dstuebe

import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.Map;
import java.util.Map.Entry;

import javax.swing.text.html.HTMLDocument.Iterator;

dstuebe

import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;




public class TestProcess {

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from netCDF4 import Dataset

import numpy

rootgrp = Dataset('test.nc','w')


### Create some groups
group1 = rootgrp.createGroup('g1')
group2 = rootgrp.createGroup('g2')

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/*-------------------------------------------------------------------------
 * Function:  H5Z_can_apply_szip
 *
 * Purpose:	Check the parameters for szip compression for validity and
 *              whether they fit a particular dataset.
 *
 * Note:        This function currently range-checks for datatypes with
 *              8-bit boundaries (8, 16, 24, etc.).  It appears that the szip
 *              library can actually handle 1-24, 32 & 64 bit samples.  If
 *              this becomes important, we should make the checks below more

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<?xml version="1.0" encoding="UTF-8"?>
<!-- This template is an example of a SWE Data Record composed of static and dynamic fields for -->
<!-- multiple stations with multiple sensors including quality elements for some quantities. -->
<!--  -->
<!-- This template is almost identical to the SWE-Multisation-TimeSeries with the addition of some -->
<!-- quality elements. Quality flags for static and dynamic data are included for station1 sensor 1.-->
<!-- An example of NilValue is also provided for wind speed in station 1 sensor 1 -->
<!--  -->
<!-- Most any element may be static or dynamic, but the static fields must be encoded inline, while -->
<!-- The dyamic elements must be block encoded in the data array. -->

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      <sml:components>
        <sml:ComponentList>          
          <sml:component name='wmo_41001'>
            <sml:System>
            <!-- Include name & description only if they have some useful human readable purpose -->

              <!-- ==================================================================== -->
              <!-- PLATFORM IDENTIFIERS                                                 -->
              <!-- Gives ability to platforms by name                                   -->
              <!-- ==================================================================== -->

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<?xml version="1.0" encoding="UTF-8"?>
<!-- Template Document for a generic (independant of feature type) Get Observation. -->
<!-- Specific feature types are referenced for example only. -->
<!--  -->
<!-- The GO contains one member observation per feature type in the response.  -->
<!-- The result block in the template is empty. Examples of the result block are in the SWE -->
<!-- templates defined seperately for each strucutre and concept. Any of these SWE results could -->
<!-- be expressed in the result block of this document with the appropriate matching metadata. -->
<!--  -->
<om:ObservationCollection

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<?xml version="1.0" encoding="UTF-8"?>
<!-- This template is an example of a SWE Data Record composed of static and dynamic fields for -->
<!-- multiple stations with multiple profiling sensors -->
<!--  -->
<!-- Most any element may be static or dynamic, but the static fields must be encoded inline, while -->
<!-- The dyamic elements must be block encoded in the data array. -->
<!--  -->
<!-- Description of data -->
<!-- SWE DataRecord containing 1 Station: -->
<!-- Station 1 has 2 sensors -->

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<?xml version="1.0" encoding="UTF-8"?>
<!-- This template is an example of a SWE Data Record composed of static and dynamic fields for -->
<!-- multiple stations with multiple profiling sensors -->
<!--  -->
<!-- Most any element may be static or dynamic, but the static fields must be encoded inline, while -->
<!-- The dyamic elements must be block encoded in the data array. -->
<!--  -->
<!-- Description of data -->
<!-- SWE DataRecord containing 1 Station: -->
<!-- Station 1 has 2 sensors -->

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For n= 100000

$ python test_coroutines.py 
Coroutine Loop Result: '14.1121757499'; loop time (ms): 393.39017868
Numpy Loop Result: '14.1121757499'; loop time (ms): 26105.5378914
Numpy Dot Result: '14.1121757499'; dot time (ms): 0.148057937622
# can't pass a scalar by reference, try passing an array of size 1
Coroutine Loop No Result: '[ 14.11217575]'; loop time (ms): 438.895225525