def __getitem__(self, i):
if type(i) is slice:
start, stop, stride = i.indices(len(self.parent_dataset))
if stride > 1:
return Numeric.arrayrange(start, stop, stride)
else:
return Numeric.arrayrange(start, stop)
else:
if i < len(self.parent_dataset):
return i
raise IndexError
def __getitem__(self, i):
if type(i) is slice:
start, stop, stride = i.indices(len(self.parent_dataset))
if stride > 1:
return Numeric.arrayrange(start, stop, stride)
else:
return Numeric.arrayrange(start, stop)
else:
if i < len(self.parent_dataset):
return i
raise IndexError
def create_graph2d_view ():
frame = VFrame (Label ("Graph2D"))
frame.topleft = 10, 10
# Create the graph.
graph = Graph2D (400, 400)
# Lock it, because we set some necessary information and want to
# avoid excessive update() calls.
graph.lock ()
# Scale units for the x and y axis.
graph.scale_units = ("cm", "kp")
# Point of origin.
graph.origin = 200, 200
# We want to see negative values.
graph.negative = True
# The evaluation function and data to use.
graph.eval_func = lambda x: x**4.0 - 3 * x**2.0 + 2 * x
if Numeric:
graph.data = Numeric.arrayrange (-10, 10, .001).tolist()
else:
graph.data = numpy.arange (-10, 10, .001).tolist()
# Done, unlock.
graph.unlock ()
button = Button ("Change function")
button.connect_signal (SIG_CLICKED, change, graph)
frame.add_child (graph, button)
return frame
def set_data (self, evt):
dB = evt.data
L = len (dB)
if self.peak_hold:
if self.peak_vals is None:
self.peak_vals = dB
else:
self.peak_vals = Numeric.maximum(dB, self.peak_vals)
dB = self.peak_vals
x = max(abs(self.facsink.sample_rate), abs(self.facsink.baseband_freq))
sf = 1000.0
units = "ms"
x_vals = ((Numeric.arrayrange (L/2)
* ( (sf / self.facsink.sample_rate ) )) )
points = Numeric.zeros((len(x_vals), 2), Numeric.Float64)
points[:,0] = x_vals
points[:,1] = dB[0:L/2]
lines = plot.PolyLine (points, colour='green') # DARKRED
graphics = plot.PlotGraphics ([lines],
title=self.facsink.title,
xLabel = units, yLabel = "dB")
self.Draw (graphics, xAxis=None, yAxis=self.y_range)
self.update_y_range ()
def run (self):
while (self.keep_running):
s = os.read (self.file_descriptor, gr.sizeof_float * self.fft_size)
# if the pipe dies, then quit
if not s:
self.keep_running = False
break
dB = Numeric.fromstring (s, Numeric.Float32)
L = len(dB)
x = max(abs(self.sample_rate), abs(self.baseband_freq))
if x >= 1e9:
self.sf = 1e-9
self.units = "GHz"
elif x >= 1e6:
self.sf = 1e-6
self.units = "MHz"
else:
self.sf = 1e-3
self.units = "kHz"
if self.input_is_real: # only plot 1/2 the points
self.x_vals = ((Numeric.arrayrange (L/2)
* (self.sample_rate * self.sf / L))
+ self.baseband_freq * self.sf)
self.y_vals = dB[0:L/2]
