using PGFPlots

x = [1,2,3]
y = [2,4,1]
plot(x, y)

Axis(Plots.Linear(x, y))

pushPGFPlotsOptions("scale=1.5")
a = Axis(Plots.Linear(x, y, legendentry="My Plot"), xlabel="X", ylabel="Y", title="My Title")

a.ylabelStyle = "rotate = -90"
a.legendStyle = "{at={(1.05,1.0)},anchor=north west}"
a

popPGFPlotsOptions();

resetPGFPlotsOptions();

a = Axis(Plots.Linear(x, y), width="3cm", height="3cm")

Axis(Plots.Linear(x, y), xlabel=L"$X$", ylabel=L"$Y$", title=L"$\int_0^\infty e^{\pi x}dx$")

Axis([
    Plots.Linear(sin, (0,10), legendentry=L"$\sin(x)$"),
    Plots.Linear(x->sqrt(2*x), (0,10), legendentry=L"$\sqrt{2x}$")
])

Axis([
    Plots.Linear(sin, (0,10), legendentry=L"$\sin(x)$"),
    Plots.Linear(x->sqrt(2*x), (0,10), legendentry=L"$\sqrt{2x}$")
    ], legendPos="north west")

Plots.Linear(1:10, sin(1:10), style="ycomb")

Plots.Linear(abs(sin(1:10)), 1:10, style="xcomb")

Plots.Linear(1:10, sin(1:10), style="smooth")

Plots.Linear(1:10, sin(1:10), style="const plot")

Plots.Linear(1:10, sin(1:10), style="ybar")

Plots.Linear(1:10, sin(1:10), style="ybar,fill=green", mark="none")

p = Plots.Linear(0.01:0.01:1, 10.^(0.01:0.01:1), mark="none")
Axis(p, ymode="log")

p = Plots.Linear(0:10, (0:10).^2, style="red, fill=blue, fill opacity=0.3", mark="none")

p = Plots.Linear(0:10, 2*(0:10))
a = Axis(p, axisEqual=true, xmin=0, xmax=10)   # note xmin and xmax are disregarded...

p = Plots.Linear(0:10, 2*(0:10))
a = Axis(p, axisEqualImage=true)

Plots.Linear(0:10, 2*(0:10), markSize=10)

Plots.Linear(0:10, 2*(0:10), onlyMarks=true)

x = [1,2,3]
y = [2,4,1]
plot(x, y, errorBars = ErrorBars(y=[1, 0.3, 0.5]))

plot(x, y, errorBars = ErrorBars(yplus=[1, 0.3, 0.5], yminus=[0.5, 0.1, 0.1]))

plot(x, y, errorBars = ErrorBars(y=[1, 0.3, 0.5], x=[0.1, 0.1, 0.05]))

plot(x, y, errorBars = ErrorBars(y=[1, 0.3, 0.5], style="red,very thick"))

plot(x, y, errorBars = ErrorBars(y=[1, 0.3, 0.5], mark="diamond"))

plot(x, y, style="red", errorBars = ErrorBars(y=[1, 0.3, 0.5], style="black,very thick", mark="diamond"))

x = 1:10
y = 2x
Plots.Scatter(x, y)

z = 3x
Plots.Scatter(x, y, z)

p = Plots.Scatter(x, y, z)
a = Axis(p, colorbar=true)

z = ["a", "a", "a", "b", "b", "b", "b", "c", "c", "c"]
sc = "{a={mark=square,blue},b={mark=triangle,red},c={mark=o,black}}"
Plots.Scatter(x, y, z, scatterClasses=sc)

Plots.Scatter(x, y, z, scatterClasses=sc, legendentry=["A", "B", "C"])

Axis(Plots.Scatter(x, y, z, scatterClasses=sc, legendentry=["A", "B", "C"]), style="legend columns=-1", legendPos="north west")

d = randn(100)
Axis(Plots.Histogram(d, bins=10), ymin=0)

Axis(Plots.Histogram(d, bins=20, cumulative=true, density=true), ymin=0)

Axis(Plots.Histogram(d, bins=10, style="red,fill=red!10"), ymin=0, ylabel="Counts")

Axis(Plots.Histogram(d, discretization=:auto), ymin=0)

discretizations = 
           [:default, # use PGFPlots for small data sizes and :auto for large
            :pgfplots, # use the PGFPlots histogram function (uses nbins, which defaults to 10)
            :specified, # use Discretizers.jl but with the specified number of bins (which defaults to 10)
            :auto, # max between :fd and :sturges. Good all-round performance
            :fd, # Freedman Diaconis Estimator, robust
            :sturges, # R's default method, only good for near-Gaussian data
            :sqrt, # used by Excel and others for its simplicity and speed
            :doane, # improves Sturges’ for non-normal datasets.
            :scott, # less robust estimator that that takes into account data variability and data size.
            ]

srand(0)
data = [randn(500).*1.8 .+ -5;
        randn(2000).*0.8 .+ -4;
        randn(500).*0.3 .+ -1;
        randn(1000).*0.8 .+ 2;
        randn(500).*1.5 .+ 4;
       ]
data = filter!(x->-15.0 <= x <= 15.0, data)

g = GroupPlot(3, 3, groupStyle = "horizontal sep = 1.75cm, vertical sep = 1.5cm")
for discretization in discretizations
    push!(g, Axis(Plots.Histogram(data, discretization=discretization), ymin=0, title=string(discretization)))
end
g

f = (x,y)->x*exp(-x^2-y^2)
Plots.Image(f, (-2,2), (-2,2))

