update chapters 4 and 5
This commit is contained in:
Bogumił Kamiński
parent
bbd8bbf571
commit
e73dbaf370
12
appB.jl
12
appB.jl
@ -16,9 +16,7 @@ y = collect(x);
|
||||
@btime sort($y);
|
||||
@edit sort(x)
|
||||
|
||||
# CODES BELOW REQUIRE RE-NUMBERING
|
||||
|
||||
# Code for exercise 3.1
|
||||
# Code for exercise 4.1
|
||||
|
||||
using Statistics
|
||||
using BenchmarkTools
|
||||
@ -36,7 +34,7 @@ aq = [10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
|
||||
@benchmark [cor($aq[:, i], $aq[:, i+1]) for i in 1:2:7]
|
||||
@benchmark [cor(view($aq, :, i), view($aq, :, i+1)) for i in 1:2:7]
|
||||
|
||||
# Code for exercise 3.2
|
||||
# Code for exercise 4.2
|
||||
|
||||
function dice_distribution(dice1, dice2)
|
||||
distribution = Dict{Int, Int}()
|
||||
@ -73,17 +71,19 @@ end
|
||||
|
||||
test_dice()
|
||||
|
||||
# Code for exercise 3.3
|
||||
# Code for exercise 4.3
|
||||
|
||||
plot(scatter(data.set1.x, data.set1.y; legend=false),
|
||||
scatter(data.set2.x, data.set2.y; legend=false),
|
||||
scatter(data.set3.x, data.set3.y; legend=false),
|
||||
scatter(data.set4.x, data.set4.y; legend=false))
|
||||
|
||||
# Code for exercise 3.4
|
||||
# Code for exercise 5.1
|
||||
|
||||
parse.(Int, ["1", "2", "3"])
|
||||
|
||||
# CODES BELOW REQUIRE RE-NUMBERING
|
||||
|
||||
# Code for exercise 4.1
|
||||
|
||||
years_table = freqtable(years)
|
||||
|
||||
@ -1,8 +1,8 @@
|
||||
# Bogumił Kamiński, 2021
|
||||
|
||||
# Codes for chapter 3
|
||||
# Codes for chapter 4
|
||||
|
||||
# Code for listing 3.1
|
||||
# Code for listing 4.1
|
||||
|
||||
aq = [10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
|
||||
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
|
||||
@ -32,13 +32,13 @@ v[1] = 10
|
||||
v
|
||||
t[1] = 10
|
||||
|
||||
# Code for figure 3.2
|
||||
# Code for figure 4.2
|
||||
|
||||
using BenchmarkTools
|
||||
@benchmark (1, 2, 3)
|
||||
@benchmark [1, 2, 3]
|
||||
|
||||
# Code for section 3.1.2
|
||||
# Code for section 4.1.2
|
||||
|
||||
using Statistics
|
||||
mean(aq; dims=1)
|
||||
@ -54,7 +54,7 @@ end
|
||||
[mean(col) for col in eachcol(aq)]
|
||||
[std(col) for col in eachcol(aq)]
|
||||
|
||||
# Code for section 3.1.3
|
||||
# Code for section 4.1.3
|
||||
|
||||
[mean(aq[:, j]) for j in axes(aq, 2)]
|
||||
[std(aq[:, j]) for j in axes(aq, 2)]
|
||||
@ -65,7 +65,7 @@ axes(aq, 2)
|
||||
[mean(view(aq, :, j)) for j in axes(aq, 2)]
|
||||
[std(@view aq[:, j]) for j in axes(aq, 2)]
|
||||
|
||||
# Code for section 3.1.4
|
||||
# Code for section 4.1.4
|
||||
|
||||
using BenchmarkTools
|
||||
x = ones(10^7, 10)
|
||||
@ -73,12 +73,12 @@ x = ones(10^7, 10)
|
||||
@benchmark [mean($x[:, j]) for j in axes($x, 2)]
|
||||
@benchmark mean($x, dims=1)
|
||||
|
||||
# Code for section 3.1.5
|
||||
# Code for section 4.1.5
|
||||
|
||||
[cor(aq[:, i], aq[:, i+1]) for i in 1:2:7]
|
||||
collect(1:2:7)
|
||||
|
||||
# Code for section 3.1.6
|
||||
# Code for section 4.1.6
|
||||
|
||||
y = aq[:, 2]
|
||||
X = [ones(11) aq[:, 1]]
|
||||
@ -99,7 +99,7 @@ end
|
||||
|
||||
?²
|
||||
|
||||
# Code for section 3.1.7
|
||||
# Code for section 4.1.7
|
||||
|
||||
using Plots
|
||||
scatter(aq[:, 1], aq[:, 2]; legend=false)
|
||||
@ -112,7 +112,7 @@ plot(scatter(aq[:, 1], aq[:, 2]; legend=false),
|
||||
plot([scatter(aq[:, i], aq[:, i+1]; legend=false)
|
||||
for i in 1:2:7]...)