#points = Numeric.zeros((len(self.x_vals), 2), Numeric.Float64)
#points[:,0] = self.x_vals
#points[:,1] = self.y_vals
else:
# the "negative freqs" are in the second half of the array
self.x_vals = ((Numeric.arrayrange (-L/2, L/2)
* (self.sample_rate * self.sf / L))
+ self.baseband_freq * self.sf)
self.y_vals = Numeric.concatenate ((dB[L/2:], dB[0:L/2]))
#points = Numeric.zeros((len(self.x_vals), 2), Numeric.Float64)
#points[:,0] = self.x_vals
#points[:,1] = self.y_vals
# scale points
self.points_subscriptions.send_data((self.x_vals*40, self.y_vals/2))
def sliced_ds(parent_dataset, idx, name=None, filter_label=None, **kwargs):
assert isinstance(idx, slice)
indicies = idx.indices(len(parent_dataset))
record_ids = Numeric.arrayrange(*indicies)
if name is None:
name = 'slice_%d_%d_%d_%s' % (indicies + (parent_dataset.name,))
if filter_label is None:
filter_label = '[%d:%d:%d] slice' % indicies
return FilteredDataset(parent_dataset, record_ids, name=name,
filter_label=filter_label, **kwargs)
def sliced_ds(parent_dataset, idx, name=None, filter_label=None, **kwargs):
assert isinstance(idx, slice)
indicies = idx.indices(len(parent_dataset))
record_ids = Numeric.arrayrange(*indicies)
if name is None:
name = 'slice_%d_%d_%d_%s' % (indicies + (parent_dataset.name, ))
if filter_label is None:
filter_label = '[%d:%d:%d] slice' % indicies
return FilteredDataset(parent_dataset,
record_ids,
name=name,
filter_label=filter_label,
**kwargs)
def suppress_rows(self, suppress_marginal_totals=False):
""" Remove marginal totals and suppressed rows from vectors """
if (not (suppress_marginal_totals and self.marginal_total_rows)
and not self.suppressed_rows):
return
all_rows = Numeric.arrayrange(len(self.values()[0].data))
suppressed_rows = self.suppressed_rows
if suppress_marginal_totals:
suppressed_rows = soomfunc.union(suppressed_rows,
self.marginal_total_rows)
non_mt_rows = soomfunc.outersect(all_rows, suppressed_rows)
for col in self.values():
col.filter_rows(non_mt_rows)
def determinant(a):
_assertRank2(a)
_assertSquareness(a)
t =_commonType(a)
a = _fastCopyAndTranspose(t, a)
n = a.shape[0]
if _array_kind[t] == 1:
lapack_routine = lapack_lite.zgetrf
else:
lapack_routine = lapack_lite.dgetrf
pivots = Numeric.zeros((n,), 'l')
results = lapack_routine(n, n, a, n, pivots, 0)
sign = Numeric.add.reduce(Numeric.not_equal(pivots,
Numeric.arrayrange(1, n+1))) % 2
return (1.-2.*sign)*Numeric.multiply.reduce(Numeric.diagonal(a))
def hist(v, nbins=10, vmin=None, vmax=None, show=None, p=None):
global HOLD, LAST, TABLE, NROWS, NCOLS, R, C
if p is None:
if HOLD:
p = HOLD
else:
t = gettable()
p = FramedPlot()
t[R,C] = p
try:
nth = p.mplotnum + 1
except KeyError:
nth = 0
p.mplotnum = nth
if vmin is None:
vmin = float(min(v))
