Das deutsche Python-Forum

Code: Alles auswählen

    forbidden = [23975, 24733, 24735]
    for index, ber in enumerate(bers):
        if not(index in forbidden):
            res.append(single_r_x13(ber,fc,r,index))
        else:
            res.append([np.nan] * fc)
        print("---------%s sekunden fuer Arima %s ------" % (((time.time() - start_time)/ (index + 1)), index))
    return res#np.array([single_r_x13(ber,fc,r) for ber in bers])

Code: Alles auswählen

def single_r_x13(ber,fc,r,c):
    #print data
    #r('library("seasonal")')
    try:
        print ber
        r.assign("rdata%s" % c, ber)
        #print(r("rdata%s" % c))
        ts_str = "my_ts%s <- ts(rdata%s, start=c(2012, 1), end=c(2014,12), frequency=12)" % (c,c)
        r(ts_str)
        
        r("ar%s <- seas(my_ts%s, forecast.save = 'forecasts')" % (c,c))

        r("res%s <- series(ar%s, 'forecast.forecasts')" % (c,c))

        forecast = r.get('res%s' % c)[:, 0][:fc]
        return forecast
    except:# TypeError:
        return [np.nan]*fc

Code: Alles auswählen

from functools import wraps
from datetime import datetime
import errno
import os
import signal
import time
import numpy as np


class TimeoutError(Exception):
    pass

def timeout(seconds=10, error_message=os.strerror(errno.ETIME)):
    def decorator(func):
        def _handle_timeout(signum, frame):
            raise TimeoutError(error_message)

        def wrapper(*args, **kwargs):
            signal.signal(signal.SIGALRM, _handle_timeout)
            signal.alarm(seconds)
            try:
                result = func(*args, **kwargs)
            finally:
                signal.alarm(0)
            return result

        return wraps(func)(wrapper)

    return decorator

@timeout(8)
def may_timeout_single_r_x13(ber, fc, r, index):
    return single_r_x13(ber, fc, r, index)

def single_r_x13(ber, fc, r, index):
    # irgendetwas wird diese Methode schon machen. Bei Index 2 und 3 braucht sie lange.
    if index in [2, 3]:
        time.sleep(20)  # Dauert sehr lange
    return [ber + r + index] * fc  # anything

def main():
    # irgendetwas fuer fc, r und bers setzen.
    fc = 2
    r = 5
    bers = range(6)
    res = []
    for index, ber in enumerate(bers):
        start_time = datetime.utcnow()
        try:
            result = may_timeout_single_r_x13(ber, fc, r, index)
        except TimeoutError:
            print(repr(e))
            result = [np.nan] * fc
        res.append(result)
        print("---------%s sekunden fuer Arima %s ------" % (datetime.utcnow() - start_time, index))
    print(res)
    return


if __name__ == '__main__':
    main()

Code: Alles auswählen

---------0:00:00.000018 sekunden fuer Arima 0 ------
---------0:00:00.000014 sekunden fuer Arima 1 ------
TimeoutError('Timer expired',)
---------0:00:08.000142 sekunden fuer Arima 2 ------
TimeoutError('Timer expired',)
---------0:00:08.000195 sekunden fuer Arima 3 ------
---------0:00:00.000019 sekunden fuer Arima 4 ------
---------0:00:00.000012 sekunden fuer Arima 5 ------
[[5, 5], [7, 7], [nan, nan], [nan, nan], [13, 13], [15, 15]]

Code: Alles auswählen

import numpy as np
import pyper as pr
import time 
from csv_read import read_in

#path_folder = r'/Users/Backup/'
#data = read_in('X.csv',path_folder)[0]
#fc=18

def r_x13(bers, fc):
    r = pr.R(RCMD='/usr/local/bin/R', use_numpy=True)
    r('library("seasonal")')
    
    if not (type(bers) is np.array):
        bers = np.array(bers)
    res = []
    start_time = time.time()
    forbidden = [23975, 24733, 24735]
    for index, ber in enumerate(bers):
        if not(index in forbidden):
            res.append(single_r_x13(ber,fc,r,index))
        else:
            res.append([np.nan] * fc)
        print("---------%s sekunden fuer Arima %s ------" % (((time.time() - start_time)/ (index + 1)), index))
    return res#np.array([single_r_x13(ber,fc,r) for ber in bers])

def single_r_x13(ber,fc,r,c):

    try:
        print ber
        r.assign("rdata%s" % c, ber)
        ts_str = "my_ts%s <- ts(rdata%s, start=c(2012, 1), end=c(2014,12), frequency=12)" % (c,c)
        r(ts_str)

        r("ar%s <- seas(my_ts%s, forecast.save = 'forecasts')" % (c,c))
        r("res%s <- series(ar%s, 'forecast.forecasts')" % (c,c))
        forecast = r.get('res%s' % c)[:, 0][:fc]
        return forecast
    except:# TypeError:
        return [np.nan]*fc