def __init__(self, base, linthresh, linscale):
Transform.__init__(self)
self.base = base
self.linthresh = linthresh
self.linscale = linscale
self._linscale_adj = (linscale / (1.0 - self.base ** -1))
self._log_base = np.log(base)
def __init__(self, **kwargs):
Transform.__init__(self, **kwargs)
self.dec0 = 0
self.ra0 = 180
self.dec1 = -60
self.dec2 = 30
self._update()
def __init__(self, nonpos):
Transform.__init__(self)
if nonpos == 'mask':
self._handle_nonpos = _mask_non_logit
else:
self._handle_nonpos = _clip_non_logit
self._nonpos = nonpos
def __init__(self, resolution):
"""
Resolution is the number of steps to interpolate between each input
line segment to approximate its path in transformed space.
"""
Transform.__init__(self)
self._resolution = resolution
def __init__(self, trans, dpi_scale_trans, fixed_point):
Transform.__init__(self)
self.input_dims = self.output_dims = 2
self.has_inverse = False
self.trans = trans
self.dpi_scale_trans = dpi_scale_trans
self.fixed_point = num.asarray(fixed_point, dtype=num.float)
def __init__(self, nonpos):
Transform.__init__(self)
if nonpos == 'mask':
self._fill_value = np.nan
else:
self._fill_value = 1e-300
self._nonpos = nonpos
def __init__(self, base, nonpos):
Transform.__init__(self)
self.base = base
if nonpos == 'mask':
self._handle_nonpos = _mask_non_positives
else:
self._handle_nonpos = _clip_non_positives
def __init__(self, resolution):
'''Create a new Split Lambert transform.
Resolution is the number of steps to interpolate between each
input line segment to approximate its path in curved Lambert space.
'''
Transform.__init__(self)
self._resolution = resolution
def __init__(self, resolution=None):
"""
Create a new WCS transform.
"""
Transform.__init__(self)
if resolution is None:
resolution = 1
self._resolution = resolution
def __init__(self, base, linthresh, linscale):
Transform.__init__(self)
symlog = SymmetricalLogTransform(base, linthresh, linscale)
self.base = base
self.linthresh = linthresh
self.invlinthresh = symlog.transform(linthresh)
self.linscale = linscale
self._linscale_adj = (linscale / (1.0 - self.base ** -1))
def __init__(self, resolution):
"""
Create a new Hammer transform. Resolution is the number of steps
to interpolate between each input line segment to approximate its
path in curved Hammer space.
"""
Transform.__init__(self)
self._resolution = resolution
def __init__(self, projection, resolution):
"""
Create a new Mollweide transform. Resolution is the number of steps
to interpolate between each input line segment to approximate its
path in curved Mollweide space.
"""
self.projection = projection
Transform.__init__(self)
self._resolution = resolution
def __init__(self, center_longitude, center_latitude, resolution):
"""
Create a new Lambert transform. Resolution is the number of steps
to interpolate between each input line segment to approximate its
path in curved Lambert space.
"""
Transform.__init__(self)
self._resolution = resolution
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def __init__(self, target_grid=None, source_crs=None, ax=None):
""" Instanciate.
