Python Timeseries.items方法代码示例

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import items [as 别名]
    def testUploadTsData(self):
        self.assert_(self.client.login(username='user1', password='password1'))
        response = self.client.put(
            "/api/tsdata/1/",
            encode_multipart(BOUNDARY,
                             {'timeseries_records': '2012-11-06 18:17,20,\n'}),
            content_type=MULTIPART_CONTENT)
        t = Timeseries(1)
        t.read_from_db(connection)
        self.assertEqual(response.status_code, 200)
        self.assertEqual(response.content, '1')
        self.assertEqual(len(t), 1)
        self.assertEqual(t.items(0)[0], datetime(2012, 11, 06, 18, 17, 0))
        self.assertEqual(t.items(0)[1], 20)
        self.client.logout()

        # Append two more records
        self.assert_(self.client.login(username='user1', password='password1'))
        response = self.client.put(
            "/api/tsdata/1/",
            encode_multipart(BOUNDARY,
                             {'timeseries_records':
                              '2012-11-06 18:18,21,\n2012-11-07 18:18,23,\n'}),
            content_type=MULTIPART_CONTENT)
        t = Timeseries(1)
        t.read_from_db(connection)
        self.assertEqual(response.status_code, 200)
        self.assertEqual(response.content, '2')
        self.assertEqual(len(t), 3)
        self.assertEqual(t.items(0)[0], datetime(2012, 11, 06, 18, 17, 0))
        self.assertEqual(t.items(0)[1], 20)
        self.assertEqual(t.items(1)[0], datetime(2012, 11, 06, 18, 18, 0))
        self.assertEqual(t.items(1)[1], 21)
        self.assertEqual(t.items(2)[0], datetime(2012, 11, 07, 18, 18, 0))
        self.assertEqual(t.items(2)[1], 23)
        self.client.logout()

        # Try to append an earlier record; should fail
        self.assert_(self.client.login(username='user1', password='password1'))
        response = self.client.put(
            "/api/tsdata/1/",
            encode_multipart(BOUNDARY,
                             {'timeseries_records': '2012-11-05 18:18,21,\n'}),
            content_type=MULTIPART_CONTENT)
        self.client.logout()
        t = Timeseries(1)
        t.read_from_db(connection)
        self.assertEqual(response.status_code, 409)
        self.assertEqual(len(t), 3)
        self.client.logout()

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import items [as 别名]
def regularize_raw_series(raw_series_db, proc_series_db, rs, re, ps, pe ):
    """
    This function regularize raw_series_db object from database and
    writes a processed proc_series_db in database.
    Raw series is a continuously increasing values time series,
    aggregating the water consumption. Resulting processed timeseries
    contains water consumption for each of its interval. I.e. if the
    timeseries is of 15 minutes time step, then each record contains
    the water consumption for each record period.
    """
    raw_series = TSeries(id=raw_series_db.id)
    raw_series.read_from_db(db.connection)
    # We keep the last value for x-checking reasons, see last print
    # command
    test_value = raw_series[raw_series.bounding_dates()[1]]
    time_step = ReadTimeStep(proc_series_db.id, proc_series_db)
    proc_series = TSeries(id=proc_series_db.id, time_step = time_step)
    # The following code can be used in real conditions to append only
    # new records to db, in a next version
    #if not pe:
    #    start = proc_series.time_step.down(rs)
    #else:
    #    start = proc_series.time_step.up(pe)
    # Instead of the above we use now:
    start = proc_series.time_step.down(rs)
    end = proc_series.time_step.up(re)
    pointer = start
    # Pass 1: Initialize proc_series
    while pointer<=end:
        proc_series[pointer] = float('nan')
        pointer = proc_series.time_step.next(pointer)
    # Pass 2: Transfer cummulative raw series to differences series:
    prev_s = 0
    for i in xrange(len(raw_series)):
        dat, value = raw_series.items(pos=i)
        if not math.isnan(value):
            raw_series[dat] = value-prev_s
            prev_s = value
    # Pass 3: Regularize step: loop over raw series records and distribute
    # floating point values to processed series
    for i in xrange(len(raw_series)):
        dat, value = raw_series.items(pos=i)
        if not math.isnan(value):
            # find previous, next timestamp of the proc time series
            d1 = proc_series.time_step.down(dat)
            d2 = proc_series.time_step.up(dat)
            if math.isnan(proc_series[d1]): proc_series[d1] = 0
            if math.isnan(proc_series[d2]): proc_series[d2] = 0
            if d1==d2: # if dat on proc step then d1=d2
                proc_series[d1] += value
                continue
            dif1 = _dif_in_secs(d1, dat)
            dif2 = _dif_in_secs(dat, d2)
            dif = dif1+dif2
            # Distribute value to d1, d2
            proc_series[d1] += (dif2/dif)*value
            proc_series[d2] += (dif1/dif)*value
    # Uncomment the following line in order to show debug information.
    # Usually the three following sums are consistent by equality. If
    # not equality is satisfied then there is a likelyhood of algorith
    # error
    print raw_series.sum(), proc_series.sum(), test_value
    proc_series.write_to_db(db=db.connection, commit=True) #False)
    #return the full timeseries
    return proc_series

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import items [as 别名]
Assuming that "dir" is the openmeteo directory, run as follows:
    export PYTHONPATH=dir:dir/enhydris
    export DJANGO_SETTINGS=settings
    ./oldopenmeteo2enhydris.sql

"""

import sys
from datetime import timedelta

from django.db import connection, transaction

from enhydris.hcore import models
from pthelma.timeseries import Timeseries

transaction.enter_transaction_management()
tms = models.Timeseries.objects.filter(time_step__id__in=[4,5])
for tm in tms:
    sys.stderr.write("Doing timeseries %d..." % (tm.id,))
    t = Timeseries(id=tm.id)
    nt = Timeseries(id=tm.id)
    t.read_from_db(connection)
    for (d, value) in t.items():
        d += timedelta(hours=1)
        assert(not d.minute and not d.hour and not d.second and d.day==1,
            "Invalid date "+str(d))
        nt[d] = value
    nt.write_to_db(connection, transaction=transaction, commit=False)
    sys.stderr.write(" Done\n")
transaction.commit()