268 lines
12 KiB
Python
268 lines
12 KiB
Python
###################################################################################################
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# Facade to JEP: Embedded Python
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###################################################################################################
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#Matplotlib won't work out of the box because it's default backend (Qt) uses signals, which only works in
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#the main thread. Ideally should find a fix, in order to mark the running thread as the main.
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#As a workaround, one can use the Tk backend:
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#
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#import matplotlib
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#matplotlib.use('TkAgg')
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#In principle just add JEP jar and library to the extensions folder.
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#
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#Alternatively on Linux:
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# Python 2:
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# - Add <python home>/lib/python3.X/site-packages/jep to LD_LIBRARY_PATH
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# - Add <python home>/lib/python3.X/site-packages/jep/jep-X.X.X.jar to the class path
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#
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#Python3:
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# - Add JEP library folder to LD_LIBRARY_PATH
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# - If using OpenJDK, add also python <python home>/lib folder to LD_LIBRARY_PATH
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# - Set LD_PRELOAD=<python home>/lib/libpython3.5m.so
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import sys
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import os
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import jep.Jep
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import jep.SharedInterpreter
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import jep.NDArray
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import java.lang.Thread
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import org.python.core.PyArray as PyArray
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import java.lang.String as String
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import java.util.List
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import java.util.Map
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import java.util.HashMap
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import ch.psi.pshell.scripting.ScriptUtils as ScriptUtils
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from startup import to_array, get_context, _get_caller, Convert, Arr
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__jep = {}
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def __get_jep():
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t = java.lang.Thread.currentThread()
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if not t in __jep:
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init_jep()
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return __jep[t]
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def __close_jep():
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t = java.lang.Thread.currentThread()
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if t in __jep:
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__jep[t].close()
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def init_jep():
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#TODO: Should do it but generates errors
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#__close_jep()
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j = jep.SharedInterpreter()
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try:
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#Faster, but statements must be complete
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j.setInteractive(False)
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except:
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pass # Removed in 4.2
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__jep[java.lang.Thread.currentThread()] = j
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j.eval("import sys")
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#sys.argv is not present in JEP and may be needed for certain modules (as Tkinter)
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j.eval("sys.argv = ['PShell']");
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#Add standard script path to python path
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j.eval("sys.path.append('" + get_context().setup.getScriptPath() + "')")
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#Redirect stdout
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j.eval("class JepStdout:\n" +
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" def write(self, str):\n" +
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" self.str += str\n" +
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" def clear(self):\n" +
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" self.str = ''\n" +
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" def flush(self):\n" +
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" pass\n")
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j.eval("sys.stdout=JepStdout()");
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j.eval("sys.stderr=JepStdout()");
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j.eval("sys.stdout.clear()")
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j.eval("sys.stderr.clear()")
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#Import reload on Python 3
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j.eval("try:\n" +
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" reload # Python 2.7\n" +
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"except NameError:\n" +
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" try:\n" +
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" from importlib import reload # Python 3.4+\n" +
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" except ImportError:\n" +
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" from imp import reload # Python 3.0 - 3.3\n")
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def __print_stdout():
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j=__get_jep()
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output = None
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err = None
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try:
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output = j.getValue("sys.stdout.str")
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err = j.getValue("sys.stderr.str")
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j.eval("sys.stdout.clear()")
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j.eval("sys.stderr.clear()")
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except:
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pass
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if (output is not None) and len(output)>0:
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print output
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if (err is not None) and len(err)>0:
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print >> sys.stderr, err
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def run_jep(script_name, vars = {}):
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global __jep
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script = get_context().scriptManager.library.resolveFile(script_name)
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if script is None :
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script= os.path.abspath(script_name)
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j=__get_jep()
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for v in vars:
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j.set(v, vars[v])
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try:
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j.runScript(script)
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finally:
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__print_stdout()
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def eval_jep(line):
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j=__get_jep()
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try:
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j.eval(line)
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finally:
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__print_stdout()
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def set_jep(var, value):
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j=__get_jep()
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j.set(var, value)
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def get_jep(var):
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j=__get_jep()
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return j.getValue(var)
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def call_jep(module, function, args = [], kwargs = {}, reload=False):
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j=__get_jep()
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if "/" in module:
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script = get_context().scriptManager.library.resolveFile(module)
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if "\\" in script:
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#Windows paths
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module_path = script[0:script.rfind("\\")]
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module = script[script.rfind("\\")+1:]
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else:
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#Linux paths
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module_path = script[0:script.rfind("/")]
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module = script[script.rfind("/")+1:]
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eval_jep("import sys")
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eval_jep("sys.path.append('" + module_path + "')")
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if module.endswith(".py"):
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module = module[0:-3]
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f = module+"_" + function+"_"+str(j.hashCode())
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try:
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if reload:
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eval_jep("import " + module)
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eval_jep("_=reload(" + module+")")
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eval_jep("from " + module + " import " + function + " as " + f)
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if (kwargs is not None) and (len(kwargs)>0):
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#invoke with kwargs only available in JEP>3.8
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hm=java.util.HashMap()
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hm.update(kwargs)
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#The only way to get the overloaded method...
