def x_data_view(self, x_window=None, flatten_y=False):
"""Helper method for getting a view of the data.
Parameters
----------
x_window : optional
The window of x variable (omega/omega_n/t/tau) for which data is requested.
flatten_y: bool, optional
If the Greens function is of size (1, 1) flatten the array as a 1d array.
Returns
-------
(X, data) : tuple
X is a 1d numpy array of the x variable inside the window requested.
data is a 3d numpy array of dim (:,:, len(X)), the corresponding slice of data.
If flatten_y is True and dim is (1, 1, *) it returns a 1d numpy array.
"""
X = [x.imag for x in self.mesh] if isinstance(self.mesh, meshes.MeshImFreq) \
else [x for x in self.mesh]
X, data = np.array(X), self.data
if x_window:
# the slice due to clip option x_window
sl = clip_array(X, *x_window) if x_window else slice(len(X))
X, data = X[sl], data[sl, :, :]
if flatten_y and data.shape[1:3] == (1, 1):
data = data[:, 0, 0]
return X, data
def x_data_view(self, x_window = None, flatten_y = False):
"""
:param x_window: the window of x variable (omega/omega_n/t/tau) for which data is requested
if None, take the full window
:param flatten_y: If the Green function is of size (1, 1) flatten the array as a 1d array
:rtype: a tuple (X, data) where
* X is a 1d numpy of the x variable inside the window requested
* data is a 3d numpy array of dim (:,:, len(X)), the corresponding slice of data
If flatten_y is True and dim is (1, 1, *), returns a 1d numpy
"""
X = [x.imag for x in self.mesh] if type(self.mesh) == MeshImFreq else [x for x in self.mesh]
X, data = numpy.array(X), self.data
if x_window:
sl = clip_array (X, *x_window) if x_window else slice(len(X)) # the slice due to clip option x_window
X, data = X[sl], data[sl,:,:]
if flatten_y and data.shape[1:3]==(1, 1): data = data[:,0,0]
return X, data
def plot_base(self, opt_dict, xlabel, ylabel, use_ris, X):
""" Plot protocol. opt_dict can contain:
*:param RIS: 'R', 'I', 'S', 'RI' [ default]
*:param x_window: (xmin,xmax) or None [default]
*:param Name: a string [default = '']. If not '', it remplaces the name of the function just for this plot.
"""
Name = opt_dict.pop('name', '') # consume it
NamePrefix = opt_dict.pop('NamePrefix', '') # consume it
if Name and NamePrefix:
raise ValueError, 'Name and NamePrefix cannot be used at the same time'
if NamePrefix: name_save, self.name = self.name, Name or NamePrefix
rx = opt_dict.pop('x_window', None) # consume it
X = numpy.array(X).real
sl = clip_array(X, *rx) if rx else slice(
len(X)) # the slice due to clip option x_window
def mdic(prefix, f):
return [{
'type': "XY",
'xlabel': xlabel,
'ylabel': ylabel(self.name),
'xdata': X[sl],
'label': Name if Name else prefix + "%s_%s" % (i, j),
'ydata': f(self.data[sl, i, j])
} for i in range(self.target_shape[0])
for j in range(self.target_shape[1])]
if use_ris:
ris = opt_dict.pop('RI', 'RI')
if ris == "R":
res = mdic('Re ', lambda x: x.real)
elif ris == "I":
res = mdic('Im ', lambda x: x.imag)
elif ris == "S":
res = mdic('', lambda x: -1 / numpy.pi * x.imag)
elif ris == 'RI':
res = mdic('Re ', lambda x: x.real) + mdic('Im ', lambda x: x.imag)
else:
raise ValueError, "RIS flags meaningless %s" % ris
else:
res = mdic('', lambda x: x)
if NamePrefix: self.name = name_save
return res
def x_data_view(self, x_window = None, flatten_y = False):
"""
:param x_window: the window of x variable (omega/omega_n/t/tau) for which data is requested
if None, take the full window
:param flatten_y: If the Green function is of size (1, 1) flatten the array as a 1d array
:rtype: a tuple (X, data) where
* X is a 1d numpy of the x variable inside the window requested
* data is a 3d numpy array of dim (:,:, len(X)), the corresponding slice of data
If flatten_y is True and dim is (1, 1, *), returns a 1d numpy
"""
X = [x.imag for x in self.mesh] if type(self.mesh) == MeshImFreq else [x for x in self.mesh]
X, data = numpy.array(X), self.data
if x_window:
sl = clip_array (X, *x_window) if x_window else slice(len(X)) # the slice due to clip option x_window
X, data = X[sl], data[sl,:,:]
if flatten_y and data.shape[1:3]==(1, 1): data = data[:,0,0]
return X, data
def plot_base (self, opt_dict, xlabel, ylabel, use_ris, X):
""" Plot protocol. opt_dict can contain:
*:param RIS: 'R', 'I', 'S', 'RI' [ default]
*:param x_window: (xmin,xmax) or None [default]
*:param Name: a string [default = '']. If not '', it remplaces the name of the function just for this plot.
