arbennett

#!/usr/bin/env Rscript
# Attempt at a somewhat complicated plot layout
# @author arbennett

dataset_1 <- rnorm(10)
dataset_2 <- rnorm(10)
dataset_3 <- rnorm(10)
dataset_4 <- rnorm(10)

arbennett

#!/usr/bin/python2
import os
import sys
import time
import numpy as np
import subprocess
import matplotlib.pyplot as plt
from netCDF4 import Dataset

# Method one, just use numpy

arbennett

"""
Script to do multiple stacked bar subplots
"""
import matplotlib.pyplot as plt

data = [[1,  2,  3,  4],
        [5,  6,  7,  8],
        [9, 10, 11, 12]]
colors=['r','g','b','y']
n_bars = len(data)

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class scdict(dict):
    """
    Separate chaining dictionary implementation allows
    for multiple values to be assigned to a single key
    in a list.
    """
    def __setitem__(self, key, val):
        """
        Sets a value to a key, and if the key already exists, 
        make a list of all of the values assigned

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"""
Just testing for efficiency across various synchronization schemes
for multiprocessing datastructures
"""
import time
import queue
import multiprocessing as mp

def dict_increments(d, q, s):
    """ Incrementally add to a dictionary """

arbennett

'''
2d Implementation of the Lenz-Ising Model

Created on May 13, 2014
Updated on Nov 02, 2016

@author: Andrew Bennett

The Ising model can be used to calculate the ground state energy of a spin lattice.  You can think 
of a spin lattice as a grid of particles with a property called spin, which can be plus or minus 1.  

arbennett

#!/usr/bin/env bash

mogrify -format jpg *.tif
convert xc:black xc:red xc:orange xc:yellow xc:green1 xc:cyan xc:blue xc:blueviolet xc:white +append -filter Cubic -flop rainbow_lut.png
find *.jpg -exec convert {} -colorspace gray rainbow_lut.png -clut {}.colored.jpg \; 
convert -antialias -delay 1x15  *.colored.jpg output.mpeg

arbennett

#!/usr/bin/env python
"""
Select out the necessary locations from a larger domain file
and output the pared down file for use in MetSim.  This script
is intended to be used when using ascii or binary input.  The 
usage can be found by running `./build_domain.py -h` or simply
by inspecting the USAGE command.

This script requires the input domain file to have the 'elev' 
field filled out, and the forcing files to be a subset of

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Preprocessing

Forcing data

Disaggregation

The forcing data is generated based on the 1/16 degree Livneh forcing dataset. The original Livneh dataset is obtained at HYDRA:/raid/blivneh/forcings/outputs/CONUS/asc.v.1.2.b/data_${latitude}_${longitude}. A copy of the data has been placed at HYAK:/civil/hydro/michaelou/summaProj/summaData/blivneh/asc.v.1.2.b. The daily forcing data is disaggregated to a hourly basis by running VIC_4.1.2. The results of disaggregation are placed at HYAK:/civil/hydro/michaelou/summaProj/summaData/blivneh/workdir.

Converting to SUMMA inputs

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