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m = j.getClass().getMethod("invoke", [String, ScriptUtils.getType("[o"), java.util.Map])
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ret = m.invoke(j, [f, to_array(args,'o'), hm])
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else:
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ret = j.invoke(f, args)
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finally:
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__print_stdout()
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return ret
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#Converts pythonlist or Java array to numpy array
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def to_npa(data, dimensions = None, type = None):
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if (not isinstance(data, PyArray)) or (type is not None):
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data = to_array(data,'d' if type is None else type)
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if dimensions is None:
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return jep.NDArray(data)
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return jep.NDArray(data, dimensions)
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#recursivelly converts all NumPy arrays to Java arrys
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def rec_from_npa(obj):
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if isinstance(obj, jep.NDArray):
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ret = obj.data
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if len(obj.dimensions)>1:
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ret=Convert.reshape(ret, obj.dimensions)
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return ret
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if isinstance(obj, java.util.List) or isinstance(obj,tuple) or isinstance(obj,list):
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ret=[]
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for i in range(len(obj)):
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ret.append(rec_from_npa(obj[i]))
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if isinstance(obj,tuple):
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return type(ret)
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return ret
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if isinstance(obj, java.util.Map) or isinstance(obj,dict):
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ret = {} if isinstance(obj,dict) else java.util.HashMap()
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for k in obj.keys():
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ret[k] = rec_from_npa(obj[k])
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return ret
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return obj
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#recursivelly converts all Java arrays to NumPy arrys
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def rec_to_npa(obj):
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if isinstance(obj, PyArray):
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dimensions = Arr.getShape(obj)
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if len(dimensions)>1:
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obj = Convert.flatten(obj)
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return to_npa(obj, dimensions = dimensions)
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if isinstance(obj, java.util.List) or isinstance(obj,tuple) or isinstance(obj,list):
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ret=[]
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for i in range(len(obj)):
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ret.append(rec_to_npa(obj[i]))
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if isinstance(obj,tuple):
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return tuple(ret)
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return ret
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if isinstance(obj, java.util.Map) or isinstance(obj,dict):
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ret = {} if isinstance(obj,dict) else java.util.HashMap()
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for k in obj.keys():
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ret[k] = rec_to_npa(obj[k])
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return ret
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return obj
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def call_py(module, function, reload_function, *args, **kwargs):
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"""
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Calls a CPython function recursively crecursively converting Java arrays in arguments to NumPy,
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and NumPy arrays in return values to Java arrays.
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"""
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ret = call_jep(module, function, rec_to_npa(args), rec_to_npa(kwargs), reload=reload_function)
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return rec_from_npa(ret)
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def import_py(module, function):
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"""
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Adds a CPython function to globals, creating a wrapper call to JEP, with
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recurvive convertion of Java arrays in arguments to NumPy arrays,
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and NumPy arrays in return values to Java arrays.
