/usr/share/pyshared/neo/io/neomatlabio.py is in python-neo 0.2.0-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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"""
Class for reading/writing neo objects in matlab format 5 to 7.2 (.mat).
This module is a bridge for matlab users who want to adopote neo object reprenstation.
Nomenclature is the same but use Matlab struct and cell arrays.
With this modules Matlab users can use neo.io to read a format and convert it to .mat.
Supported : Read/Write
Author: sgarcia
"""
from .baseio import BaseIO
from ..core import *
from .tools import create_many_to_one_relationship
import numpy as np
import quantities as pq
from .. import description
classname_lower_to_upper = { }
for k in description.class_by_name.keys():
classname_lower_to_upper[k.lower()] = k
from datetime import datetime
import os
import re
# check if version scipy
import scipy
from distutils import version
if version.LooseVersion(scipy.version.version) < '0.8':
raise ImportError("your scipy version is too old to support MatlabIO, you need at least 0.8 you have %s"%scipy.version.version)
from scipy import io as sio
class NeoMatlabIO(BaseIO):
"""
Class for reading/writting neo objects in mat matlab format (.mat) 5 to 7.2.
This module is a bridge for matlab users who want to adopote neo object reprenstation.
Nomenclature is the same but use Matlab struct and cell arrays.
With this modules Matlab users can use neo.io to read a format and convert it to .mat.
Rules of conversion:
* neo classes are converted to matlab struct.
Ex: Block in neo will be a struct with name, file_datetime, ...
* neo one_to_many relationship are cellarray in matlab.
Ex: seg.analogsignals[2] in neo will be seg.analogsignals{3} in matlab.
Note the one based in matlab and braket vs singleton.
* Quantity attributes in neo in will be 2 fields in mallab?
Ex: anasig.t_start = 1.5 * s (pq.Quantiy) in neo
will be anasig.t_start = 1.5 and anasig.t_start_unit = 's' in matlab
* classes that inherits Quantity (AnalogSIgnal, SpikeTrain, ...) in neo will
have 2 fields (array and units) in matlab struct.
Ex: AnalogSignal( [1., 2., 3.], 'V') in neo will be
anasig.array = [1. 2. 3] and anasig.units = 'V' in matlab
1 - **Senario 1: create data in matlab and read them in neo**
This matlab code generate a block::
block = struct();
block.segments = { };
block.name = 'my block with matlab';
for s = 1:3
seg = struct();
seg.name = strcat('segment ',num2str(s));
seg.analogsignals = { };
for a = 1:5
anasig = struct();
anasig.array = rand(100,1);
anasig.units = 'mV';
anasig.t_start = 0;
anasig.t_start_units = 's';
anasig.sampling_rate = 100;
anasig.sampling_rate_units = 'Hz';
seg.analogsignals{a} = anasig;
end
seg.spiketrains = { };
for t = 1:7
sptr = struct();
sptr.array = rand(30,1)*10;
sptr.units = 'ms';
sptr.t_start = 0;
sptr.t_start_units = 'ms';
sptr.t_stop = 10;
sptr.t_stop_units = 'ms';
seg.spiketrains{t} = sptr;
end
block.segments{s} = seg;
end
save 'myblock.mat' block -V7
This code read it in python::
import neo
r = neo.io.NeoMatlabIO(filename = 'myblock.mat')
bl = r.read_block()
print bl.segments[1].analogsignals[2]
print bl.segments[1].spiketrains[4]
2 - **Senario 2: create data in python with neo and read them in matlab**
This python code generate the same block as previous (yes, it is more elegant, it is pyhton)::
import neo
import quantities as pq
from scipy import rand
bl = neo.Block(name = 'my block with neo')
for s in range(3):
seg = neo.Segment( name = 'segment'+str(s))
bl.segments.append(seg)
for a in range(5):
anasig = neo.AnalogSignal( rand(100), units = 'mV', t_start = 0 * pq.s, sampling_rate = 100*pq.Hz)
seg.analogsignals.append(anasig)
for t in range(7):
sptr = neo.SpikeTrain( rand(30), units = 'ms', t_start = 0*pq.ms, t_stop = 10*pq.ms)
seg.spiketrains.append(sptr)
w = neo.io.NeoMatlabIO(filename = 'myblock.mat')
w.write_block(bl)
This matlab code read it ::
load 'myblock.mat'
block.name
block.segments{2}.analogsignals{3}.array
block.segments{2}.analogsignals{3}.units
block.segments{2}.analogsignals{3}.t_start
block.segments{2}.analogsignals{3}.t_start_units
3 - **Senario 3: convertion**
This python code convert a spike2 file to matlab::
from neo import *
r = Spike2IO(filename = 'myspike2file.smr')
w = NeoMatlabIO(filename ='convertedfile.mat')
seg = r.read_segment()
bl = Block(name = 'a block')
bl.segments.append(seg)
w.write_block(bl)
"""
is_readable = True
is_writable = True
supported_objects = [ Block, Segment , AnalogSignal , EventArray, SpikeTrain ]
readable_objects = [Block, ]
writeable_objects = [Block, ]
has_header = False
is_streameable = False
read_params = { Block : [ ] }
write_params = { Block : [ ] }
name = 'neomatlab'
extensions = [ 'mat' ]
mode = 'file'
def __init__(self , filename = None) :
"""
This class read/write neo objects in matlab 5 to 7.2 format.
