def applyConstraints(dm_exp, dm_fillers):
"""
Arguments:
dm_exp --- dm containing exp scene-object combinations
dm_fillers --- dm containing filler scene-object combinations
Returns:
final_dm_test_feedback --- final datamatrix for the test feedback blockloop
final_dm_criterion_test --- final datamatrix for the test feedback blockloop
"""
# Add distractors:
dm_exp = addDistractors.addDistractors(dm_exp)
dm_fillers = addDistractors.addDistractors(dm_fillers)
# Make sure we will collect two dms
list_dms = []
for block in ["test_feedback", "criterion_test"]:
# Shuffle the fillers:
dm_fillers = ops.shuffle(dm_fillers)
# Merge first 8 fillers to the main dm
# NOTE: we leave out four fillers because we will use them for the
# very first and the very last trials
dm_fillers_slice = dm_fillers[0:8]
main_dm = dm_exp << dm_fillers_slice
# Shuffle the main dm:
main_dm = ops.shuffle(main_dm)
# Create an Enforce object, and add two constraints
ef = Enforce(main_dm)
ef.add_constraint(MaxRep, cols=[main_dm.Emotion], maxrep=3)
ef.add_constraint(MinDist, cols=[main_dm.Trial_ID], mindist=2)
# Enforce the constraints
main_dm = ef.enforce()
# See the resulting DataFrame and a report of how long the enforcement took.
# Add two fillers to the beginning of the final dm:
dm_fillers_slice_first = dm_fillers[8:10]
final_dm = dm_fillers_slice_first << main_dm
# And to the end fo the final dm:
dm_fillers_slice_last = dm_fillers[10:]
final_dm = final_dm << dm_fillers_slice_last
# Append to the dm list:
list_dms.append(final_dm)
# Unpack the list so we can return two separate dms
dm1, dm2 = list_dms
return dm1, dm2
def check_shuffle(col_type):
dm = DataMatrix(length=3, default_col_type=col_type)
dm.col1 = 11, 12, 13
dm.col2 = 1, 2, 3
dm = operations.shuffle(dm)
for row in dm:
ok_(row.col1 == row.col2 + 10)
dm.col1 = operations.shuffle(dm.col1)
dm.col2 = operations.shuffle(dm.col2)
check_integrity(dm)
def check_shuffle(col_type): dm = DataMatrix(length=3, default_col_type=col_type) dm.col1 = 11,12,13 dm.col2 = 1,2,3 dm = operations.shuffle(dm) for row in dm: ok_(row.col1 == row.col2+10) dm.col1 = operations.shuffle(dm.col1) dm.col2 = operations.shuffle(dm.col2) check_integrity(dm)
def check_mixedcolumn_sorting():
dm = DataMatrix(length=24)
dm.c = [
1, '1', 2, '2', 1.1, '1.1', 2.1, '2.1', INF, -INF, 'inf', '-inf', NAN,
NAN, 'nan', 'nan', None, None, None, None, 'alpha', 'beta', 'None', ''
]
dm.c = ops.shuffle(dm.c)
dm = ops.sort(dm, by=dm.c)
check_col(dm.c, [
-INF,
-INF,
1,
1,
1.1,
1.1,
2,
2,
2.1,
2.1,
INF,
INF,
'',
'None',
'alpha',
'beta',
None,
None,
None,
None,
NAN,
NAN,
NAN,
NAN,
])
def applyConstraints(dm_exp, dm_fillers):
"""
Arguments:
dm_exp --- dm containing exp scene-object combinations
dm_fillers --- dm containing filler scene-object combinations
Returns:
final_dm --- final datamatrix for the IMDF MC memory task
"""
# Add distractors:
dm_exp = addDistractorsImdf.addDistractors(dm_exp)
dm_fillers = addDistractorsImdf.addDistractors(dm_fillers)
# Shuffle the fillers:
dm_fillers = ops.shuffle(dm_fillers)
# Merge first 4 fillers to the main dm
# NOTE: we leave out four fillers because we will use them for the
# very first and the very last trials
# TODO: select 2 neg en 2 neutral
dm_fillers_slice = dm_fillers[0:4]
main_dm = dm_exp << dm_fillers_slice
# Shuffle the main dm:
main_dm = ops.shuffle(main_dm)
# Create an Enforce object, and add two constraints
ef = Enforce(main_dm)
ef.add_constraint(MaxRep, cols=[main_dm.Emotion], maxrep=3)
ef.add_constraint(MinDist, cols=[main_dm.Trial_ID], mindist=2)
# Enforce the constraints
main_dm = ef.enforce()
