# autoplot.py v1.53 # do not edit this file, changes will be lost.
# See "1.53" below, and in org.virbo.jythonsupport.JythonUtil
# This is copied into each enduser's autoplot_data/jython folder to be picked up
# along with all the other python codes.
from org.virbo.dsops.Ops import *
from org.virbo.jythonsupport.JythonOps import *
from org.virbo.jythonsupport.Util import *
from org.virbo.dataset import QDataSet
from org.virbo.dsutil.BinAverage import *
from org.virbo.dsutil import DataSetBuilder
_autoplot_jython_version= 1.53
#_autoplot_jython_version= float(getAutoplotScriptingVersion()[1:])
from org.das2.datum import DatumRange, Units, DatumRangeUtil, TimeUtil
from java.net import URL, URI
from org.das2.datum import TimeParser
# security concerns
#from java.io import File
#from org.das2.util.filesystem import FileSystem
#from org.das2.fsm import FileStorageModel
from org.virbo.datasource.DataSetURI import getFile
from org.virbo.datasource.DataSetURI import downloadResourceAsTempFile
#import java
#import org
# end, security concerns.
# jython is tricky with single-jar releases, and using star imports to find classes doesn't work.
#import org.das2
#import org.das2.dataset
#import org.das2.dataset.NoDataInIntervalException
#import org.das2.graph
params= dict()
_paramMap= dict()
_paramSort= []
import operator.isNumberType
# name is the name of the input parameter.
# deflt is the default value for the input parameter.
# doc is any documentation for the parameter.
# constraint is used to declare any constraints, presently one of: a list of enumerated values, or a dictionary with VALID_MIN, VALID_MAX and other relevant QDataSet properties.
def getParam( name, deflt, doc='', constraint='' ):
"""get the parameter from the URI
- name is the name of the input parameter.
- deflt is the default value for the input parameter.
- doc is any documentation for the parameter.
- constraint is used to declare any constraints, presently one of: a list of enumerated values, or a dictionary with VALID_MIN, VALID_MAX and other relevant QDataSet properties.
"""
if ( type(name).__name__=='int' ):
name= 'arg_%d' % name
_paramMap[ name ]= [ name, deflt, doc, constraint ]
_paramSort.append( name )
if type(params) is dict:
if params.has_key(name):
t= type(deflt) # Ed demonstrated this allows some pretty crazy things, e.g. open file, so be careful...
return t(params[name])
else:
return deflt
else:
print 'in jython script, variable params was overriden.'
return deflt
outputParams= dict()
_outputParamMap= dict()
_outputParamSort= []
# name is the name of the output parameter.
# value is the value of the output parameter.
# doc is any documentation for the output parameter.
# constraint is used to declare any constraints, presently one of: a list of enumerated values, or a dictionary with VALID_MIN, VALID_MAX and other relevant QDataSet properties.
def setOutputParam( name, value, doc='', constraint='' ):
_outputParamMap[ name ]= [ name, value, doc, constraint ]
_outputParamSort.append( name )
globals()[name]= value #TODO: this isn't working
if type(outputParams) is dict:
outputParams[name]= value
else:
raise Exception( 'in jython script, variable outputParams was overriden.' )
# invokeLater command is a scientist-friendly way to define a function that
# is called on a different thread.
import java.lang.Thread as _Thread
import java.lang.Runnable as _Runnable
class InvokeLaterRunnable( _Runnable ):
def __init__( self, fun, args, kw ):
self.fun= fun
self.args= args
self.kw= kw
def run( self ):
self.fun( *self.args, **self.kw )
def invokeLater( functn, *args, **kw ):
"invoke the function later. It should be followed by the parameters passed to the function"
r= InvokeLaterRunnable( functn, args, kw )
# Ed suggests this use ThreadPoolExecutor
_Thread(r,'invokeLater').start()