asinghvi17

#=
# Getting (noninteractive) raster images from the MapTiles/TileProviders ecosystem
=#

import HTTP # to run the actual request and fetch the tiles
import ImageMagick # to read returned images, since they may be any bitmap format
using MapTiles, TileProviders # Julia map-tile infrastructure
# Julia geographic infrastructure
using Extents 
import GeoInterface as GI

asinghvi17

using Colors

function cgrad2svgf(cgrad)
    stops = LinRange(0, 1, 256)
    colors = cgrad[stops]
    # no Alpha support yet
    # but soon!
    # <feFuncA type="table" tableValues="$(join(alpha.(colors), ","))"></feFuncA>
    return """
    <filter id="table" x="0" y="0" width="100%" height="100%">

asinghvi17

using GLMakie
using Meshing, GeometryBasics

isoval = 100
algo = MarchingCubes(iso=isoval, insidepositive=false)


struct CameraRotationMove{T} <: FlyThroughPaths.PathChange{T}
  duration::T

asinghvi17

#=
This file provides integration for R's SF objects 
which are essentially geo-dataframes, 
into Julia DataFrames with GeoInterface wrapper 
geometries.

This requires https://github.com/JuliaInterop/RCall.jl/pull/528,
so run `Pkg.add((; url = "https://github.com/asinghvi17/RCall.jl", rev = "patch-1"))` to get that.

TODO:

asinghvi17

using SHA

function archive_source_string(prefix_name, prefix, suffix, oldhash::String; joinchar = "", unpack_target = nothing)
    url = join((prefix, suffix,), joinchar)
    hash = bytes2hex(get_hash(url))
    print("ArchiveSource(\"\$($(prefix_name))$(joinchar)$(suffix)\", \"$(hash)\"")
    if !isnothing(unpack_target)
        print("; unpack_target = \"$(unpack_target)\")")
    else
        print(")")

asinghvi17

using Proj, BenchmarkTools
import GeometryOps as GO

# using proj_trans_generic on a vector of tuples - or could be GB.Point or SVector or GI.Point with arbitrary metadata, doesn't matter!

points = tuple.(rand(10000), rand(10000))

t = Proj.Transformation("+proj=longlat", "+proj=natearth"; always_xy = true)
function batch_project_numsfirst!(points, projection)
    # GC.@preserve points begin # not technically necessary

asinghvi17

_stix_fonts = Dict(:regular => "/System/Library/Fonts/Supplemental/STIXTwoMath.otf",#joinpath("NewComputerModern", "NewCMMath-Regular.otf"),
           :italic => "/System/Library/Fonts/Supplemental/STIXTwoMath.otf",#joinpath("NewComputerModern", "NewCM10-Italic.otf"),
           :bold => "/System/Library/Fonts/Supplemental/STIXTwoMath.otf",#joinpath("NewComputerModern", "NewCM10-Bold.otf"),
           :bolditalic => "/System/Library/Fonts/Supplemental/STIXTwoMath.otf",#joinpath("NewComputerModern", "NewCM10-BoldItalic.otf"),
           :math => "/System/Library/Fonts/Supplemental/STIXTwoMath.otf"
       )

Makie.MathTeXEngine.default_font_families["STIX"] = Makie.MathTeXEngine.FontFamily(
    _stix_fonts,

asinghvi17

using BenchmarkTools, Metal
using Makie, CairoMakie
using RecurrenceAnalysis

function recurrence_kernel!(output_matrix, x1, x2)
    x, y = Metal.thread_range()

end

asinghvi17

# # A GUI to display location "attractiveness"

# The following code creates a GUI which allows you to inspect 
# a map of Toronto, and see the attractiveness of different locations
# based on different nearness measures.

# First, we load the necessary packages.  

# We will build our GUI with the `Makie` toolchain, consisting of `Makie`, `[W]GLMakie`, and `Tyler` for map tile visualization.  
# Data is from OpenStreetMap and is parsed using `OpenStreetMapX`.  Attractiveness scores are obtained using `OSMToolset`.

asinghvi17

using Makie: GeometryBasics
using Makie.GeometryBasics: StructArrays

@recipe(MeshImage) do scene
    Attributes(
        npoints = 100,
        space = :data,
    )
end