# See the resulting DataFrame and a report of how long the enforcement took.
# Add two fillers to the beginning of the final dm:
dm_fillers_slice_first = dm_fillers[4:6]
final_dm = dm_fillers_slice_first << main_dm
# And to the end fo the final dm:
dm_fillers_slice_last = dm_fillers[6:]
final_dm = final_dm << dm_fillers_slice_last
return final_dm
def check_intcolumn_sorting(): dm = DataMatrix(length=8, default_col_type=IntColumn) dm.c = [ 1, '1', 2, '2', 1.1, '1.1', 2.1, '2.8', ] dm.c = ops.shuffle(dm.c) dm = ops.sort(dm, by=dm.c) check_col(dm.c, [ 1, 1, 1, 1, 2, 2, 2, 2 ])
def test_shuffle(): dm = DataMatrix(length=2) dm.a = 'a', 'b' dm.b = 0, 1 while True: dm.a = ops.shuffle(dm.a) check_col(dm.b, [0, 1]) try: check_col(dm.a, ['b', 'a']) break except: pass dm = DataMatrix(length=2) dm.a = 'a', 'b' dm.b = 0, 1 while True: dm = ops.shuffle(dm) try: check_col(dm.a, ['b', 'a']) check_col(dm.b, [1, 0]) break except: pass
def test_shuffle():
dm = DataMatrix(length=2)
dm.a = 'a', 'b'
dm.b = 0, 1
while True:
dm.a = ops.shuffle(dm.a)
check_col(dm.b, [0, 1])
try:
check_col(dm.a, ['b', 'a'])
break
except:
pass
dm = DataMatrix(length=2)
dm.a = 'a', 'b'
dm.b = 0, 1
while True:
dm = ops.shuffle(dm)
try:
check_col(dm.a, ['b', 'a'])
check_col(dm.b, [1, 0])
break
except:
pass
def test_bin_split(): dm = DataMatrix(length=4) dm.a = range(4) dm = ops.shuffle(dm) dm1, dm2 = ops.bin_split(dm.a, 2) check_col(dm1.a, [0,1]) check_col(dm2.a, [2,3]) dm1, dm2, dm3 = ops.bin_split(dm.a, 3) check_col(dm1.a, [0]) check_col(dm2.a, [1]) check_col(dm3.a, [2,3]) dm1, = ops.bin_split(dm.a, 1) check_col(dm1.a, [0,1,2,3]) @raises(ValueError) def _(): x, = ops.bin_split(dm.a, 5) _()
def addDistractors(dm):
"""
Adds distractors to a given datamatrix, making sure that both
distractors are different from the target and from each other
Arguments:
dm --- a DataMatrix() instance without distractors
Returns:
new_dm --- a DataMatrix instance with distractors
"""
# Shuffle the dm:
dm = ops.shuffle(dm)
# Split the original dm by emotion:
neg_dm = dm.Emotion == "neg"
neu_dm = dm.Emotion == "neu"
# Make a list of potential scenes for negative distractor 1
L_NEG_DIST1 = list(neg_dm.Scene)
# and negative distractor 2
L_NEG_DIST2 = list(neg_dm.Scene)
# Make a list of potential scenes for neutral distractor 1
L_NEU_DIST1 = list(neu_dm.Scene)
# and 2
L_NEU_DIST2 = list(neu_dm.Scene)
new_dm = combine(dm, L_NEG_DIST1[:], L_NEG_DIST2[:], L_NEU_DIST1[:],
L_NEU_DIST2[:])
# Make sure target, distractor 1 and distractor 2 are different scenes:
while any(row.distractor_scene_1 == row.distractor_scene_2
or row.distractor_scene_1 == row.Scene
or row.distractor_scene_2 == row.Scene for row in new_dm):
# If not, try again:
print("try again")
new_dm = combine(dm, L_NEG_DIST1[:], L_NEG_DIST2[:], L_NEU_DIST1[:],
L_NEU_DIST2[:])
return new_dm
def test_bin_split():
dm = DataMatrix(length=4)
dm.a = range(4)
dm = ops.shuffle(dm)
