<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">Well, the fix then will break other codes that don’t have error and mean.<div class=""><br class=""></div><div class="">The proper one is pyalps.mean(x).</div><div class="">I will try to push the change tomorrow.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Best,</div><div class="">Michele</div><div class=""><br class=""></div><div class=""><br class=""><div><blockquote type="cite" class=""><div class="">On 29 Mar 2017, at 08:52, Dominik Schildknecht <<a href="mailto:dominik.schildknecht@psi.ch" class="">dominik.schildknecht@psi.ch</a>> wrote:</div><br class="Apple-interchange-newline"><div class="">
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<div bgcolor="#FFFFFF" text="#000000" class=""><p class="">Dear Michele,</p><p class="">thanks a lot. This helped. However I think I found a bug in this
function. The sort in the end of the function is non-functional as
there is no sort in the class MCScalarData (totally understandable
why). I assume the python interpreter will work with a default for
the comparison rather than raise an error. In the case of EXMC the
error of all the x-values are 0, such that the sort function shows
undefined behavior.<br class="">
</p><p class="">To circumvent the problem I propose to change the following line
in the ResultsToXY function<br class="">
</p><p class=""> order = np.argsort(res.x, kind = 'mergesort')</p><p class="">To:<br class="">
</p><p class=""> order = np.argsort([x.mean for x in res.x], kind =
'mergesort')</p><p class="">This would fix the bug locally (to give the expected result),
without changing the rest of the code basis. Is it possible to
incorporate this change in the code basis?</p><p class="">Best,</p><p class="">Dominik<br class="">
</p>
<br class="">
<div class="moz-cite-prefix">On 29.03.2017 07:45, Michele Dolfi
wrote:<br class="">
</div>
<blockquote cite="mid:0BA2DAD6-6D69-4132-8A5D-ECE6E5F55FEA@phys.ethz.ch" type="cite" class="">
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There a function for this, but it is note used a lot.
<div class=""><br class="">
</div>
<div class="">Here the doc string:</div>
<div class=""><br class="">
<font class="" face="Courier">def
ResultsToXY(sets,x,y,foreach=[]):<br class="">
""" combines observable x and y to build a list of DataSet
with y vs x<br class="">
<br class="">
this function is used to collect data from a hierarchy of
DataSet objects, to prepare plots or evaluation.<br class="">
the inner-most list has to contain one DataSet with
props['observable'] = x and one props['observable'] = y,<br class="">
this will be the pair x-y used in the collection.<br class="">
<br class="">
The parameters are:<br class="">
sets: hierarchy of datasets where the inner-most list
must contain to pair x-y<br class="">
x: the name of the observable to be used as
x-value of the collected results <br class="">
y: the name of the observable to be used as
y-value of the collected results <br class="">
foreach: an optional list of properties used for
grouping the results. A separate DataSet object is created for
each unique set of values of the specified parameers.<br class="">
<br class="">
The function returns a list of DataSet objects.<br class="">
"""<br class="">
</font><br class="">
</div>
<div class=""><br class="">
</div>
<div class="">Best,</div>
<div class="">Michele<br class="">
<div class=""><br class="">
</div>
<div class=""><br class="">
<div class="">
<blockquote type="cite" class="">
<div class="">On 28 Mar 2017, at 15:23, Dominik
Schildknecht <<a moz-do-not-send="true" href="mailto:dominik.schildknecht@psi.ch" class="">dominik.schildknecht@psi.ch</a>>
wrote:</div>
<br class="Apple-interchange-newline">
<div class="">
<div class="">Dear all,<br class="">
I wanted to know if it's already implemented to plot
two observables<br class="">
against each other with the combination of
pyalps.collectXY and<br class="">
pyalps.plot.plot.<br class="">
As an example I would like to be able to plot energy
vs. magnetization<br class="">
in an example like MC-07. This mainly arises as a
question if I want to<br class="">
use the exchange Monte Carlo formalism (thanks for
that, it seems to<br class="">
work great with very little modification to my code).
There the<br class="">
optimized temperature set is saved as an observable.
If I still want to<br class="">
be able to plot M vs. T I would need the ability to
plot two observables<br class="">
against each other. However it crashes in
alps/lib/pyalps/tools.py in<br class="">
the function collectXY at the line<br class="">
xvalue = np.array([data.props[x] for i in
range(len(data.y))])<br class="">
Is what I intend to do possible with collectXY?<br class="">
Best,<br class="">
Dominik<br class="">
<br class="">
-- <br class="">
Paul Scherrer Institut<br class="">
Dominik Schildknecht<br class="">
PhD Student<br class="">
WHGA/129<br class="">
CH-5232 Villigen-PSI<br class="">
Phone: +41 56 310 55 68<br class="">
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<pre class="moz-signature" cols="72">--
Paul Scherrer Institut
Dominik Schildknecht
PhD Student
WHGA/129
CH-5232 Villigen-PSI
Phone: +41 56 310 55 68
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