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using CairoMakie | |
fig = Figure() | |
# Number of neurons per layer | |
neurons_per_column = [1, 10, 7, 5, 8, 1] | |
# A grid for each layer (arranged in a column) | |
col_grids = [GridLayout(fig[1, i]; valign = :center) for i in eachindex(neurons_per_column)] | |
# An axis per neuron | |
col_axes = [ | |
[Axis(col_grids[i][j, 1]) for j in 1:neurons_per_column[i]] |
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#= | |
# 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 |
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using Colors | |
function cgrad2svgf(cgrad) | |
stops = LinRange(0, 1, 256) | |
colors = cgrad[stops] | |
# no Alpha support yet | |
# but soon! | |
# <feFuncA type="table" tableValues="$(join(alpha.(colors), ","))"></feFuncA> | |
return """ | |
<filter id="table" x="0" y="0" width="100%" height="100%"> |
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using GLMakie | |
using Meshing, GeometryBasics | |
isoval = 100 | |
algo = MarchingCubes(iso=isoval, insidepositive=false) | |
struct CameraRotationMove{T} <: FlyThroughPaths.PathChange{T} | |
duration::T |
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#= | |
This file provides integration for R's SF objects | |
which are essentially geo-dataframes, | |
into Julia DataFrames with GeoInterface wrapper | |
geometries. | |
This requires https://github.com/JuliaInterop/RCall.jl/pull/528, | |
so run `Pkg.add((; url = "https://github.com/asinghvi17/RCall.jl", rev = "patch-1"))` to get that. | |
TODO: |
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using SHA | |
function archive_source_string(prefix_name, prefix, suffix, oldhash::String; joinchar = "", unpack_target = nothing) | |
url = join((prefix, suffix,), joinchar) | |
hash = bytes2hex(get_hash(url)) | |
print("ArchiveSource(\"\$($(prefix_name))$(joinchar)$(suffix)\", \"$(hash)\"") | |
if !isnothing(unpack_target) | |
print("; unpack_target = \"$(unpack_target)\")") | |
else | |
print(")") |
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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 |
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_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, |
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using BenchmarkTools, Metal | |
using Makie, CairoMakie | |
using RecurrenceAnalysis | |
function recurrence_kernel!(output_matrix, x1, x2) | |
x, y = Metal.thread_range() | |
end | |
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# # 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`. |
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