dm1, dm2 = ops.bin_split(dm.a, 2)
check_col(dm1.a, [0, 1])
check_col(dm2.a, [2, 3])
dm1, dm2, dm3 = ops.bin_split(dm.a, 3)
check_col(dm1.a, [0])
check_col(dm2.a, [1])
check_col(dm3.a, [2, 3])
dm1, = ops.bin_split(dm.a, 1)
check_col(dm1.a, [0, 1, 2, 3])
def _():
with pytest.raises(ValueError):
x, = ops.bin_split(dm.a, 5)
_()
def enforce(self, maxreshuffle=100, maxpass=100):
"""
desc:
Enforces constraints.
keywords:
maxpass:
desc: The maximum number of times that the enforce algorithm
may be restarted.
type: int
returns:
desc: A `DataMatrix` that respects the constraints.
type: DataMatrix
"""
t0 = time.time()
reverse = False
for i in range(maxreshuffle):
self.dm = operations.shuffle(self.dm)
for j in range(maxpass):
if not self._enforce(reverse=reverse):
break
reverse = not reverse
else:
# If the maximum passes were exhausted, restart the loop
continue
# If the maximum passes were not exhausted, we are done
break
else:
raise EnforceFailed(
u'Failed to enforce constraints (maxreshuffle = %d)' \
% maxreshuffle)
t1 = time.time()
self.report = {
u'time': t1 - t0,
u'reshuffle': i + 1,
}
return self.dm
def run(self):
"""See item."""
self.set_item_onset()
if self.live_dm is None or self.var.continuous == u'no':
self.live_dm = self._create_live_datamatrix()
self.live_row = 0
first = True
while self.live_row < len(self.live_dm):
self.experiment.var.repeat_cycle = 0
self.experiment.var.live_row = self.live_row
self.experiment.var.set('live_row_%s' % self.name, self.live_row)
for name, val in self.live_dm[self.live_row]:
if isinstance(val, basestring) and val.startswith(u'='):
val = self.python_workspace._eval(val[1:])
self.experiment.var.set(name, val)
# Evaluate the run if statement
if self._break_if is not None and \
(not first or self.var.break_if_on_first == u'yes'):
self.python_workspace[u'self'] = self
if self.python_workspace._eval(self._break_if):
break
# Run the item!
self.experiment.items.execute(self._item)
# If the repeat_cycle flag was set, run the item again later
if self.experiment.var.repeat_cycle:
self.live_dm <<= self.live_dm[self.live_row:self.live_row+1]
if self.var.order == u'random':
self.live_dm = self.live_dm[:self.live_row+1] \
<< operations.shuffle(self.live_dm[self.live_row+1:])
self.live_row += 1
first = False
else:
# If the loop finished without breaking, it needs to be reset on
# the next run of the loop item
self.live_row = None
self.live_dm = None
def check_floatcolumn_sorting():
dm = DataMatrix(length=24, default_col_type=FloatColumn)
with pytest.warns(UserWarning):
dm.c = [
1, '1', 2, '2', 1.1, '1.1', 2.1, '2.1', INF, -INF, 'inf', '-inf',
NAN, NAN, 'nan', 'nan', None, None, None, None, 'alpha', 'beta',
'None', ''
]
dm.c = ops.shuffle(dm.c)
dm = ops.sort(dm, by=dm.c)
check_col(dm.c, [
-INF,
-INF,
1,
1,
1.1,
1.1,
2,
2,
2.1,
2.1,
INF,
INF,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
NAN,
])
def run(self):
"""See item."""
