def __init__(self, tstart=0, tend=None, dur=None, delay=None, time='time'):
"""
t0 is always event[time]; A time window is specified through 'tstart'
and either 'tend' or 'dur' (=duration)
tend as Var is read relative to t0
kwargs
------
tstart = 0 (relative to t0)
tend
dur (duration)
delay (constant shift of time points)
time: event-Variable specifying t0
"""
# check input
for t in tstart, tend, dur, delay:
if t is not None:
assert np.isscalar(t) or _vars.isvar(t)
self.tstart = tstart
assert (tend is None) or (dur is None)
self.tend = tend
self.dur = dur
self.delay = delay
assert isinstance(time, basestring) or _vars.isvar(time)
self.time = time
def t2(self, colony):
"return t2 relative to the var-colony"
t0 = colony[self.time]
if _vars.isvar(self.tend):
out = t0 + colony[self.tend]
elif np.isscalar(self.tend):
out = t0 + self.tend
else:
if _vars.isvar(self.dur):
return self.t1(colony) + colony[self.dur]
elif np.isscalar(self.dur):
return self.t1(colony) + self.dur
else:
raise NotImplementedError()
return self._add_delay(out, colony)
def __setitem__(self, name, value):
if isvar(name):
self.variables[name]=value
elif isinstance(name, basestring):
self.properties[name] = value
else:
raise KeyError("Key must be VarCommander or String (for setting properties)")
def _derive_segment_data_(self, segment, preview=False):
source = segment._p_attr['source']
var = self.compiled['var']
key = self.compiled['key']
shift = self.compiled['shift']
data = deepcopy(source.data)
var_i = source.varlist.index(var)
if np.isscalar(shift):
data[:, var_i] += shift
elif type(shift) == list:
data_len = data.shape[0]
shift = deepcopy(shift)
while len(shift) < data_len:
shift.append(shift[-1])
if len(shift) > data_len:
shift = shift[:data_len]
data[:, var_i] += np.array(shift)
else:
if isvar(key):
for i, evt in enumerate(source):
data[i, var_i] += shift[evt[key]]
else:
for i, evt in enumerate(source):
data[i, var_i] += evt[shift]
return data
def __setitem__(self, name, value):
isslice = isinstance(name, slice)
isint = isinstance(name, int)
if isslice:
name = _slice2tuple_(name)
if isint or isslice:
if isvar(value):
var = value
elif isinstance(value, basestring):
try:
var = self._p._dataset.experiment.variables.get(value)
except:
# create = ui.ask(title="Create Variable",
# message="No variable named '%s', create variable?"%value,
# cancel=False)
create = True
if create is True:
var = self._p._dataset.experiment.variables.new(value, dtype='dict')
else:
ui.msg("Aborted")
return
self._value[name] = var
self._changed()
else:
raise ValueError("key needs to be int or slice")
def _add_delay(self, t, colony):
if self.delay is None:
return t
elif np.isscalar(self.delay):
return t + self.delay
elif _vars.isvar(self.delay):
return t + colony[self.delay]
def _derive_segment_data_(self, segment, preview=False):
source = segment._p_attr['source']
add = self.compiled['add']
e_list = deepcopy(source.data)
for var, LIST in add.iteritems():
if isvar(LIST[0]):
keyvar, list_dic = LIST
key = source[keyvar] # ???
if key not in list_dic:
key_label = keyvar.label(key)
if key_label in list_dic:
key = key_label
else:
msg = "Append: key {k}='{l}' not in list-dic"
raise KeyError(msg.format(k=key, l=key_label))
new = np.array(list_dic[key])
else:
new = np.array(LIST)
if new.ndim == 1:
new = new[:,None]
l_diff = e_list.shape[0] - new.shape[0]
if l_diff > 0:
logging.warning(" Append-LIST too short; nan-padded")
new = np.vstack((new, np.array([[np.NAN]]*l_diff)))
elif l_diff < 0:
logging.warning(" Append-LIST too long; clipped")
new = new[:l_diff,:]
e_list = np.hstack((e_list, new))
return e_list
def toax(self, ax, t0, t1, rc=True, dur=.5):
"""
"""
# print "TOAX: %s -- %s"%(t0, t1)
# index from t0 and t1
# find standard color and color_var
color = self._seg.color
if color is None:
color = (.1, .1, .9)
if _vars.isvar(self._color):
color_var = self._color
else:
color_var = None
if self._color is not None:
color = self._color
time = self._var_time
kwargs = {'alpha':.4}
# prepare scaling factor
if rc and self._var_magnitude:
scaling = max(self._seg.subdata(var=self._var_magnitude))
else:
scaling = 1
# print "TOAX FOR start"
# loop events
for evt in self._seg.sub_iter(time, t0, t1):
# print 'evt'
#time
e_start = evt[time]
# if self._var_duration in evt:
try:
e_end = e_start + evt[self._var_duration]
except:
e_end = e_start + self.duration
# color
if color_var is None:
kwargs['color'] = color
else:
c = self._color.get_color_for_colony(evt)
if c is None:
kwargs['color'] = color
else:
kwargs['color'] = c
# height
# if self._var_magnitude and self._var_magnitude in evt:
try:
y = evt[self._var_magnitude] / scaling
except:
y = self.magnitude
span = ax.axvspan(e_start, e_end, ymax=y, **kwargs)
def names_to_vars(self):
"""
converts all the variables provided as strings into real
variables
"""
for k, v in self._value.items():
if not isvar(v):
var = self._p._dataset.experiment.get_var_with_name(v)
self._value[k] = var
def t1(self, colony):
"return t1 relative to the var-colony"
t0 = colony[self.time]
if _vars.isvar(self.tstart):
out = t0 + colony[self.tstart]
elif np.isscalar(self.tstart):
out = t0 + self.tstart
else:
out = t0
return self._add_delay(out, colony)
def __init__(self, dataset, mag=None, dur=None, color=None, i=0, address=None):
"""
kwargs
------
mag: variable coding the magnitude (displayed as block height). By
default, all blocks will have the same height.
