We love solving puzzles at Priceonomics. We also like meeting people who like to solve puzzles. Here are two interesting puzzles we've faced at some point in the past months that we'd like to share with you.
If you have any questions, contact [email protected].
| all_tracts = lapply(income, function(county) | |
| lapply(county$tracts, function(tract) as.data.frame(c(county[1:3],tract)))) | |
| all_tracts_temp = lapply(all_tracts, function(county) as.data.frame(do.call(rbind, county))) | |
| income_df = as.data.frame(do.call(rbind, all_tracts_temp)) | |
| summary(income_df) | |
| ff = as.numeric(income_df$medianIncome) | |
| ff = as.numeric(as.character(income_df$medianIncome)) | |
| income_df$medianIncome = as.numeric(as.character(income_df$medianIncome)) |
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
| #!/usr/bin/env python | |
| # distance_from_shore.py: compute true distance between points | |
| # and closest geometry. | |
| # shaun walbridge, 2012.05.15 | |
| # TODO: no indexing used currently, could stand if performance needs | |
| # improving (currently runs in ~1.5hr for 13k points) | |
| from geopy import distance |
| float phi = (sqrt(5)+1)/2; | |
| size(323,200); | |
| translate(height/phi,0); | |
| scale(height); | |
| noStroke(); | |
| smooth(); | |
| for (float i=0; i<10; i++) { | |
| fill(i/10*255); |
Create an arc like shape by specifying two points and drawing the points between them using HTML canvas
| #!/usr/bin/env sh | |
| ## | |
| # This is script with usefull tips taken from: | |
| # https://github.com/mathiasbynens/dotfiles/blob/master/.osx | |
| # | |
| # install it: | |
| # curl -sL https://raw.github.com/gist/2108403/hack.sh | sh | |
| # |
| import numpy as np | |
| class Perceptron: | |
| def __init__(self,Weights,Biases): | |
| self.Weights = Weights | |
| self.Biases = Biases | |
| def Train(self, Training, LearningRate): |
| if (typeof (AC) === "undefined") { | |
| AC = {} | |
| } | |
| AC.ImageReplacer = Class.create({ | |
| _defaultOptions: { | |
| listenToSwapView: true, | |
| filenameRegex: /(.*)(\.[a-z]{3}($|#.*|\?.*))/i, | |
| filenameInsert: "_☃x", | |
| ignoreCheck: /(^http:\/\/movies\.apple\.com\/|\/105\/|\/global\/elements\/quicktime\/|_(([2-9]|[1-9][0-9]+)x|nohires)(\.[a-z]{3})($|#.*|\?.*))/i, | |
| attribute: "data-hires", |
| # path taken from brew install notes | |
| POSTGIS_SQL_PATH=/usr/local/share/postgis | |
| # Creating the template spatial database. | |
| createdb -E UTF8 template_postgis | |
| createlang -d template_postgis plpgsql # Adding PLPGSQL language support. | |
| # Allows non-superusers the ability to create from this template | |
| psql -d postgres -c "UPDATE pg_database SET datistemplate='true' WHERE datname='template_postgis';" |