self.set_item_onset()
if self.live_dm is None or self.var.continuous == u'no':
self.live_dm = self._create_live_datamatrix()
self.live_row = 0
first = True
while self.live_row < len(self.live_dm):
self.experiment.var.repeat_cycle = 0
self.experiment.var.live_row = self.live_row
self.experiment.var.set('live_row_%s' % self.name, self.live_row)
for name, val in self.live_dm[self.live_row]:
if isinstance(val, basestring) and val.startswith(u'='):
val = self.python_workspace._eval(val[1:])
self.experiment.var.set(name, val)
# Evaluate the run if statement
if self._break_if is not None and \
(not first or self.var.break_if_on_first == u'yes'):
self.python_workspace[u'self'] = self
if self.python_workspace._eval(self._break_if):
break
# Run the item!
self.experiment.items.execute(self._item)
# If the repeat_cycle flag was set, run the item again later
if self.experiment.var.repeat_cycle:
self.live_dm <<= self.live_dm[self.live_row:self.live_row + 1]
if self.var.order == u'random':
self.live_dm = self.live_dm[:self.live_row+1] \
<< operations.shuffle(self.live_dm[self.live_row+1:])
self.live_row += 1
first = False
else:
# If the loop finished without breaking, it needs to be reset on
# the next run of the loop item
self.live_row = None
self.live_dm = None
def splitFillers(dm):
"""
Splits filler trials into:
- 2 first fillers, one negative, one neutral
- 2 last fillers, one negative, one neutral
- remaining fillers, that should be mixed with the experimental trials
Arguments:
dm --- DataMatrix containing filler objects
Returns:
dm_first --- dm containing only 2 rows, corresponding to the first 2 fillers
dm_last --- dm containing only 2 rows, corresponding to the last 2 fillers
dm_remaining --- dm containing the remainder (if any) of the fillers
NOTE the order
"""
# Below is an awful piece of script to make sure the first and last two fillers
# consist of one neg and one neu trial.
# I just don't see a way to do this more elegantly
# Shuffle the fillers:
dm = ops.shuffle(dm)
# Split the fillers on the basis of valence:
(cat1, filler_dm_negative), (cat2,
filler_dm_neutral) = ops.split(dm["Emotion"])
# Select 2 fillers, one from each valence category, as first 2 fillers:
identifier_filler1_neg = filler_dm_negative["Object"][0]
identifier_filler1_neu = filler_dm_neutral["Object"][0]
dm_filler1_neg = filler_dm_negative["Object"] == identifier_filler1_neg
dm_filler1_neu = filler_dm_neutral["Object"] == identifier_filler1_neu
# Merge the two first trial_dms
dm_first = dm_filler1_neg << dm_filler1_neu
# Shuffle
dm_first = ops.shuffle(dm_first)
# Add a column indicating the type of filler (for later debugging/cross
# checking)
dm_first["filler_type"] = "first"
# Remove the already selected pairs from the dms
# (i.e., select WITHOUT replacement):
filler_dm_negative = filler_dm_negative[1:]
filler_dm_neutral = filler_dm_neutral[1:]
# Do the same thing for the last 2 fillers:
# Select 2 fillers, one from each valence category, as first 2 fillers:
identifier_filler2_neg = filler_dm_negative["Object"][0]
identifier_filler2_neu = filler_dm_neutral["Object"][0]
dm_filler2_neg = filler_dm_negative["Object"] == identifier_filler2_neg
dm_filler2_neu = filler_dm_neutral["Object"] == identifier_filler2_neu
# Merge:
dm_last = dm_filler2_neg << dm_filler2_neu
# And shuffle:
dm_last = ops.shuffle(dm_last)
# Add column with filler type
dm_last["filler_type"] = "last"
