercise for the interested reader.

% For the interested reader, Q5 asks for the instantaneous frequency.
% This can be found with a signal processing technique,
% research 'Analytic signal' which is covered in 4th year's

## flips.py
import matplotlib.pyplot as plt

flips = [0 for _ in range(100)]
flips[0] = 1
for i in range(1, len(flips)):
    flips[i] = flips[i-1]/2

total_mass = sum(flips)

prob = [f/total_mass for f in flips]

## serial-test.py
import serial # ONLY USE PYSERIAL!! pip install pyserial
import time
import sys
import glob

def serial_ports():
    """ Lists serial port names

        :raises EnvironmentError:
            On unsupported or unknown platforms

## sine_fit.m
clear all; close all; clc;

% the below code fits a sine wave which has a zero DC component.
% the output is 'bestx' which is a 1x3 matrix with components
% [amplitude, omega, phase 0-2*pi]

% we also have a fitting function @fitfun which can be used y =
% fitfun(bestx,time_arry) to generate our fitted sine wave for some generic
% time array.

## vis_psf.m
clear all; close all; clc;

xp = linspace(-2,2,1000);
yp = xp';

d = (xp.^2 + yp.^2).^0.5;
d2 = (abs(xp) + abs(yp));

% defines pupil
p = (d<0.1); % circle
	Arrows:
	Dash, Equals


	Greek
	Superscripts
	Type formatting - Mathbb and Bold
	Mathcal P for powersets
	Scientific Constants
	Sum, Integral, Product, Sqrt, Not, cdot for multiply
	function [interference_present] = detect_interference(dataRX)
	% takes a structure `dataRX` which has fields `x` and `y` which is an
	% oscilloscope capture.
	% Returns a boolean if interference is detected
	% tested bands are defined in this function, below.

	% use this function to determine if the capture has interference.
	% this can be used to cause an error and then place capture code in a 'try catch' block.
	function [screen, yscale] = eyediagram_dense(signal, time, rep)
	% EYEDIAGRAM_DENSE Creates a very pretty eyediagram compared to MATLAB's default rubbish.
	% uses the same arguments as matlab's eyediagram function


	scr = 500;
	num2delete = rep*mod(numel(signal)/rep,1);
	num2delete = round(num2delete);

	signal = signal((num2delete + 1):end);
	import os, sys
	from yoctopuce.yocto_api import *
	from yoctopuce.yocto_lightsensor import *
	import datetime
	import csv

	errmsg = YRefParam()

	# Setup the API to use local USB devices
	if YAPI.RegisterHub("usb", errmsg) != YAPI.SUCCESS:
	import matplotlib.pyplot as plt
	import numpy as np
	import math as m

	def Rx(theta):
	return np.matrix([[ 1, 0 , 0 ],
	[ 0, m.cos(theta),-m.sin(theta)],
	[ 0, m.sin(theta), m.cos(theta)]])

	def Ry(theta):
	clear all; close all; clc;

	% 3B13c Q1 Tutorial Exploration Sandbox
	% Written by William Matthews 25/02/2021
	% Q2, Q3, Q4, Q6 can be applied here,
	% but is left as an exercise for the interested reader.

	% For the interested reader, Q5 asks for the instantaneous frequency.
	% This can be found with a signal processing technique,
	% research 'Analytic signal' which is covered in 4th year's
	import matplotlib.pyplot as plt

	flips = [0 for _ in range(100)]
	flips[0] = 1
	for i in range(1, len(flips)):
	flips[i] = flips[i-1]/2

	total_mass = sum(flips)

	prob = [f/total_mass for f in flips]
	import serial # ONLY USE PYSERIAL!! pip install pyserial
	import time
	import sys
	import glob

	def serial_ports():
	""" Lists serial port names

	:raises EnvironmentError:
	On unsupported or unknown platforms
	clear all; close all; clc;

	% the below code fits a sine wave which has a zero DC component.
	% the output is 'bestx' which is a 1x3 matrix with components
	% [amplitude, omega, phase 0-2*pi]

	% we also have a fitting function @fitfun which can be used y =
	% fitfun(bestx,time_arry) to generate our fitted sine wave for some generic
	% time array.
	clear all; close all; clc;

	xp = linspace(-2,2,1000);
	yp = xp';

	d = (xp.^2 + yp.^2).^0.5;
	d2 = (abs(xp) + abs(yp));

	% defines pupil
	p = (d<0.1); % circle