class PipeContainer(Prototype):
"""Class containing all the program data."""
def __init__(self):
"""Set up all the PipeContainer data structures."""
# The molecule-residue-spin object.
self.mol = MoleculeList()
# The interatomic data object.
self.interatomic = InteratomList()
# The data pipe type.
self.pipe_type = None
# Hybrid models.
self.hybrid_pipes = []
def __repr__(self):
"""The string representation of the object.
Rather than using the standard Python conventions (either the string representation of the
value or the "<...desc...>" notation), a rich-formatted description of the object is given.
"""
# Intro text.
text = "The data pipe storage object.\n"
# Special objects/methods (to avoid the getattr() function call on).
spec_obj = ['exp_info', 'mol', 'interatomic', 'diff_tensor', 'structure']
# Objects.
text = text + "\n"
text = text + "Objects:\n"
for name in dir(self):
# Molecular list.
if name == 'mol':
text = text + " mol: The molecule list (for the storage of the spin system specific data)\n"
# Interatomic data list.
if name == 'interatomic':
text = text + " interatomic: The interatomic data list (for the storage of the inter-spin system data)\n"
# Diffusion tensor.
if name == 'diff_tensor':
text = text + " diff_tensor: The Brownian rotational diffusion tensor data object\n"
# Molecular structure.
if name == 'structure':
text = text + " structure: The 3D molecular data object\n"
# The experimental info data container.
if name == 'exp_info':
text = text + " exp_info: The data container for experimental information\n"
# Skip the PipeContainer methods.
if name in list(self.__class__.__dict__.keys()):
continue
# Skip certain objects.
if match("^_", name) or name in spec_obj:
continue
# Add the object's attribute to the text string.
text = text + " " + name + ": " + repr(getattr(self, name)) + "\n"
# Return the text representation.
return text
def _back_compat_hook(self, file_version=None):
"""Method for converting old data structures to the new ones.
@keyword file_version: The relax XML version of the XML file.
@type file_version: int
"""
# Relaxation data.
self._back_compat_hook_ri_data()
def _back_compat_hook_ri_data(self):
"""Converting the old relaxation data structures to the new ones."""
# Nothing to do.
if not (hasattr(cdp, 'frq_labels') and hasattr(cdp, 'noe_r1_table') and hasattr(cdp, 'remap_table')):
return
# Initialise the new structures.
cdp.ri_ids = []
cdp.ri_type = {}
frq = {} # This will be placed into cdp later as cdp.spectrometer_frq still exists.
# Generate the new structures.
for i in range(cdp.num_ri):
# The ID.
ri_id = "%s_%s" % (cdp.ri_labels[i], cdp.frq_labels[cdp.remap_table[i]])
# Not unique.
if ri_id in cdp.ri_ids:
# Loop until a unique ID is found.
for j in range(100):
# New id.
new_id = "%s_%s" % (ri_id, j)
# Unique.
if not new_id in cdp.ri_ids:
ri_id = new_id
break
# Add the ID.
cdp.ri_ids.append(ri_id)
# The relaxation data type.
cdp.ri_type[ri_id] = cdp.ri_labels[i]
# The frequency data.
frq[ri_id] = cdp.frq[cdp.remap_table[i]]
# Delete the old structures.
del cdp.frq
del cdp.frq_labels
del cdp.noe_r1_table
del cdp.num_frq
del cdp.num_ri
del cdp.remap_table
del cdp.ri_labels
# Set the frequencies.
cdp.frq = frq
def from_xml(self, pipe_node, file_version=None, dir=None):
"""Read a pipe container XML element and place the contents into this pipe.
@param pipe_node: The data pipe XML node.
@type pipe_node: xml.dom.minidom.Element instance
@keyword file_version: The relax XML version of the XML file.
@type file_version: int
@keyword dir: The name of the directory containing the results file (needed for loading external files).
