Menu
▾
▴
[moose-devel] [PATCH 11/19] Remove some unnecessary .keys() and list() calls
|
From: Zbigniew Jędrzejewski-S. <zb...@in...> - 2014-04-01 21:10:39
|
This makes the code more palatable for 2to3, which then doesn't
try to wrap all uses of .keys() with list().
---
python/moose/alternate.py | 8 +++----
python/moose/graphutil.py | 2 +-
python/moose/hdfutil.py | 28 ++++++++++------------
python/moose/moose.py | 6 ++---
python/moose/moose_py3k.py | 6 ++---
python/moose/multiscale/core/simulator.py | 4 ++--
python/moose/multiscale/helper/graph_methods.py | 4 ++--
python/moose/multiscale/helper/moose_methods.py | 1 +
python/moose/multiscale/parser/ChannelML.py | 6 ++---
python/moose/multiscale/parser/MorphML.py | 4 ++--
python/moose/multiscale/parser/utils.py | 2 +-
python/moose/neuroml/ChannelML.py | 6 ++---
python/moose/neuroml/MorphML.py | 4 ++--
python/moose/neuroml/utils.py | 2 +-
python/moose/neuroml2/converter.py | 3 ++-
python/moose/neuroml2/generated_neuroml.py | 5 +---
python/moose/neuroml2/hhfit.py | 2 +-
python/moose/xmls_to_network/.noweb/main.nw | 6 ++---
python/moose/xmls_to_network/core/hhfit.py | 2 +-
python/moose/xmls_to_network/core/multiscale.py | 2 +-
.../moose/xmls_to_network/core/neuroml2_parser.py | 5 +---
.../moose/xmls_to_network/helper/graph_methods.py | 4 ++--
python/moose/xmls_to_network/parser/nml_parser.py | 5 +---
.../generatedNEURON/NEURONUtils/NEURONSimUtils.py | 2 +-
.../NeuroMLUtils/NetworkMLHDF5Handler.py | 8 +++----
.../NeuroMLUtils/NetworkMLSaxHandler.py | 16 ++++++-------
.../twoNeurons/generatedNEURON/twoNeurons.hoc | 4 ++--
.../NeuroMLUtils/NetworkMLHDF5Handler.py | 8 +++----
.../NeuroMLUtils/NetworkMLSaxHandler.py | 10 ++++----
.../generatedPyNN/PyNNUtils/PyNNUtils.py | 4 ++--
30 files changed, 80 insertions(+), 89 deletions(-)
diff --git a/python/moose/alternate.py b/python/moose/alternate.py
index 24a0d41..ccd4f93 100644
--- a/python/moose/alternate.py
+++ b/python/moose/alternate.py
@@ -669,7 +669,7 @@ class Neutral(object):
return self.oid_.getFieldNames(ftype)
def getNeighbors(self, fieldName):
- if fieldName in getFieldDict(self.className).keys():
+ if fieldName in getFieldDict(self.className):
return [eval('%s("%s")' % (id_[0].getField('class'), id_.getPath())) for id_ in self.oid_.getNeighbors(fieldName)]
raise ValueError('%s: no such field on %s' % (fieldName, self.path))
@@ -885,8 +885,8 @@ def showfield(element, field='*', showtype=False):
element = Neutral(element)
if field == '*':
value_field_dict = getFieldDict(element.className, 'valueFinfo')
- max_type_len = max([len(dtype) for dtype in value_field_dict.values()])
- max_field_len = max([len(dtype) for dtype in value_field_dict.keys()])
+ max_type_len = max(len(dtype) for dtype in value_field_dict.values())
+ max_field_len = max(len(dtype) for dtype in value_field_dict)
print()
print('[', element.path, ']')
for key, dtype in value_field_dict.items():
@@ -1003,7 +1003,7 @@ def update_class(cls, class_id):
def define_class(class_id):
"""Define a class based on Cinfo element with Id=class_id."""