if vmax is None:
vmax = float(max(v))
binwidth = (vmax - vmin) / float(nbins-1)
x = Numeric.arrayrange(vmin, vmax+binwidth, binwidth)
y = Numeric.zeros(x.shape, 'i')
for i in range(len(v)):
n = int(round((float(v[i]) - vmin) / binwidth, 0))
try:
y[n] = y[n] + 1
except IndexError:
pass
xx = Numeric.zeros(len(x) * 2 + 3, 'f')
yy = Numeric.zeros(len(y) * 2 + 3)
xx[0] = x[0]
yy[0] = 0
for i in range(0, len(x)):
xx[1+2*i],xx[1+2*i+1] = x[i],x[i]+binwidth
yy[1+2*i],yy[1+2*i+1] = y[i],y[i]
xx[1+2*i+2] = x[i]+binwidth
yy[1+2*i+2] = 0;
xx[1+2*i+3] = x[0];
yy[1+2*i+3] = 0;
p.add(FillBelow(xx, yy), Curve(xx, yy))
p.yrange = 0, max(y)
if show:
p.show()
LAST = p
return p
def hist(v, nbins=10, vmin=None, vmax=None, show=None, p=None):
global HOLD, LAST, TABLE, NROWS, NCOLS, R, C
if p is None:
if HOLD:
p = HOLD
else:
t = gettable()
p = FramedPlot()
t[R, C] = p
try:
nth = p.mplotnum + 1
except KeyError:
nth = 0
p.mplotnum = nth
if vmin is None:
vmin = float(min(v))
if vmax is None:
vmax = float(max(v))
binwidth = (vmax - vmin) / float(nbins - 1)
x = Numeric.arrayrange(vmin, vmax + binwidth, binwidth)
y = Numeric.zeros(x.shape, 'i')
for i in range(len(v)):
n = int(round((float(v[i]) - vmin) / binwidth, 0))
try:
y[n] = y[n] + 1
except IndexError:
pass
xx = Numeric.zeros(len(x) * 2 + 3, 'f')
yy = Numeric.zeros(len(y) * 2 + 3)
xx[0] = x[0]
yy[0] = 0
for i in range(0, len(x)):
xx[1 + 2 * i], xx[1 + 2 * i + 1] = x[i], x[i] + binwidth
yy[1 + 2 * i], yy[1 + 2 * i + 1] = y[i], y[i]
xx[1 + 2 * i + 2] = x[i] + binwidth
yy[1 + 2 * i + 2] = 0
xx[1 + 2 * i + 3] = x[0]
yy[1 + 2 * i + 3] = 0
p.add(FillBelow(xx, yy), Curve(xx, yy))
p.yrange = 0, max(y)
if show:
p.show()
LAST = p
return p
def comparison(self):
_token_ = self._peek('"\\\\("', '"not"', 'ID')
if _token_ == 'ID':
col = self.col()
op = self.op()
term = self.term()
return col.filter_op(op, term, self.filter_keys)
elif _token_ == '"\\\\("':
self._scan('"\\\\("')
expr = self.expr()
self._scan('"\\\\)"')
return expr
else:# == '"not"'
self._scan('"not"')
comparison = self.comparison()
return soomfunc.outersect(Numeric.arrayrange(len(self.dataset)), comparison)
def demo():
data = Numeric.arrayrange(w*h)
## fftdata = FFT.fft(data)
## fftdata2 = FFT.fft(data2)
## fftdata3 = (fftdata + fftdata2) / 2.
## invfftdata = FFT.inverse_fft(fftdata3)
## data = invfftdata.real
data = data.astype('l')
im = Image.new("RGBA", (w, h))
print len(data.tostring("raw", "RGBX", 0, -1))
print len(im.tostring("raw", "RGBX", 0, -1))
im.fromstring(data.tostring("raw", "RGBX", 0, -1),"raw", "RGBX", 0, -1)
root = Tkinter.Tk()
image = ImageTk.PhotoImage(im)
x = Tkinter.Label(root, image=image)
x.pack()
root.mainloop()
def demo():
data = Numeric.arrayrange(w * h)