@type dir: str
"""
# Test if empty.
if not self.is_empty():
raise RelaxFromXMLNotEmptyError(self.__class__.__name__)
# Get the global data node, and fill the contents of the pipe.
global_node = pipe_node.getElementsByTagName('global')[0]
xml_to_object(global_node, self, file_version=file_version)
# Backwards compatibility transformations.
self._back_compat_hook(file_version)
# Get the hybrid node (and its sub-node), and recreate the hybrid object.
hybrid_node = pipe_node.getElementsByTagName('hybrid')[0]
pipes_node = hybrid_node.getElementsByTagName('pipes')[0]
setattr(self, 'hybrid_pipes', node_value_to_python(pipes_node.childNodes[0]))
# Get the experimental information data nodes and, if they exist, fill the contents.
exp_info_nodes = pipe_node.getElementsByTagName('exp_info')
if exp_info_nodes:
# Create the data container.
self.exp_info = ExpInfo()
# Fill its contents.
self.exp_info.from_xml(exp_info_nodes[0], file_version=file_version)
# Get the diffusion tensor data nodes and, if they exist, fill the contents.
diff_tensor_nodes = pipe_node.getElementsByTagName('diff_tensor')
if diff_tensor_nodes:
# Create the diffusion tensor object.
self.diff_tensor = DiffTensorData()
# Fill its contents.
self.diff_tensor.from_xml(diff_tensor_nodes[0], file_version=file_version)
# Get the alignment tensor data nodes and, if they exist, fill the contents.
align_tensor_nodes = pipe_node.getElementsByTagName('align_tensors')
if align_tensor_nodes:
# Create the alignment tensor object.
self.align_tensors = AlignTensorList()
# Fill its contents.
self.align_tensors.from_xml(align_tensor_nodes[0], file_version=file_version)
# Recreate the interatomic data structure (this needs to be before the 'mol' structure as the backward compatibility hooks can create interatomic data containers!).
interatom_nodes = pipe_node.getElementsByTagName('interatomic')
self.interatomic.from_xml(interatom_nodes, file_version=file_version)
# Recreate the molecule, residue, and spin data structure.
mol_nodes = pipe_node.getElementsByTagName('mol')
self.mol.from_xml(mol_nodes, file_version=file_version)
# Get the structural object nodes and, if they exist, fill the contents.
str_nodes = pipe_node.getElementsByTagName('structure')
if str_nodes:
# Create the structural object.
fail = False
self.structure = Internal()
# Fill its contents.
if not fail:
self.structure.from_xml(str_nodes[0], dir=dir, file_version=file_version)
def is_empty(self):
"""Method for testing if the data pipe is empty.
@return: True if the data pipe is empty, False otherwise.
@rtype: bool
"""
# Is the molecule structure data object empty?
if hasattr(self, 'structure'):
return False
# Is the molecule/residue/spin data object empty?
if not self.mol.is_empty():
return False
# Is the interatomic data object empty?
if not self.interatomic.is_empty():
return False
# Tests for the initialised data (the pipe type can be set in an empty data pipe, so this isn't checked).
if self.hybrid_pipes:
return False
# An object has been added to the container.
for name in dir(self):
# Skip the objects initialised in __init__().
if name in ['mol', 'interatomic', 'pipe_type', 'hybrid_pipes']:
continue
# Skip the PipeContainer methods.
if name in list(self.__class__.__dict__.keys()):
continue
# Skip special objects.
if match("^_", name):
continue
# An object has been added.
return False
# The data pipe is empty.
return True
def to_xml(self, doc, element):
"""Create a XML element for the current data pipe.
@param doc: The XML document object.
@type doc: xml.dom.minidom.Document instance
@param element: The XML element to add the pipe XML element to.
@type element: XML element object
"""
# Add all simple python objects within the PipeContainer to the global element.
global_element = doc.createElement('global')
element.appendChild(global_element)
global_element.setAttribute('desc', 'Global data located in the top level of the data pipe')
fill_object_contents(doc, global_element, object=self, blacklist=['align_tensors', 'diff_tensor', 'exp_info', 'interatomic', 'hybrid_pipes', 'mol', 'pipe_type', 'structure'] + list(self.__class__.__dict__.keys()))
# Hybrid info.
self.xml_create_hybrid_element(doc, element)
# Add the experimental information.
if hasattr(self, 'exp_info'):
self.exp_info.to_xml(doc, element)