# Remove from the dms:
filler_dm_negative = filler_dm_negative[1:]
filler_dm_neutral = filler_dm_neutral[1:]
# Merge the remaining filler dms:
dm_remaining = filler_dm_negative << filler_dm_neutral
# Shuffle:
dm_remaining = ops.shuffle(dm_remaining)
# Add column with filler type
dm_remaining["filler_type"] = "middle"
return dm_first, dm_last, dm_remaining
def _create_live_datamatrix(self): """ desc: Builds a live DataMatrix. That is, it takes the orignal DataMatrix and applies all the operations as specified. returns: desc: A live DataMatrix. type: DataMatrix """ if self.var.source == u'table': src_dm = self.dm else: from datamatrix import io src = self.experiment.pool[self.var.source_file] if src.endswith(u'.xlsx'): try: src_dm = io.readxlsx(src) except Exception as e: raise osexception(u'Failed to read .xlsx file: %s' % src, exception=e) else: try: src_dm = io.readtxt(src) except Exception as e: raise osexception(u'Failed to read text file (perhaps it has the wrong format or it is not utf-8 encoded): %s' % src, exception=e) for column_name in src_dm.column_names: if not self.syntax.valid_var_name(column_name): raise osexception( u'The loop table contains an invalid column name: 'u'\'%s\'' \ % column_name) # The number of repeats should be numeric. If not, then give an error. # This can also occur when generating a preview of a loop table if # repeat is variable. if not isinstance(self.var.repeat, (int, float)): raise osexception( u'Don\'t know how to generate a DataMatrix for "%s" repeats' \ % self.var.repeat) length = int(len(src_dm) * self.var.repeat) dm = DataMatrix(length=0) while len(dm) < length: i = min(length-len(dm), len(src_dm)) if self.var.order == u'random': dm <<= operations.shuffle(src_dm)[:i] else: dm <<= src_dm[:i] if self.var.order == u'random': dm = operations.shuffle(dm) if self.ef is not None: self.ef.dm = dm dm = self.ef.enforce() for cmd, arglist in self.operations: # The column name is always specified last, or not at all if arglist: try: colname = arglist[-1] col = dm[colname] except: raise osexception( u'Column %s does not exist' % arglist[-1]) if cmd == u'fullfactorial': dm = operations.fullfactorial(dm) elif cmd == u'shuffle': if not arglist: dm = operations.shuffle(dm) else: dm[colname] = operations.shuffle(col) elif cmd == u'shuffle_horiz': if not arglist: dm = operations.shuffle_horiz(dm) else: dm = operations.shuffle_horiz( *[dm[_colname] for _colname in arglist]) elif cmd == u'slice': self._require_arglist(cmd, arglist, minlen=2) dm = dm[arglist[0]: arglist[1]] elif cmd == u'sort': self._require_arglist(cmd, arglist) dm[colname] = operations.sort(col) elif cmd == u'sortby': self._require_arglist(cmd, arglist) dm = operations.sort(dm, by=col) elif cmd == u'reverse': if not arglist: dm = dm[::-1] else: dm[colname] = col[::-1] elif cmd == u'roll': self._require_arglist(cmd, arglist) steps = arglist[0] if not isinstance(steps, int): raise osexception(u'roll steps should be numeric') if len(arglist) == 1: dm = dm[-steps:] << dm[:-steps] else: dm[colname] = list(col[-steps:]) + list(col[:-steps]) elif cmd == u'weight': self._require_arglist(cmd, arglist) dm = operations.weight(col) return dm
def _create_live_datamatrix(self):
"""
desc:
Builds a live DataMatrix. That is, it takes the orignal DataMatrix
and applies all the operations as specified.
returns:
desc: A live DataMatrix.
