def dmSim():
"""
"""
dm = CsvReader('./simulation/data.csv').dataMatrix()
# X coordinates, where positive values indicate a deviation towards the handle
dm = dm.addField('sacc1_ex', dtype=float)
dm = dm.addField('sacc2_ex', dtype=float)
dm = dm.addField('sacc3_ex', dtype=float)
dm = dm.addField('sacc1_ey', dtype=float)
dm = dm.addField('sacc2_ey', dtype=float)
dm = dm.addField('sacc3_ey', dtype=float)
dm = dm.addField("trialId", dtype = str)
# Timestamps for each fixation
dm = dm.addField('saccLat1', dtype=float)
dm = dm.addField('saccLat2', dtype=float)
dm = dm.addField('saccLat3', dtype=float)
for i in dm.range():
trial = dm[i]
trialNr = dm['count_trial_sequence'][i]
dm["trialId"][i] = trialNr
handleSide = trial['flip'][0]
print 'Trial %d (%s)' % (trialNr, handleSide)
sim = CsvReader('simulation/simulation/csv/%.4d.csv' % trialNr).dataMatrix()
fixNr = 1
for fix in sim:
t = fix['t'][0]
dx = fix['x'][0]
dy = fix['y'][0]
dm["sacc%s_ey" % fixNr][i] = dy
dm['sacc%d_ex' % fixNr][i] = dx
dm['saccLat%d' % fixNr][i] = t
fixNr += 1
if fixNr > 3:
break
dm.save('dm_simulation.csv')
dm = dm.addField("expId", dtype = str, default = "sim")
dm = dm.addField("symm", dtype = str, default = "asymm")
dm = dm.addField("saccCount", default = 3)
dm = dm.addField("mask_side", dtype = str, default = "control")
dm = dm.addField("cond", dtype = str, default = "not_practice")
dm = dm.addField("rep", dtype = str, default = "not_practice")
dm = dm.addField("checkFixDotFailed", dtype = str, default = "False")
dm = dm.addField("checkObjectFailed", dtype = str, default = "False")
dm = dm.addField("file", dtype = str, default = "sim")
return dm
dm['endX%sNormToHandle' % fixNr][i] = xToHandle
fixNr += 1
# if int(xNorm) == 0:
# if fixNr == 2:
# if abs(dy) > constants.minSaccSize:
# print fix['t']
# print dy
# raw_input()
if fixNr > 3:
break
# Save the dm containing the simulation data:
dm.save('dm_004C_simulation.csv')
if printSum:
print '\nSummary:\n'
for gap in (None, 'overlap', 'zero'):
print 'Gap: %s' % gap
if gap == None:
_dm = dm
else:
_dm = dm.select('gap == "%s"' % gap, verbose=False)
fix1 = _dm['endX1NormToHandle'].mean()
fix2 = _dm['endX2NormToHandle'].mean()
fix3 = _dm['endX3NormToHandle'].mean()
t1 = _dm['saccLat1'].mean()
t2 = _dm['saccLat2'].mean()
t3 = _dm['saccLat3'].mean()