# Add the diffusion tensor data.
if hasattr(self, 'diff_tensor'):
self.diff_tensor.to_xml(doc, element)
# Add the alignment tensor data.
if hasattr(self, 'align_tensors'):
self.align_tensors.to_xml(doc, element)
# Add the molecule-residue-spin data.
self.mol.to_xml(doc, element)
# Add the interatomic data.
self.interatomic.to_xml(doc, element)
# Add the structural data, if it exists.
if hasattr(self, 'structure'):
self.structure.to_xml(doc, element)
def xml_create_hybrid_element(self, doc, element):
"""Create an XML element for the data pipe hybridisation information.
@param doc: The XML document object.
@type doc: xml.dom.minidom.Document instance
@param element: The element to add the hybridisation info to.
@type element: XML element object
"""
# Create the hybrid element and add it to the higher level element.
hybrid_element = doc.createElement('hybrid')
element.appendChild(hybrid_element)
# Set the hybridisation attributes.
hybrid_element.setAttribute('desc', 'Data pipe hybridisation information')
# Create an element to store the pipes list.
list_element = doc.createElement('pipes')
hybrid_element.appendChild(list_element)
# Add the pipes list.
text_val = doc.createTextNode(str(self.hybrid_pipes))
list_element.appendChild(text_val)
class PipeContainer(Prototype):
"""Class containing all the program data."""
def __init__(self):
"""Set up all the PipeContainer data structures."""
# The molecule-residue-spin object.
self.mol = MoleculeList()
# The interatomic data object.
self.interatomic = InteratomList()
# The data pipe type.
self.pipe_type = None
# Hybrid models.
self.hybrid_pipes = []
def __repr__(self):
"""The string representation of the object.
Rather than using the standard Python conventions (either the string representation of the
value or the "<...desc...>" notation), a rich-formatted description of the object is given.
"""
# Intro text.
text = "The data pipe storage object.\n"
# Special objects/methods (to avoid the getattr() function call on).
spec_obj = [
'exp_info', 'mol', 'interatomic', 'diff_tensor', 'structure'
]
# Objects.
text = text + "\n"
text = text + "Objects:\n"
for name in dir(self):
# Molecular list.
if name == 'mol':
text = text + " mol: The molecule list (for the storage of the spin system specific data)\n"
# Interatomic data list.
if name == 'interatomic':
text = text + " interatomic: The interatomic data list (for the storage of the inter-spin system data)\n"
# Diffusion tensor.
if name == 'diff_tensor':
text = text + " diff_tensor: The Brownian rotational diffusion tensor data object\n"
# Molecular structure.
if name == 'structure':
text = text + " structure: The 3D molecular data object\n"
# The experimental info data container.
if name == 'exp_info':
text = text + " exp_info: The data container for experimental information\n"
# Skip the PipeContainer methods.
if name in self.__class__.__dict__:
continue
# Skip certain objects.
if match("^_", name) or name in spec_obj:
continue
# Add the object's attribute to the text string.
text = text + " " + name + ": " + repr(getattr(self, name)) + "\n"
# Return the text representation.
return text
def _back_compat_hook(self, file_version=None):
"""Method for converting old data structures to the new ones.
@keyword file_version: The relax XML version of the XML file.
@type file_version: int
"""
# Relaxation data.
self._back_compat_hook_ri_data()
def _back_compat_hook_ri_data(self):
"""Converting the old relaxation data structures to the new ones."""
# Nothing to do.
if not (hasattr(cdp, 'frq_labels') and hasattr(cdp, 'noe_r1_table')
and hasattr(cdp, 'remap_table')):
return
# Initialise the new structures.
cdp.ri_ids = []
cdp.ri_type = {}
frq = {
} # This will be placed into cdp later as cdp.spectrometer_frq still exists.