type: DataMatrix
"""
if self.var.source == u'table':
src_dm = self.dm
else:
from datamatrix import io
src = self.experiment.pool[self.var.source_file]
if src.endswith(u'.xlsx'):
try:
src_dm = io.readxlsx(src)
except Exception as e:
raise osexception(u'Failed to read .xlsx file: %s' % src,
exception=e)
else:
try:
src_dm = io.readtxt(src)
except Exception as e:
raise osexception(u'Failed to read text file: %s' % src,
exception=e)
length = int(len(src_dm) * self.var.repeat)
dm = DataMatrix(length=0)
while len(dm) < length:
i = min(length - len(dm), len(src_dm))
if self.var.order == u'random':
dm <<= operations.shuffle(src_dm)[:i]
else:
dm <<= src_dm[:i]
if self.var.order == u'random':
dm = operations.shuffle(dm)
if self.ef is not None:
self.ef.dm = dm
dm = self.ef.enforce()
for cmd, arglist in self.operations:
# The column name is always specified last, or not at all
if arglist:
try:
colname = arglist[-1]
col = dm[colname]
except:
raise osexception(u'Column %s does not exist' %
arglist[-1])
if cmd == u'fullfactorial':
dm = operations.fullfactorial(dm)
elif cmd == u'shuffle':
if not arglist:
dm = operations.shuffle(dm)
else:
dm[colname] = operations.shuffle(col)
elif cmd == u'shuffle_horiz':
if not arglist:
dm = operations.shuffle_horiz(dm)
else:
dm = operations.shuffle_horiz(
*[dm[_colname] for _colname in arglist])
elif cmd == u'slice':
self._require_arglist(cmd, arglist, minlen=2)
dm = dm[arglist[0]:arglist[1]]
elif cmd == u'sort':
self._require_arglist(cmd, arglist)
dm[colname] = operations.sort(col)
elif cmd == u'sortby':
self._require_arglist(cmd, arglist)
dm = operations.sort(dm, by=col)
elif cmd == u'reverse':
if not arglist:
dm = dm[::-1]
else:
dm[colname] = col[::-1]
elif cmd == u'roll':
self._require_arglist(cmd, arglist)
steps = arglist[0]
if not isinstance(steps, int):
raise osexception(u'roll steps should be numeric')
if len(arglist) == 1:
dm = dm[-steps:] << dm[:-steps]
else:
dm[colname] = list(col[-steps:]) + list(col[:-steps])
elif cmd == u'weight':
self._require_arglist(cmd, arglist)
dm = operations.weight(col)
return dm
def _create_live_datamatrix(self): """ desc: Builds a live DataMatrix. That is, it takes the orignal DataMatrix and applies all the operations as specified. returns: desc: A live DataMatrix. type: DataMatrix """ if self.var.source == u'table': src_dm = self.dm else: from datamatrix import io src = self.experiment.pool[self.var.source_file] if src.endswith(u'.xlsx'): try: src_dm = io.readxlsx(src) except Exception as e: raise osexception(u'Failed to read .xlsx file: %s' % src, exception=e) else: try: src_dm = io.readtxt(src) except Exception as e: raise osexception(u'Failed to read text file: %s' % src, exception=e) length = int(len(src_dm) * self.var.repeat) dm = DataMatrix(length=0) while len(dm) < length: i = min(length-len(dm), len(src_dm)) if self.var.order == u'random': dm <<= operations.shuffle(src_dm)[:i] else: dm <<= src_dm[:i] if self.var.order == u'random': dm = operations.shuffle(dm) if self.ef is not None: self.ef.dm = dm dm = self.ef.enforce() for cmd, arglist in self.operations: # The column name is always specified last, or not at all if arglist: try: colname = arglist[-1] col = dm[colname] except: raise osexception( u'Column %s does not exist' % arglist[-1]) if cmd == u'fullfactorial': dm = operations.fullfactorial(dm) elif cmd == u'shuffle': if not arglist: dm = operations.shuffle(dm) else: dm[colname] = operations.shuffle(col) elif cmd == u'shuffle_horiz': if not arglist: dm = operations.shuffle_horiz(dm) else: dm = operations.shuffle_horiz( *[dm[_colname] for _colname in arglist]) elif cmd == u'slice': self._require_arglist(cmd, arglist, minlen=2) dm = dm[arglist[0]: arglist[1]] elif cmd == u'sort': self._require_arglist(cmd, arglist) dm[colname] = operations.sort(col) elif cmd == u'sortby': self._require_arglist(cmd, arglist) dm = operations.sort(dm, by=col) elif cmd == u'reverse': if not arglist: dm = dm[::-1] else: dm[colname] = col[::-1] elif cmd == u'roll': self._require_arglist(cmd, arglist) steps = arglist[0] if not isinstance(steps, int): raise osexception(u'roll steps should be numeric') if len(arglist) == 1: dm = dm[-steps:] << dm[:-steps] else: dm[colname] = list(col[-steps:]) + list(col[:-steps]) elif cmd == u'weight': self._require_arglist(cmd, arglist) dm = operations.weight(col) return dm
def _create_live_datamatrix(self):
"""
desc:
Builds a live DataMatrix. That is, it takes the orignal DataMatrix
and applies all the operations as specified.
