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!SESSION 2014-12-13 12:58:37.593 ----------------------------------------------- | |
eclipse.buildId=4.4.1.M20140925-0400 | |
java.version=1.8.0_25 | |
java.vendor=Oracle Corporation | |
BootLoader constants: OS=linux, ARCH=x86_64, WS=gtk, NL=en_US | |
Framework arguments: -product org.eclipse.epp.package.standard.product | |
Command-line arguments: -os linux -ws gtk -arch x86_64 -product org.eclipse.epp.package.standard.product | |
!ENTRY org.eclipse.equinox.p2.publisher.eclipse 4 0 2014-12-13 12:58:40.906 | |
!MESSAGE Unable to acquire PluginConverter service during generation for: /usr/share/eclipse/plugins/colorer. |
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def _load_data(data, n_prev = INIC): | |
docX = [] | |
docY = [] | |
for i in range(len(data)-n_prev): | |
docX.append(data.iloc[i:i+n_prev].as_matrix()) | |
docY.append(data.iloc[i+n_prev].as_matrix()) | |
alsX = np.array(docX) | |
alsY = np.array(docY) | |
return(alsX, alsY) |
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""" From: http://danielhnyk.cz/predicting-sequences-vectors-keras-using-rnn-lstm/ """ | |
from keras.models import Sequential | |
from keras.layers.core import TimeDistributedDense, Activation, Dropout | |
from keras.layers.recurrent import GRU | |
import numpy as np | |
def _load_data(data, steps = 40): | |
docX, docY = [], [] | |
for i in range(0, data.shape[0]/steps-1): | |
docX.append(data[i*steps:(i+1)*steps,:]) |
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---------------------------- LOGCAT ---------------------------- | |
--------- beginning of system | |
I/SystemServer( 765): NetworkTimeUpdateService | |
I/SystemServer( 765): CommonTimeManagementService | |
I/SystemServer( 765): CertBlacklister | |
I/SystemServiceManager( 765): Starting com.android.server.dreams.DreamManagerService | |
I/SystemServer( 765): Assets Atlas Service | |
I/SystemServiceManager( 765): Starting com.android.server.print.PrintManagerService |
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import pandas as pd | |
from random import random | |
flow = (list(range(1,10,1)) + list(range(10,1,-1)))*100 | |
pdata = pd.DataFrame({"a":flow, "b":flow}) | |
pdata.b = pdata.b.shift(9) | |
data = pdata.iloc[10:] * random() # some noise | |
import numpy as np |
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---------------------------- LOGCAT ---------------------------- | |
--------- beginning of system | |
I/auditd ( 0): Starting up | |
I/audit_log( 0): Previous audit logfile detected, rotating | |
E/audit_rules( 0): Could not read audit rules /data/misc/audit/audit.rules: No such file or directory | |
I/irsc_util( 0): irsc tool created:0xb7048020 | |
I/irsc_util( 0): Starting irsc tool | |
I/irsc_util( 0): Trying to open sec config file |
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jan 07 07:30:39 rpielec systemd[1]: time has been changed | |
jan 07 07:30:42 rpielec kernel: usb 1-1.3: new high-speed usb device number 6 using dwc_otg | |
jan 07 07:30:42 rpielec kernel: bluetooth: core ver 2.21 | |
jan 07 07:30:42 rpielec kernel: net: registered protocol family 31 | |
jan 07 07:30:42 rpielec kernel: bluetooth: hci device and connection manager initialized | |
jan 07 07:30:42 rpielec kernel: bluetooth: hci socket layer initialized | |
jan 07 07:30:42 rpielec kernel: bluetooth: l2cap socket layer initialized | |
jan 07 07:30:42 rpielec kernel: bluetooth: sco socket layer initialized | |
jan 07 07:30:42 rpielec kernel: bluetooth: hci uart driver ver 2.3 | |
jan 07 07:30:42 rpielec kernel: bluetooth: hci uart protocol h4 registered |
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# priklad vstupniho XML souboru - je nutne si ho upravit dle sveho | |
"""<?xml version="1.0" encoding="UTF-8"?> | |
<Pisemnost nazevSW="EPO MF ČR" verzeSW="39.15.1"> | |
<DPHSHV verzePis="01.02"> | |
<VetaD d_poddp="29.03.2017" dokument="SHV" k_uladis="DPH" mesic="8" rok="2017" shvies_forma="R" /> | |
<VetaP c_pop="379" c_pracufo="2401" c_ufo="455" dic="<DIC>" jmeno="Daniel" naz_obce="<A>" prijmeni="<PRIJMENI>" psc="<PSC>" stat="ČESKÁ REPUBLIKA" titul="Bc." typ_ds="F" ulice="<ULICE>" /> | |
<VetaR c_rad="1" c_vat="<VAT>" k_pln_eu="3" k_stat="GB" pln_hodnota="<CASTKA>" pln_pocet="1" por_c_stran="1" /> | |
</DPHSHV> | |
<Kontrola> | |
<Uzivatel jmeno="null" prijmeni="null" /> |
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import os | |
from time import time | |
import pandas as pd | |
from memory_profiler import memory_usage | |
FILENAME='compressed_df' | |
def get_size(flnm): | |
return round(os.path.getsize(flnm) / (1024*1024), 2) |
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$ spss2py -v 0 execute data/q2-scripts-reduced/reduced/1.hdf data/q2-scripts-reduced/processed/2_statements.csv data/q2-scripts-reduced/processed/2_out.hdf | |
20170703 21:03:05:root:INFO - ######### STARTING ######### | |
20170703 21:03:05:root:DEBUG - Received command line arguments: | |
Namespace(data='data/q2-scripts-reduced/reduced/1.hdf', func=<function execute at 0x7f30159812f0>, output='data/q2-scripts-reduced/processed/2_out.hdf', statements=<_io.TextIOWrapper name='data/q2-scripts-reduced/processed/2_statements.csv' mode='r' encoding='UTF-8'>, verbosity=0) | |
<class 'pandas.core.frame.DataFrame'> | |
Int64Index: 72423 entries, 0 to 72422 | |
Columns: 4861 entries, A1 to uid | |
dtypes: float16(4651), float32(7), int16(1), int8(184), object(18) | |
memory usage: 667.7+ MB | |
20170703 21:03:07:spss2py.executer:DEBUG - |
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