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pip install logentries
Downloading/unpacking logentries
Running setup.py egg_info for package logentries
Traceback (most recent call last):
File "<string>", line 14, in <module>
File "/home/vagrant/build/logentries/setup.py", line 13, in <module>
long_description=open('README.rst').read(),
IOError: [Errno 2] No such file or directory: 'README.rst'
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
@travisbrady
travisbrady / siege_cohttp_output
Created December 22, 2014 23:43
Siege output from a run against Cohttp (lwt) hello world
Transactions: 999993 hits
Availability: 100.00 %
Elapsed time: 83.15 secs
Data transferred: 9.54 MB
Response time: 0.07 secs
Transaction rate: 12026.37 trans/sec
Throughput: 0.11 MB/sec
Concurrency: 830.26
Successful transactions: 999993
Failed transactions: 7
./test_net_async.native
err (lib/monitor.ml.Error_
((exn (Failure "SSL unsupported"))
(backtrace
("Raised by primitive operation at file \"lib/core_unix.ml\", line 111, characters 2-55"
"Called from file \"lib/interruptor.ml\", line 74, characters 16-132"
""))
(monitor
(((name try_with) (here ()) (id 2) (has_seen_error true)
(is_detached true) (kill_index 0)))))).
{
"objectType": "activity",
"id": "tag:search.twitter.com,2005:487332866842300416",
"postedTime": "2014-07-10T20:29:44.000Z",
"provider": {
"objectType": "service",
"displayName": "Twitter",
"link": "http://www.twitter.com"
},
"link": "http://twitter.com/Danie11eWi1cox/statuses/487332866842300416",
Rscript classify-autosplit.R "james.txt" "/Users/travisbrady/pp/" TRUE
YOLoading required package: methods
Loaded glmnet 1.9-8
randomForest 4.6-7
Type rfNews() to see new features/changes/bug fixes.
Loading required package: rJava
Loading required package: iterators
Loading required package: parallel
4HI7
@travisbrady
travisbrady / mean_stddev.rb
Created May 1, 2014 15:53
Ruby one-pass mean and stddev
# One pass mean and standard deviation in Ruby
def a_mean_std(a)
n = a.length.to_f
sum = 0.0
sq_sum = 0.0
for x in a
sum += x
sq_sum += x * x
end
mean = sum / n
def linspace(start, stop, num=50, endpoint=true)
start_f = start.to_f
stop_f = stop.to_f
step = (stop_f - start_f) / (num.to_f - (endpoint ? 1.0 : 0.0))
i = 1
n = num - 1
result = [start_f]
while i < n
result.push(result.last + step)
i += 1
@travisbrady
travisbrady / ocaml_gpr
Last active August 29, 2015 13:56
ocaml_gpr
################################
# train
$ ocaml_gpr -verbose -cmd train -model foo.model < train.data
target variance: 53980.91115
iter 1: MSLL=20677.0739875 SMSE=0.6434589 MAD=144.2473817 MAXAD=395.0879824
iter 1: |gradient|=406648.85928
result: MSLL=0.0000006 SMSE=1.0000000 MAD=186.1172019 MAXAD=488.0434778
####################################################
# Now apply, all data is just the mean of the series
@travisbrady
travisbrady / SN_newsmakers
Created October 14, 2013 22:52
SportsNation
1 290 Boston
2 59 Torii Hunter
3 55 Gawker
4 48 Sportsnation
5 45 Steve Bartman incident
6 32 Steve Horgan
7 30 Boston Red Sox
8 19 Chicago
9 17 Mike Epps
10 16 Colts
Facebook 21
YouTube 12
Twitter 12
Lk Bajaj 10
Absolut 9
United States 9
Adriana 8
yahoo 8
Linda Cunningham 6
Adelaide Raiders 5