class_name = class_id[0].getField('name')
- if class_name in globals().keys():
+ if class_name in globals():
return
base = class_id[0].getField('baseClass')
if base != 'none':
diff --git a/python/moose/graphutil.py b/python/moose/graphutil.py
index c62db9f..13216f9 100644
--- a/python/moose/graphutil.py
+++ b/python/moose/graphutil.py
@@ -171,7 +171,7 @@ class TestMooseGraph(unittest.TestCase):
def test_edgelabels(self):
for ee in self.graph.edges():
- keys = self.graph.edge[ee[0]][ee[1]].keys()
+ keys = self.graph.edge[ee[0]][ee[1]]
self.assertTrue('src' in keys)
self.assertTrue('dest' in keys)
diff --git a/python/moose/hdfutil.py b/python/moose/hdfutil.py
index a17ff5a..b7d9ce6 100644
--- a/python/moose/hdfutil.py
+++ b/python/moose/hdfutil.py
@@ -85,6 +85,7 @@
# Code:
from __future__ import print_function
+from future_builtins import zip
import moose as moose__
import numpy as np
import h5py as h5
@@ -122,19 +123,17 @@ def get_rec_dtype(em):
print('Creating entries for class:', obj.className)
fielddict = moose__.getFieldDict(obj.className, 'valueFinfo')
print(fielddict)
- keys = sorted(list(fielddict.keys()))
- fields = [] # [('path', 'S1024')]
- for fieldname in keys:
- ftype = fielddict[fieldname]
- # If we do not have the type of this field in cpp-np data
- # type map, skip it. We can handle vectors as nested
- # table, but the problem with that is numpy requires all
- # entries to have a fixed size for this table. Since
- # vectors can have arbitrary length, we cannot get such a
- # fixed size without checking the size of the vector field
- # in all elements.
- if ftype in cpptonp:
- fields.append((fieldname, cpptonp[ftype]))
+
+ # If we do not have the type of this field in cpp-np data
+ # type map, skip it. We can handle vectors as nested
+ # table, but the problem with that is numpy requires all
+ # entries to have a fixed size for this table. Since
+ # vectors can have arbitrary length, we cannot get such a
+ # fixed size without checking the size of the vector field
+ # in all elements.
+ fields = [(fieldname, cpptonp[ftype]) # [('path', 'S1024')]
+ for fieldname, ftype in sorted(fielddict.items())
+ if ftype in cpptonp]
dtype_table[obj.className] = np.dtype(fields)
return dtype_table[obj.className]
@@ -257,7 +256,7 @@ def savestate(filename=None):
print('Creating entries for class:', obj.className)
fielddict = moose__.getFieldDict(obj.className, 'valueFinfo')
print(fielddict)
- keys = sorted(list(fielddict.keys()))
+ keys = sorted(fielddict)
fields = [] # [('path', 'S1024')]
for fieldname in keys:
ftype = fielddict[fieldname]
@@ -309,7 +308,6 @@ def restorestate(filename):
if f.startswith('set_') and f not in ['set_this', 'set_name', 'set_lastDimension', 'set_runTime'] and not f.startswith('set_num_')]
with h5.File(filename, 'r') as fd:
typeinfo = fd['/metadata/typeinfo'][:]
- classdict = {}
dimsdict = dict(zip(typeinfo['path'], typeinfo['dims']))
classdict = dict(zip(typeinfo['path'], typeinfo['class']))
parentdict = dict(zip(typeinfo['path'], typeinfo['parent']))
diff --git a/python/moose/moose.py b/python/moose/moose.py
index af62d19..e995ab6 100644
--- a/python/moose/moose.py
+++ b/python/moose/moose.py
@@ -162,10 +162,10 @@ def showfield(el, field='*', showtype=False):
el = element(el)
if field == '*':
value_field_dict = getFieldDict(el.className, 'valueFinfo')
- max_type_len = max([len(dtype) for dtype in list(value_field_dict.values())])
- max_field_len = max([len(dtype) for dtype in list(value_field_dict.keys())])
+ max_type_len = max(len(dtype) for dtype in value_field_dict.values())
+ max_field_len = max(len(dtype) for dtype in value_field_dict)
print('\n[', el.path, ']')
- for key, dtype in list(value_field_dict.items()):
+ for key, dtype in value_field_dict.items():
if dtype == 'bad' or key == 'this' or key == 'dummy' or key == 'me' or dtype.startswith('vector') or 'ObjId' in dtype:
continue
value = el.getField(key)
diff --git a/python/moose/moose_py3k.py b/python/moose/moose_py3k.py
index f4c5302..0a8e82d 100644
--- a/python/moose/moose_py3k.py
+++ b/python/moose/moose_py3k.py
@@ -156,10 +156,10 @@ def showfield(elem, field='*', showtype=False):
elem = element(elem)
if field == '*':
value_field_dict = getFieldDict(elem.className, 'valueFinfo')