|
||||
|
||||
# Code for section 3.2
|
||||
# Code for section 4.2
|
||||
|
||||
two_standard = Dict{Int, Int}()
|
||||
for i in [1, 2, 3, 4, 5, 6]
|
||||
@ -156,7 +156,7 @@ for d1 in all_dice, d2 in all_dice
|
||||
end
|
||||
end
|
||||
|
||||
# Code for section 3.3
|
||||
# Code for section 4.3
|
||||
|
||||
aq = [10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
|
||||
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
|
||||
@ -175,14 +175,14 @@ dataset1 = (x=aq[:, 1], y=aq[:, 2])
|
||||
dataset1[1]
|
||||
dataset1.x
|
||||
|
||||
# Code for listing 3.2
|
||||
# Code for listing 4.2
|
||||
|
||||
data = (set1=(x=aq[:, 1], y=aq[:, 2]),
|
||||
set2=(x=aq[:, 3], y=aq[:, 4]),
|
||||
set3=(x=aq[:, 5], y=aq[:, 6]),
|
||||
set4=(x=aq[:, 7], y=aq[:, 8]))
|
||||
|
||||
# Code for section 3.3.2
|
||||
# Code for section 4.3.2
|
||||
|
||||
using Statistics
|
||||
map(s -> mean(s.x), data)
|
||||
@ -194,7 +194,7 @@ model = lm(@formula(y ~ x), data.set1)
|
||||
|
||||
r2(model)
|
||||
|
||||
# Code for section 3.3.3
|
||||
# Code for section 4.3.3
|
||||
|
||||
model.mm
|
||||
|
||||
@ -208,152 +208,3 @@ empty_field!(nt, i) = empty!(nt[i])
|
||||
nt = (dict = Dict("a" => 1, "b" => 2), int=10)
|
||||
empty_field!(nt, 1)
|
||||
nt
|
||||
|
||||
# Code for section 3.4.1
|
||||
|
||||
x = [1 2 3]
|
||||
y = [1, 2, 3]
|
||||
x * y
|
||||
|
||||
a = [1, 2, 3]
|
||||
b = [4, 5, 6]
|
||||
a * b
|
||||
|
||||
a .* b
|
||||
|
||||
map(*, a, b)
|
||||
[a[i] * b[i] for i in eachindex(a, b)]
|
||||
|
||||
eachindex(a, b)
|
||||
|
||||
eachindex([1, 2, 3], [4, 5])
|
||||
|
||||
map(*, [1, 2, 3], [4, 5])
|
||||
|
||||
[1, 2, 3] .* [4, 5]
|
||||
|
||||
# Code for section 3.4.2
|
||||
|
||||
[1, 2, 3] .* [4]
|
||||
|
||||
[1, 2, 3] .^ 2
|
||||
|
||||
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] .* [1 2 3 4 5 6 7 8 9 10]
|
||||
|
||||
["x", "y", "z"] .=> [sum minimum maximum]
|
||||
|
||||
abs.([1, -2, 3, -4])
|
||||
|
||||
abs([1, 2, 3])
|
||||
|
||||
string(1, 2, 3)
|
||||
|
||||
string.("x", 1:10)
|
||||
|
||||
f(i::Int) = string("got integer ", i)
|
||||
f(s::String) = string("got string ", s)
|
||||
f.([1, "1"])
|
||||
|
||||
# Code for section 3.4.3
|
||||
|
||||
in(1, [1, 2, 3])
|
||||
in(4, [1, 2, 3])
|
||||
|
||||
in([1, 3, 5, 7, 9], [1, 2, 3, 4])
|
||||
|
||||
in.([1, 3, 5, 7, 9], [1, 2, 3, 4])
|
||||
|
||||
in.([1, 3, 5, 7, 9], Ref([1, 2, 3, 4]))
|
||||
|
||||
# Code for section 3.4.4
|
||||
|
||||
aq = [10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
|
||||
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
|
||||
13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71
|
||||
9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84
|
||||
11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47
|
||||
14.0 9.96 14.0 8.1 14.0 8.84 8.0 7.04
|
||||
6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25
|
||||
4.0 4.26 4.0 3.1 4.0 5.39 19.0 12.50
|
||||
12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56
|
||||