# Generate the new structures.
for i in range(cdp.num_ri):
# The ID.
ri_id = "%s_%s" % (cdp.ri_labels[i],
cdp.frq_labels[cdp.remap_table[i]])
# Not unique.
if ri_id in cdp.ri_ids:
# Loop until a unique ID is found.
for j in range(100):
# New id.
new_id = "%s_%s" % (ri_id, j)
# Unique.
if not new_id in cdp.ri_ids:
ri_id = new_id
break
# Add the ID.
cdp.ri_ids.append(ri_id)
# The relaxation data type.
cdp.ri_type[ri_id] = cdp.ri_labels[i]
# The frequency data.
frq[ri_id] = cdp.frq[cdp.remap_table[i]]
# Delete the old structures.
del cdp.frq
del cdp.frq_labels
del cdp.noe_r1_table
del cdp.num_frq
del cdp.num_ri
del cdp.remap_table
del cdp.ri_labels
# Set the frequencies.
cdp.frq = frq
def from_xml(self, pipe_node, file_version=None, dir=None):
"""Read a pipe container XML element and place the contents into this pipe.
@param pipe_node: The data pipe XML node.
@type pipe_node: xml.dom.minidom.Element instance
@keyword file_version: The relax XML version of the XML file.
@type file_version: int
@keyword dir: The name of the directory containing the results file (needed for loading external files).
@type dir: str
"""
# Test if empty.
if not self.is_empty():
raise RelaxFromXMLNotEmptyError(self.__class__.__name__)
# Get the global data node, and fill the contents of the pipe.
global_node = pipe_node.getElementsByTagName('global')[0]
xml_to_object(global_node, self, file_version=file_version)
# Backwards compatibility transformations.
self._back_compat_hook(file_version)
# Get the hybrid node (and its sub-node), and recreate the hybrid object.
hybrid_node = pipe_node.getElementsByTagName('hybrid')[0]
pipes_node = hybrid_node.getElementsByTagName('pipes')[0]
setattr(self, 'hybrid_pipes',
node_value_to_python(pipes_node.childNodes[0]))
# Get the experimental information data nodes and, if they exist, fill the contents.
exp_info_nodes = pipe_node.getElementsByTagName('exp_info')
if exp_info_nodes:
# Create the data container.
self.exp_info = ExpInfo()
# Fill its contents.
self.exp_info.from_xml(exp_info_nodes[0],
file_version=file_version)
# Get the diffusion tensor data nodes and, if they exist, fill the contents.
diff_tensor_nodes = pipe_node.getElementsByTagName('diff_tensor')
if diff_tensor_nodes:
# Create the diffusion tensor object.
self.diff_tensor = DiffTensorData()
# Fill its contents.
self.diff_tensor.from_xml(diff_tensor_nodes[0],
file_version=file_version)
# Get the alignment tensor data nodes and, if they exist, fill the contents.
align_tensor_nodes = pipe_node.getElementsByTagName('align_tensors')
if align_tensor_nodes:
# Create the alignment tensor object.
self.align_tensors = AlignTensorList()
# Fill its contents.
self.align_tensors.from_xml(align_tensor_nodes[0],
file_version=file_version)
# Recreate the interatomic data structure (this needs to be before the 'mol' structure as the backward compatibility hooks can create interatomic data containers!).
interatom_nodes = pipe_node.getElementsByTagName('interatomic')
self.interatomic.from_xml(interatom_nodes, file_version=file_version)
# Recreate the molecule, residue, and spin data structure.
mol_nodes = pipe_node.getElementsByTagName('mol')
self.mol.from_xml(mol_nodes, file_version=file_version)
# Get the structural object nodes and, if they exist, fill the contents.
str_nodes = pipe_node.getElementsByTagName('structure')
if str_nodes:
# Create the structural object.
fail = False
self.structure = Internal()
# Fill its contents.
if not fail:
self.structure.from_xml(str_nodes[0],
dir=dir,
file_version=file_version)
def is_empty(self):
"""Method for testing if the data pipe is empty.
@return: True if the data pipe is empty, False otherwise.
