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#!/usr/bin/env bash

# I did this with OS X Yosemite 10.10.5 in May 2016
# Adding some changes from original

# Install XCode and command line tools
# See https://itunes.apple.com/us/app/xcode/id497799835?mt=12#
# See https://developer.apple.com/library/mac/documentation/Darwin/Reference/ManPages/man1/xcode-select.1.html
xcode-select --install

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import seaborn as sns
sns.set_style('darkgrid')
from matplotlib.colors import ListedColormap
# Enter hex values of desired colors
color_map = ListedColormap(['#00bfff', '#ff8000'])
x = np.linspace(0, 2*np.pi, 100)
for i in range(2):
    plt.plot(x, np.sin(x+np.pi/2*i), c=color_map.colors[i], lw=5, alpha=0.7)

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___________________________________

TO MAKE CAFFE (NOT FROM SCRATCH)

make all -j2; make pycaffe -j2

make distribute

export PYTHONPATH="/Users/kristinhebert/Documents/GitClones/caffe/distribute/python:$PYTHONPATH"

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import matplotlib.pyplot as plt
import numpy as np

plt.xkcd()
ax = plt.subplot(111)
x = np.linspace(0,4*np.pi,100)
ax.plot(x, np.sin(x)/x)
ax.annotate('Hell ya!', xy=(2, 0.5), xytext=(6, 0.7), 
            xycoords='data', textcoords='data', ha='right', va='bottom', 
            arrowprops=dict(arrowstyle='->', lw=2))

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see all available commands:
git

grab a repository from git:
git clone ___url___

>  COMMANDS FOR MAKING NEW GIT REPOSITORY

git init
git add -A

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Useful commands for Pandas dataframes

import pandas as pd

---

Loading data

• from .csv
  df = pd.read_csv('file.csv', header=1)
• from dictionary
  df = pd.DataFrame(dict)
• from lists
  df = pd.DataFrame([[y, x1_1, x2_1, ...], [y, x1_2, x2_2, ...], ... ])

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Useful commands for Numpy

import numpy as np

---

Arrays

• Random mask for shuffle
  np.random.permutation(size)
• Split array a into N pieces
  np.array_split(a, N)
• Initialize empty array and join
  a = np.empty(shape=(0, b.shape[1]))

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---
title: "Functions"
---

1. __What are the three components of a function?__  
* Envionment, arguments, and body.
```{r}
e <- new.env()
e$body <- print("Schrodinger's cat")
e$a <- function(argument){

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# -*- coding: utf-8 -*-
__author__ = 'Alex Galea'

"""
* No longer maintained *
See here for newer versions: https://github.com/agalea91/photo-batch-resize
"""

# Usage e.g.
# python photo-batch-resize-constrained.py --images-folder=lightroom-exports --max-px-size=1080

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### Miscellaneous tips for using R

# Select a set of columns from a dataframe
wage_red = wage %>% select(-sibs, -brthord, -meduc, -feduc)
wage_subset = wage %>% select(hours, lwage)

# Use q + dist type to get confidence interval
beta_iq_mean = summary(lm.wage_1)$coefficients[2]
beta_iq_std = summary(lm.wage_1)$coefficients[4]
qt(p = c(0.025, 0.975), df = 933)*beta_iq_std + beta_iq_mean # t = student-t dist., can also use e.g. qnorm