Carlos, After looking through your code, I am pretty sure you are not feeding in the ship data properly. Please see the video I made explaining this: https://youtu.be/pBKqdmejYHI
Regards, --------- Matt Taylor OS Community Flag-Bearer Numenta On Mon, Feb 22, 2016 at 3:14 PM, carlos arenas <[email protected]> wrote: > You would run maritimeanomalies.py as you would run run.py in Geospatial > Tracking. First of all, it makes a conversion from the original format to > the one needed by the application (convertion.py). Then it calls run.py and > preprocesses the data (preprocess_data.py) grouping it by ship ID code > (MMSI) and deletes all the tracks with a time interval lower than 30s (the > actualization rate of the API is 2 min) or a difference lower than 0.03 > minutes in both latitude and longitude. Then it runs geospatial_anomaly.py > (It`s the same as in Geospatial tracking but it adds trackName to the exit > file). Once it has anomaly_scores.csv it creates from it a KML file to > present graphically the results. All the deeper stuff is the same as > Geospatial Tracking, I haven’t modified it. > Does this make any sense? > > 2016-02-22 23:24 GMT+01:00 carlos arenas <[email protected]>: >> >> Ok, thank you very much. >> One of the doubts I have is if modifiying some model parameters, like the >> size of the encoder vector, the column count, the cells per column or the >> synapses number I could improve the performance. >> >> Another doubt I have, but not so important, is if i can save the learning >> made by the system, avoiding having to introduce all my data every time. >> >> 2016-02-22 23:01 GMT+01:00 Matthew Taylor <[email protected]>: >>> >>> Thanks Carlos. I'll try to look into this tomorrow morning. >>> >>> By the way, I am working on getting access to a lot of geospatial data >>> for free from a local source. If I can get it (fingers crossed), it >>> will mean that I have a dataset I can experiment with to help solve >>> these types of problems, because this data set contains many multiple >>> tracks that could be analyzed in the same fashion as your data. >>> >>> --------- >>> Matt Taylor >>> OS Community Flag-Bearer >>> Numenta >>> >>> >>> On Mon, Feb 22, 2016 at 1:53 PM, carlos arenas <[email protected]> >>> wrote: >>> > The positions are supposed to have a two minutes interval. Here you >>> > have an >>> > extract of how the data gets to me and I have attached the principal >>> > modules >>> > of my code. The rest of it is the same as Geospatial Tracking. >>> > >>> > MMSI, LAT, LON, SPEED, COURSE, STATUS, TIMESTAMP >>> > 210047000,43.468670,-9.770435,82,29,0,2016-02-22T17:18:24 >>> > 212376000,43.243820,-10.084700,92,191,0,2016-02-22T17:20:11 >>> > 219023000,43.146660,-9.937616,105,349,0,2016-02-22T17:18:56 >>> > 224013910,43.066790,-9.612607,9,0,15,2016-02-22T17:19:18 >>> > 224123730,43.101720,-9.610230,21,226,7,2016-02-22T17:16:03 >>> > 235084298,43.426110,-9.640910,192,17,0,2016-02-22T17:20:47 >>> > 235096368,43.040520,-9.771927,120,358,7,2016-02-22T17:21:17 >>> > 244650165,42.986370,-9.797475,89,357,0,2016-02-22T17:20:28 >>> > 245947000,43.236970,-9.724459,94,27,0,2016-02-22T17:20:35 >>> > 247325500,43.293460,-9.927738,123,28,0,2016-02-22T17:20:13 >>> > 256612000,43.125930,-10.072610,116,185,0,2016-02-22T17:18:56 >>> > 257833000,43.380730,-9.852883,108,12,0,2016-02-22T17:21:24 >>> > 258649000,43.369920,-9.643563,168,30,0,2016-02-22T17:20:36 >>> > 304031000,43.204720,-10.103680,115,179,0,2016-02-22T17:19:33 >>> > 304050982,43.399410,-10.119990,139,207,0,2016-02-22T17:22:01 >>> > 351675000,43.376810,-10.049390,164,205,0,2016-02-22T17:16:14 >>> > 355289000,43.149670,-9.784833,180,7,0,2016-02-22T17:21:37 >>> > 428044000,42.999350,-9.777610,116,357,3,2016-02-22T17:19:22 >>> > 566577000,42.976810,-9.956157,122,1,0,2016-02-22T17:20:20 >>> > 636015262,43.199380,-9.751516,94,27,0,2016-02-22T17:19:09 >>> > 636015529,43.194890,-9.781404,137,1,0,2016-02-22T17:16:14 >>> >> >