- max_type_len = max([len(dtype) for dtype in list(value_field_dict.values())])
- max_field_len = max([len(dtype) for dtype in list(value_field_dict.keys())])
+ max_type_len = max(len(dtype) for dtype in value_field_dict.values())
+ max_field_len = max(len(dtype) for dtype in value_field_dict)
print('\n[', elem.path, ']')
- for key, dtype in list(value_field_dict.items()):
+ for key, dtype in value_field_dict.items():
if dtype == 'bad' or key == 'this' or key == 'dummy' or key == 'me' or dtype.startswith('vector') or 'ObjId' in dtype:
continue
value = elem.getField(key)
diff --git a/python/moose/multiscale/core/simulator.py b/python/moose/multiscale/core/simulator.py
index 03f519b..ed6ffb6 100644
--- a/python/moose/multiscale/core/simulator.py
+++ b/python/moose/multiscale/core/simulator.py
@@ -320,7 +320,7 @@ class Simulator:
# for i, var in enumerate(variables):
# varType, varName, plotXml = var
# varName = varType + varName
-# assert varName in self.tableDict.keys()
+# assert varName in self.tableDict
# configDict = self.configurePlot(plotXml)
# yvec, xvec = self.getPlotData(varName)
# pylab.subplot(self.totalPlots, 1, i)
@@ -401,7 +401,7 @@ class Simulator:
def getPlotData(self, varName):
"""Get the plot data from dictionary
"""
- assert varName in self.tableDict.keys(), "{} not found in {}".format(
+ assert varName in self.tableDict, "{} not found in {}".format(
varName
, self.tableDict.keys()
)
diff --git a/python/moose/multiscale/helper/graph_methods.py b/python/moose/multiscale/helper/graph_methods.py
index b5d1360..6135e5c 100644
--- a/python/moose/multiscale/helper/graph_methods.py
+++ b/python/moose/multiscale/helper/graph_methods.py
@@ -46,7 +46,7 @@ def write_dot(g, filename):
for n in g.nodes():
i += 1
nodeLabel = "[label=\"\"".format(i)
- if 'proximal' in g.node[n].keys():
+ if 'proximal' in g.node[n]:
x = (float(g.node[n]['proximal'].get('x')) + float(g.node[n]['distal'].get('x')))/2
y = (float(g.node[n]['proximal'].get('y')) + float(g.node[n]['distal'].get('y')))/2
z = (float(g.node[n]['proximal'].get('z')) + float(g.node[n]['distal'].get('z')))/2
@@ -65,7 +65,7 @@ def write_dot(g, filename):
for (f, t) in g.edges():
edge = g.node[f]['label'] + " -> " + g.node[t]['label']
edge += " ["
- if 'synapse' in g.edge[f][t].keys():
+ if 'synapse' in g.edge[f][t]:
# color this edge and make it look like a synapse
edge += " label=\"{0}\",".format(g.edge[f][t]['id'])
edge += "color=blue,style=dotted,"
diff --git a/python/moose/multiscale/helper/moose_methods.py b/python/moose/multiscale/helper/moose_methods.py
index e3e9d68..f19c0a1 100644
--- a/python/moose/multiscale/helper/moose_methods.py
+++ b/python/moose/multiscale/helper/moose_methods.py
@@ -8,6 +8,7 @@ Last modified: Tue Jan 28, 2014 10:31PM
"""
from __future__ import print_function
+from future_builtins import filter
__author__ = "Dilawar Singh"
__copyright__ = "Copyright 2013, NCBS Bangalore"
diff --git a/python/moose/multiscale/parser/ChannelML.py b/python/moose/multiscale/parser/ChannelML.py
index 48f642e..e1a819d 100644
--- a/python/moose/multiscale/parser/ChannelML.py
+++ b/python/moose/multiscale/parser/ChannelML.py
@@ -226,7 +226,7 @@ class ChannelML:
q10sets = IVrelation.findall('./{'+self.cml+'}q10_settings')
for q10settings in q10sets:
# self.temperature from neuro.utils
- if 'gate' in list(q10settings.attrib.keys()):
+ if 'gate' in q10settings.attrib:
if q10settings.attrib['gate'] == self.gate_name:
self.setQ10(q10settings)
break
@@ -400,12 +400,12 @@ class ChannelML:
def setQ10(self, q10settings):
- if 'q10_factor' in list(q10settings.attrib.keys()):
+ if 'q10_factor' in q10settings.attrib:
expTemp = float(q10settings.attrib['experimental_temp'])
self.q10factor = float(q10settings.attrib['q10_factor']) ** (
( self.temperature - expTemp) /10.0
)
- elif 'fixed_q10' in list(q10settings.attrib.keys()):
+ elif 'fixed_q10' in q10settings.attrib:
self.q10factor = float(q10settings.attrib['fixed_q10'])
diff --git a/python/moose/multiscale/parser/MorphML.py b/python/moose/multiscale/parser/MorphML.py
index d492541..e658d04 100644
--- a/python/moose/multiscale/parser/MorphML.py
+++ b/python/moose/multiscale/parser/MorphML.py
@@ -285,7 +285,7 @@ class MorphML():
cablegroups = cable.findall(".//{"+self.meta+"}group")
