Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix type instability regression #125

Merged
merged 1 commit into from
Dec 14, 2021
Merged

Fix type instability regression #125

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion Project.toml
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "PlotUtils"
uuid = "995b91a9-d308-5afd-9ec6-746e21dbc043"
version = "1.1.0"
version = "1.1.1"

[deps]
ColorSchemes = "35d6a980-a343-548e-a6ea-1d62b119f2f4"
Expand Down
60 changes: 33 additions & 27 deletions src/ticks.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,22 +6,22 @@ const _logScaleBases = Dict(:ln => ℯ, :log2 => 2.0, :log10 => 10.0)
# Find the smallest order of magnitude that is larger than xspan This is a
# little opaque because I want to avoid assuming the log function is defined
# over typeof(xspan)
function bounding_order_of_magnitude(xspan::T, base) where T
function bounding_order_of_magnitude(xspan::T, base::T) where T
a = 1
step = 1
while xspan < T(base^a)
while xspan < base^a
a -= step
end

b = 1
step = 1
while xspan > T(base^b)
while xspan > base^b
b += step
end

while a + 1 < b
c = div(a + b, 2)
if xspan < T(base^c)
if xspan < base^c
b = c
else
a = c
Expand All @@ -31,8 +31,8 @@ function bounding_order_of_magnitude(xspan::T, base) where T
return b
end

const float_digit_range = floor(Int,log10(floatmin())):ceil(Int,log10(floatmax()))
postdecimal_digits(x) = first(i for i in float_digit_range if x==floor(x; digits=i))
float_digit_range(T) = floor(Int, log10(floatmin(T))):ceil(Int, log10(floatmax(T)))
postdecimal_digits(x) = first(i for i in float_digit_range(typeof(x)) if x == floor(x; digits=i))

fallback_ticks(x_min::T, x_max::T, k_min, k_max) where T = collect(T, range(x_min, x_max; length=k_min)), x_min, x_max

Expand Down Expand Up @@ -129,25 +129,25 @@ and the variables here are:
* `v`: 1 if label range includes 0, 0 otherwise.
"""
function optimize_ticks(x_min::T, x_max::T; extend_ticks::Bool=false,
Q=[(1., 1.), (5., .9), (2., .7), (2.5, .5), (3., .2)],
k_min::Int=2, k_max::Int=10, k_ideal::Int=5,
granularity_weight::Float64=1/4, simplicity_weight::Float64=1/6,
coverage_weight::Float64=1/3, niceness_weight::Float64=1/4,
strict_span=true, span_buffer=nothing, scale=nothing) where T
Q=[(1., 1.), (5., .9), (2., .7), (2.5, .5), (3., .2)],
k_min::Int=2, k_max::Int=10, k_ideal::Int=5,
granularity_weight::Float64=1/4, simplicity_weight::Float64=1/6,
coverage_weight::Float64=1/3, niceness_weight::Float64=1/4,
strict_span=true, span_buffer=nothing, scale=nothing) where T

Qv = [(Float64(q[1]), Float64(q[2])) for q in Q]
optimize_ticks_typed(x_min, x_max, extend_ticks, Qv, k_min, k_max, k_ideal,
granularity_weight, simplicity_weight,
coverage_weight, niceness_weight, strict_span, span_buffer, scale)
F = float(T)
Qv = [(F(q[1]), F(q[2])) for q in Q]
optimize_ticks_typed(F(x_min), F(x_max), extend_ticks, Qv, k_min, k_max, k_ideal,
F(granularity_weight), F(simplicity_weight),
F(coverage_weight), F(niceness_weight), strict_span, span_buffer, scale)
end

function optimize_ticks_typed(x_min::T, x_max::T, extend_ticks,
Q::Vector{Tuple{Float64,Float64}}, k_min, k_max, k_ideal,
granularity_weight::Float64, simplicity_weight::Float64,
coverage_weight::Float64, niceness_weight::Float64,
strict_span, span_buffer, scale) where T

F = float(T)
function optimize_ticks_typed(x_min::F, x_max::F, extend_ticks,
Q::AbstractVector, k_min, k_max, k_ideal,
granularity_weight::F, simplicity_weight::F,
coverage_weight::F, niceness_weight::F,
strict_span, span_buffer, scale) where F

if (xspan = x_max - x_min) < eps(F)
return fallback_ticks(x_min, x_max, k_min, k_max)
end
Expand Down Expand Up @@ -193,8 +193,8 @@ function optimize_ticks_typed(x_min::T, x_max::T, extend_ticks,
isfinite(r) || continue
r = ceil(Int, r)

# try to favor integer exponents for log scales
if is_log_scale && !isinteger(tickspan)
# try to favor integer exponents for log scales
nice_scale = false
qscore = 0
else
Expand Down Expand Up @@ -243,18 +243,24 @@ function optimize_ticks_typed(x_min::T, x_max::T, extend_ticks,
S = view(S, 1:counter)
end

len_S = length(S)

# evaluate quality of ticks
has_zero = r <= 0 && abs(r) < k

# simplicity
s = has_zero && nice_scale ? 1 : 0

# granularity
g = 0 < length(S) < 2k_ideal ? 1 - abs(length(S) - k_ideal) / k_ideal : 0
g = 0 < len_S < 2k_ideal ? 1 - abs(len_S - k_ideal) / k_ideal : F(0)

# coverage
effective_span = (length(S) - 1) * tickspan
c = abs(effective_span) > eps(F) ? 1.5xspan / effective_span : 0
c = if len_S > 1
effective_span = (len_S - 1) * tickspan
1.5xspan / effective_span
else
F(0)
end

score = granularity_weight * g +
simplicity_weight * s +
Expand All @@ -269,7 +275,7 @@ function optimize_ticks_typed(x_min::T, x_max::T, extend_ticks,
score -= 1000
end

if score > high_score && (k_min <= length(S) <= k_max)
if score > high_score && (k_min <= len_S <= k_max)
if strict_span
# make S a copy because it is a view and
# could otherwise be mutated in the next runs
Expand Down