returns:
desc: A live DataMatrix.
type: DataMatrix
"""
if self.var.source == u'table':
src_dm = self.dm
else:
from datamatrix import io
src = self.experiment.pool[self.var.source_file]
if src.endswith(u'.xlsx'):
try:
src_dm = io.readxlsx(src)
except Exception as e:
raise osexception(u'Failed to read .xlsx file: %s' % src,
exception=e)
else:
try:
src_dm = io.readtxt(src)
except Exception as e:
raise osexception(
u'Failed to read text file (perhaps it has the wrong format or it is not utf-8 encoded): %s'
% src,
exception=e)
for column_name in src_dm.column_names:
if not self.syntax.valid_var_name(column_name):
raise osexception(
u'The loop table contains an invalid column name: 'u'\'%s\'' \
% column_name)
# The number of repeats should be numeric. If not, then give an error.
# This can also occur when generating a preview of a loop table if
# repeat is variable.
if not isinstance(self.var.repeat, (int, float)):
raise osexception(
u'Don\'t know how to generate a DataMatrix for "%s" repeats' \
% self.var.repeat)
length = int(len(src_dm) * self.var.repeat)
dm = DataMatrix(length=0)
while len(dm) < length:
i = min(length - len(dm), len(src_dm))
if self.var.order == u'random':
dm <<= operations.shuffle(src_dm)[:i]
else:
dm <<= src_dm[:i]
if self.var.order == u'random':
dm = operations.shuffle(dm)
if self.ef is not None:
self.ef.dm = dm
dm = self.ef.enforce()
for cmd, arglist in self.operations:
# The column name is always specified last, or not at all
if arglist:
try:
colname = arglist[-1]
col = dm[colname]
except:
raise osexception(u'Column %s does not exist' %
arglist[-1])
if cmd == u'fullfactorial':
dm = operations.fullfactorial(dm)
elif cmd == u'shuffle':
if not arglist:
dm = operations.shuffle(dm)
else:
dm[colname] = operations.shuffle(col)
elif cmd == u'shuffle_horiz':
if not arglist:
dm = operations.shuffle_horiz(dm)
else:
dm = operations.shuffle_horiz(
*[dm[_colname] for _colname in arglist])
elif cmd == u'slice':
self._require_arglist(cmd, arglist, minlen=2)
dm = dm[arglist[0]:arglist[1]]
elif cmd == u'sort':
self._require_arglist(cmd, arglist)
dm[colname] = operations.sort(col)
elif cmd == u'sortby':
self._require_arglist(cmd, arglist)
dm = operations.sort(dm, by=col)
elif cmd == u'reverse':
if not arglist:
dm = dm[::-1]
else:
dm[colname] = col[::-1]
elif cmd == u'roll':
self._require_arglist(cmd, arglist)
steps = arglist[0]
if not isinstance(steps, int):
raise osexception(u'roll steps should be numeric')
if len(arglist) == 1:
dm = dm[-steps:] << dm[:-steps]
else:
dm[colname] = list(col[-steps:]) + list(col[:-steps])
elif cmd == u'weight':
self._require_arglist(cmd, arglist)
dm = operations.weight(col)
return dm
exp_phase = block.split("_")[-1]
dst = "trial list %s/block loops TNT %s" % (exp_phase, exp_phase)
for pp_ID in range(1, 71):
main_dm = io.readtxt(src_exp)
# Read in fillers:
dm = io.readtxt(src_fillers)
dm_first, dm_last, dm_remaining = helpers.splitFillers(dm)
# Merge the remaining fillers with the main dm:
merged_dm = main_dm << dm_remaining
# Shuffle the merged dm:
merged_dm = ops.shuffle(merged_dm)
# Create an Enforce object, and add constraint
ef = Enforce(merged_dm)
ef.add_constraint(MaxRep, cols=[merged_dm.Emotion], maxrep=3)
ef.add_constraint(MinDist, cols=[merged_dm.Trial_ID], mindist=2)
# Enforce the constraints
merged_dm = ef.enforce()
# Add the first fillers:
merged_dm = dm_first << merged_dm
# Add the last fillers:
merged_dm = merged_dm << dm_last
# Add exp ID to the dm:
def _create_live_datamatrix(self):
"""
desc:
Builds a live DataMatrix. That is, it takes the orignal DataMatrix
and applies all the operations as specified.