Plots.Image(f, (-2,2), (-2,2), zmin=-1, zmax=1)

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Gray(invert = true))

Plots.Image(f, (-2,2), (-2,2), colorbar = false)

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Distinguishable(3))

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Distinguishable(4))

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Distinguishable(4, invert=true))

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Named("Blues"))

using Colors
cm = colormap("RdBu")

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.RGBArray(cm))

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Named("Jet"))

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Brew("Set1", 3))

Plots.Image(f, (-2,2), (-2,2), colormap = ColorMaps.Brew("Set1", 3, invert=true))

p = Plots.Patch2D([0 1 2     1 2 3     2 3 4;  # x
                   0 1 0     1 0 1     0 1 0]) # y

p = Plots.Patch2D([0   1 2     1 2 3     2 3 4;    # x
                   0   1 0     1 0 1     0 1 0;    # y
                   0.2 0 1     0 1 0     1 0 0.5]) # color

p = Plots.Patch2D([0   1 2     1 2 3     2 3 4;    # x
                   0   1 0     1 0 1     0 1 0;    # y
                   0.2 0 1     0 1 0     1 0 0.5], # color
                  shader = "interp")

p = Plots.Patch2D([0   1 2     1  2 3     2   3 4;    # x
                   0   1 0     1  0 1     0   1 0;    # y
                   0.2 0 1     0 -1 0     0.5 1 0.5], # color
                  shader = "interp")

p = Plots.Patch2D([0   1 1 0     1  2 2 1    1   2 2   1;  # x
                   0   0 1 1     0  0 1 1    1   1 2   2;  # y
                   0.2 0 1 1     0 -1 0 1    0.5 1 0.5 0], # color
                  shader = "interp", patch_type="rectangle")

x = randn(10000)*2 + 1
y = randn(10000) - 2
Plots.Histogram2(x, y)

Plots.Histogram2(x, y, xmin=-3, xmax=3, ymin=-3, ymax=3, zmin=-1, colormap=ColorMaps.Named("Jet"))

Plots.Histogram2(x, y, xmin=-3, xmax=3, ymin=-3, ymax=3, zmin=5, zmax=15, colormap=ColorMaps.Named("Jet"))

Axis(Plots.Histogram2(x, y, density=true, xmin=-3, xmax=3, ymin=-3, ymax=3), axisEqualImage=true)

Plots.Histogram2(x, y, density=true)

x = randn(10000)+1.0
y = randn(10000)
edges_x = [-3.0,-1.0,0.0,0.5,0.75,1.0,1.25,1.5,2.0,3.0]
edges_y = linspace(-3.0,3.0,11)
p = Plots.Histogram2(x, y, edges_x, edges_y, density=true, style="colormap/blackwhite")
ax = Axis(p, enlargelimits=0)

Plots.Contour(f, (-2,2), (-2,2))

Plots.Contour(f, (-2,2), (-2,2), levels=-0.4:0.1:4)

Plots.Contour(f, (-2,2), (-2,2), number=20)

Plots.Contour(f, (-2,2), (-2,2), style="very thick")

x = linspace(-2,2)
y = linspace(-2,2)
A = Float64[f(xi, yi) for xi in x, yi in y]
Plots.Contour(A, x, y)

Plots.Contour(randn(11,11), 0:10, 0:10)

h(x,y) = [exp(-x^2-y^2)*(1-2*x^2), exp(-x^2-y^2)*(-2*x*y)]
Plots.Quiver(h,(-2,2),(-2,2))

h2(x,y) = [exp(-x^2-y^2)*(1-2*x^2), exp(-x^2-y^2)*(-2*x*y)]
Plots.Quiver(h2,(-2,2),(-2,2), style="-stealth'")

Plots.Quiver(h,(-2,2),(-2,2), normalize=false)

# generate 1000 samples
d = randn(1000)
# try out histograms with a variety of different number of bins
bins = [3 10 50 1000]
g = GroupPlot(2,2) # create a 2 x 2 group plot
for i = 1:length(bins)
    push!(g, Axis(Plots.Histogram(d, bins=bins[i]), ymin=0))
end
g

g = GroupPlot(2, 2, groupStyle = "horizontal sep = 3cm") # create a 2 x 2 group plot
for i = 1:length(bins)
    push!(g, Axis(Plots.Histogram(d, bins=bins[i]), ymin=0))
end
g

#Create the first axis and add to it two lines
a1 = PGFPlots.Axis(style="width=10cm, height=10cm, grid=both");
push!(a1, PGFPlots.Linear([1,2],[10, 10], style="blue"))
push!(a1, PGFPlots.Linear([1,2],[10, 3],  style="red"))