Parameters
----------
target_grid : salem.Grid
typically, the map grid
source_grid
"""
self.source_crs = source_crs
self.target_grid = target_grid
self.ax = ax
MPLTranform.__init__(self)
def __init__(self, dist, as_pct=True, out_of_bounds='mask'):
Transform.__init__(self)
self.dist = dist
self.as_pct = as_pct
self.out_of_bounds = out_of_bounds
if self.as_pct:
self.factor = 100.0
else:
self.factor = 1.0
if self.out_of_bounds == 'mask':
self._handle_out_of_bounds = _mask_out_of_bounds
elif self.out_of_bounds == 'clip':
self._handle_out_of_bounds = _clip_out_of_bounds
else:
raise ValueError("`out_of_bounds` muse be either 'mask' or 'clip'")
def __init__(self, nonpos='mask'):
Transform.__init__(self)
self._nonpos = nonpos
set(gca(), 'yticks', [])
xlabel('intensity')
ylabel('MRI density')
if 1: # plot the EEG
# load the data
numSamples, numRows = 800, 4
data = fromstring(file('data/eeg.dat', 'rb').read(), Float)
data.shape = numSamples, numRows
t = arange(numSamples) / float(numSamples) * 10.0
ticklocs = []
ax = subplot(212)
height = 72 # height of one EEG in pixels
# transform data to axes coord (0,1)
transy = Transform(Bound1D(-.05, .05), Bound1D(-.2, .2))
for i in range(numRows):
thisLine = Line2D(ax.dpi,
ax.bbox,
t,
data[:, i] - data[0, i],
transx=ax.xaxis.transData,
transy=transy)
offset = (i + 1) / (numRows + 1)
thisLine.set_vertical_offset(offset, ax.yaxis.transAxis)
ax.add_line(thisLine)
ticklocs.append(offset)
set(gca(), 'xlim', [0, 10])
set(gca(), 'xticks', arange(10))
def __init__(self, projection):
self.projection = projection
Transform.__init__(self)
def __init__(self, nonpos='mask'):
Transform.__init__(self)
cbook._check_in_list(['mask', 'clip'], nonpos=nonpos)
self._nonpos = nonpos
self._clip = {"clip": True, "mask": False}[nonpos]
def __init__(self, axis=None):
Transform.__init__(self)
self._axis = axis
def __init__(self, nonpos):
Transform.__init__(self)
if nonpos == 'mask':
self._fill_value = np.nan
else:
self._fill_value = 1e-300
def __init__(self):
Transform.__init__(self)
def __init__(self, dist):
self.dist = dist
Transform.__init__(self)
def __init__(self, nonpos='mask'):
Transform.__init__(self)
self._nonpos = nonpos
self._clip = {"clip": True, "mask": False}[nonpos]
def invalidate(self):
#print("I don't feel validated! (%s)" % (self.pass_through))
return Transform.invalidate(self)
def __init__(self, base):
Transform.__init__(self)
self.base = base
def __init__(self, x_from, y_to):
self.xpoints = x_from
self.ypoints = y_to
Transform.__init__(self)
def __init__(self, nonpos="mask"):
Transform.__init__(self)
self._nonpos = nonpos
def __init__(self, nonpos):
Transform.__init__(self)
if nonpos == 'mask':
self._handle_nonpos = _mask_non_positives
else:
self._handle_nonpos = _clip_non_positives
def transform_affine(self, values):
print 'affine'
return Transform.transform_affine(self, values)
def __init__(self, axis=None, use_rmin=True):
Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
def __init__(self, base, nonpos='clip'):
Transform.__init__(self)
self.base = base
self._clip = {"clip": True, "mask": False}[nonpos]
def __init__(self, center_longitude, center_latitude, resolution):
Transform.__init__(self)
self._resolution = resolution
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def __init__(self, nonpos='mask'):
Transform.__init__(self)
self._nonpos = nonpos
def __init__(self, base):
Transform.__init__(self)
self.base = base
def __init__(self, exponent):
Transform.__init__(self)
self.exponent = exponent
def __init__(self, dist, nonpos='mask'):
Transform.__init__(self)
self.dist = dist
self._nonpos = nonpos
def __init__(self, center_longitude, center_latitude, resolution):
Transform.__init__(self)
self._resolution = resolution
self._center_longitude = center_longitude
self._center_latitude = center_latitude
def __init__(self, nonpos='clip'):
Transform.__init__(self)
self._clip = {"clip": True, "mask": False}[nonpos]
def __init__(self, resolution):
Transform.__init__(self)
self._resolution = resolution
def __init__(self, dist):
self.dist = dist
Transform.__init__(self)
def invalidate(self):
#print("I don't feel validated! (%s)" % (self.pass_through))
return Transform.invalidate(self)
def __init__(self, axis=None):
Transform.__init__(self)
self._axis = axis
def __init__(self, x_from, y_to):
self.xpoints = x_from
self.ypoints = y_to
Transform.__init__(self)
def __init__(self, inverted, **kwargs):
Transform.__init__(self, **kwargs)
self.inverted = inverted
def __init__(self, axis=None, use_rmin=True):
Transform.__init__(self)
self._axis = axis
self._use_rmin = use_rmin
def __init__(self, resolution):
Transform.__init__(self)
self._resolution = resolution
