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Clients

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Click the checkbox for SALT and O2. For both, set the range of z_index to. 0 to 0' ... Command line client is the tool used to move the data ... – PowerPoint PPT presentation

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Title: Clients


1
Clients
2
Accessing Data with DAP
  • Web Browser
  • Already discussed
  • Graphical clients
  • ncBrowse, ODC, Ferret, GrADS
  • Command-line clients
  • getdap (UNIX, win32), loaddap (Matlab, IDL), nco
    (UNIX, win32)
  • Custom clients
  • C, C, Java, Python
  • netCDF

3
Using a Graphical Client
  • Example The OPeNDAP Data Connector
  • Combines data location with retrieval and display
  • Shows the built URL, including constraint
    expression
  • Can be transferred to another application

4
Start the ODC
5
The ODC opens to the search pane
Five different panes
Choices within a pane
6
Use the dataset list to find the TPAC
climatologies
Choose the Antarctic Cooperative Research Centre
TPAC/CISRO Climatologies
then hit To Retrieve to move the selection to
the next pane
7
The Retrieve pane
Double click levitus_annual_97.nc To see the
contents of the file in The area on the right
8
The ODC shows the URL as it builds it.
Click the checkbox for SALT and O2. For both, set
the range of z_index to 0 to 0. Make sure to
hit tab/return in The boxes.
then hit Output to to move to the View pane
9
(No Transcript)
10
There are a number of ways to view The data. Here
the plotter has been Chosen (the default).
Hit Plot to to generate a plot using
the Default settings.
11
When the plot is made, the interface Switches to
the Preview tab
Switch back to the Variables tab to Plot O2
12
Choose O2 from the menu, then hit Plot to.
13
Now that the data have been read and Cached, you
can switch back and Forth between variables
quickly without Any additional data transfers
When ready, go back to the Retrieve Pane.
14
Choose TEMP
Set the constraint
then plot
15
(No Transcript)
16
ODC Summary
  • The ODC provides a way to search for, access and
    plot data
  • Acts as a URL builder the URLs can be pasted
    into other applications
  • We didnt need to know anything about DAP, its
    Request or Response objects or how a URL is used
    to request data
  • The data set list often contains stale entries
  • Also supports using the GCMD for data location -
    more on this when we cover searching

17
Using a Command-line Client
  • Matlab - demonstration
  • NCO - a powerful tool developed and maintained by
    another group

18
Matlab
  • Demonstration of custom-built Graphical
    interfaces for Matlab
  • Matlab scripting is used to build the interfaces
    and provide some dataset-specific processing
  • A Matlab command extension is used to read the
    data (written in C/C).
  • Two things are required in addition to Matlab
    The DAP command extension (loaddap) and the
    graphical interface software.

19
Running the Matlab Demonstration
  • Start Matlab
  • Download the command extension
  • Download the interface software
  • In Matlab change directory to the
    ml-ocean-testbed directory.
  • Type OCEAN_TOOLBOX
  • The interface will start

20
The Ocean Toolbox
21
Open a dataset
I choose the Pathfinder dataset
22
Fill in the information
SST Quality fields
Load data into the Matlab workspace
23
Get the data
Load data into the Matlab workspace
24
Plot/Display the data
25
Using the loaddap command extension directly
  • Start Matlab
  • Add the directory with the extension to the
    Matlab command path
  • Verify the command extension is working
  • Feed it a URL
  • Plot the data

26
Pass a URL, constrain the response To the u and
v vectors only
Plot those vectors See Figure 1
27
Matlab Summary
  • Command line client is the tool used to move the
    data
  • Easily used in Matlab scripts to hide the details
    and make custom interfaces
  • To the the command extension directory, user must
    know
  • Data location (URL)
  • Internal structure of the data set (syntactic
    metadata - DDS/DDX)
  • How to write a constraint expression

28
NetCDF Operators (NCO)
  • Unix command line client
  • Unlike the previous two clients, NCO uses the
    netCDF client library to read from a DAP server
  • A client library is a collection of functions
    which hide the mechanics of (most of) the
    interaction with a server so the client can go
    about its business
  • The NCO client is, in fact, just the NCO package
    linked to our (OPeNDAPs) version of the netCDF
    library (aka. the netCDF client library)