for cablegroup in cablegroups:
cablegroupname = cablegroup.text
- if cablegroupname in list(self.cablegroupsDict.keys()):
+ if cablegroupname in self.cablegroupsDict:
self.cablegroupsDict[cablegroupname].append(cableid)
else:
self.cablegroupsDict[cablegroupname] = [cableid]
@@ -306,7 +306,7 @@ class MorphML():
"""
synLocs = cell.findall(".//{"+self.nml+"}potential_syn_loc")
for psl in synLocs:
- if 'synapse_direction' in list(psl.attrib.keys()):
+ if 'synapse_direction' in psl.attrib:
if psl.attrib['synapse_direction'] in ['post']:
self.set_group_compartment_param(
cell
diff --git a/python/moose/multiscale/parser/utils.py b/python/moose/multiscale/parser/utils.py
index 18e2ae2..749c28d 100644
--- a/python/moose/multiscale/parser/utils.py
+++ b/python/moose/multiscale/parser/utils.py
@@ -196,7 +196,7 @@ def keepOnlyInclude(network, onlyInclude):
populations = network.find(".//{"+nml_ns+"}populations")
for population in network.findall(".//{"+nml_ns+"}population"):
popname = population.attrib["name"]
- if popname in list(includeCellsDict.keys()):
+ if popname in includeCellsDict:
includecellids = includeCellsDict[popname]
instances = population.find(".//{"+nml_ns+"}instances")
for instance in instances.findall(".//{"+nml_ns+"}instance"):
diff --git a/python/moose/neuroml/ChannelML.py b/python/moose/neuroml/ChannelML.py
index 830ee4b..3cc3fc6 100644
--- a/python/moose/neuroml/ChannelML.py
+++ b/python/moose/neuroml/ChannelML.py
@@ -149,7 +149,7 @@ class ChannelML():
self.gate_name = gate.attrib['name']
for q10settings in IVrelation.findall('./{'+self.cml+'}q10_settings'):
## self.temperature from neuro.utils
- if 'gate' in q10settings.attrib.keys():
+ if 'gate' in q10settings.attrib:
if q10settings.attrib['gate'] == self.gate_name:
self.setQ10(q10settings)
break
@@ -301,10 +301,10 @@ class ChannelML():
moosegate_tableB.tableVector2D = tableB
def setQ10(self,q10settings):
- if 'q10_factor' in q10settings.attrib.keys():
+ if 'q10_factor' in q10settings.attrib:
self.q10factor = float(q10settings.attrib['q10_factor'])\
**((self.temperature-float(q10settings.attrib['experimental_temp']))/10.0)
- elif 'fixed_q10' in q10settings.attrib.keys():
+ elif 'fixed_q10' in q10settings.attrib:
self.q10factor = float(q10settings.attrib['fixed_q10'])
diff --git a/python/moose/neuroml/MorphML.py b/python/moose/neuroml/MorphML.py
index 08a20d4..38ab865 100644
--- a/python/moose/neuroml/MorphML.py
+++ b/python/moose/neuroml/MorphML.py
@@ -208,7 +208,7 @@ class MorphML():
cablegroups = cable.findall(".//{"+self.meta+"}group")
for cablegroup in cablegroups:
cablegroupname = cablegroup.text
- if cablegroupname in self.cablegroupsDict.keys():
+ if cablegroupname in self.cablegroupsDict:
self.cablegroupsDict[cablegroupname].append(cableid)
else:
self.cablegroupsDict[cablegroupname] = [cableid]
@@ -337,7 +337,7 @@ class MorphML():
connectivity = cell.find(".//{"+self.neuroml+"}connectivity")
if connectivity is not None:
for potential_syn_loc in cell.findall(".//{"+self.nml+"}potential_syn_loc"):
- if 'synapse_direction' in potential_syn_loc.attrib.keys():
+ if 'synapse_direction' in potential_syn_loc.attrib:
if potential_syn_loc.attrib['synapse_direction'] in ['post']:
self.set_group_compartment_param(cell, cellname, potential_syn_loc,\
'synapse_type', potential_syn_loc.attrib['synapse_type'], self.nml, mechanismname='synapse')
diff --git a/python/moose/neuroml/utils.py b/python/moose/neuroml/utils.py
index 3a1e3c0..749c28d 100644
--- a/python/moose/neuroml/utils.py
+++ b/python/moose/neuroml/utils.py
@@ -196,7 +196,7 @@ def keepOnlyInclude(network, onlyInclude):
populations = network.find(".//{"+nml_ns+"}populations")
for population in network.findall(".//{"+nml_ns+"}population"):
popname = population.attrib["name"]
- if popname in includeCellsDict.keys():
+ if popname in includeCellsDict:
includecellids = includeCellsDict[popname]
instances = population.find(".//{"+nml_ns+"}instances")
for instance in instances.findall(".//{"+nml_ns+"}instance"):
diff --git a/python/moose/neuroml2/converter.py b/python/moose/neuroml2/converter.py
index 24c64ce..d932581 100644
--- a/python/moose/neuroml2/converter.py
+++ b/python/moose/neuroml2/converter.py
@@ -50,6 +50,7 @@
#!!!!! TODO: unit conversion !!!!
