Commit 74d686b4 authored by Jonathan Mattingly's avatar Jonathan Mattingly
Browse files

clearn up

parent 7362e302

example_atlas_multilevel_precinctHistogram.py

+6 −0
Original line number Diff line number Diff line
@@ -23,6 +23,8 @@ pctToDistVotes = {} 
for node in pctData["nodes"]:

    pctToDistVotes[node["id"]] = {}



count=0



while map is not None:  # This loops through all of the map in the atlas

    try:

        map = Atlas.nextMap(atlas)  # Get the next map in the atlas
@@ -44,6 +46,10 @@ while map is not None: # This loops through all of the map in the atlas 
            votes["Total"] = distVoteT[node_to_dist[id]]

            pctToDistVotes[id][map.name] = votes

    

        count+=1

        if count>500:

            break



    except Exception:

        break

example_atlas_multilevel_precinctOutcomes.py

+46 −45
Original line number Diff line number Diff line 
import Atlas

import helper_functions as hf

import numpy as np

import json



from time import sleep

from tqdm import tqdm



import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns
@@ -8,66 +13,62 @@ import seaborn as sns 






pctDataF = open("pct21_20cen_wMCD.json")

pctData = json.load(pctDataF)

pctDataFile = open("pct21_20cen_wMCD_updated.json")

pctData = json.load(pctDataFile)

dataElection = pctData['nodes']

hf.addTotalVotes(dataElection)



atlas = Atlas.openAtlas("./truncated_nc_multiscale.jsonl")

#atlas = Atlas.openAtlas("./truncated_nc_multiscale.jsonl")

atlas = Atlas.openAtlas("./atlas_measureID12.jsonl.gz")

print(atlas)

map = []

print("\n")

electionName = "G16_USS"  # This is the name of the eleection we will consider.



pctToDistVotes = {}

swingElections=[]

swings=[.47+i/200 for i in range(13)]

electons=["G20_USS","G20_LG","G20_GV","G20_PR","G16_PR"]

for election in electons:

    hf.addUniformSwings(swings,electons,dataElection)

    for s in swings:

       swingElections.append(election+"_USF"+str(s)) 





pctDemWinnersHist = {}

for node in pctData["nodes"]:

    pctToDistVotes[node["id"]] = {}

    pctDemWinnersHist[node["id"]] = {}



count=0



while map is not None:  # This loops through all of the map in the atlas

    try:

        map = Atlas.nextMap(atlas)  # Get the next map in the atlas 

        print(map.name)

        

        # The maps are multi scale in the sense that if a county is kept whole

        # the following fuction makes a map from precicts to districts out of 

        # the multiscale assignement 

        node_to_dist = hf.get_node_to_district(map.districting, 

                                               pctData["nodes"])

        # The next fuction  sums up the election for this districting (defined 

        # by the map)

        distVoteR, distVoteD, distVoteT = hf.sumElection(electionName, 

                                                         node_to_dist, 

                                                         dataElection)

        for id in pctToDistVotes.keys():

            votes = {}

            votes["Dem"] = distVoteD[node_to_dist[id]]

            votes["Rep"] = distVoteD[node_to_dist[id]]

            votes["Total"] = distVoteT[node_to_dist[id]]

            pctToDistVotes[id][map.name] = votes

    

    except Exception:

        break



# This secton adds the uniform swings by the amounts listed in swings for the lections

# listed in ellections to the dataEllections

swings=[.47+i/200 for i in range(13)]

electons=["G16_AG","G12_PR","G08_USS"]

hf.addUniformSwings(swings,electons,dataElection)

        

        numDemsPrecinct=np.zeros(len(node_to_dist.keys()))

        for e in swingElections:

            distVoteR, distVoteD, distVoteT = hf.sumElection(e, node_to_dist,

                                                             dataElection)

            for id in node_to_dist.keys():

                if distVoteD[node_to_dist[id]] >distVoteR[node_to_dist[id]]:

                    numDemsPrecinct[id]+=1



# now do somthing with data

id = 100  # Choose precinct

print(dataElection[id]["county"], dataElection[id]["prec_id"])

        for id in node_to_dist.keys():

            if (numDemsPrecinct[id] in pctDemWinnersHist[id].keys()):

                 pctDemWinnersHist[id][numDemsPrecinct[id]]+=1

            else:

                pctDemWinnersHist[id][numDemsPrecinct[id]]=1



# or

county = "BEAUFORT"

prec_id = "BLCK"

id = [ii for ii in range(len(dataElection)) 

      if dataElection[ii]["county"] == county 

      and dataElection[ii]["prec_id"] == prec_id][0]

print(id)

        

df = pd.DataFrame(pctToDistVotes[id]).T

df["Dem %"] = df["Dem"]/df["Total"]

print(df)

        if (count % 50) == 0:

            print(count," ; ",map.name)

        count+=1

        if count>500:

            break

    except Exception:

        break

sns.displot(data=df, x="Dem %", bins=10, stat="density")

plt.show()

helper_functions.py

+9 −1
Original line number Diff line number Diff line
@@ -54,4 +54,12 @@ def addUniformSwings(targetDemFractions,electionNames,dataElection): 




def listElections(dataElection, prefix="G", exluded={'id','prec_id','pop2020cen','MCD','area','border_length'},idx=0):

    return [ e[0:-2] for e in dataElection[idx].keys() if e not in {'id','prec_id','pop2020cen','MCD','area','border_length'} and e[-1] == 'T']
 
    return [ e[0:-2] for e in dataElection[idx].keys() if e not in {'id','prec_id','pop2020cen','MCD','area','border_length'} and e[-1] == 'D']



def addTotalVotes(dataElection):

    elections=listElections(dataElection)

    for e in elections:

        if (e+"_T" not in dataElection[0].keys()):

            for p in dataElection:

                p[e+"_T"]=p[e+"_D"]+p[e+"_R"]

        
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