@rtype: bool
"""
# Is the molecule structure data object empty?
if hasattr(self, 'structure'):
return False
# Is the molecule/residue/spin data object empty?
if not self.mol.is_empty():
return False
# Is the interatomic data object empty?
if not self.interatomic.is_empty():
return False
# Tests for the initialised data (the pipe type can be set in an empty data pipe, so this isn't checked).
if self.hybrid_pipes:
return False
# An object has been added to the container.
for name in dir(self):
# Skip the objects initialised in __init__().
if name in ['mol', 'interatomic', 'pipe_type', 'hybrid_pipes']:
continue
# Skip the PipeContainer methods.
if name in self.__class__.__dict__:
continue
# Skip special objects.
if match("^_", name):
continue
# An object has been added.
return False
# The data pipe is empty.
return True
def to_xml(self, doc, element, pipe_type=None):
"""Create a XML element for the current data pipe.
@param doc: The XML document object.
@type doc: xml.dom.minidom.Document instance
@param element: The XML element to add the pipe XML element to.
@type element: XML element object
@keyword pipe_type: The type of the pipe being converted to XML.
@type pipe_type: str
"""
# Add all simple python objects within the PipeContainer to the global element.
global_element = doc.createElement('global')
element.appendChild(global_element)
global_element.setAttribute(
'desc', 'Global data located in the top level of the data pipe')
fill_object_contents(
doc,
global_element,
object=self,
blacklist=[
'align_tensors', 'diff_tensor', 'exp_info', 'interatomic',
'hybrid_pipes', 'mol', 'pipe_type', 'structure'
] + list(self.__class__.__dict__.keys()))
# Hybrid info.
self.xml_create_hybrid_element(doc, element)
# Add the experimental information.
if hasattr(self, 'exp_info'):
self.exp_info.to_xml(doc, element)
# Add the diffusion tensor data.
if hasattr(self, 'diff_tensor'):
self.diff_tensor.to_xml(doc, element)
# Add the alignment tensor data.
if hasattr(self, 'align_tensors'):
self.align_tensors.to_xml(doc, element)
# Add the molecule-residue-spin data.
self.mol.to_xml(doc, element, pipe_type=pipe_type)
# Add the interatomic data.
self.interatomic.to_xml(doc, element, pipe_type=pipe_type)
# Add the structural data, if it exists.
if hasattr(self, 'structure'):
self.structure.to_xml(doc, element)
def xml_create_hybrid_element(self, doc, element):
"""Create an XML element for the data pipe hybridisation information.
@param doc: The XML document object.
@type doc: xml.dom.minidom.Document instance
@param element: The element to add the hybridisation info to.
@type element: XML element object
"""
# Create the hybrid element and add it to the higher level element.
hybrid_element = doc.createElement('hybrid')
element.appendChild(hybrid_element)
# Set the hybridisation attributes.
hybrid_element.setAttribute('desc',
'Data pipe hybridisation information')
# Create an element to store the pipes list.
list_element = doc.createElement('pipes')
hybrid_element.appendChild(list_element)
# Add the pipes list.
text_val = doc.createTextNode(str(self.hybrid_pipes))
list_element.appendChild(text_val)
def from_xml(self, pipe_node, file_version=None, dir=None):
"""Read a pipe container XML element and place the contents into this pipe.
@param pipe_node: The data pipe XML node.
@type pipe_node: xml.dom.minidom.Element instance
@keyword file_version: The relax XML version of the XML file.
@type file_version: int
@keyword dir: The name of the directory containing the results file (needed for loading external files).
@type dir: str
"""
# Test if empty.
if not self.is_empty():
raise RelaxFromXMLNotEmptyError(self.__class__.__name__)
# Get the global data node, and fill the contents of the pipe.
global_node = pipe_node.getElementsByTagName('global')[0]
xml_to_object(global_node, self, file_version=file_version)
# Backwards compatibility transformations.
self._back_compat_hook(file_version)
# Get the hybrid node (and its sub-node), and recreate the hybrid object.
hybrid_node = pipe_node.getElementsByTagName('hybrid')[0]
pipes_node = hybrid_node.getElementsByTagName('pipes')[0]
setattr(self, 'hybrid_pipes', node_value_to_python(pipes_node.childNodes[0]))
# Get the experimental information data nodes and, if they exist, fill the contents.
exp_info_nodes = pipe_node.getElementsByTagName('exp_info')
if exp_info_nodes:
# Create the data container.
self.exp_info = ExpInfo()