returns:
desc: A live DataMatrix.
type: DataMatrix
"""
src_dm = self.dm if self.var.source == u'table' else self._read_file()
for column_name in src_dm.column_names:
if not self.syntax.valid_var_name(column_name):
raise osexception(
u'The loop table contains an invalid column name: '
u'\'%s\'' % column_name)
# The number of repeats should be numeric. If not, then give an error.
# This can also occur when generating a preview of a loop table if
# repeat is variable.
if not isinstance(self.var.repeat, (int, float)):
raise osexception(
u'Don\'t know how to generate a DataMatrix for "%s" repeats' %
self.var.repeat)
length = int(len(src_dm) * self.var.repeat)
dm = DataMatrix(length=0)
while len(dm) < length:
i = min(length - len(dm), len(src_dm))
if self.var.order == u'random':
dm <<= operations.shuffle(src_dm)[:i]
else:
dm <<= src_dm[:i]
if self.var.order == u'random':
dm = operations.shuffle(dm)
# Constraints come before loop operations
if self._constraints:
self.ef = Enforce(dm)
for constraint_cls, colname, kwargs in self._constraints:
self.ef.add_constraint(constraint_cls,
cols=dm[colname],
**kwargs)
dm = self.ef.enforce()
# Operations come last
for cmd, arglist in self._operations:
# The column name is always specified last, or not at all
if arglist:
try:
colname = arglist[-1]
col = dm[colname]
except:
raise osexception(u'Column %s does not exist' %
arglist[-1])
if cmd == u'fullfactorial':
dm = operations.fullfactorial(dm)
elif cmd == u'shuffle':
if not arglist:
dm = operations.shuffle(dm)
else:
dm[colname] = operations.shuffle(col)
elif cmd == u'shuffle_horiz':
if not arglist:
dm = operations.shuffle_horiz(dm)
else:
# There can be multiple column names, so we need to check
# if all of them exist, rather than only the last one as
# we did above.
for _colname in arglist:
try:
dm[_colname]
except:
raise osexception(u'Column %s does not exist' %
_colname)
dm = operations.shuffle_horiz(
*[dm[_colname] for _colname in arglist])
elif cmd == u'slice':
self._require_arglist(cmd, arglist, minlen=2)
dm = dm[arglist[0]:arglist[1]]
elif cmd == u'sort':
self._require_arglist(cmd, arglist)
dm[colname] = operations.sort(col)
elif cmd == u'sortby':
self._require_arglist(cmd, arglist)
dm = operations.sort(dm, by=col)
elif cmd == u'reverse':
if not arglist:
dm = dm[::-1]
else:
dm[colname] = col[::-1]
elif cmd == u'roll':
self._require_arglist(cmd, arglist)
steps = arglist[0]
if not isinstance(steps, int):
raise osexception(u'roll steps should be numeric')
if len(arglist) == 1:
dm = dm[-steps:] << dm[:-steps]
else:
dm[colname] = list(col[-steps:]) + list(col[:-steps])
elif cmd == u'weight':
self._require_arglist(cmd, arglist)
try:
dm = operations.weight(col)
except TypeError:
raise osexception(
u'weight values should be non-negative numeric values')
return dm