"""
Name = opt_dict.pop('name', '' ) # consume it
NamePrefix = opt_dict.pop('NamePrefix', '' ) # consume it
if Name and NamePrefix: raise ValueError, 'Name and NamePrefix cannot be used at the same time'
if NamePrefix: name_save, self.name = self.name, Name or NamePrefix
rx = opt_dict.pop('x_window',None ) # consume it
X = numpy.array(X).real
sl = clip_array (X, *rx) if rx else slice(len(X)) # the slice due to clip option x_window
def mdic( prefix, f):
return [{'type': "XY",
'xlabel': xlabel,
'ylabel': ylabel (self.name),
'xdata': X[sl],
'label': Name if Name else prefix + "%s_%s"%(i,j),
'ydata': f( self.data[sl,i,j] ) } for i in range(self.target_shape[0]) for j in range(self.target_shape[1])]
if use_ris:
ris = opt_dict.pop('RI','RI')
if ris == "R":
res = mdic( 'Re ', lambda x : x.real)
elif ris == "I":
res = mdic( 'Im ', lambda x : x.imag)
elif ris == "S":
res = mdic( '', lambda x : -1/numpy.pi *x.imag)
elif ris == 'RI':
res = mdic( 'Re ', lambda x : x.real) + mdic( 'Im ', lambda x : x.imag)
else:
raise ValueError, "RIS flags meaningless %s"%ris
else:
res = mdic( '', lambda x : x)
if NamePrefix: self.name = name_save
return res
def plot_base(self, opt_dict, xlabel, ylabel, X, allow_spectral_mode=False):
r"""
Plot protocol for Green's function objects.
Parameters
----------
opt_dict: dictionary
Can contain:
- mode: string, default None
Mode to plot the Green's function in:
-- 'R': real part only
-- 'I': imaginary part only
-- 'S': spectral function
- x_window: tuple, default None
(xmin,xmax)
- name: string, default = ''
If not '', it remplaces the name of the function just for this plot.
xlabel: string
Label to apply to the x axis.
ylabel: string
Label to apply to the y axis.
X: list
The x values the object can take, i.e. the mesh.
allow_spectral_mode: boolean, default False
Can the spectral function be measured for this type of Green's function?
Returns
-------
plot_data: list of dict
Object passed to oplot to plot.
"""
name = opt_dict.pop('name', self.name) # consume it
name_prefix = opt_dict.pop('name_prefix', '') # consume it
if name and name_prefix:
raise ValueError, 'name and name_prefix cannot be used at the same time'
if name_prefix:
name_save, self.name = self.name, name or name_prefix
rx = opt_dict.pop('x_window', None) # consume it
X = numpy.array(X).real
sl = clip_array(X, *rx) if rx else slice(
len(X)) # the slice due to clip option x_window
def mdic(prefix, f):
from itertools import product
ind_range = product(*map(range, reversed(self.target_shape)))
make_label = lambda ind: "%s%s %s" % (prefix, name, "_".join(
map(str, reversed(ind))))
make_data_sl = lambda ind: (sl, ) + tuple(reversed(ind))
return [{
'xlabel': xlabel,
'ylabel': ylabel(self.name or name),
'xdata': X[sl],
'label': make_label(ind),
'ydata': f(self.data[make_data_sl(ind)])
} for ind in ind_range]
# backward compat.
if 'RI' in opt_dict:
assert 'mode' not in opt_dict, "Can not have both flags RI and mode."
import warnings
warnings.warn("oplot: 'RI' flag is deprecated, use 'mode' instead")
opt_dict['mode'] = opt_dict.pop('RI', '')
mode = opt_dict.pop('mode', '')
if mode == '':
res = mdic('Re ', lambda x: x.real) + mdic('Im ', lambda x: x.imag)
elif mode == 'R':
res = mdic('Re ', lambda x: x.real)
elif mode == 'I':
res = mdic('Im ', lambda x: x.imag)
elif mode == 'S':
if allow_spectral_mode:
res = mdic('', lambda x: -1 / numpy.pi * x.imag)
else:
raise ValueError, "Cannot measure the spectral function for this type of Green's function."
else:
raise ValueError, "The 'mode' flag is meaningless. Expected 'R', 'I', or 'S' and I got %s." % mode
res[0].update(opt_dict) # Add all other unused parameters to the dict
if name_prefix:
self.name = name_save
return res
def plot_base(self, opt_dict, xlabel, ylabel, X, allow_spectral_mode=False):
r"""
Plot protocol for Green's function objects.
