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tests.py
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import nipype.pipeline.engine as pe
import nipype.interfaces.utility as util # utility
import pandas as pd
from nipype.interfaces.fsl import GLM, MELODIC, FAST, BET, MeanImage, FLIRT, ApplyMask, ImageMaths, Level1Design, FEATModel, Merge, L2Model, FLAMEO
from nipype.interfaces.base import Bunch
from nipype.algorithms.modelgen import SpecifyModel
from os import path
import matplotlib.pyplot as plt
import matplotlib
matplotlib.style.use('ggplot')
def get_subjectinfo(subject_delay, scan_type, scan_types):
import pandas as pd
from copy import deepcopy
import sys
sys.path.append('/home/chymera/src/LabbookDB/db/')
from query import loadSession
from common_classes import LaserStimulationProtocol
db_path="~/meta.db"
session, engine = loadSession(db_path)
sql_query=session.query(LaserStimulationProtocol).filter(LaserStimulationProtocol.code==scan_types[scan_type])
mystring = sql_query.statement
mydf = pd.read_sql_query(mystring,engine)
delay = int(mydf["stimulation_onset"][0])
inter_stimulus_duration = int(mydf["inter_stimulus_duration"][0])
stimulus_duration = mydf["stimulus_duration"][0]
stimulus_repetitions = mydf["stimulus_repetitions"][0]
onsets=[]
names=[]
for i in range(stimulus_repetitions):
onset = delay+(inter_stimulus_duration+stimulus_duration)*i
onsets.append([onset])
names.append("s"+str(i+1))
output = []
for idx_a, a in enumerate(onsets):
for idx_b, b in enumerate(a):
onsets[idx_a][idx_b] = round(b-subject_delay, 2) #floating point values don't add up nicely, so we have to round (https://docs.python.org/2/tutorial/floatingpoint.html)
output.append(Bunch(conditions=names,
onsets=deepcopy(onsets),
durations=[[stimulus_duration]]*stimulus_repetitions
))
return output
def plotmodel(matfile):
with open(matfile, 'r') as f:
first_line = f.readline()
length = first_line.split("\t")[1]
column_names = range(int(length))
df = pd.read_csv(matfile, skiprows=5, sep="\t", header=None, names=column_names, index_col=False)
df.plot()
plt.show()
def subjectinfo(subject_delay):
from nipype.interfaces.base import Bunch
from copy import deepcopy
onsets=[]
for i in range(6):
onsets.append([range(222,222+180*6,180)[i]])
output = []
names = ['s1', 's2', 's3', 's4', 's5', 's6']
for idx_a, a in enumerate(onsets):
for idx_b, b in enumerate(a):
onsets[idx_a][idx_b] = b-subject_delay
output.append(Bunch(conditions=names,
onsets=deepcopy(onsets),
durations=[[20.0], [20.0], [20.0], [20.0], [20.0], [20.0]],
))
return output
def test_model(base_dir, plot=False, workflow_name="test_model_wf"):
specify_model = pe.Node(interface=SpecifyModel(), name="specify_model")
specify_model.inputs.input_units = 'secs'
specify_model.inputs.functional_runs = ["/home/chymera/NIdata/ofM.dr/level1/Preprocessing/_condition_ofM_subject_4011/functional_bandpass/corr_16_trans_filt.nii.gz"]
specify_model.inputs.time_repetition = 1
specify_model.inputs.high_pass_filter_cutoff = 0 #switch to 240
specify_model.inputs.subject_info = subjectinfo(49.55)
level1design = pe.Node(interface=Level1Design(), name="level1design")
level1design.inputs.interscan_interval = 1
level1design.inputs.bases = {'gamma': {'derivs': False}}
level1design.inputs.model_serial_correlations = True
level1design.inputs.contrasts = [('allStim','T', ["s1","s2","s3","s4","s5","s6"],[1,1,1,1,1,1])]
modelgen = pe.Node(interface=FEATModel(), name='modelgen')
test_model_wf = pe.Workflow(name=workflow_name)
test_model_wf.base_dir = base_dir
test_model_wf.connect([
(specify_model,level1design,[('session_info','session_info')]),
(level1design, modelgen, [('ev_files', 'ev_files')]),
(level1design, modelgen, [('fsf_files', 'fsf_file')]),
