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import momepy
import geopandas as gpd

def create_graph(linestrings):
  gdf = gpd.GeoDataFrame(geometry=linestrings)
  graph = momepy.gdf_to_nx(gdf, approach="primal")
  return graph

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from shapely.geometry import LineString, Point
from shapely.ops import unary_union
from geopy.distance import geodesic

def snap_to_nearest_node(point, nodes, tolerance):
    for node in nodes:
        if geodesic((point.y, point.x), (node.y, node.x)).meters <= tolerance:
            return node
    return point

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First Steps for a Citywide Fiber Network

Here's a breakdown of the initial steps you'd take to initiate a citywide fiber project, incorporating elements from the provided feasibility studies and focusing on funding, ISP evaluation, and infrastructure considerations:

Phase 1: Strategy & Policy Development

1. Establish a Broadband Policy: Define the city's vision for broadband. This should cover:

• Goals: Ubiquity, affordability, competition, open access, desired speeds, and financial sustainability.
• Roles: The city's role as owner, facilitator, or partner.
• Community Engagement: Processes for gathering public input and ongoing communication.

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# Some quick snippets for points to lines

address_df = pd.DataFrame([[0, Point([c for c in h3.cell_to_latlng(h3_8)[::-1]])]], columns=['id', 'geometry'])
address_gdf = gpd.GeoDataFrame(address_df, geometry="geometry", crs="epsg:4326")

gdf = gpd.read_file(
    "./data/all_the_data.fgb",
    engine="pyogrio", bbox=location_box)
gdf = gdf.to_crs('epsg:3310') # https://epsg.io/3310

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import sys
import json
import csv


def main():
    input_json = sys.argv[1]
    output_csv_data = [['name', 'lastdate', 'desc', 'shorturl']]
    with open(input_json, mode='r') as ijson:
        data = json.load(ijson)

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#!/Usr/bin/env python
# -*- coding: utf-8 -*-

'''
Searches a graph and yields all the minimum spanning trees in order of increasing cost.
This could be used to solve minimum spanning trees with constraints by yielding trees until
we reach the first one which satisfies a constraint.
For example it could solve the degree constrained minimum spanning tree DCMST
'''

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wget https://golang.org/dl/go1.16.7.linux-amd64.tar.gz;
rm -rf /usr/local/go && tar -C /usr/local -xzf go1.16.7.linux-amd64.tar.gz;
export PATH=$PATH:/usr/local/go/bin;
export GOPATH=$HOME/go;
export PATH=$PATH:$GOROOT/bin:$GOPATH/bin;
go get github.com/fraugster/parquet-go/cmd/csv2parquet;

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Linear Programming Solver running in the browser?

So I wanted to see if I could get a solver running in the browser.

Why you might ask? Well its pretty typical to need to deploy a back end for a webapp or even to have a specific install on your OS.

This makes things clunky if we wanted to say:

1. Visualize solutions in realtime using some js libs on the client side
2. Solve models on the client side of a web app

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