Parameters
----------
opt_dict: dictionary
MUST contain:
- name: str
Name for the plotting label
Can contain:
- mode: string, default None
Mode to plot the Green's function in:
-- 'R': real part only
-- 'I': imaginary part only
-- 'S': spectral function
- x_window: tuple, default None
(xmin,xmax)
xlabel: str
Label to apply to the x axis.
ylabel: lambda : str -> str
Label to apply to the y axis.
X: list
The x values the object can take, i.e. the mesh.
allow_spectral_mode: boolean, default False
Can the spectral function be measured for this type of Green's function?
Returns
-------
plot_data: list of dict
Object passed to oplot to plot.
"""
assert 'name_prefix' not in opt_dict, "name_prefix is deprecated"
#if 'name' not in opt_dict:
# warnings.warn("oplot REQUIRES a name = for making the legend and labels. Using self.name, but it is deprecated and WILL BE REMOVED")
name = opt_dict.pop('name', self.name) # consume it
if not name:
warn("oplot of gf : no name provided !")
rx = opt_dict.pop('x_window', None) # consume it
X = numpy.array(X).real
sl = clip_array(X, *rx) if rx else slice(
len(X)) # the slice due to clip option x_window
def mdic(prefix, f):
from itertools import product
ind_range = product(*map(range, reversed(self.target_shape)))
make_label = lambda ind: "%s%s %s" % (prefix, name, "_".join(
map(str, reversed(ind))))
make_data_sl = lambda ind: (sl, ) + tuple(reversed(ind))
return [{
'xlabel': xlabel,
'ylabel': ylabel(name),
'xdata': X[sl],
'label': make_label(ind),
'ydata': f(self.data[make_data_sl(ind)])
} for ind in ind_range]
# backward compat.
if 'RI' in opt_dict:
assert 'mode' not in opt_dict, "Can not have both flags RI and mode."
import warnings
warnings.warn("oplot: 'RI' flag is deprecated, use 'mode' instead")
opt_dict['mode'] = opt_dict.pop('RI', '')
# if data is real, overrule
mode = opt_dict.pop('mode', '')
if self.data.dtype == numpy.float64:
res = mdic('', lambda x: x)
elif mode == '':
res = mdic('Re ', lambda x: x.real) + mdic('Im ', lambda x: x.imag)
elif mode == 'R':
res = mdic('Re ', lambda x: x.real)
elif mode == 'I':
res = mdic('Im ', lambda x: x.imag)
elif mode == 'S':
if allow_spectral_mode:
res = mdic('', lambda x: -1 / numpy.pi * x.imag)
else:
raise ValueError, "Cannot measure the spectral function for this type of Green's function."
else:
raise ValueError, "The 'mode' flag is meaningless. Expected 'R', 'I', or 'S' and I got %s." % mode
res[0].update(opt_dict) # Add all other unused parameters to the dict
return res
def plot_base(self, opt_dict, xlabel, ylabel, X, allow_spectral_mode=False):
r"""
Plot protocol for Green's function objects.
Parameters
----------
opt_dict: dictionary
Can contain:
- mode: string, default None
Mode to plot the Green's function in:
-- 'R': real part only
-- 'I': imaginary part only
-- 'S': spectral function
- x_window: tuple, default None
(xmin,xmax)
- name: string, default = ''
If not '', it remplaces the name of the function just for this plot.
xlabel: string
Label to apply to the x axis.
ylabel: string
Label to apply to the y axis.
X: list
The x values the object can take, i.e. the mesh.
allow_spectral_mode: boolean, default False
Can the spectral function be measured for this type of Green's function?
Returns
-------
plot_data: list of dict
Object passed to oplot to plot.
