# -*- coding: utf-8 -*-
"""
Created on Fri Sep 30 14:56:51 2016
@author: txia
retrieve log file from log server
"""
import os, sys
import params as ps
from datetime import datetime
import connectors
param = ps.Parameters()
class DataSourceRetriever():
def copy_files_from_remote_to_local(self, source, destination):
#use scp to copy the file 'source' to destination
sshconnector = connectors.SSHConnector(param)
sshconnector.createSCPClient()
sshconnector.scp(source, destination)
sshconnector.close()
def execute(self):
print 'execute starts.'
start_time = datetime.time()
print 'execute ends.'
end_time = datetime.time()
# -*- coding: utf-8 -*-
"""
Created on Fri Sep 23 07:20:09 2016
@author: txia
functions
"""
from datetime import datetime
import pandas as pd
import params
import json
##### functions for blob
p = params.Parameters()
tableIATA = pd.read_csv(filepath_or_buffer=p.path_IATAinfo,
header=None,
names=p.fields_IATAinfo)
# table of property information that found in blob 08-26 (whole day)
table_propertyInfo = pd.read_csv(
filepath_or_buffer=p.path_propertyInfo_0826blob,
header=None,
names=p.fields_propertyInfo)
################ functions for decoded blob
def lineClean(line):
#replace all "" in a line to "
#replace all \' by ""+' #s = s.replace("\\\'", "")
#replace \+digits by ""+digit -> combine these two, replace /
while (line.find('\"\"') != -1):
line = line.replace('\"\"', '\"')
line = line.replace(
# -*- coding: utf-8 -*-
"""
Created on Fri Sep 23 09:28:41 2016
@author: txia
main script:
load data, format data and import data to ES
"""
import params as ps
import connectors
import data_handlers
import pandas as pd
p = ps.Parameters()
table_hotelDespInfo_20minavailRS = pd.read_csv(
filepath_or_buffer=p.path_propertyInfo_0826_20minavailRS,
header=None,
names=p.fields_propertyInfo)
table_IATAinfo = pd.read_csv(filepath_or_buffer=p.path_IATAinfo,
header=None,
names=p.fields_IATAinfo)
table_singleAvailRQ = pd.read_csv(filepath_or_buffer=p.path_singleAvailRQ,
header=None,
names=p.fieldName_availRQ)
table_multiAvailRQ = pd.read_csv(filepath_or_buffer=p.path_multiAvailRQ,
header=None,
names=p.fieldName_availRQ)
table_availRQ = pd.concat([table_singleAvailRQ, table_multiAvailRQ])
#after concatenation, index should be reset, otherwise the index is not unique.
"""
import connectors as ct
import params as pm
import pandas as pd
import data_handlers
#pms = pm.Parameters()
#connectEx = ct.ElasticsearchConnector(pms.es_host, pms.es_port)
#data = []
#mapping={}
#for i in range(0, 100):
# data.append("{\"message\":{\"a\":\"asd\", \"temp_id\":"+str(i)+"}}")
#connectEx.execute("indexbulkex", mapping, "dd", data)
pms = pm.Parameters()
table_reserv = pd.read_csv(filepath_or_buffer=pms.path_reserv,
header=None,
names=pms.fieldName_reserv)
table_singleAvailRS = pd.read_csv(filepath_or_buffer=pms.path_singleAvailRS,
header=None,
names=pms.fieldName_singleAvailRS)
#result of group by
res_series = table_reserv.groupby(['chain_code',
'roomTypeCode'])['roomTypeCode'].count()
#rename it
res_series = res_series.rename('NbrReserv')
res_table = pd.DataFrame(res_series)
res_table.reset_index(inplace=True)
while depth < info.depth_max:
traced = funclib.trace_ray(rayO, rayD, info)
if not traced:
break
obj, M, N, col_ray = traced
# Reflection: create a new ray.
rayO, rayD = M + N * .0001, funclib.normalize(rayD - 2 * np.dot(rayD, N) * N)
depth += 1
col += reflection * col_ray
reflection *= obj.get('reflection', 1.)
array[i, :] = np.clip(col, 0, 1)
return Piece(inputdata[0], array)
global info
info = params.Parameters()
img = np.zeros((info.height, info.width, 3))
#start = timer()
# Loop through all pixels.
inputdata = []
mapping = {};
for j, y in enumerate(np.linspace(info.Screen[1], info.Screen[3], info.height)):
d = (j, y)
inputdata.append(d)
p = multiprocessing.Pool(multiprocessing.cpu_count())
pieces = p.map(computepiece, inputdata)
#print(timer()-start)
for piece in pieces:
def setUp(self):
self.params = params.Parameters()
self.params.fluor_frame_params.phase_file = 'Images/1hOxa_1_w1Phase.TIF'
self.params.fluor_frame_params.fluor_file = 'Images/1hOxa_1_w1Phase.TIF'
self.ehooke = ehooke.EHooke(self.params)
}
Energy = {
'0': '12.95',
'30': '16.027',
'45': '21.71',
'60': '36.55',
'70': '70.0',
'25.90': '25.90',
'51.80': '51.80',
'103.60': '103.60'
}
te = 15 // 0.025 #default equilibration time
t_eq = int(fp * 0.025) + 1
###### Chosen Input Parameters
params.Parameters(temperature, energy)
name = 'a' + Angle[angle] + 't' + Temperature[temperature] + 'e' + Energy[
energy] # shorthand notation "a<rad>t<K>e<[float]meV>"
nameS = 'a' + angle + 't' + Temperature[temperature] + 'e' + Energy[
energy].split('.')[0] # shorthand "a<deg>t<K>e<[int]meV>"
nameAng = angle + u"\u00b0, " + temperature + ' K, ' + Energy[
energy] + ' meV' # notation for titles "[deg], [temp] K, [energy] meV"
''' # Ar-Pt analysis
g.jobs = (7331694, 7331705, 7331706, 7331713, 7331723, 7344079, 7344080, 7344081)
name = 'Pta'+Angle[angle]+'t'+Temperature[temperature]+'e'+Energy[energy]
'''
surface = '111'
in_folder = g.HOME + '/lammps/' + surface + '/' + name + '/'
from pathlib import Path
home = str(Path.home())