#Create another axis with smaller width.
#xshift and yshift are used to position the axis.
a2 = PGFPlots.Axis(style="width=4cm, xshift=1cm, yshift=1cm", title="xy reflection");
push!(a2, PGFPlots.Linear([10, 10], [1,2], style="no marks, blue, thick"))
push!(a2, PGFPlots.Linear([10, 3] , [1,2], style="no marks, red, thick"));

#Group the two axes together as a list
[a1, a2]

Axis([
    Plots.Image(f, (-2,2), (-2,2)),
    Plots.Node(L"\sqrt{2}",1,0)        
])

Axis([
    Plots.Image(f, (-2,2), (-2,2)),
    Plots.Node(L"\sqrt{2}",-1,0,style="yellow"),        
    Plots.Node("Hi there!",1,0,style="right")        
])

Axis([
    Plots.Image(f, (-2,2), (-2,2)),
    Plots.Node(L"\sqrt{2}",0.9,0.9,axis="axis description cs")
])

p1 = Plots.Circle(5,5,5)
p2 = Plots.Ellipse(5,5,3,5)
a = Axis([p1,p2], xmin=0,ymin=0,xmax=10,ymax=10)

a = Axis([p1,p2], xmin=0,ymin=0,xmax=10,ymax=10, hideAxis=true)

t = rad2deg(linspace(0,5pi,60))
x = sind(t)
y = cosd(t)
z = 2t/(5pi)
p = Plots.Linear3(x, y, z, mark="none")
Axis(p, xlabel="x", ylabel="y", zlabel="z")

Axis(p, view="{60}{30}", xlabel="x", ylabel="y", zlabel="z")

using TikzPictures
TikzPictures.tikzDeleteIntermediate(false)
angles = [0,90,180,270]
radii = ones(4)
p = Plots.Linear(angles, radii)
pa = PolarAxis(p)

define_color("myrgbcolor1", [1,0.2,0.3])
Plots.Linear(x, y, style="myrgbcolor1")

define_color("mycmykcolor1", [1,0.2,0.3,0])
Plots.Linear(x, y, style="mycmykcolor1")

define_color("myRGBcolor", [82,227,246])
Plots.Linear(x, y, style="myRGBcolor")

define_color("mylightgray", 0.9)
Plots.Linear(x, y, style="mylightgray")

define_color("myhtmlcolor", 0xff7f00)
Plots.Linear(x, y, style="myhtmlcolor")

define_color("mycolor", HSV(300, 0.2, 0.9))
Plots.Linear(x, y, style="mycolor, very thick")

using DataFrames

df = DataFrame(x=[1,2,3], y=[2,4,1], z=[0.0,0.5,1.0])
df_big = DataFrame(x=randn(1000), y=randn(1000))
df_quiver = DataFrame(x=[0,0,1,1], y=[0,1,0,1], u=[0.25,0.25,-0.25,-0.25], v=[0.25,-0.25,0.25,-0.25])

g = GroupPlot(3, 3, groupStyle = "horizontal sep = 1.75cm, vertical sep = 1.5cm")
push!(g, Axis(Plots.Linear(df), title="Linear"))
push!(g, Axis(Plots.Linear(df, x=:y, y=:z, style="red", mark="none"), title="Linear with Options"))
push!(g, Axis(Plots.Linear3(df), title="Linear3"))
push!(g, Axis(Plots.Scatter(df), title="Scatter"))
push!(g, Axis(Plots.Histogram(df_big), title="Histogram"))
push!(g, Axis(Plots.Quiver(df_quiver), title="Quiver"))
push!(g, Axis(Plots.Histogram2(df_big), title="Histogram2 - Image"))
push!(g, Axis(Plots.Histogram2(df_big, Float64[-3,-1,1,3], Float64[-3,-2,-1,0,1,2,3], style="colormap/blackwhite"), enlargelimits=0, title="Histogram2 = Patch2D"))
g

df = DataFrame(position=[0.0,0.5,1.5,4.0], time=[0.0,1.0,2.0,3.0])
Axis(Plots.Linear(df, x=:time, y=:position), xlabel="time [s]", ylabel="position [m]")

Axis([
    Plots.Linear(x, y, style="mycolor, very thick"),
    Plots.Command("\\legend{Test}")
    ])

pushPGFPlotsPreamble("\\usepackage{cmbright}")
Plots.Linear(x, y, legendentry = "Test")

popPGFPlotsPreamble()
Plots.Linear(x, y, legendentry = "Test")

p = Plots.Histogram(rand(10))
save("myfile.tex", p)
save("myfile.pdf", p)
save("myfile.svg", p)

p = Plots.Histogram(rand(10))
save("myfile.tex", p, include_preamble=false)

using Reel
Reel.set_output_type("gif") # may be necessary for use in IJulia

frames = Frames(MIME("image/svg+xml"), fps=10)
for frame in 1:10
    t = frame/5
    ax = Axis(Plots.Linear(x -> sin(x+t*π), (0,6)), xlabel="x", ylabel="y")
    push!(frames, ax)
end 
frames