dur: shown event duration, variable or scalar
color: event color (variable)
i: index of the initial segment
address: address indicating the subset of events to draw. By default,
all events are drawn.
"""
self._var_time = dataset.experiment.variables.get('time')
if _vars.isvar(mag):
if id(mag) in [id(v) for v in dataset[0].varlist]:
self._var_magnitude = mag
else:
raise KeyError("segment does not contain magnitude var")
else:
self._var_magnitude = None
if np.isscalar(mag):
self.magnitude = mag
else:
self.magnitude = 1
if dur is None:
self._var_duration = dataset.experiment.variables.get('duration')
self.duration = .5
elif _vars.isvar(dur):
self._var_duration = dur
self.duration = .5
elif np.isscalar(dur):
self._var_duration = None
self.duration = dur
else:
raise ValueError("duration must be either scalar or variable, "
"not %r"%type(dur))
self.set_evt_address(address)
_Visualizer.__init__(self, dataset, color=color, i=i)
def __repr__(self):
s = self.get()
if isvar(s):
return s.name
elif s is None:
return "None"
elif np.isreal(s):
return "%f sec."%s
elif np.iscomplex(s):
return "%i samples"%(s.imag)
def __getitem__(self, name):
"accepts: VarCommanders, str(->properties), indices(->data)"
if isvar(name):
return self.variables[name]
elif isinstance(name, basestring):
if name in self.properties:
return self.properties[name]
elif hasattr(self, 'dataset'):
return self.dataset[name]
else:
raise KeyError("%r not in properties"%name)
else:
return self.data[name]
def in_samples(self, samplingrate, varcolony=None):
"returns None if Time is a variable and segment is None"
v = Param.get(self)
if isvar(v):
if varcolony is None:
return None
else:
v = varcolony[v]
if np.isreal(v):
return int(v * samplingrate)
elif np.iscomplex(v):
out = v.imag
return out
def dt(self, colony=None):
"return t2-t1"
if self.tend is None:
if np.isscalar(self.dur):
return self.dur
elif _vars.isvar(self.dur):
return colony[self.dur]
else:
if np.isscalar(self.tend):
tend = self.tend
else: # _vars.isvar(self.tend)
tend = colony[self.tend]
# subtract tstart
if np.isscalar(self.tstart):
return tend - self.tstart
else:
return tend - colony[self.tstart]
def set(self, time):
"""
Use real values to indicate time in seconds, and complex values to
indicate sample points (e.g. at 200 Hz, 100i == .5)
Note
----
the value is stored in sample points and does not adapt when the
samlingrate of the dataset changes; the value has to be changed
manually.
"""
if isvar(time):
if not self._can_be_var:
raise ValueError("Parameter does not accept variable")
else:
assert np.isscalar(time)
Param.set(self, time)
def __getitem__(self, name):
"""
returns, for the following inputs:
int -> return event with index
Address ->
else -> Segment.__getitem__
"""
# if hasattr(name, 'contains'):
if isvar(name) or isinstance(name, basestring):
return Segment.__getitem__(self, name)
elif np.isscalar(name):
if int(name) != name:
raise ValueError("index needs to be int")
if name >= len(self.data):
raise KeyError("n events < %s"%name)
else:
values = self.data[name]
evt = self._get_static_vars()
for var, val in zip(self.varlist, values):
evt[var] = val
return evt
else:
properties = self.get_full_properties()
if isaddress(name):
select = []
for i, evt in enumerate(self):
if name.contains(evt):
select.append(i)
data = self.data[select]
else:
data = self.data[name]
assert data.shape[1] == len(self.varlist)
return Event_Segment(properties, self.varlist[:],
varsource=self.variables, data=data,
name=self.name)
def __setitem__(self, var, value):
if isinstance(var, basestring):
var = self._p._dataset.experiment.variables.var_with_name(var)
if not isvar(var):
raise ValueError("Key needs to be variable")
Dict.__setitem__(self, var, value)