## fftdata = FFT.fft(data)
## fftdata2 = FFT.fft(data2)
## fftdata3 = (fftdata + fftdata2) / 2.
## invfftdata = FFT.inverse_fft(fftdata3)
## data = invfftdata.real
data = data.astype('l')
im = Image.new("RGBA", (w, h))
print len(data.tostring("raw", "RGBX", 0, -1))
print len(im.tostring("raw", "RGBX", 0, -1))
im.fromstring(data.tostring("raw", "RGBX", 0, -1), "raw", "RGBX", 0, -1)
root = Tkinter.Tk()
image = ImageTk.PhotoImage(im)
x = Tkinter.Label(root, image=image)
x.pack()
root.mainloop()
def test_arraydict(self):
def _check(a):
self.assertEqual(a['na'], na)
self.assertEqual(a['maa'], maa)
self.assertEqual(a['na'][500:-500], na[500:-500])
self.assertEqual(a['maa'][500:-500], maa[500:-500])
scatter = Numeric.array(xrange(0, len(na), 3))
self.assertEqual(a['na'].take(scatter), Numeric.take(na, scatter))
self.assertEqual(Numeric.take(a['na'],scatter),
Numeric.take(na, scatter))
self.assertEqual(MA.take(a['maa'], scatter), MA.take(maa, scatter))
tmpfile = TempFile('soomtestarray_tmpfile')
try:
a = soomarray.ArrayDict(tmpfile.fn(), 'w')
self.assertEqual(len(a), 0)
self.assertRaises(KeyError, a.__getitem__, 'not_found')
na = Numeric.arrayrange(10000)
a['na'] = na
na[1000] = -2222
# MmapArray __setitem__
a['na'][1000] = -2222
maa = MA.arrayrange(10000)
for i in xrange(0, len(maa), 5):
maa[i] = MA.masked
a['maa'] = maa
maa[1000] = -2222
a['maa'][1000] = -2222
_check(a)
del a
a = soomarray.ArrayDict(tmpfile.fn(), 'r')
_check(a)
finally:
try: del a
except UnboundLocalError: pass
tmpfile.done()
def op_less_equal(self, value, filter_keys):
return Numeric.arrayrange(value+1)
def op_less_than(self, value, filter_keys):
return Numeric.arrayrange(value)
p.yrange = 0, max(y)
if show:
p.show()
LAST = p
return p
def psprint(dest="-"):
if TABLE:
TABLE.write_eps(dest)
if __name__ == '__main__':
import sys, Numeric, RandomArray
x = Numeric.arrayrange(-10, 10)
y = x**2
e = y / 4
a = RandomArray.random([20, 20, 3])
imagesc(a, x=range(-10, 10), y=range(-10, 10))
drawnow()
sys.stdin.readline()
a = Numeric.array([[[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]])
imagesc(a)
drawnow()
sys.stdin.readline()
src_band = src_ds.GetRasterBand(band_number)
# ----------------------------------------------------------------------------
# Ensure we recognise the driver.
dst_driver = gdal.GetDriverByName(format)
if dst_driver is None:
print '"%s" driver not registered.' % format
sys.exit(1)
# ----------------------------------------------------------------------------
# Build color table.
lookup = [
Numeric.arrayrange(256),
Numeric.arrayrange(256),
Numeric.arrayrange(256),
Numeric.ones(256) * 255
]
ct = src_band.GetRasterColorTable()
if ct is not None:
for i in range(min(256, ct.GetCount())):
entry = ct.GetColorEntry(i)
for c in range(4):
lookup[c][i] = entry[c]
# ----------------------------------------------------------------------------
# Create the working file.
terms.add(term_re)
trans_re = re.compile(r"\b(%s)\b" % "|".join(terms), re.I)
outtrans_fns[column] = Highlighter(trans_re)
return outtrans_fns
def go(self):
kwargs = self.get_params()
ds = self.workspace.get_dataset()
filterexpr = self.workspace.params.dsparams.filterexpr
if filterexpr:
try:
dsrows = ds.filter(filterexpr).record_ids
except Exception, e:
raise UIError('Could not make filter: %s' % e)
else:
dsrows = Numeric.arrayrange(len(ds))
# set any output translations
self.generate_title(ds, filterexpr)
self.workspace.output.dsrows = dsrows
self.workspace.output.highlight_fns = self.get_highlight_fns(
filterexpr)
self.workspace.output.colnames = kwargs['stratacols']
try:
self.workspace.output.pagesize = int(
self.workspace.params.pagesize)
except ValueError:
self.workspace.output.pagesize = 0
self.hide_params = True
class Highlighter:
def op_greater_equal(self, value, filter_keys):
return Numeric.arrayrange(value, len(self))
def op_between(self, value, filter_keys):
return Numeric.arrayrange(*value)
# This module is a lite version of LinAlg.py module which contains
def op_less_equal(self, value, filter_keys):
return Numeric.arrayrange(value + 1)
sys.exit(1)
src_band = src_ds.GetRasterBand(band_number)
