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Not my first rodeo
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betatim / serial.cpp
Created July 17, 2013 07:44
On my mac it compiles with: $ g++ -g serial.cpp -o serial -lboost_serialization-mt running it create dead_pixels.archive $ ./serial somewhere I have the magic line to add to the requirements file to get it to link to boost_serialisation ...
#include <fstream>
#include <map>
#include <boost/archive/binary_oarchive.hpp>
#include <boost/archive/binary_iarchive.hpp>
#include <boost/serialization/map.hpp>
int main() {
std::ofstream ofs("dead_pixels.archive", std::ios::binary);
The big velo tidy
inline void channel_neighbours(const LHCb::VPChannelID& seedChannel,
Pix* adjecent,
std::bitset<9>& adjecent_set) {
// Loop over the possible positions in the 3x3 cluster
// around the seedChannel
int pixY = (seedChannel).pixel_hp();
int pixX = (seedChannel).pixel_lp();
int chip = (seedChannel).chip();
// hardcoded for the compact VP design
// number of chips in a ladder and
std::vector<std::function<Matrix5d()>> covariances;
for (int i(0); i<10000000; ++i) {
// delay calculation by sending back a lambda
//r3 += m*c*m.transpose();
covariances.push_back([=]() {return m*c*m.transpose();});
}
for (auto fun: covariances) {
if (rand.Rndm() > 0.75) {
r3 += fun();
}
from collections import namedtuple
from pprint import pprint
import numpy as np
np.random.seed(12345)
import matplotlib.pyplot as plt
Appointment = namedtuple("Appointment", "scheduled late_by emergency")
import random
random.seed(12345)
class Dice(object):
def __init__(self, sides=6):
print "creating a dice with %i sides."%sides
self.sides = sides
# All sorts of stuff for setting up the Forward tracking
# itneresting stuff towards the bottom
FstForward = PrForwardTracking("FstForward")
FstForward.InputName = self.getProp("RootInTES") + "Track/VeloUTFst"
FstForward.OutputName = self.getProp("RootInTES") + "Track/Forward"
FstForward.addTool(PrForwardTool)
FstForward.PrForwardTool.AddUTHitsToolName = ""
# Now with the momentum estimate FstForward.PrForwardTool.UseMomentumEstimate = True
# MinPt determines the size of the search window, set # this to the lowest pT you want to be able to find
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from collections import namedtuple
Infos = namedtuple('Infos', ["bias"," threshold", "alignment"])
# information about runs 1234 and 1235
run_info = {1234: Infos(12.3, 2., 42.),
1235: Infos(12.2, 2.1, 42.3)}
# retrieve it
print run_info[1234]
@betatim
betatim / gist:a0f5c9ef5681e84a5e87
Created June 2, 2014 14:42
sklearn sample weights before they are ready!
$ git clone https://github.com/scikit-learn/scikit-learn.git
$ git remote add pprett https://github.com/pprett/scikit-learn.git
$ git remote add ndawe https://github.com/ndawe/scikit-learn.git
$ git fetch
$ git checkout -b weighted_scores ndawe/weighted_scores
$ git rebase master
$ git checkout master
$ git merge weighted_scores
$ git checkout -b gbrt-sample-weight pprett/gbrt-sample-weight
$ git rebase master