<!-- 
RSS generated by JIRA (8.3.4#803005-sha1:1f96e09b3c60279a408a2ae47be3c745f571388b) at Sat Feb 10 15:50:24 JST 2024

It is possible to restrict the fields that are returned in this document by specifying the 'field' parameter in your request.
For example, to request only the issue key and summary append 'field=key&field=summary' to the URL of your request.
-->
<rss version="0.92" >
<channel>
    <title>PFS-JIRA</title>
    <link>https://pfspipe.ipmu.jp/jira</link>
    <description>This file is an XML representation of an issue</description>
    <language>en-us</language>    <build-info>
        <version>8.3.4</version>
        <build-number>803005</build-number>
        <build-date>13-09-2019</build-date>
    </build-info>


<item>
            <title>[PIPE2D-269] How to correctly and quickly estimate wavefront</title>
                <link>https://pfspipe.ipmu.jp/jira/browse/PIPE2D-269</link>
                <project id="10002" key="PIPE2D">DRP 2-D Pipeline</project>
                    <description>&lt;p&gt;I have to find more efficient method to estimate wavefront aberrations. &lt;/p&gt;

&lt;p&gt;First I used Levenberg&#8211;Marquardt algorithm, as used by Josh Meyers in HSC work. In early stages of the project I convinced myself that the algorithm was prone to find only local minimum and was giving poor results. I then switched to using emcee algorithm, but this had similar problem. At the moment I am using Parallel-Tempering Ensemble MCMC algorithm which more efficiently explores the parameter space. Problem is that this is very slow and takes large amount of computational time (e.g., ~10 hours on 28 cores for a single donut).&lt;/p&gt;

&lt;p&gt;There are several avenues to explore:&lt;/p&gt;

&lt;p&gt;1. &lt;b&gt;Speeding up computation of individual donuts&lt;/b&gt;. This probably means breaking out from GALSIM -&amp;gt; potentially painful&lt;/p&gt;

&lt;p&gt;2. &lt;b&gt;Improving current code or the code that I know&lt;/b&gt;.  Do I really have to use cool methods such as parallel tempering? Can I get faster convergence, by e.g., evaluating code in stages or setting better initial values? Is it really true that LM settles to wrong local minima and I can not use it? Should I use nested sampling to converge faster?&lt;/p&gt;

&lt;p&gt;3. &lt;b&gt;Use methods from literature&lt;/b&gt;. I found two papers that give some details on how they calculated Zernike coefficients relatively cheaply, using iterative methods.&lt;br/&gt;
     Tokovinin &amp;amp; Heathcote 2006&lt;br/&gt;
     Roodman 2010 and connected DECcam papers&lt;br/&gt;
     +Bo Xin et al. algorithm, as mentioned in their papers and DM-Donuts slack channel&lt;/p&gt;




</description>
                <environment></environment>
        <key id="12024">PIPE2D-269</key>
            <summary>How to correctly and quickly estimate wavefront</summary>
                <type id="5" iconUrl="https://pfspipe.ipmu.jp/jira/secure/viewavatar?size=xsmall&amp;avatarId=10516&amp;avatarType=issuetype">Sub-task</type>
                            <parent id="11862">PIPE2D-243</parent>
                                    <priority id="10000" iconUrl="https://pfspipe.ipmu.jp/jira/images/icons/priorities/medium.svg">Normal</priority>
                        <status id="10002" iconUrl="https://pfspipe.ipmu.jp/jira/images/icons/statuses/generic.png" description="The issue is resolved, reviewed, and merged">Done</status>
                    <statusCategory id="3" key="done" colorName="green"/>
                                    <resolution id="10000">Done</resolution>
                                        <assignee username="ncaplar">ncaplar</assignee>
                                    <reporter username="ncaplar">ncaplar</reporter>
                        <labels>
                    </labels>
                <created>Thu, 7 Dec 2017 20:09:53 +0000</created>
                <updated>Mon, 18 Mar 2019 12:42:31 +0000</updated>
                            <resolved>Mon, 18 Mar 2019 12:42:31 +0000</resolved>
                                                                        <due></due>
                            <votes>0</votes>
                                    <watches>1</watches>
                                                                <comments>
                            <comment id="13102" author="ncaplar" created="Tue, 10 Apr 2018 15:51:58 +0000"  >&lt;p&gt;Update as of April 10:&lt;/p&gt;

&lt;p&gt;1.&#160;&lt;b&gt;Speeding up computation of individual donuts:&lt;/b&gt;&#160;This does not seem to be possible. The most time has been spent in fft computation. This is already quite optimized. I tried scipy, numpy, and galsim implementations and they are all basically the same. Only potential avenue is to go through direct c (e.g., cython). In the meantime, the added complexity of the code (inclusion of convolution by the fiber which drops toward the edges, inclusion of radiometric effect (flux in the exit pupil not uniformly distributed)) has added time overhead.&lt;/p&gt;

&lt;p&gt;2.&#160;&lt;b&gt;Improving current code or the code that I know:&lt;/b&gt;&#160;Not fully explored as I concentrated on the code working at the most basic level. At the moment I am just throwing cpu cores at the problem.&lt;/p&gt;

&lt;p&gt;3.&#160;&lt;b&gt;Use methods from literature&lt;/b&gt;. Same as above&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;

&lt;p&gt;&#160;&lt;/p&gt;</comment>
                            <comment id="14949" author="ncaplar" created="Mon, 11 Feb 2019 15:50:57 +0000"  >&lt;p&gt;I recommend closing this ticket. Some speed up has been achieved through evolution of the code. If I find that I am critically blocked by the speed of my code, I recommend reopening the new issue. &lt;/p&gt;</comment>
                            <comment id="15130" author="hassan" created="Mon, 18 Mar 2019 12:42:31 +0000"  >&lt;p&gt;Agree with Neven&apos;s last comment - some speed updates have been made, and further work in speed performance will be captured in future tickets.&lt;/p&gt;</comment>
                    </comments>
                    <attachments>
                    </attachments>
                <subtasks>
                    </subtasks>
                <customfields>
                                                <customfield id="customfield_10500" key="com.atlassian.jira.plugins.jira-development-integration-plugin:devsummary">
                        <customfieldname>Development</customfieldname>
                        <customfieldvalues>
                            
                        </customfieldvalues>
                    </customfield>
                                                                                                                                                                                                            <customfield id="customfield_10010" key="com.pyxis.greenhopper.jira:gh-lexo-rank">
                        <customfieldname>Rank</customfieldname>
                        <customfieldvalues>
                            <customfieldvalue>0|ii03on:</customfieldvalue>

                        </customfieldvalues>
                    </customfield>
                                                                                            <customfield id="customfield_10100" key="com.atlassian.jira.plugin.system.customfieldtypes:userpicker">
                        <customfieldname>Reviewers</customfieldname>
                        <customfieldvalues>
                            <customfieldvalue>hassan</customfieldvalue>

                        </customfieldvalues>
                    </customfield>
                                                                <customfield id="customfield_10005" key="com.pyxis.greenhopper.jira:gh-sprint">
                        <customfieldname>Sprint</customfieldname>
                        <customfieldvalues>
                                <customfieldvalue id="46">2DDRP-2019 D</customfieldvalue>

                        </customfieldvalues>
                    </customfield>
                                                                                                                                                    </customfields>
    </item>
</channel>
</rss>