])
# test_model_wf.run(plugin="MultiProc", plugin_args={'n_procs' : 4})
test_model_wf.run()
test_model_wf.write_graph(dotfilename="graph.dot", graph2use="hierarchical", format="png")
if plot:
matfile = path.join(base_dir,workflow_name,"modelgen/run0.mat")
plotmodel(matfile)
def get_scan(c,s,d):
result = str(c)+str(s)+str(d)
return result, d
def firstfunction(c,s,d):
result = str(c)+str(s)+str(d)
return result
def secondfunction(e,f):
result = str(e)+"|"+str(f)
return result
def bru2nii(input_dir,f):
result = str(input_dir)+str(f)
return result
def final_function(inp):
result = "final"+str(inp)
return result
def test_multiconnection():
infosource = pe.Node(interface=util.IdentityInterface(fields=['condition','subject']), name="infosource")
infosource.iterables = [('condition',["a","b","c"]), ('subject',[1,2,3])]
firstfunctionA = pe.Node(name='firstfunctionA', interface=util.Function(function=firstfunction,input_names=["c","s","d"], output_names=['result']))
firstfunctionA.iterables = ("d", ["x","y","z"])
firstfunctionB = pe.Node(name='firstfunctionB', interface=util.Function(function=firstfunction,input_names=["c","s","d"], output_names=['result']))
firstfunctionB.iterables = ("d", ["X","Y","Z"])
secondfunctionX = pe.Node(name='secondfunctionX', interface=util.Function(function=secondfunction,input_names=["e","f"], output_names=['myresult']))
workflow = pe.Workflow(name="test_connections")
workflow_connections = [
(infosource, firstfunctionA, [('condition', 'c'),('subject', 's')]),
(infosource, firstfunctionB, [('condition', 'c'),('subject', 's')]),
(firstfunctionA, secondfunctionX, [('result', 'e')]),
(firstfunctionB, secondfunctionX, [('result', 'f')]),
]
workflow.connect(workflow_connections)
workflow.write_graph(dotfilename="graph.dot", graph2use="flat", format="png")
workflow.base_dir = "/home/chymera/test"
workflow.run(plugin="MultiProc", plugin_args={'n_procs' : 4})
def test_connections():
infosource = pe.Node(interface=util.IdentityInterface(fields=['condition','subject']), name="infosource")
infosource.iterables = [('condition',["a","b","c"]), ('subject',[1,2,3])]
get_functional_scan = pe.Node(name='get_functional_scan', interface=util.Function(function=get_scan,input_names=["c","s","d"], output_names=['scan_path','d']))
get_functional_scan.iterables = ("d", ["x","y","z"])
# functional_bru2nii = pe.Node(name='functional_bru2nii', interface=util.Function(function=bru2nii,input_names=["input_dir","f"], output_names=['myresult']))
finalI = pe.Node(name='finalI', interface=util.Function(function=final_function,input_names=["inp"], output_names=['myfinalresult']))
# functional_bru2nii.inputs.f = 1
def concat(first):
result = str(first)+"second"
return result
# def concat(first,second):
# result = str(first)+str(second)
# return result
workflow = pe.Workflow(name="test_connections")
workflow_connections = [
(infosource, get_functional_scan, [('condition', 'c'),('subject', 's')]),
(('get_functional_scan.scan_path',concat),'final.inp'),
]
# (get_functional_scan, functional_bru2nii, [('scan_path', 'input_dir')]),
# (get_functional_scan, functional_bru2nii, [('d', 'f')]),
workflow.connect(workflow_connections)
workflow.write_graph(dotfilename="graph.dot", graph2use="flat", format="png")
workflow.base_dir = "/home/chymera/test"
workflow.run(plugin="MultiProc", plugin_args={'n_procs' : 4})
if __name__ == '__main__':
# plotmodel("/home/chymera/src/chyMRI/tests/test_model_wf/level1design/run0.mat")
# test_model("/home/chymera/src/chyMRI/tests", plot=True)
test_multiconnection()
# scan_type = "EPI_CBV_jin10"
# scan_types = {'EPI_CBV_jin10': 'jin10', 'EPI_CBV_jin60': 'jin60'}
# subject_delay = 49.35
# print get_subjectinfo(subject_delay, scan_type, scan_types)