Arguments:
filename : the filename to read
"""
BaseIO.__init__(self)
self.filename = filename
def read_block(self, cascade = True, lazy = False,):
"""
Arguments:
"""
d = sio.loadmat(self.filename, struct_as_record=False, squeeze_me=True)
assert'block' in d, 'no block in'+self.filename
bl_struct = d['block']
bl = self.create_ob_from_struct(bl_struct, 'Block', cascade = cascade, lazy = lazy)
create_many_to_one_relationship(bl)
return bl
def write_block(self, bl,):
"""
Arguments::
bl: the block to b saved
"""
bl_struct = self.create_struct_from_obj(bl)
for seg in bl.segments:
seg_struct = self.create_struct_from_obj(seg)
bl_struct['segments'].append(seg_struct)
for anasig in seg.analogsignals:
anasig_struct = self.create_struct_from_obj(anasig)
seg_struct['analogsignals'].append(anasig_struct)
for ea in seg.eventarrays:
ea_struct = self.create_struct_from_obj(ea)
seg_struct['eventarrays'].append(ea_struct)
for sptr in seg.spiketrains:
sptr_struct = self.create_struct_from_obj(sptr)
seg_struct['spiketrains'].append(sptr_struct)
sio.savemat(self.filename, {'block':bl_struct}, oned_as = 'row')
def create_struct_from_obj(self, ob, ):
classname = ob.__class__.__name__
struct = { }
# relationship
rel = description.one_to_many_relationship
if classname in rel:
for childname in rel[classname]:
if description.class_by_name[childname] in self.supported_objects:
struct[childname.lower()+'s'] = [ ]
# attributes
necess = description.classes_necessary_attributes[classname]
recomm = description.classes_recommended_attributes[classname]
attributes = necess + recomm
for i, attr in enumerate(attributes):
attrname, attrtype = attr[0], attr[1]
#~ if attrname =='':
#~ struct['array'] = ob.magnitude
#~ struct['units'] = ob.dimensionality.string
#~ continue
if classname in description.classes_inheriting_quantities and \
description.classes_inheriting_quantities[classname] == attrname:
struct[attrname] = ob.magnitude
struct[attrname+'_units'] = ob.dimensionality.string
continue
if not(attrname in ob.annotations or hasattr(ob, attrname)): continue
if getattr(ob, attrname) is None : continue
if attrtype == pq.Quantity:
#ndim = attr[2]
struct[attrname] = getattr(ob,attrname).magnitude
struct[attrname+'_units'] = getattr(ob,attrname).dimensionality.string
elif attrtype ==datetime:
struct[attrname] = str(getattr(ob,attrname))
else:
struct[attrname] = getattr(ob,attrname)
return struct
def create_ob_from_struct(self, struct, classname, cascade = True, lazy = False,):
cl = description.class_by_name[classname]
# check if hinerits Quantity
#~ is_quantity = False
#~ for attr in description.classes_necessary_attributes[classname]:
#~ if attr[0] == '' and attr[1] == pq.Quantity:
#~ is_quantity = True
#~ break
#~ is_quantiy = classname in description.classes_inheriting_quantities
#~ if is_quantity:
if classname in description.classes_inheriting_quantities:
quantity_attr = description.classes_inheriting_quantities[classname]
arr = getattr(struct,quantity_attr)
#~ data_complement = dict(units=str(struct.units))
data_complement = dict(units=str(getattr(struct,quantity_attr+'_units')))
if "sampling_rate" in (at[0] for at in description.classes_necessary_attributes[classname]):
data_complement["sampling_rate"] = 0*pq.kHz # put fake value for now, put correct value later
if "t_stop" in (at[0] for at in description.classes_necessary_attributes[classname]):
if len(arr) > 0:
data_complement["t_stop"] =arr.max()
else:
data_complement["t_stop"] = 0.0
if lazy:
ob = cl([ ], **data_complement)
ob.lazy_shape = arr.shape
else:
ob = cl(arr, **data_complement)
else:
ob = cl()
for attrname in struct._fieldnames:
# check children
rel = description.one_to_many_relationship
if classname in rel and attrname[:-1] in [ r.lower() for r in rel[classname] ]:
for c in range(len(getattr(struct,attrname))):
if cascade:
child = self.create_ob_from_struct(getattr(struct,attrname)[c] , classname_lower_to_upper[attrname[:-1]],
cascade = cascade, lazy = lazy)
getattr(ob, attrname.lower()).append(child)
continue
# attributes
if attrname.endswith('_units') or attrname =='units' :#or attrname == 'array':
# linked with another field
continue
if classname in description.classes_inheriting_quantities and \
description.classes_inheriting_quantities[classname] == attrname:
continue
item = getattr(struct, attrname)
# put the good type
necess = description.classes_necessary_attributes[classname]
recomm = description.classes_recommended_attributes[classname]
attributes = necess + recomm
dict_attributes = dict( [ (a[0], a[1:]) for a in attributes])
if attrname in dict_attributes:
attrtype = dict_attributes[attrname][0]
if attrtype == datetime:
m = '(\d+)-(\d+)-(\d+) (\d+):(\d+):(\d+).(\d+)'
r = re.findall(m, str(item))
if len(r)==1:
item = datetime( *[ int(e) for e in r[0] ] )
else:
item = None
elif attrtype == np.ndarray:
dt = dict_attributes[attrname][2]
if lazy:
item = np.array([ ], dtype = dt)
ob.lazy_shape = item.shape
else:
item = item.astype( dt )
elif attrtype == pq.Quantity:
ndim = dict_attributes[attrname][1]
units = str(getattr(struct, attrname+'_units'))
if ndim == 0:
item = pq.Quantity(item, units)
else:
if lazy:
item = pq.Quantity([ ], units)
item.lazy_shape = item.shape
else:
item = pq.Quantity(item, units)
else:
item = attrtype(item)
setattr(ob, attrname, item)
return ob
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