# Fill its contents.
self.exp_info.from_xml(exp_info_nodes[0], file_version=file_version)
# Get the diffusion tensor data nodes and, if they exist, fill the contents.
diff_tensor_nodes = pipe_node.getElementsByTagName('diff_tensor')
if diff_tensor_nodes:
# Create the diffusion tensor object.
self.diff_tensor = DiffTensorData()
# Fill its contents.
self.diff_tensor.from_xml(diff_tensor_nodes[0], file_version=file_version)
# Get the alignment tensor data nodes and, if they exist, fill the contents.
align_tensor_nodes = pipe_node.getElementsByTagName('align_tensors')
if align_tensor_nodes:
# Create the alignment tensor object.
self.align_tensors = AlignTensorList()
# Fill its contents.
self.align_tensors.from_xml(align_tensor_nodes[0], file_version=file_version)
# Recreate the interatomic data structure (this needs to be before the 'mol' structure as the backward compatibility hooks can create interatomic data containers!).
interatom_nodes = pipe_node.getElementsByTagName('interatomic')
self.interatomic.from_xml(interatom_nodes, file_version=file_version)
# Recreate the molecule, residue, and spin data structure.
mol_nodes = pipe_node.getElementsByTagName('mol')
self.mol.from_xml(mol_nodes, file_version=file_version)
# Get the structural object nodes and, if they exist, fill the contents.
str_nodes = pipe_node.getElementsByTagName('structure')
if str_nodes:
# Create the structural object.
fail = False
self.structure = Internal()
# Fill its contents.
if not fail:
self.structure.from_xml(str_nodes[0], dir=dir, file_version=file_version)
def from_xml(self, pipe_node, file_version=None, dir=None):
"""Read a pipe container XML element and place the contents into this pipe.
@param pipe_node: The data pipe XML node.
@type pipe_node: xml.dom.minidom.Element instance
@keyword file_version: The relax XML version of the XML file.
@type file_version: int
@keyword dir: The name of the directory containing the results file (needed for loading external files).
@type dir: str
"""
# Test if empty.
if not self.is_empty():
raise RelaxFromXMLNotEmptyError(self.__class__.__name__)
# Get the global data node, and fill the contents of the pipe.
global_node = pipe_node.getElementsByTagName('global')[0]
xml_to_object(global_node, self, file_version=file_version)
# Backwards compatibility transformations.
self._back_compat_hook(file_version)
# Get the hybrid node (and its sub-node), and recreate the hybrid object.
hybrid_node = pipe_node.getElementsByTagName('hybrid')[0]
pipes_node = hybrid_node.getElementsByTagName('pipes')[0]
setattr(self, 'hybrid_pipes',
node_value_to_python(pipes_node.childNodes[0]))
# Get the experimental information data nodes and, if they exist, fill the contents.
exp_info_nodes = pipe_node.getElementsByTagName('exp_info')
if exp_info_nodes:
# Create the data container.
self.exp_info = ExpInfo()
# Fill its contents.
self.exp_info.from_xml(exp_info_nodes[0],
file_version=file_version)
# Get the diffusion tensor data nodes and, if they exist, fill the contents.
diff_tensor_nodes = pipe_node.getElementsByTagName('diff_tensor')
if diff_tensor_nodes:
# Create the diffusion tensor object.
self.diff_tensor = DiffTensorData()
# Fill its contents.
self.diff_tensor.from_xml(diff_tensor_nodes[0],
file_version=file_version)
# Get the alignment tensor data nodes and, if they exist, fill the contents.
align_tensor_nodes = pipe_node.getElementsByTagName('align_tensors')
if align_tensor_nodes:
# Create the alignment tensor object.
self.align_tensors = AlignTensorList()
# Fill its contents.
self.align_tensors.from_xml(align_tensor_nodes[0],
file_version=file_version)
# Recreate the interatomic data structure (this needs to be before the 'mol' structure as the backward compatibility hooks can create interatomic data containers!).
