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springcoil / Bayesian_Model_2.py
Last active August 29, 2015 14:21
A Bayesian model for myself to debug - PyData Berlin
df_avg = pd.DataFrame({'avg_att': atts.stats()['mean'],
'avg_def': defs.stats()['mean']},
index=teams.team.values)
df_avg = pd.merge(df_avg, df_observed, left_index=True, right_on='team', how='left')
fig, ax = plt.subplots(figsize=(8,6))
for outcome in ['winner', 'triple_crown', 'wooden_spooon', '']:
ax.plot(df_avg.avg_att[df_avg.QR == outcome],
df_avg.avg_def[df_avg.QR == outcome], 'o', label=outcome)
@springcoil
springcoil / bayesian_model3.py
Created May 15, 2015 12:38
Another Bayesian_Model which needs edited
df_hpd = pd.DataFrame(atts.stats()['95% HPD interval'],
columns=['hpd_low', 'hpd_high'],
index=teams.team.values)
df_median = pd.DataFrame(atts.stats()['quantiles'][50],
columns=['hpd_median'],
index=teams.team.values)
df_hpd = df_hpd.join(df_median)
df_hpd['relative_lower'] = df_hpd.hpd_median - df_hpd.hpd_low
df_hpd['relative_upper'] = df_hpd.hpd_high - df_hpd.hpd_median
df_hpd = df_hpd.sort_index(by='hpd_median')
@springcoil
springcoil / machine-create.sh
Last active August 29, 2015 14:25 — forked from tshauck/machine-create.sh
docker-machine create \
--driver amazonec2 \
--amazonec2-access-key $ACCESS_KEY \
--amazonec2-secret-key $SECRET_KEY \
--amazonec2-vpc-id $VPC \
--amazonec2-security-group $SECURITY_GROUP \
--amazonec2-instance-type "m4.2xlarge" \
--amazonec2-root-size 20 \
--amazonec2-request-spot-instance \
--amazonec2-spot-price 0.20 \
@springcoil
springcoil / machinecreate.sh
Created July 19, 2015 11:42
Influenced by Trent Hauck
LC_ALL=C docker-machine create \
--driver amazonec2 \
--amazonec2-access-key $AWS_ACCESS_KEY_ID \
--amazonec2-secret-key $AWS_SECRET_ACCESS_KEY \
--amazonec2-region "eu-west-1" \
--amazonec2-vpc-id $VPC \
--amazonec2-instance-type "m4.2xlarge" \
--amazonec2-root-size 20 \
--amazonec2-request-spot-instance \
--amazonec2-spot-price 0.20 \
@springcoil
springcoil / basic_income_monte_carlo.py
Last active August 29, 2015 14:25 — forked from stucchio/basic_income_monte_carlo.py
Monte carlo simulation of basic income/basic job calculations, from blog.
from pylab import *
from scipy.stats import *
num_adults = 227e6
basic_income = 7.25*40*50
labor_force = 154e6
disabled_adults = 21e6
current_wealth_transfers = 3369e9
def jk_rowling(num_non_workers):
@springcoil
springcoil / assert_frames_equal.ipynb
Created October 5, 2015 15:44 — forked from jiffyclub/assert_frames_equal.ipynb
Example of a function to compare two DataFrames independent of row/column ordering and with handling of null values.
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@springcoil
springcoil / gist:3231352
Created August 1, 2012 22:41 — forked from swannodette/gist:3217582
sudoku_compact.clj
(ns sudoku
(:refer-clojure :exclude [==])
(:use clojure.core.logic))
(defn get-square [rows x y]
(for [x (range x (+ x 3))
y (range y (+ y 3))]
(get-in rows [x y])))
(defn init [vars hints]
@springcoil
springcoil / FremontBridge.ipynb
Created October 20, 2015 20:53 — forked from jakevdp/FremontBridge.ipynb
Fremont Bike Counts 2015
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@springcoil
springcoil / Experiment.ipnb
Created October 22, 2015 11:39
This file has been truncated, but you can view the full file.
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Reproducibility from the start"
]
},
{
@springcoil
springcoil / numba_test.py
Created October 26, 2015 17:07 — forked from jhemann/numba_test.py
Testing numba's autojit decorator on simple code for matrix factorization.
# -*- coding: utf-8 -*-
#!/usr/bin/python
#
# Modified example of Albert Au Yeung's on matrix factorization:
# http://www.quuxlabs.com/blog/2010/09/matrix-factorization-a-simple-tutorial-and-implementation-in-python/#source-code
import numpy as np
from numba.decorators import autojit, jit