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ticks.jl
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ticks.jl
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# 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{DT}(xspan::DT)
one_dt = convert(DT, one(DT))
a = 1
step = 1
while xspan < 10.0^a * one_dt
a -= step
end
b = 1
step = 1
while xspan > 10.0^b * one_dt
b += step
end
while a + 1 < b
c = div(a + b, 2)
if xspan < 10.0^c * one_dt
b = c
else
a = c
end
end
return b
end
# Empty catchall
optimize_ticks() = Any[]
# Find some reasonable values for tick marks.
#
# This is basically Wilkinson's ad-hoc scoring method that tries to balance
# tight fit around the data, optimal number of ticks, and simple numbers.
#
# Args:
# x_min: minimum value occuring in the data.
# x_max: maximum value occuring in the data.
# Q: tick intervals and scores
# k_min: minimum number of ticks
# k_max: maximum number of ticks
# k_ideal: ideal number of ticks
# strict_span: true if no ticks should be outside [x_min, x_max].
#
# Returns:
# A Float64 vector containing tick marks.
#
function optimize_ticks{T}(x_min::T, x_max::T; extend_ticks::Bool=false,
Q=[(1.0,1.0), (5.0, 0.9), (2.0, 0.7), (2.5, 0.5), (3.0, 0.2)],
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=false)
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)
end
function optimize_ticks_typed{T}(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)
one_t = convert(T, one(T))
if x_max - x_min < eps()*one_t
R = typeof(1.0 * one_t)
return R[x_min], x_min - one_t, x_min + one_t
end
const n = length(Q)
# generalizing "order of magnitude"
xspan = x_max - x_min
z = bounding_order_of_magnitude(xspan)
high_score = -Inf
z_best = 0.0
k_best = 0
r_best = 0.0
q_best = 0.0
while k_max * 10.0^(z+1) * one_t > xspan
for k in k_min:k_max
for (q, qscore) in Q
span = (k - 1) * q * 10.0^z * one_t
if span < xspan
continue
end
stp = q*10.0^z
if stp < eps()
continue
end
r = ceil((x_max - span) / (stp * one_t))
while r*stp * one_t <= x_min
has_zero = r <= 0 && abs(r) < k
# simplicity
s = has_zero ? 1.0 : 0.0
# granularity
g = 0 < k < 2k_ideal ? 1 - abs(k - k_ideal) / k_ideal : 0.0
# coverage
c = 1.5 * xspan/span
score = granularity_weight * g +
simplicity_weight * s +
coverage_weight * c +
niceness_weight * qscore
# strict limits on coverage
if strict_span && span > xspan
score -= 10000
elseif !strict_span && (span >= 2.0*xspan || span < xspan)
score -= 1000
end
if score > high_score
(q_best, r_best, k_best, z_best) = (q, r, k, z)
high_score = score
end
# Fix for #932
r += max(1, eps(r))
end
end
end
z -= 1
end
if isinf(high_score)
R = typeof(1.0 * one_t)
return R[x_min], x_min - one_t, x_min + one_t
end
span = q_best * 10.0^z_best * one_t
if extend_ticks
S = Array{typeof(1.0 * one_t)}(Int(3 * k_best))
for i in 0:(3*k_best - 1)
S[i+1] = (r_best + i - k_best) * span
end
viewmin, viewmax = S[k_best + 1], S[2 * k_best]
else
S = Array{typeof(1.0 * one_t)}(k_best)
for i in 0:(k_best - 1)
S[i+1] = (r_best + i) * span
end
viewmin, viewmax = S[1], S[end]
end
if strict_span
viewmin = max(viewmin, x_min)
viewmax = min(viewmax, x_max)
end
return S, viewmin, viewmax
end
function optimize_ticks(x_min::Date, x_max::Date; extend_ticks::Bool=false,
k_min=nothing, k_max=nothing, scale=:auto,
granularity_weight=nothing, simplicity_weight=nothing,
coverage_weight=nothing, niceness_weight=nothing,
strict_span=false)
return optimize_ticks(convert(DateTime, x_min), convert(DateTime, x_max),
extend_ticks=extend_ticks, scale=scale)
end
function optimize_ticks(x_min::DateTime, x_max::DateTime; extend_ticks::Bool=false,