interatom_nodes = pipe_node.getElementsByTagName('interatomic')
self.interatomic.from_xml(interatom_nodes, file_version=file_version)
# Recreate the molecule, residue, and spin data structure.
mol_nodes = pipe_node.getElementsByTagName('mol')
self.mol.from_xml(mol_nodes, file_version=file_version)
# Get the structural object nodes and, if they exist, fill the contents.
str_nodes = pipe_node.getElementsByTagName('structure')
if str_nodes:
# Create the structural object.
fail = False
self.structure = Internal()
# Fill its contents.
if not fail:
self.structure.from_xml(str_nodes[0],
dir=dir,
file_version=file_version)
def setUp(self):
"""Set 'self.diff_data' to an empty instance of the DiffTensorData class."""
self.diff_data = DiffTensorData()
class Test_diff_tensor(TestCase):
"""Unit tests for the data.diff_tensor relax module."""
def calc_spheroid_objects(self, tm, Da, theta, phi):
"""Function for calculating the spheroidal diffusion tensor objects."""
# The parameter values.
Diso = 1/(6*tm)
Dpar = Diso + 2.0/3.0 * Da
Dper = Diso - 1.0/3.0 * Da
Dratio = Dpar / Dper
# Vectors.
Dpar_unit = array([sin(theta) * cos(phi), sin(theta) * sin(phi), cos(theta)])
# Matrices.
if Dpar > Dper:
axis = array([0, 0, 1], float64)
tensor_diag = array([[ Dper, 0.0, 0.0],
[ 0.0, Dper, 0.0],
[ 0.0, 0.0, Dpar]])
else:
axis = array([1, 0, 0], float64)
tensor_diag = array([[ Dpar, 0.0, 0.0],
[ 0.0, Dper, 0.0],
[ 0.0, 0.0, Dper]])
# The rotation.
rotation = zeros((3, 3), float64)
two_vect_to_R(Dpar_unit, axis, rotation)
# The diffusion tensor.
tensor = dot(rotation, dot(tensor_diag, transpose(rotation)))
# Return the objects.
return Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor
def setUp(self):
"""Set 'self.diff_data' to an empty instance of the DiffTensorData class."""
self.diff_data = DiffTensorData()
def test_append_spheroid_sim(self):
"""Test the appending of Monte Carlo simulation spheroidal diffusion tensor parameters.
The following parameters will be appended to empty lists:
- tm: 8 ns
- Da: -1e7
- theta: 150 degrees
- phi: 30 degrees
"""
# The MC sim parameter values.
tm = 8e-9
Da = -1e7
theta = (150 / 360.0) * 2.0 * pi
phi = (30 / 360.0) * 2.0 * pi
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='oblate')
# Set the number of MC sims.
self.diff_data.set_sim_num(1)
# Set the initial values.
self.diff_data.set(param='tm', value=tm, category='sim', sim_index=0)
self.diff_data.set(param='Da', value=Da, category='sim', sim_index=0)
self.diff_data.set(param='theta', value=theta, category='sim', sim_index=0)
self.diff_data.set(param='phi', value=phi, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm_sim[0], tm)
self.assertEqual(self.diff_data.Da_sim[0], Da)
self.assertEqual(self.diff_data.theta_sim[0], theta)
self.assertEqual(self.diff_data.phi_sim[0], phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso_sim[0], Diso)
self.assertEqual(self.diff_data.Dpar_sim[0], Dpar)
self.assertEqual(self.diff_data.Dper_sim[0], Dper)
self.assertEqual(self.diff_data.Dratio_sim[0], Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit_sim[0].tostring(), Dpar_unit.tostring())
# Test the matrices.
self.assertEqual(self.diff_data.tensor_diag_sim[0].tostring(), tensor_diag.tostring())
self.assertEqual(self.diff_data.rotation_sim[0].tostring(), rotation.tostring())
self.assertEqual(self.diff_data.tensor_sim[0].tostring(), tensor.tostring())
def test_display(self):
"""Test that the contents of the diffusion tensor object can be displayed."""
print(self.diff_data)
def test_set_Diso(self):
"""Test that the Diso parameter cannot be set."""
# Assert that a RelaxError occurs when Diso is set (to the tm value of 10 ns).
self.assertRaises(RelaxError, setattr, self.diff_data, 'Diso', 1/(6*1e-8))
# Make sure that the Diso parameter has not been set.
self.assert_(not hasattr(self.diff_data, 'Diso'))
def test_set_spheroid_errors(self):
"""Test the setting of spheroidal diffusion tensor parameter errors.