7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91
|
||||
5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89]
|
||||
using Statistics
|
||||
|
||||
mean.(eachcol(aq))
|
||||
|
||||
mean(eachcol(aq))
|
||||
|
||||
function R²(x, y)
|
||||
X = [ones(11) x]
|
||||
model = X \ y
|
||||
prediction = X * model
|
||||
error = y - prediction
|
||||
SS_res = sum(v -> v ^ 2, error)
|
||||
mean_y = mean(y)
|
||||
SS_tot = sum(v -> (v - mean_y) ^ 2, y)
|
||||
return 1 - SS_res / SS_tot
|
||||
end
|
||||
|
||||
function R²(x, y)
|
||||
X = [ones(11) x]
|
||||
model = X \ y
|
||||
prediction = X * model
|
||||
SS_res = sum((y .- prediction) .^ 2)
|
||||
SS_tot = sum((y .- mean(y)) .^ 2)
|
||||
return 1 - SS_res / SS_tot
|
||||
end
|
||||
|
||||
# Code for section 3.5
|
||||
|
||||
[]
|
||||
Dict()
|
||||
|
||||
Float64[1, 2, 3]
|
||||
|
||||
Dict{UInt8, Float64}(0 => 0, 1 => 1)
|
||||
|
||||
UInt32(200)
|
||||
|
||||
Real[1, 1.0, 0x3]
|
||||
|
||||
v1 = Any[1, 2, 3]
|
||||
eltype(v1)
|
||||
v2 = Float64[1, 2, 3]
|
||||
eltype(v2)
|
||||
v3 = [1, 2, 3]
|
||||
eltype(v2)
|
||||
d1 = Dict()
|
||||
eltype(d1)
|
||||
d2 = Dict(1 => 2, 3 => 4)
|
||||
eltype(d2)
|
||||
|
||||
p = 1 => 2
|
||||
typeof(p)
|
||||
|
||||
# Code for section 3.5.1
|
||||
|
||||
[1, 2, 3] isa AbstractVector{Int}
|
||||
[1, 2, 3] isa AbstractVector{Real}
|
||||
|
||||
AbstractVector{<:Real}
|
||||
|
||||
# Code for section 3.5.2
|
||||
|
||||
using Statistics
|
||||
function ourcov(x::AbstractVector{<:Real},
|
||||
y::AbstractVector{<:Real})
|
||||
len = length(x)
|
||||
@assert len == length(y) > 0
|
||||
return sum((x .- mean(x)) .* (y .- mean(y))) / (len - 1)
|
||||
end
|
||||
|
||||
ourcov(1:4, [1.0, 3.0, 2.0, 4.0])
|
||||
cov(1:4, [1.0, 3.0, 2.0, 4.0])
|
||||
|
||||
ourcov(1:4, Any[1.0, 3.0, 2.0, 4.0])
|
||||
|
||||
x = Any[1, 2, 3]
|
||||
identity.(x)
|
||||
y = Any[1, 2.0]
|
||||
identity.(y)
|
||||
161
ch05.jl
Normal file
161
ch05.jl
Normal file
@ -0,0 +1,161 @@
|
||||
# Bogumił Kamiński, 2021
|
||||
|
||||
# Codes for chapter 5
|
||||
|
||||
# Code for section 5.1.1
|
||||
|
||||
x = [1 2 3]
|
||||
y = [1, 2, 3]
|
||||
x * y
|
||||
|
||||
a = [1, 2, 3]
|
||||
b = [4, 5, 6]
|
||||
a * b
|
||||
|
||||
a .* b
|
||||
|
||||
map(*, a, b)
|
||||
[a[i] * b[i] for i in eachindex(a, b)]
|
||||
|
||||
eachindex(a, b)
|
||||
|
||||
eachindex([1, 2, 3], [4, 5])
|
||||
|
||||
map(*, [1, 2, 3], [4, 5])
|
||||
|
||||
[1, 2, 3] .* [4, 5]
|
||||
|
||||
# Code for section 5.1.2
|
||||
|
||||
[1, 2, 3] .^ [2]
|
||||
|
||||
[1, 2, 3] .^ 2
|
||||
|
||||
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] .* [1 2 3 4 5 6 7 8 9 10]
|
||||
|
||||
["x", "y", "z"] .=> [sum minimum maximum]
|
||||
|
||||
abs.([1, -2, 3, -4])
|
||||
|
||||
abs([1, 2, 3])
|
||||
|
||||
string(1, 2, 3)
|
||||
|
||||
string.("x", 1:10)
|
||||
|
||||
f(i::Int) = string("got integer ", i)
|
||||
f(s::String) = string("got string ", s)
|
||||
f.([1, "1"])
|
||||
|
||||
# Code for section 5.1.3
|
||||
|
||||
in(1, [1, 2, 3])
|
||||
in(4, [1, 2, 3])
|
||||