+from future_builtins import map
import traceback
import warnings
from collections import deque
@@ -111,7 +112,7 @@ def convert_morphology(root, positions='auto'):
y=compartment.y,
z=compartment.z,
diameter=compartment.diameter)
- plist = map(moose.element, compartment.neighbours['axial'])
+ plist = list(map(moose.element, compartment.neighbours['axial']))
try:
parent = neuroml.SegmentParent(segments=comp_seg[moose.element(plist[0])].id)
except (KeyError, IndexError) as e:
diff --git a/python/moose/neuroml2/generated_neuroml.py b/python/moose/neuroml2/generated_neuroml.py
index 0ea0243..e39161d 100644
--- a/python/moose/neuroml2/generated_neuroml.py
+++ b/python/moose/neuroml2/generated_neuroml.py
@@ -14,10 +14,7 @@ import datetime as datetime_
etree_ = None
Verbose_import_ = False
-(
- XMLParser_import_none, XMLParser_import_lxml,
- XMLParser_import_elementtree
-) = range(3)
+XMLParser_import_none, XMLParser_import_lxml, XMLParser_import_elementtree = 0, 1, 2
XMLParser_import_library = None
try:
# lxml
diff --git a/python/moose/neuroml2/hhfit.py b/python/moose/neuroml2/hhfit.py
index fe4165e..764d1c8 100644
--- a/python/moose/neuroml2/hhfit.py
+++ b/python/moose/neuroml2/hhfit.py
@@ -214,7 +214,7 @@ def find_ratefn(x, y, **kwargs):
rms_error = 1e10 # arbitrarily setting this
best_fn = None
best_p = None
- for fn in fn_rate_map.keys():
+ for fn in fn_rate_map:
p = randomized_curve_fit(fn, x, y, **kwargs)
if p is None:
continue
diff --git a/python/moose/xmls_to_network/.noweb/main.nw b/python/moose/xmls_to_network/.noweb/main.nw
index 685e697..08402d1 100644
--- a/python/moose/xmls_to_network/.noweb/main.nw
+++ b/python/moose/xmls_to_network/.noweb/main.nw
@@ -544,13 +544,13 @@ for nw in network :
if xml_helper.isTaggedWith(nw, "population") :
try :
populationId = nw.get('id')
- if 'cell' in nw.keys() :
+ if 'cell' in nw :
typeOfPopulation = 'cell'
populationId = nw.get('cell')
- elif 'network' in nw.keys() :
+ elif 'network' in nw :
typeOfPopulation = 'network'
populationId = nw.get('network')
- elif 'component' in nw.keys() :
+ elif 'component' in nw :
debug.printDebug("DEVL", "Component in network is not implmeneted yet.")
else : pass
print typeOfPopulation, populationId
diff --git a/python/moose/xmls_to_network/core/hhfit.py b/python/moose/xmls_to_network/core/hhfit.py
index e367a5e..1aeef89 100644
--- a/python/moose/xmls_to_network/core/hhfit.py
+++ b/python/moose/xmls_to_network/core/hhfit.py
@@ -214,7 +214,7 @@ def find_ratefn(x, y, **kwargs):
rms_error = 1e10 # arbitrarily setting this
best_fn = None
best_p = None
- for fn in fn_rate_map.keys():
+ for fn in fn_rate_map:
p = randomized_curve_fit(fn, x, y, **kwargs)
if p is None:
continue
diff --git a/python/moose/xmls_to_network/core/multiscale.py b/python/moose/xmls_to_network/core/multiscale.py
index a78d72a..5ab62e6 100644
--- a/python/moose/xmls_to_network/core/multiscale.py
+++ b/python/moose/xmls_to_network/core/multiscale.py
@@ -151,7 +151,7 @@ class Multiscale:
segName = os.path.join(instId, cellType, segmentId)
self.mooseG.add_node(segName)
self.mooseG.node[segName]['population'] = populationName
- for k in cellG.node[n].keys():
+ for k in cellG.node[n]:
self.mooseG.node[segName][k] = cellG.node[n][k]
self.attachLabel(self.mooseG, segName)
diff --git a/python/moose/xmls_to_network/core/neuroml2_parser.py b/python/moose/xmls_to_network/core/neuroml2_parser.py
index 89fa1de..4e20177 100644
--- a/python/moose/xmls_to_network/core/neuroml2_parser.py
+++ b/python/moose/xmls_to_network/core/neuroml2_parser.py
@@ -14,10 +14,7 @@ import datetime as datetime_
etree_ = None
Verbose_import_ = False
-(
- XMLParser_import_none, XMLParser_import_lxml,
- XMLParser_import_elementtree
-) = range(3)
+XMLParser_import_none, XMLParser_import_lxml, XMLParser_import_elementtree = 0, 1, 2
XMLParser_import_library = None
try:
# lxml
diff --git a/python/moose/xmls_to_network/helper/graph_methods.py b/python/moose/xmls_to_network/helper/graph_methods.py
index b5d1360..6135e5c 100644
