rplzzz

savepkgs <- function(saveloc)
{
    instpkg <- installed.packages()
    cranpkg <- available.packages()
    iscran <- instpkg[,'Package'] %in% cranpkg[,'Package']
    pkgdata <- data.frame(package=instpkg[,'Package'], iscran=iscran, instvers=instpkg[,'Version'])
    write.csv(pkgdata, saveloc)
}

restore_pkgs <- function(pkglistfile)

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---
title: "R Notebook"
output: html_notebook
---

```{r setup}
library(hector)
library(assertthat)
library(ggplot2)
library(ggthemes)

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## a batch of 3 4x4x2 images as input.  We will upsample these to 8x8
input_data = np.ones([3, 4, 4, 2])

filter_shape = [3,3,4,2]  # width, height, channels-out, channels-in
tconv_filter = np.ones(filter_shape)  # make the filter all ones so that we can manually calculate the output
                                      # obviously, having all the filter channels have the same coefficients defeats
                                      # the purpose of having multiple channels, but this is just an example
output_shape = [8, 8, 4] # width, height, channels-out  (notice we don't have the batch size dimension -- more on that later)

## set up the slots for the data

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rplzzz

#!/usr/bin/env python
# coding: utf-8

"""
Calculates total, nonblank and net lines of code for Python scripts.
"""
import os
import re

def get_line_count(blob):

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library(sp)
library(rgdal)
library(raster)
library(ncdf)

##aez map
## extract data from shape file

GIS_DIR <- "./cropdata"
GIS_FILE <- "GCAM_region_AEZ"

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;; emacs startup file.

;; uncomment next line to disable loading of "default.el" at startup
;; (setq inhibit-default-init t)

;; add personal load path                                                                                               
(push "~/.emacs.d/lisp" load-path)

;; set up MELPA package archive
(require 'package)