"""
name = opt_dict.pop('name', self.name) # consume it
name_prefix = opt_dict.pop('name_prefix', '') # consume it
if name and name_prefix:
raise ValueError, 'name and name_prefix cannot be used at the same time'
if name_prefix:
name_save, self.name = self.name, name or name_prefix
rx = opt_dict.pop('x_window', None) # consume it
X = numpy.array(X).real
sl = clip_array(X, *rx) if rx else slice(len(X)) # the slice due to clip option x_window
def mdic(prefix, f):
return [{'xlabel': xlabel,
'ylabel': ylabel(self.name or name),
'xdata': X[sl],
'label': prefix + "%s %s_%s" % (name, i, j),
'ydata': f(self.data[sl, i, j])} for i in range(self.target_shape[0]) for j in range(self.target_shape[1])]
# backward compat.
if 'RI' in opt_dict:
assert 'mode' not in opt_dict, "Can not have both flags RI and mode."
import warnings
warnings.warn("oplot: 'RI' flag is deprecated, use 'mode' instead")
opt_dict['mode'] = opt_dict.pop('RI', '')
mode = opt_dict.pop('mode', '')
if mode == '':
res = mdic('Re ', lambda x: x.real) + mdic('Im ', lambda x: x.imag)
elif mode == 'R':
res = mdic('Re ', lambda x: x.real)
elif mode == 'I':
res = mdic('Im ', lambda x: x.imag)
elif mode == 'S':
if allow_spectral_mode:
res = mdic('', lambda x: -1 / numpy.pi * x.imag)
else:
raise ValueError, "Cannot measure the spectral function for this type of Green's function."
else:
raise ValueError, "The 'mode' flag is meaningless. Expected 'R', 'I', or 'S' and I got %s." % mode
res[0].update(opt_dict) # Add all other unused parameters to the dict
if name_prefix:
self.name = name_save
return res
def plot_base(self, opt_dict, xlabel, ylabel, X, allow_spectral_mode=False):
r"""
Plot protocol for Green's function objects.
Parameters
----------
opt_dict: dictionary
MUST contain:
- name: str
Name for the plotting label
Can contain:
- mode: string, default None
Mode to plot the Green's function in:
-- 'R': real part only
-- 'I': imaginary part only
-- 'S': spectral function
- x_window: tuple, default None
(xmin,xmax)
xlabel: str
Label to apply to the x axis.
ylabel: lambda : str -> str
Label to apply to the y axis.
X: list
The x values the object can take, i.e. the mesh.
allow_spectral_mode: boolean, default False
Can the spectral function be measured for this type of Green's function?
Returns
-------
plot_data: list of dict
Object passed to oplot to plot.
"""
assert 'name_prefix' not in opt_dict, "name_prefix is deprecated"
#if 'name' not in opt_dict:
# warnings.warn("oplot REQUIRES a name = for making the legend and labels. Using self.name, but it is deprecated and WILL BE REMOVED")
name = opt_dict.pop('name', self.name) # consume it
if not name:
warn("oplot of gf : no name provided !")
rx = opt_dict.pop('x_window', None) # consume it
X = numpy.array(X).real
sl = clip_array(X, *rx) if rx else slice(len(X)) # the slice due to clip option x_window
def mdic(prefix, f):
from itertools import product
ind_range = product(*map(range,reversed(self.target_shape)))
make_label = lambda ind: "%s%s %s" % (prefix,name,"_".join(map(str, reversed(ind))))
make_data_sl = lambda ind: (sl,) + tuple(reversed(ind))
return [{'xlabel': xlabel,
'ylabel': ylabel(name),
'xdata': X[sl],
'label': make_label(ind),
'ydata': f(self.data[make_data_sl(ind)])} for ind in ind_range]
# backward compat.
if 'RI' in opt_dict:
assert 'mode' not in opt_dict, "Can not have both flags RI and mode."
import warnings
warnings.warn("oplot: 'RI' flag is deprecated, use 'mode' instead")
opt_dict['mode'] = opt_dict.pop('RI', '')
# if data is real, overrule
mode = opt_dict.pop('mode', '')
if self.data.dtype == numpy.float64 :
res = mdic('', lambda x: x)
elif mode == '':
res = mdic('Re ', lambda x: x.real) + mdic('Im ', lambda x: x.imag)
elif mode == 'R':
res = mdic('Re ', lambda x: x.real)
elif mode == 'I':
res = mdic('Im ', lambda x: x.imag)
elif mode == 'S':
if allow_spectral_mode:
res = mdic('', lambda x: -1 / numpy.pi * x.imag)
else:
raise ValueError, "Cannot measure the spectral function for this type of Green's function."
else:
raise ValueError, "The 'mode' flag is meaningless. Expected 'R', 'I', or 'S' and I got %s." % mode
res[0].update(opt_dict) # Add all other unused parameters to the dict
return res
