Hi David, thanks for the report. Unfortunately, I cannot tell what the root error is, because of https://github.com/numenta/nupic/issues/1815.
If you don't mind doing a little legwork, you might be able to help us identify the problem. 1. Download our source code by either: - git clone https://github.com/numenta/nupic.git - or get the tarball at https://github.com/numenta/nupic/archive/master.zip 2. Run the simple hotgym example code: - cd nupic/examples/opf/clients/hotgym/simple - python hotgym.py Does this give you any errors? Thanks, --------- Matt Taylor OS Community Flag-Bearer Numenta On Sat, Feb 21, 2015 at 5:43 PM, David Wood <[email protected]> wrote: > Hi all, > > I have recently read Jeff’s book and the Numenta white paper, and am very > interested in getting started with NuPIC. Unfortunately, I am having some > trouble getting a clean installation. > > My environment is a Rackspace cloud VM running: > - Ubuntu 14.10 (Utopic Unicorn) > - Python 2.7.8 > - mysql Ver 14.14 Distrib 5.6.19, for debian-linux-gnu (x86_64) using > EditLine wrapper > > I installed NuPIC as follows: > [[ > # apt-get install python-pip > # apt-get install python-dev > # pip install numpy > # pip install > https://s3-us-west-2.amazonaws.com/artifacts.numenta.org/numenta/nupic/releases/nupic-0.1.3-cp27-none-linux_x86_64.whl > ]] > > …and then attempted to run the “hot gym” predication example: > [[ > # cd ~/nupic/examples/opf/clients/hotgym/prediction/one_gym > # ./swarm.py > ]] > > The output of the swarm run is provided below my signature. > > Unfortunately, the numpy and nupic installations as well as the hotgym > example as seem to have significant numbers of python errors. The errors are > both trivial and apparently problematic, such as API changes. The swarm run > shows, for example, a TypeError. > > Should I expect this example to “just work” in the 0.13 release, or is my > environment too new? Would a downgrade of Ubuntu or Python “fix” the > problem? Does anyone have other suggestions? Thanks in advance! > > Regards, > Dave > -- > http://about.me/david_wood > > > The output of the swarm run was: > [[ > This script runs a swarm on the input data (rec-center-hourly.csv) and > creates a model parameters file in the `model_params` directory containing > the best model found by the swarm. Dumps a bunch of crud to stdout because > that is just what swarming does at this point. You really don't need to > pay any attention to it. > > ================================================= > = Swarming on rec-center-hourly data... > = Medium swarm. Sit back and relax, this could take awhile. > ================================================= > Generating experiment files in directory: > /root/nupic/examples/opf/clients/hotgym/prediction/one_gym/swarm... > Writing 313 lines... > Writing 113 lines... > done. > None > Successfully submitted new HyperSearch job, jobID=1002 > Evaluated 0 models > HyperSearch finished! > Worker completion message: None > > Results from all experiments: > ---------------------------------------------------------------- > Generating experiment files in directory: /tmp/tmpBvtweU... > Writing 313 lines... > Writing 113 lines... > done. > None > json.loads(jobInfo.results) raised an exception. Here is some info to help > with debugging: > jobInfo: _jobInfoNamedTuple(jobId=1002, client=u'GRP', clientInfo=u'', > clientKey=u'', cmdLine=u'$HYPERSEARCH', params=u'{"hsVersion": "v2", > "maxModels": null, "persistentJobGUID": > "8090e46e-ba32-11e4-ad72-bc764e202244", "useTerminators": false, > "description": {"includedFields": [{"fieldName": "timestamp", "fieldType": > "datetime"}, {"maxValue": 53.0, "fieldName": "kw_energy_consumption", > "fieldType": "float", "minValue": 0.0}], "streamDef": {"info": > "kw_energy_consumption", "version": 1, "streams": [{"info": "Rec Center", > "source": "file://rec-center-hourly.csv", "columns": ["*"]}]}, > "inferenceType": "TemporalMultiStep", "inferenceArgs": {"predictionSteps": > [1], "predictedField": "kw_energy_consumption"}, "iterationCount": -1, > "swarmSize": "medium"}}', jobHash='\x80\x90\xe4o\xba2\x11\xe4\xadr\xbcvN > "D', status=u'notStarted', completionReason=None, completionMsg=None, > workerCompletionReason=u'success', workerCompletionMsg=None, cancel=0, > startTime=None, endTime=None, results=None, engJobType=u'hypersearch', > minimumWorkers=1, maximumWorkers=4, priority=0, engAllocateNewWorkers=1, > engUntendedDeadWorkers=0, numFailedWorkers=0, lastFailedWorkerErrorMsg=None, > engCleaningStatus=u'notdone', genBaseDescription=None, genPermutations=None, > engLastUpdateTime=datetime.datetime(2015, 2, 22, 1, 31, 19), > engCjmConnId=None, engWorkerState=None, engStatus=None, > engModelMilestones=None) > jobInfo.results: None > EXCEPTION: expected string or buffer > Traceback (most recent call last): > File "./swarm.py", line 109, in <module> > swarm(INPUT_FILE) > File "./swarm.py", line 101, in swarm > modelParams = swarmForBestModelParams(SWARM_DESCRIPTION, name) > File "./swarm.py", line 78, in swarmForBestModelParams > verbosity=0 > File > "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", > line 276, in runWithConfig > return _runAction(runOptions) > File > "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", > line 217, in _runAction > returnValue = _runHyperSearch(runOptions) > File > "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", > line 160, in _runHyperSearch > metricsKeys=search.getDiscoveredMetricsKeys()) > File > "/usr/local/lib/python2.7/dist-packages/nupic/swarming/permutations_runner.py", > line 825, in generateReport > results = json.loads(jobInfo.results) > File > "/usr/local/lib/python2.7/dist-packages/nupic/support/object_json.py", line > 163, in loads > json.loads(s, object_hook=objectDecoderHook, **kwargs)) > File "/usr/lib/python2.7/json/__init__.py", line 351, in loads > return cls(encoding=encoding, **kw).decode(s) > File "/usr/lib/python2.7/json/decoder.py", line 366, in decode > obj, end = self.raw_decode(s, idx=_w(s, 0).end()) > TypeError: expected string or buffer > ]] >