29
Build the NCO Software
  • Change directory to /root/src/nco-3.9.2
  • root_at_slax cd /root/src/nco-3.9.2
  • Run configure to build the Makefile, then build
    and install the software
  • root_at_slax ./configure
  • root_at_slax make
  • root_at_slax make install

30
Use NCO to Convert the FNOC1 vectors into a speed
  • NCAP NCO Arithmetic Processor
  • ncap2 -s speedsqrt(u2,v2) http//localhost80
    80/opendap/data/nc/fnoc1.nc spd.nc
  • The URL is the input file and wndspd.nc is the
    output
  • Use ncdump to look at the result file
  • ncdump -h spd.nc
  • ncdump -v speed spd.nc

31
View the Result ncBrowse
  • We can use ncBrowse to look at the local neetCDFZ
    we just built
  • ncBrowse can also look at the DAP server directly
  • Built using the DAP-enabled Java netCDF library
    (a client library where access to DAP servers
    hides behind the netCDF API)

32
Start ncBrowse
Double click on speed - the new data we made
with the previous NCO example
33
Fix up the latitude and longitude axes, the
Graph Variable.
34
We have to be somewhat savvy about the units -
check back and look at the attributes
35
Custom clients
  • What options exist to build clients
  • C using libdap
  • C using Ocapi
  • C,Fortran using the netcdf client library
  • Python using PyDAP
  • Java using Java-OPeNDAP
  • Matlab IDL using the respective versions of
    loaddap

36
Clients Summary
  • Custom clients offer an opportunity to develop
    for a specific audience or a particular
    problem/project.
  • Example ComMIT Tsunami inundation model client
    developed by NOAA/PMEL and BOM
  • General purpose clients like loaddap can read any
    kind of data while clients built using the netCDF
    client library are limited to the semantics of
    netCDF
  • Example Record access is slow because each
    access is separate network request

37
Clients Summary, cont.
  • ODC A client built specifically to provide a
    browse capability for any data source
  • Uses Java-OPeNDAP
  • Loaddap a client built to read any data into an
    analysis application
  • Can be used as a building block for more
    sophisticated applications
  • Use libdap (C, Matlab) or Ocapi (C, IDL)
  • netCDF client library A client-building tool
  • convert legacy code
  • provide a simple way to write new applications
  • C, C, Fortran

38
Finding Data
  • Ways to find data
  • The OPeNDAP Data Set List
  • GCMD
  • TPAC
  • Google
  • THREDDS
  • We maintain a page with links to dataset
    searching sites
  • http//www.opendap.org/data/index.html

39
Common Features
  • All of these data location features except Google
    depend on active community involvement in
    building catalogs of data
  • The solutions can be described as static
    documents or crawlers
  • Google and TPAC are crawlers
  • Crawlers can discover datasets without human
    intervention
  • They can make mistakes that seem silly
  • The The Dataset List, GCMD and THREDDS are static
    documents or collections of static documents
  • Static lists can be tailored by hand
  • They can go out of date quickly

40
Differentiating Features
  • Google TPAC
  • Google is just crawling HTML. If a server is not
    linked to a HTML page, it wont be found.
  • TPAC is preset with server locations and picks up
    changes at those sites

41
Differentiating Features, cont.
  • The Static Lists
  • The Dataset List has a very low metadata
    requirement
  • Not maintained as actively as either GCMD or
    THREDDS catalogs
  • GCMD
  • The GCMD has a fairly high entry level threshold
  • Professional staff maintain the GCMD as their
    sole job
  • THREDDS
  • THREDDS catalogs are, or can be, located at the
    data - locality distributes maintenance
  • Quality varies from site to site

42
Finding Data Summary
  • Locating data seems like it would be the place to
    start building a system, but its far more varied
    than the one-size-fits-all approach most tried in
    the 1990s
  • Crawlers and hierarchical lists show the most
    promise but maintained centralized lists are also
    useful
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