|
||||
1 in [1, 2, 3]
|
||||
4 in [1, 2, 3]
|
||||
|
||||
in([1, 3, 5, 7, 9], [1, 2, 3, 4])
|
||||
|
||||
in([1, 3, 5, 7, 9], [1, 2, 3, 4, ([1, 3, 5, 7, 9]])
|
||||
|
||||
in.([1, 3, 5, 7, 9], [1, 2, 3, 4])
|
||||
|
||||
in.([1, 3, 5, 7, 9], Ref([1, 2, 3, 4]))
|
||||
|
||||
isodd.([1, 2, 3, 4, 5, 6, 7, 8, 9, 10] .+ [1 2 3 4 5 6 7 8 9 10])
|
||||
|
||||
Matrix{Any}(isodd.([1, 2, 3, 4, 5, 6, 7, 8, 9, 10] .* [1 2 3 4 5 6 7 8 9 10]))
|
||||
|
||||
# Code for section 5.1.4
|
||||
|
||||
aq = [10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
|
||||
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
|
||||
13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71
|
||||
9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84
|
||||
11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47
|
||||
14.0 9.96 14.0 8.1 14.0 8.84 8.0 7.04
|
||||
6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25
|
||||
4.0 4.26 4.0 3.1 4.0 5.39 19.0 12.50
|
||||
12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56
|
||||
7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91
|
||||
5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89]
|
||||
using Statistics
|
||||
|
||||
mean.(eachcol(aq))
|
||||
|
||||
mean(eachcol(aq))
|
||||
|
||||
function R²(x, y)
|
||||
X = [ones(11) x]
|
||||
model = X \ y
|
||||
prediction = X * model
|
||||
error = y - prediction
|
||||
SS_res = sum(v -> v ^ 2, error)
|
||||
mean_y = mean(y)
|
||||
SS_tot = sum(v -> (v - mean_y) ^ 2, y)
|
||||
return 1 - SS_res / SS_tot
|
||||
end
|
||||
|
||||
function R²(x, y)
|
||||
X = [ones(11) x]
|
||||
model = X \ y
|
||||
prediction = X * model
|
||||
SS_res = sum((y .- prediction) .^ 2)
|
||||
SS_tot = sum((y .- mean(y)) .^ 2)
|
||||
return 1 - SS_res / SS_tot
|
||||
end
|
||||
|
||||
# Code for section 5.2
|
||||
|
||||
[]
|
||||
Dict()
|
||||
|
||||
Float64[1, 2, 3]
|
||||
|
||||
Dict{UInt8, Float64}(0 => 0, 1 => 1)
|
||||
|
||||
UInt32(200)
|
||||
|
||||
Real[1, 1.0, 0x3]
|
||||
|
||||
v1 = Any[1, 2, 3]
|
||||
eltype(v1)
|
||||
v2 = Float64[1, 2, 3]
|
||||
eltype(v2)
|
||||
v3 = [1, 2, 3]
|
||||
eltype(v3)
|
||||
d1 = Dict()
|
||||
eltype(d1)
|
||||
d2 = Dict(1 => 2, 3 => 4)
|
||||
eltype(d2)
|
||||
|
||||
p = 1 => 2
|
||||
typeof(p)
|
||||
|
||||
# Code for section 5.2.1
|
||||
|
||||
[1, 2, 3] isa AbstractVector{Int}
|
||||
[1, 2, 3] isa AbstractVector{Real}
|
||||
|
||||
AbstractVector{<:Real} == AbstractVector{T} where T<:Real
|
||||
|
||||
# Code for section 5.2.2
|
||||
|
||||
using Statistics
|
||||
function ourcov(x::AbstractVector{<:Real},
|
||||
y::AbstractVector{<:Real})
|
||||
len = length(x)
|
||||
@assert len == length(y) > 0
|
||||
return sum((x .- mean(x)) .* (y .- mean(y))) / (len - 1)
|
||||
end
|
||||
|
||||
ourcov(1:4, [1.0, 3.0, 2.0, 4.0])
|
||||
cov(1:4, [1.0, 3.0, 2.0, 4.0])
|
||||
|
||||
ourcov(1:4, Any[1.0, 3.0, 2.0, 4.0])
|
||||
|
||||
x = Any[1, 2, 3]
|
||||
identity.(x)
|
||||
y = Any[1, 2.0]
|
||||
identity.(y)
|
||||
Loading…
Reference in New Issue
Block a user