k_min=nothing, k_max=nothing, scale=:auto,
granularity_weight=nothing, simplicity_weight=nothing,
coverage_weight=nothing, niceness_weight=nothing,
strict_span=false)
if x_min == x_max
x_max += Second(1)
end
if year(x_max) - year(x_min) <= 1 && scale != :year
if year(x_max) == year(x_min) && month(x_max) - month(x_min) <= 1 && scale != :month
ticks = DateTime[]
const scales = [
Day(1), Hour(1), Minute(1), Second(1), Millisecond(100),
Millisecond(10), Millisecond(1)
]
# ticks on week boundries
if x_min + Day(7) < x_max || scale == :week
push!(ticks, x_min)
while true
next_month = Date(year(ticks[end]), month(ticks[end])) + Month(1)
while ticks[end] + Week(1) < next_month - Day(2)
push!(ticks, ticks[end] + Week(1))
end
push!(ticks, next_month)
if next_month >= x_max
break
end
end
else
scale = nothing
if scale != :auto
# TODO: manually setting scale with :day, :minute, etc
end
if scale === nothing
for proposed_scale in [Day(1), Hour(1), Minute(1),
Second(1), Millisecond(100),
Millisecond(10), Millisecond(1)]
if x_min + proposed_scale < x_max
scale = proposed_scale
break
end
end
end
if scale === nothing
scale = Millisecond(1)
end
# round x_min down
if scale === Day(1)
first_tick = DateTime(year(x_min), month(x_min), day(x_min))
elseif scale === Hour(1)
first_tick = DateTime(year(x_min), month(x_min), day(x_min),
hour(x_min))
elseif scale === Minute(1)
first_tick = DateTime(year(x_min), month(x_min), day(x_min),
hour(x_min), minute(x_min))
elseif scale === Second(1)
first_tick = DateTime(year(x_min), month(x_min), day(x_min),
hour(x_min), minute(x_min), second(x_min))
elseif scale === Millisecond(100)
first_tick = DateTime(year(x_min), month(x_min), day(x_min),
hour(x_min), minute(x_min),
second(x_min), millisecond(x_min) % 100)
elseif scale === Millisecond(10)
first_tick = DateTime(year(x_min), month(x_min), day(x_min),
hour(x_min), minute(x_min),
second(x_min), millisecond(x_min) % 10)
else
first_tick = x_min
end
push!(ticks, first_tick)
while ticks[end] < x_max
push!(ticks, ticks[end] + scale)
end
end
viewmin, viewmax = ticks[1], ticks[end]
return ticks, viewmin, viewmax
else
ticks = DateTime[]
push!(ticks, Date(year(x_min), month(x_min)))
while ticks[end] < x_max
push!(ticks, ticks[end] + Month(1))
end
viewmin, viewmax = ticks[1], ticks[end]
return ticks, x_min, x_max
end
else
ticks, viewmin, viewmax =
optimize_ticks(year(x_min), year(x_max + Year(1) - Day(1)), extend_ticks=extend_ticks)
return DateTime[DateTime(round(y)) for y in ticks],
DateTime(round(viewmin)), DateTime(round(viewmax))
end
end
# Generate ticks suitable for multiple scales.
function multilevel_ticks{T}(viewmin::T, viewmax::T;
scales=[0.5, 5.0, 10.0])
ticks = Dict()
for scale in scales
ticks[scale] = optimize_ticks(viewmin, viewmax,
k_min=max(1, (round(Int, 2*scale))),
k_max=max(3, (round(Int, 10*scale))),
k_ideal=max(2, (round(Int, 15*scale))))[1]
end
return ticks
end
function multilevel_ticks(viewmin::Date, viewmax::Date;
scales=[:year, :month, :day])
return multilevel_ticks(convert(DateTime, viewmin),
convert(DateTime, viewmax),
scales=scales)
end
function multilevel_ticks(viewmin::DateTime, viewmax::DateTime;
scales=[:year, :month, :day])
# TODO: This needs to be improved for DateTime
span = convert(Float64, Dates.toms(viewmax - viewmin))
ticks = Dict()
for scale in scales
if scale == :year
s = span / Dates.toms(Day(360))
elseif scale == :month
s = span / Dates.toms(Day(90))
else
s = span / Dates.toms(Day(1))
end
ticks[s/20] = optimize_ticks(viewmin, viewmax, scale=scale)[1]
end
return ticks
end