--- a/python/moose/xmls_to_network/helper/graph_methods.py
+++ b/python/moose/xmls_to_network/helper/graph_methods.py
@@ -46,7 +46,7 @@ def write_dot(g, filename):
for n in g.nodes():
i += 1
nodeLabel = "[label=\"\"".format(i)
- if 'proximal' in g.node[n].keys():
+ if 'proximal' in g.node[n]:
x = (float(g.node[n]['proximal'].get('x')) + float(g.node[n]['distal'].get('x')))/2
y = (float(g.node[n]['proximal'].get('y')) + float(g.node[n]['distal'].get('y')))/2
z = (float(g.node[n]['proximal'].get('z')) + float(g.node[n]['distal'].get('z')))/2
@@ -65,7 +65,7 @@ def write_dot(g, filename):
for (f, t) in g.edges():
edge = g.node[f]['label'] + " -> " + g.node[t]['label']
edge += " ["
- if 'synapse' in g.edge[f][t].keys():
+ if 'synapse' in g.edge[f][t]:
# color this edge and make it look like a synapse
edge += " label=\"{0}\",".format(g.edge[f][t]['id'])
edge += "color=blue,style=dotted,"
diff --git a/python/moose/xmls_to_network/parser/nml_parser.py b/python/moose/xmls_to_network/parser/nml_parser.py
index 1930979..16f4186 100644
--- a/python/moose/xmls_to_network/parser/nml_parser.py
+++ b/python/moose/xmls_to_network/parser/nml_parser.py
@@ -14,10 +14,7 @@ import datetime as datetime_
etree_ = None
Verbose_import_ = False
-(
- XMLParser_import_none, XMLParser_import_lxml,
- XMLParser_import_elementtree
-) = range(3)
+XMLParser_import_none, XMLParser_import_lxml, XMLParser_import_elementtree = 0, 1, 2
XMLParser_import_library = None
try:
# lxml
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NEURONUtils/NEURONSimUtils.py b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NEURONUtils/NEURONSimUtils.py
index a5ea349..5432bc3 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NEURONUtils/NEURONSimUtils.py
+++ b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NEURONUtils/NEURONSimUtils.py
@@ -125,7 +125,7 @@ class NetManagerNEURON(NetworkHandler):
self.log.info("Projection: "+projName+" from "+source+" to "+target+" with "+sizeInfo)
- for synapseType in synapseTypes.keys():
+ for synapseType in synapseTypes:
synObjName = projName+"_"+synapseType+"["+str(size)+"]"
self.log.info("Creating array for syns: "+synObjName)
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLHDF5Handler.py b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLHDF5Handler.py
index ac85153..ac285f4 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLHDF5Handler.py
+++ b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLHDF5Handler.py
@@ -150,7 +150,7 @@ class NetworkMLHDF5Handler():
elif val == 'post_fraction_along' or val[0] == 'post_fraction_along':
indexPostFractAlong = int(attrName[len('column_'):])
- for synType in self.globalSynapseProps.keys():
+ for synType in self.globalSynapseProps:
if str(val).count(synType) >0:
extraParamIndices[str(val)] = int(attrName[len('column_'):])
@@ -164,7 +164,7 @@ class NetworkMLHDF5Handler():
for i in range(0, d.shape[0]):
row = d[i,:]
localSynapseProps = {}
- synTypes = self.globalSynapseProps.keys()
+ synTypes = self.globalSynapseProps
for synType in synTypes:
localSynapseProps[synType] = self.globalSynapseProps[synType].copy()
@@ -186,7 +186,7 @@ class NetworkMLHDF5Handler():
if len(extraParamIndices)>0:
for synType in localSynapseProps:
- for paramName in extraParamIndices.keys():
+ for paramName in extraParamIndices:
if paramName.count(synType)>0:
self.log.debug(paramName +"->"+synType)
if paramName.count('weight')>0:
@@ -206,7 +206,7 @@ class NetworkMLHDF5Handler():
self.log.debug("Connection %d from %f to %f" % (id, preCellId, postCellId))
- for synType in localSynapseProps.keys():
+ for synType in localSynapseProps:
synProps = localSynapseProps[synType]
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLSaxHandler.py b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLSaxHandler.py
index e73b0b2..fed1d85 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLSaxHandler.py
+++ b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/NeuroMLUtils/NetworkMLSaxHandler.py
@@ -223,7 +223,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.postFract = 0.5
