g-leech

import math
import scipy.stats as st

# assumes bivariate normal, dichotomised groups
def dichotomy_r_to_d(r) :
    d = 2*r / (math.sqrt(1 - r**2))
    return d

# Equation 9
# https://sci-hub.tw/10.1037/1082-989X.11.4.386

g-leech

from scipy.spatial.distance import cdist
import numpy as np
import matplotlib.pyplot as plt

# First write a covariance function. e.g. rbf
def radial_basis_kernel(x1, x2, varSigma, lengthScale):
    if x2 is None:
        d = cdist(x1, x1)
    else:
        d = cdist(x1, x2)

g-leech

import numpy as np

probability = 1/10000
wealth = 120000
houseValue = 100000

bound = probability * np.log(wealth - houseValue) \
		+ (1 - probability) * np.log(wealth)
maxPremium = wealth - np.exp(bound)

g-leech

# https://help.open.ac.uk/documents/policies/working-out-your-class-of-honours/files/50/honours-class-working-out.pdf
# Only 2nd and 3rd year courses count.

# Course, credits, grade, year
courses = [
        ["M343", 30, "Distinction", 3],
        ["M249", 30, "Distinction", 2],
        ["M248", 30, "Distinction", 2],
        ["MST210", 60, "Grade 2 Pass", 2]
    ]

g-leech

##################################
## DAY 1

# Evaluate 1 + 1 and then 1 + "one". Is Io strongly typed or weakly typed? 
1 + 1
1+"one" 
# > Exception: argument 0 to method '+' must be a Number, not a 'Sequence'

# Io is Strong: it does not perform implicit casts between types. 

g-leech

# Every thing is an object. 
# Every interaction with an object is a message.
# You don’t instantiate classes; you clone other objects called prototypes.
# Objects remember their prototypes. 
# Objects have slots. Slots contain objects, including method objects.
# A message returns the value in a slot or invokes the method in a slot.
# If an object can’t respond to a message, it sends that message to its prototype.

Vehicle := Object clone
Vehicle description := "Something to take you places"

g-leech

gdp = 80683787e6 # in 2017: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD 
population = 7.6e9 	# http://www.worldometers.info/world-population/
perCap =  gdp / population

# >>> $10616 
# Sanity check: the World Bank estimate, 10714, is very close. 
# https://data.worldbank.org/indicator/NY.GDP.PCAP.CD


# Subtract depreciation 

g-leech

#!/usr/bin/env python3

from pandas import DataFrame
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np


#%%
# Figures are not time-consistent: they each represent a point between 2010 - 2016

g-leech

sys.setrecursionlimit(500)

from ai_safety_gridworlds.environments.shared.safety_game import Actions
from ai_safety_gridworlds.environments.shared.rl.environment import TimeStep
from hashlib import sha1
import numpy
import copy

ACTIONS = [ a for a in Actions if a is not Actions.QUIT ]

g-leech

from ai_safety_gridworlds.environments.shared.safety_game import Actions
from hashlib import sha1
import numpy
import time
from IPython import display
import copy

env = sokoban_game(level=0)
ACTIONS = [ a for a in Actions if a is not Actions.QUIT ]