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"""
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def jep_wrapper(*args, **kwargs):
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reload_function = jep_wrapper.reload
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jep_wrapper.reload = False
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print module, function, reload_function
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return call_py(module, function, reload_function, *args, **kwargs)
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jep_wrapper.reload=True
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_get_caller().f_globals[function] = jep_wrapper
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return jep_wrapper
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import_py("CPython/linfit", "linfit")
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import_py("CPython/gfitoff", "gfitoff")
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x=[0,1,2,3,4,5,6,7,8,9]
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y=[1,2,3,6,9,6,3,2,1,0]
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(p, x_fit, y_fit, R2) = linfit(x,y)
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#print "Fit: ", (p, x_fit, y_fit, R2)
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plot((y,y_fit), name=("data", "fit"),xdata=(x,x_fit))
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from mathutils import Gaussian
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x=to_array([-200.30429237268825, -200.2650700434188, -200.22115208318002, -199.9457671375377, -199.86345548879072, -199.85213073174933, -199.35687977133284, -199.13811861090275, -197.97304970346386, -197.2952215624348, -195.09076092936948, -192.92276048970703, -191.96871876227698, -189.49577852322938, -187.9652790409825, -183.63756456925222, -180.04899765472996, -178.43839623242422, -174.07311671294445, -172.0410133577918, -165.90824309893102, -160.99771795989466, -159.30176653939253, -154.27688897558514, -152.0854103810786, -145.75652847587313, -140.80843828908465, -139.23982133191495, -134.27073891256106, -132.12649284133064, -125.95947209775511, -121.00309550337462, -119.26736932643232, -114.2706655484383, -112.07393889578914, -105.72295990367157, -100.8088439880125, -99.2034906238494, -94.30042325164636, -92.15010048151461, -85.92203653534293, -81.03913275494665, -79.27412793784428, -74.33487658582118, -72.06274362408762, -65.76562628131825, -60.91255356825276, -59.20334389560392, -54.33286972659312, -52.19387171350535, -45.94978737932291, -41.03014719193582, -39.301602568238906, -34.35572209014114, -32.04464301272608, -25.8221033382824, -20.922074315528747, -19.21590299233186, -14.31090212502093, -12.217203140101386, -5.9283722049240435, -0.9863587170369246, 0.7408048387279834, 5.71126832601389, 7.972628957879352, 14.204559894256546, 19.11839959633025, 20.8218087836657, 25.678748486941828, 27.822718344586864, 34.062659474970715, 38.9745656819391, 40.77409719734158, 45.72080631619803, 47.974156754056835, 54.23453768983539, 59.12020360609568, 60.77306570712026, 65.70734521458867, 67.8344660434617, 74.03187028154134, 78.96532114824849, 80.76070945985495, 85.74802197591286, 87.9140889204674, 94.18082276873524, 99.25790470037091, 100.68454787413205, 105.7213026221542, 107.79483801526698, 113.99555681638138, 119.0707052529143, 120.72715813056156, 125.77551384921307, 127.91257836719551, 134.2011330887875, 139.23043006997628, 140.71673537840158, 145.76288138835983, 147.80216629676042, 154.06420451405637, 159.0846626604798, 160.76183155710717, 165.73699067536242, 167.9265357747636, 173.96705069576544, 178.2522282751915, 179.9042617354548, 183.54586165856657, 185.23269803071796, 189.41678143751972, 191.87149157986588, 192.8741468985015, 195.0241934550453, 195.966634211846, 197.9821647518146, 198.99006812859284, 199.33202054855676, 199.91897441965887, 200.11536227958896, 200.22280936469997, 200.25181179127208],'d')
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y=to_array([11.0, 6.0, 8.0, 5.0, 11.0, 7.0, 18.0, 11.0, 12.0, 10.0, 8.0, 6.0, 16.0, 4.0, 12.0, 9.0, 15.0, 14.0, 8.0, 20.0, 15.0, 8.0, 9.0, 11.0, 13.0, 12.0, 13.0, 15.0, 13.0, 20.0, 10.0, 7.0, 17.0, 11.0, 20.0, 13.0, 13.0, 23.0, 14.0, 10.0, 17.0, 15.0, 20.0, 16.0, 14.0, 13.0, 18.0, 22.0, 9.0, 20.0, 12.0, 14.0, 17.0, 19.0, 14.0, 14.0, 23.0, 19.0, 15.0, 20.0, 20.0, 21.0, 20.0, 23.0, 22.0, 15.0, 10.0, 17.0, 21.0, 15.0, 23.0, 23.0, 25.0, 18.0, 16.0, 21.0, 22.0, 16.0, 16.0, 14.0, 19.0, 20.0, 18.0, 20.0, 23.0, 13.0, 16.0, 20.0, 25.0, 15.0, 15.0, 17.0, 22.0, 26.0, 19.0, 30.0, 25.0, 17.0, 17.0, 23.0, 16.0, 27.0, 21.0, 21.0, 26.0, 27.0, 21.0, 17.0, 20.0, 20.0, 21.0, 19.0, 25.0, 19.0, 13.0, 23.0, 20.0, 20.0, 18.0, 20.0, 19.0, 25.0],'d')
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[off, amp, com, sigma] = gfitoff(x, y, off=None, amp=None, com=None, sigma=None)
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#print "Fit: ", [off, amp, com, sigma]
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g = Gaussian(amp, com, sigma)
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plot([y, [g.value(i)+off for i in x]], ["data", "fit"], xdata = x)
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