lazear

implementation ::=          
             { impl-phrase ;;}

impl-phrase ::=
              expression | value-definition 
            | type-definition  |  exception-definition  |  directive

value-definition ::= 
          let [ rec ] let-binding { and let-binding } 

lazear

\documentclass{article}
\title{Reference sheet for ``Introduction to Logic''}
\date{2019-04-15}
\author{Michael Lazear}
\pagestyle{headings}
\usepackage{amsmath}

\begin{document}
	\pagenumbering{gobble}
	\maketitle

lazear

import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
import pandas as pd
from mpl_toolkits.mplot3d import Axes3D
from datetime import datetime
from datetime import timedelta
from scipy.interpolate import CubicSpline

lazear

use std::fmt;

#[derive(Clone, Debug)]
pub enum CpsTerm {
    Var(String),
    Abs(String, Box<CpsTerm>),
    App(Box<CpsTerm>, Box<CpsTerm>),
}

#[derive(Clone, Debug)]

lazear

signature NAME = sig
  type t
  val empty: string -> t
  val fresh: t -> string  
end;

structure Name = struct
  datatype t = T of {name: string, id: int ref};  
  fun empty name = T {name=name, id=ref 0};  
  fun fresh (T {name, id}) = 

lazear

import requests
from multiprocessing import Pool

TOKEN = "eyJhbGciOiJSUzI1NiJ9.<your JWT here>"

def download(f):
    print(f"downloading {f['name']}...")
    try:
        resp = requests.get(f["href"])
        with open(f["name"], 'wb') as file:

lazear

import requests
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm

URL = 'https://app.dimensions.ai/viz/data/publication/timeline-source-published.json?search_mode=content&search_text="{engine}" AND "proteomics"&search_type=kws&search_field=full_search'

def get(engine: str):

lazear

#!/bin/bash
# This script sets up a benchmarking harness for MaxQuant on a c5ad ubuntu EC2 instance
sudo apt update && \
sudo apt install -y \
    tmux \
    htop \
    awscli \
    unzip \
    mono-complete \
    gdb