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that was weird

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hiro98 2020-05-07 21:45:30 +02:00
parent 06416830a9
commit e9e5805cc5
5 changed files with 11 additions and 5 deletions
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16
prog/python/qqgg/parton_density_function_stuff.org
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@ -676,14 +676,14 @@ figure out the cpu mapping.
proc="auto",
report_efficiency=True,
upper_bound=pb_to_gev(xs_int_res.maximum),
cache="cache/pdf/total_xs_1000_000",
cache="cache/pdf/total_xs_1000_000_2",
status_path="/tmp/status1"
)
eff
#+end_src
#+RESULTS:
: 0.0023869765050168546
: 0.002390855461178507
The efficiency is still quite horrible, but at least an order of
mag. better than with cosθ.
@ -698,10 +698,16 @@ Let's look at a histogramm of eta samples.
#+RESULTS:
:RESULTS:
: 1000000
[[file:./.ob-jupyter/77494a4df478f6ad80a17e68473d648e0384c145.png]]
[[file:./.ob-jupyter/cfe23f7e455b85ed6c8818447761b5934382fb29.png]]
:END:
#+RESULTS:
#+begin_src jupyter-python :exports both :results raw drawer
result[:, 0].min()
#+end_src
#+RESULTS:
: -0.9999856686520736
#+begin_src jupyter-python :exports both :results raw drawer
yoda_file = yoda.read("../../runcards/pp/analysis/Analysis.yoda")
@ -718,8 +724,8 @@ Let's look at a histogramm of eta samples.
#+RESULTS:
:RESULTS:
: <matplotlib.legend.Legend at 0x7fe0b0570550>
[[file:./.ob-jupyter/26dc7431fbfd0c82d5d216653b3be99e09d6f0ca.png]]
: <matplotlib.legend.Legend at 0x7fdfb8a7edf0>
[[file:./.ob-jupyter/bd59d61da1b968f792b44024f13cd82400341f50.png]]
:END:
Hah! there we have it!