Re: ClimateDataCalculation
Posted: Mon May 25, 2015 3:02 pm
Hello, I have made a new version supporting gaps (it was actually a supported HighCharts api feature)
Code: Select all
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:18:45', 1432916325, u'Loftet', 25.600000000000001, u'', 10.0, 10.0, 25.579999999999998)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:21:09', 1432916469, u'Loftet', 25.600000000000001, u'', 10.0, 10.0, 25.579999999999998)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:21:57', 1432916517, u'Loftet', 25.5, u'', 10.0, 10.0, 25.57)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:22:45', 1432916565, u'Loftet', 25.5, u'', 10.0, 10.0, 25.550000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:24:21', 1432916661, u'Loftet', 25.5, u'', 10.0, 10.0, 25.550000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:25:09', 1432916709, u'Loftet', 25.5, u'', 10.0, 10.0, 25.530000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:25:57', 1432916757, u'Loftet', 25.5, u'', 10.0, 10.0, 25.52)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:26:45', 1432916805, u'Loftet', 25.5, u'', 10.0, 10.0, 25.5)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:27:33', 1432916853, u'Loftet', 25.5, u'', 10.0, 10.0, 25.5)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:28:21', 1432916901, u'Loftet', 25.5, u'', 10.0, 10.0, 25.5)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:29:09', 1432916949, u'Loftet', 25.5, u'', 10.0, 10.0, 25.5)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:29:57', 1432916997, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.48)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:30:45', 1432917045, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.469999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:31:33', 1432917093, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.449999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:32:21', 1432917141, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.43)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:33:09', 1432917189, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.420000000000002)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:33:57', 1432917237, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.399999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:34:45', 1432917285, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.399999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:35:33', 1432917333, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.399999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:36:21', 1432917381, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.399999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:37:09', 1432917429, u'Loftet', 25.399999999999999, u'', 10.0, 10.0, 25.399999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:37:57', 1432917477, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.379999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:38:45', 1432917525, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.370000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:39:33', 1432917573, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.350000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:40:21', 1432917622, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.329999999999998)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:41:09', 1432917669, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.32)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:42:45', 1432917765, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.300000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:43:33', 1432917813, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.300000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:44:21', 1432917861, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.300000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:45:09', 1432917909, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.300000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:46:45', 1432918005, u'Loftet', 25.300000000000001, u'', 10.0, 10.0, 25.300000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:47:33', 1432918054, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.280000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:48:21', 1432918101, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.27)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:49:09', 1432918150, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.25)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:49:57', 1432918198, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.23)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:51:33', 1432918293, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.219999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:52:21', 1432918341, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.199999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:53:09', 1432918389, u'Loftet', 25.199999999999999, u'', 10.0, 10.0, 25.199999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:54:45', 1432918486, u'Loftet', 25.100000000000001, u'', 10.0, 10.0, 25.18)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:55:33', 1432918534, u'Loftet', 25.100000000000001, u'', 10.0, 10.0, 25.170000000000002)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:56:21', 1432918581, u'Loftet', 25.100000000000001, u'', 10.0, 10.0, 25.149999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:57:09', 1432918629, u'Loftet', 25.100000000000001, u'', 10.0, 10.0, 25.129999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:57:57', 1432918677, u'Loftet', 25.100000000000001, u'', 10.0, 10.0, 25.120000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:58:45', 1432918726, u'Loftet', 25.0, u'', 10.0, 10.0, 25.079999999999998)
2015-06-02 09:26:36 INFO: (u'2015-05-29 18:59:33', 1432918774, u'Loftet', 25.0, u'', 10.0, 10.0, 25.07)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:00:21', 1432918822, u'Loftet', 25.0, u'', 10.0, 10.0, 25.050000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:01:09', 1432918869, u'Loftet', 25.0, u'', 10.0, 10.0, 25.030000000000001)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:01:57', 1432918917, u'Loftet', 25.0, u'', 10.0, 10.0, 25.02)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:02:45', 1432918966, u'Loftet', 25.0, u'', 10.0, 10.0, 25.0)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:03:33', 1432919014, u'Loftet', 25.0, u'', 10.0, 10.0, 25.0)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:04:21', 1432919062, u'Loftet', 25.0, u'', 10.0, 10.0, 25.0)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:05:09', 1432919110, u'Loftet', 25.0, u'', 10.0, 10.0, 25.0)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:05:57', 1432919158, u'Loftet', 25.0, u'', 10.0, 10.0, 25.0)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:08:21', 1432919301, u'Loftet', 24.899999999999999, u'', 10.0, 10.0, 24.98)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:09:09', 1432919350, u'Loftet', 24.899999999999999, u'', 10.0, 10.0, 24.969999999999999)
2015-06-02 09:26:36 INFO: (u'2015-05-29 19:09:57', 1432919398, u'Loftet', 24.899999999999999, u'', 10.0, 10.0, 24.949999999999999)I have nothing special, normally I just write a suitable python script if we are talking about the databases for this plugin. But I guess there could be many other alternatives. Have you tried with excel?1. What program do you use to look at the database?
Hmm, it looks like there should not be any gap here...2. I found the area with data for the gap
It works that way (or should). In the python code I am looking at the time when it is changing. Lets say it is now 18:19, I will then pick the first value found recorded at that time. The next will be the first value found at 18:20. And so onIs it possible in any way to read the closest data to the ten minutes instead of getting that gap
Sorry, I don't use that featureOh, btw: Do you get mails warning you about new posts in your threads?
Code: Select all
import sqlite3
def GetAllData(
dbName,
dbTableId
):
dbName = str(dbName)
conn = sqlite3.connect(dbName)
c = conn.cursor()
t = ((dbTableId),)
try:
c.execute('SELECT * FROM '+dbName.split('.')[0]+' WHERE tableId=?', t)
coll = c.fetchall()
conn.close()
return coll
except:
conn.close()
return None
rows = GetAllData('tempData.db', 'Loftet')
for row in rows:
print rowCode: Select all
import sqlite3
def GetAllData(
dbName,
dbTableId
):
dbName = str(dbName)
conn = sqlite3.connect(dbName)
c = conn.cursor()
t = ((dbTableId),)
try:
c.execute('SELECT * FROM '+dbName.split('.')[0]+' WHERE tableId=?', t)
coll = c.fetchall()
conn.close()
return coll
except:
conn.close()
return None
rows = GetAllData('tempData.db', 'Loftet')
fileHandle = None
fileHandle = open('dbExport.txt', 'a')
for row in rows:
if row[0].find('2015-05-29 21')> -1 or row[0].find('2015-05-29 23')> -1:
fileHandle.write(str(row)+'\r\n')
fileHandle.close()
print 'Export done'