self.localSynapseProps.clear()
- synTypes = self.globalSynapseProps.keys()
+ synTypes = self.globalSynapseProps
for synType in synTypes:
self.localSynapseProps[synType] = self.globalSynapseProps[synType].copy()
@@ -282,7 +282,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.globalSynapseProps[self.latestSynapseType] = newSynapseProps
- for synProp in self.globalSynapseProps.keys():
+ for synProp in self.globalSynapseProps:
self.log.debug("globalSynapseProp "+synProp+": "+ str(self.globalSynapseProps[synProp]))
@@ -310,7 +310,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.globalSynapseProps[self.latestSynapseType] = newSynapseProps
- for synProp in self.globalSynapseProps.keys():
+ for synProp in self.globalSynapseProps:
self.log.debug("globalSynapseProp "+synProp+": "+ str(self.globalSynapseProps[synProp]))
@@ -322,7 +322,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
if 'synapse_type' in attrs:
synapse_type = attrs.get('synapse_type',"")
elif len(self.localSynapseProps) == 1:
- synapse_type = self.localSynapseProps.keys()[0]
+ synapse_type = self.localSynapseProps.popitem()[0]
if synapse_type != "":
synProps = self.localSynapseProps[synapse_type]
@@ -388,9 +388,9 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
else:
- others = ["populations", "projections", "connections", "inputs",
- "meta:tag", "meta:value", "meta:property", "meta:properties"]
- if (others.count(name) == 0):
+ others = {"populations", "projections", "connections", "inputs",
+ "meta:tag", "meta:value", "meta:property", "meta:properties"}
+ if name not in others:
print('Unhandled, unknown element: '+ name)
return
@@ -455,7 +455,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.log.debug(" Gathered all details of connection: " + self.currentConnId)
- for synType in self.localSynapseProps.keys():
+ for synType in self.localSynapseProps:
synProps = self.localSynapseProps[synType]
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/twoNeurons.hoc b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/twoNeurons.hoc
index 8c264ee..d1b303d 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedNEURON/twoNeurons.hoc
+++ b/python/moose/xmls_to_network/twoNeurons/generatedNEURON/twoNeurons.hoc
@@ -349,7 +349,7 @@ for cellNum=0, n_PurkinjeCellGroup-1 {
{nrnpython("group1._v_attrs.Population = 'PurkinjeCellGroup'")}
{nrnpython("hArray = h5file.createArray(group1, 'VOLTAGE', allData, 'Values of VOLTAGE from cell group: PurkinjeCellGroup')")}
{nrnpython("hArray.setAttr('Variable', 'VOLTAGE')")}
-{nrnpython("for columnIndex in columnsVsCellNums.keys(): hArray.setAttr('column_'+str(columnIndex), 'cellNum_'+ str(columnsVsCellNums[columnIndex]))")}
+{nrnpython("for columnIndex in columnsVsCellNums: hArray.setAttr('column_'+str(columnIndex), 'cellNum_'+ str(columnsVsCellNums[columnIndex]))")}
// Saving VOLTAGE on only one seg, id: 0, in the only cell in SimpleCellGroup
@@ -381,7 +381,7 @@ for cellNum=0, n_SimpleCellGroup-1 {
{nrnpython("group1._v_attrs.Population = 'SimpleCellGroup'")}
{nrnpython("hArray = h5file.createArray(group1, 'VOLTAGE', allData, 'Values of VOLTAGE from cell group: SimpleCellGroup')")}
{nrnpython("hArray.setAttr('Variable', 'VOLTAGE')")}
-{nrnpython("for columnIndex in columnsVsCellNums.keys(): hArray.setAttr('column_'+str(columnIndex), 'cellNum_'+ str(columnsVsCellNums[columnIndex]))")}
+{nrnpython("for columnIndex in columnsVsCellNums: hArray.setAttr('column_'+str(columnIndex), 'cellNum_'+ str(columnsVsCellNums[columnIndex]))")}
{ sprint(timeFilename, "%s%s", targetDir, "time.dat")}
{ f_time.wopen(timeFilename) }
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLHDF5Handler.py b/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLHDF5Handler.py
index ac85153..ac285f4 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLHDF5Handler.py
+++ b/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLHDF5Handler.py
@@ -150,7 +150,7 @@ class NetworkMLHDF5Handler():
elif val == 'post_fraction_along' or val[0] == 'post_fraction_along':