# ----------------------------------------------------------------------------
# Ensure we recognise the driver.
dst_driver = gdal.GetDriverByName(format)
if dst_driver is None:
print '"%s" driver not registered.' % format
sys.exit(1)
# ----------------------------------------------------------------------------
# Build color table.
lookup = [ Numeric.arrayrange(256),
Numeric.arrayrange(256),
Numeric.arrayrange(256),
Numeric.ones(256)*255 ]
ct = src_band.GetRasterColorTable()
if ct is not None:
for i in range(min(256,ct.GetCount())):
entry = ct.GetColorEntry(i)
for c in range(4):
lookup[c][i] = entry[c]
# ----------------------------------------------------------------------------
# Create the working file.
def op_greater_than(self, value, filter_keys):
return Numeric.arrayrange(value + 1, len(self))
p.add(FillBelow(xx, yy), Curve(xx, yy))
p.yrange = 0, max(y)
if show:
p.show()
LAST = p
return p
def psprint(dest="-"):
if TABLE:
TABLE.write_eps(dest)
if __name__=='__main__' :
import sys, Numeric, RandomArray
x = Numeric.arrayrange(-10,10);
y = x**2;
e = y/4
a = RandomArray.random([20,20,3])
imagesc(a, x=range(-10,10), y=range(-10,10))
drawnow()
sys.stdin.readline()
a = Numeric.array([[[1, 0, 0],
[0, 1, 0],
[0, 0, 1],
[0, 0, 0]],
[[0, 0, 0],
[0, 0, 0],
terms.add(term_re)
trans_re = re.compile(r"\b(%s)\b" % "|".join(terms), re.I)
outtrans_fns[column] = Highlighter(trans_re)
return outtrans_fns
def go(self):
kwargs = self.get_params()
ds = self.workspace.get_dataset()
filterexpr = self.workspace.params.dsparams.filterexpr
if filterexpr:
try:
dsrows = ds.filter(filterexpr).record_ids
except Exception, e:
raise UIError('Could not make filter: %s' % e)
else:
dsrows = Numeric.arrayrange(len(ds))
# set any output translations
self.generate_title(ds, filterexpr)
self.workspace.output.dsrows = dsrows
self.workspace.output.highlight_fns = self.get_highlight_fns(filterexpr)
self.workspace.output.colnames = kwargs['stratacols']
try:
self.workspace.output.pagesize = int(self.workspace.params.pagesize)
except ValueError:
self.workspace.output.pagesize = 0
self.hide_params = True
class Highlighter:
def __init__(self, trans_re):
self.trans_re = trans_re
def op_greater_than(self, value, filter_keys):
return Numeric.arrayrange(value+1, len(self))
def op_greater_equal(self, value, filter_keys):
return Numeric.arrayrange(value, len(self))
import Numeric
import FFT
import Tkinter
import Image
import ImageTk
import sys
w = 256
h = 256
if __name__ == '__main__':
data = Numeric.arrayrange(w*h)
data = data.astype('l')
im = Image.new("RGBA", (w, h))
print len(data.tostring())
print len(im.tostring())
im.fromstring(data.tostring())
root = Tkinter.Tk()
image = ImageTk.PhotoImage(im)
x = Tkinter.Label(root, image=image)
x.pack()
root.mainloop()
def op_less_than(self, value, filter_keys):
return Numeric.arrayrange(value)
def op_between(self, value, filter_keys):
return Numeric.arrayrange(*value)
