[Swift-commit] r6315 - SwiftApps/modis

[ketan at ci.uchicago.edu]

Author: ketan
Date: 2013-02-26 22:03:46 -0600 (Tue, 26 Feb 2013)
New Revision: 6315

Modified:
   SwiftApps/modis/README
Log:
Reading README and minor updates

Modified: SwiftApps/modis/README
===================================================================
--- SwiftApps/modis/README	2013-02-27 03:22:36 UTC (rev 6314)
+++ SwiftApps/modis/README	2013-02-27 04:03:46 UTC (rev 6315)
@@ -4,11 +4,11 @@
 
 $ svn co https://svn.ci.uchicago.edu/svn/vdl2/SwiftApps/modis
 
-Once you do this, you all also need the associated modis data. 
-To download the images, run:
+Once you do this, you also need the associated modis data. 
+To download the image data, run:
 
 $ cd modis/data/modis/2002
-$ wget http://www.ci.uchicago.edu/swift/modis/modis-2002.tar
+$ wget http://www.ci.uchicago.edu/swift/modis/modis-2002.tar 
 $ tar xf modis-2002.tar 
 
 Hello world
@@ -16,7 +16,7 @@
 The script tutorial/hello.swift demonstrates a simple "hello world" 
 script. It demonstrates how to define apps, passing arguments to 
 an app, and how to work with files. In this example, a file called
-hello.txt gets created with with the contents of "Hello, world!".
+hello.txt gets created with the contents of "Hello, world!".
 
 To run the application, the command is:
 
@@ -25,7 +25,7 @@
 modis01.swift
 -------------
 The first modis example defines one app function called getLandUse.
-This app takes a sallite image (data/modis/2002/h00v09.pgm.gz) as 
+This app takes a satellite image (data/modis/2002/h00v09.pgm.gz) as 
 input. getLandUse creates a text file called landuse/h00v08.landuse.byfreq
 that counts the frequency of each land type defined in the input image.
 
@@ -49,7 +49,7 @@
 and creates two summary files called topselected.txt and selectedtiles.txt. These
 files contain information about the top 10 urban areas.
 
-In the previous example, you have have noticed that running all 317 input files on 
+In the previous example, you have noticed that running all 317 input files on 
 your laptop, even with 4 tasks a time, is not very efficient. In the next example,
 instead of running locally, we will use a cluster called midway at the University of
 Chicago to improve performance.