indexPostFractAlong = int(attrName[len('column_'):])
- for synType in self.globalSynapseProps.keys():
+ for synType in self.globalSynapseProps:
if str(val).count(synType) >0:
extraParamIndices[str(val)] = int(attrName[len('column_'):])
@@ -164,7 +164,7 @@ class NetworkMLHDF5Handler():
for i in range(0, d.shape[0]):
row = d[i,:]
localSynapseProps = {}
- synTypes = self.globalSynapseProps.keys()
+ synTypes = self.globalSynapseProps
for synType in synTypes:
localSynapseProps[synType] = self.globalSynapseProps[synType].copy()
@@ -186,7 +186,7 @@ class NetworkMLHDF5Handler():
if len(extraParamIndices)>0:
for synType in localSynapseProps:
- for paramName in extraParamIndices.keys():
+ for paramName in extraParamIndices:
if paramName.count(synType)>0:
self.log.debug(paramName +"->"+synType)
if paramName.count('weight')>0:
@@ -206,7 +206,7 @@ class NetworkMLHDF5Handler():
self.log.debug("Connection %d from %f to %f" % (id, preCellId, postCellId))
- for synType in localSynapseProps.keys():
+ for synType in localSynapseProps:
synProps = localSynapseProps[synType]
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLSaxHandler.py b/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLSaxHandler.py
index e73b0b2..1f03327 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLSaxHandler.py
+++ b/python/moose/xmls_to_network/twoNeurons/generatedPyNN/NeuroMLUtils/NetworkMLSaxHandler.py
@@ -223,7 +223,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.postFract = 0.5
self.localSynapseProps.clear()
- synTypes = self.globalSynapseProps.keys()
+ synTypes = self.globalSynapseProps
for synType in synTypes:
self.localSynapseProps[synType] = self.globalSynapseProps[synType].copy()
@@ -282,7 +282,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.globalSynapseProps[self.latestSynapseType] = newSynapseProps
- for synProp in self.globalSynapseProps.keys():
+ for synProp in self.globalSynapseProps:
self.log.debug("globalSynapseProp "+synProp+": "+ str(self.globalSynapseProps[synProp]))
@@ -310,7 +310,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.globalSynapseProps[self.latestSynapseType] = newSynapseProps
- for synProp in self.globalSynapseProps.keys():
+ for synProp in self.globalSynapseProps:
self.log.debug("globalSynapseProp "+synProp+": "+ str(self.globalSynapseProps[synProp]))
@@ -322,7 +322,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
if 'synapse_type' in attrs:
synapse_type = attrs.get('synapse_type',"")
elif len(self.localSynapseProps) == 1:
- synapse_type = self.localSynapseProps.keys()[0]
+ synapse_type = self.localSynapseProps.popitem()[0]
if synapse_type != "":
synProps = self.localSynapseProps[synapse_type]
@@ -455,7 +455,7 @@ class NetworkMLSaxHandler(xml.sax.ContentHandler):
self.log.debug(" Gathered all details of connection: " + self.currentConnId)
- for synType in self.localSynapseProps.keys():
+ for synType in self.localSynapseProps:
synProps = self.localSynapseProps[synType]
diff --git a/python/moose/xmls_to_network/twoNeurons/generatedPyNN/PyNNUtils/PyNNUtils.py b/python/moose/xmls_to_network/twoNeurons/generatedPyNN/PyNNUtils/PyNNUtils.py
index a9c04c0..424e356 100644
--- a/python/moose/xmls_to_network/twoNeurons/generatedPyNN/PyNNUtils/PyNNUtils.py
+++ b/python/moose/xmls_to_network/twoNeurons/generatedPyNN/PyNNUtils/PyNNUtils.py
@@ -196,7 +196,7 @@ class NetManagerPyNN(NetworkHandler):
self.log.error("Error at handleInputSource! Need a size attribute in sites element to create spike source!")
return
- if inputProps.keys().count("synaptic_mechanism")>0 and inputProps.keys().count("frequency")>0:
+ if "synaptic_mechanism" in inputProps and "frequency" in inputProps:
freq = float(inputProps["frequency"])
@@ -247,7 +247,7 @@ class NetManagerPyNN(NetworkHandler):
exec("from pyNN.%s import *" % self.my_simulator) # Does this really need to be imported every time?
- if self.inputCount.keys().count(inputName)==0:
+ if inputName not in self.inputCount:
self.inputCount[inputName] = 0
weight = float(self.inputWeights[inputName])
--
1.8.5.3
|
