def read1Dv(self, fname, tname):
# open file and read column 0, 1 and 2 (variance), separator is tab
data_t = []
data_x = []
data_v = []
fp = open(fname, 'r')
for l in fp:
args = l.split('\t')
if args[0][0].isalpha() == 0:
data_t.append(float(args[0]))
data_x.append(float(args[1]))
data_v.append(float(args[2]))
fp.close()
if len(data_v)<len(data_x):
data_v = np.zeros(len(data_x))
data1 = DataArray(name=tname+" 0", shape=[len(data_t)])
data2 = DataArray(name=tname+" 1", shape=[len(data_t)])
data1.coords = [np.array(data_t)]
data1.data = np.array(data_x)
data1.shape = [len(data_x)]
data2.coords = [np.array(data_t)]
data2.data = np.array(data_v)
data2.shape = [len(data_v)]
return [data1, data2]
def read1D(self, fname, tname):
# open file and read column 0 and 1, separator is tab
data_t = []
data_x = []
fp = open(fname, 'r')
for l in fp:
args = l.split('\t')
if args[0][0].isalpha() == 0:
data_t.append(float(args[0]))
data_x.append(float(args[1]))
fp.close()
data = DataArray(name=tname, shape=[len(data_t)])
data.coords = [np.array(data_t)]
data.data = np.array(data_x)
data.shape = [len(data_x)]
return [data]
def ComputeReference(self, inst):
"""
Compute reference from given data if reference filter exists.
Parameters:
inst - array (DataArray)
or pubsub event data
inst.data must be DataArray
"""
if not(isinstance(inst,DataArray)):
array = inst.data
else:
array = inst
narray = DataArray(shape=array.shape[:])
narray.coords = array.coords[:]
narray.data = array.data[:]
# build reference data
# first apply previous filter banks
bank = self
while bank.parent!=None:
bank = bank.parent
while bank!=self:
narray = bank.ApplyFilters(narray)
bank = bank.children[-1]
# then apply current filter bank up to reference filter
for ft in self.filters:
if not(ft.is_reference):
if ft.is_active:
ft.apply_filter(narray)
else:
ft.ref = narray
ft.source = array
if inst!=array:
pub.sendMessage("filter.change", data=self) # send filter change notification with filter bank as object
break
def UpdateFilterDisplay(self, inst=None):
"""
Update display of apodization window.
Parameters:
inst - pubsub event data
"""
# update apodization filter preview
arr = DataArray(shape=[201])
arr.coords = [np.linspace(-1.0,1.0,201)]
arr.data = np.ones(201)
is_before_ft = True
if isinstance(self.bank,FilterBank):
for ft in self.bank.filters:
if ft.is_pre_filter and is_before_ft and ft.is_active:
ft.apply_filter(arr)
if ft.is_transform:
is_before_ft = False
data_x = np.concatenate(([-1.5,-1.0], arr.coords[0], [1.0,1.5]))
data_y = np.concatenate(([0.0,0.0], arr.data, [0.0,0.0]))
self.line_filter.set_data(data_x, data_y)
self.plot_filter.draw()