The following parameter errors will be set:
- tm: 1 ns
- Da: 1e3
- theta: 3 degrees
- phi: 5 degrees
"""
# The parameter errors.
tm = 1e-8
Da = 1e3
theta = (3 / 360.0) * 2.0 * pi
phi = (5 / 360.0) * 2.0 * pi
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='prolate')
# Set the diffusion parameter errors.
self.diff_data.set(param='tm', value=tm, category='err')
self.diff_data.set(param='Da', value=Da, category='err')
self.diff_data.set(param='theta', value=theta, category='err')
self.diff_data.set(param='phi', value=phi, category='err')
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm_err, tm)
self.assertEqual(self.diff_data.Da_err, Da)
self.assertEqual(self.diff_data.theta_err, theta)
self.assertEqual(self.diff_data.phi_err, phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso_err, Diso)
self.assertEqual(self.diff_data.Dpar_err, Dpar)
self.assertEqual(self.diff_data.Dper_err, Dper)
self.assertEqual(self.diff_data.Dratio_err, Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit_err.tostring(), Dpar_unit.tostring())
def test_set_spheroid_params(self):
"""Test the setting of spheroidal diffusion tensor parameters.
The following parameters will be set:
- tm: 20 ns
- Da: 2e6
- theta: 60 degrees
- phi: 290 degrees
"""
# The parameter values.
tm = 2e-8
Da = 2e6
theta = (60 / 360.0) * 2.0 * pi
phi = (290 / 360.0) * 2.0 * pi
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='prolate')
# Set the diffusion parameters.
self.diff_data.set(param='tm', value=tm)
self.diff_data.set(param='Da', value=Da)
self.diff_data.set(param='theta', value=theta)
self.diff_data.set(param='phi', value=phi)
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm, tm)
self.assertEqual(self.diff_data.Da, Da)
self.assertEqual(self.diff_data.theta, theta)
self.assertEqual(self.diff_data.phi, phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso, Diso)
self.assertEqual(self.diff_data.Dpar, Dpar)
self.assertEqual(self.diff_data.Dper, Dper)
self.assertEqual(self.diff_data.Dratio, Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit.tostring(), Dpar_unit.tostring())
# Test the matrices.
self.assertEqual(self.diff_data.tensor_diag.tostring(), tensor_diag.tostring())
self.assertEqual(self.diff_data.rotation.tostring(), rotation.tostring())
self.assertEqual(self.diff_data.tensor.tostring(), tensor.tostring())
def test_set_spheroid_sim(self):
"""Test the setting of Monte Carlo simulation spheroidal diffusion tensor parameters.
Firstly the following parameters will be appended to empty lists:
- tm: 2 ns
- Da: 1e5
- theta: 0 degrees
- phi: 360 degrees
These MC sim values will then be explicity overwritten by setting the first elements of the
lists to:
- tm: 0.5 ns
- Da: 3e5
- theta: 2 degrees
- phi: 0 degrees
"""
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='prolate')
# Set the number of MC sims.
self.diff_data.set_sim_num(1)
# Set the initial values.
self.diff_data.set(param='tm', value=2e-9, category='sim', sim_index=0)
self.diff_data.set(param='Da', value=1e5, category='sim', sim_index=0)
self.diff_data.set(param='theta', value=0.0, category='sim', sim_index=0)
self.diff_data.set(param='phi', value=2.0 * pi, category='sim', sim_index=0)
# The new MC sim parameter values.
tm = 0.5e-9
Da = 3e5
theta = (2 / 360.0) * 2.0 * pi
phi = 0.0
# Set the MC sim parameter values (overwriting the initial values).
self.diff_data.set(param='tm', value=tm, category='sim', sim_index=0)
self.diff_data.set(param='Da', value=Da, category='sim', sim_index=0)
self.diff_data.set(param='theta', value=theta, category='sim', sim_index=0)
self.diff_data.set(param='phi', value=phi, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm_sim[0], tm)
self.assertEqual(self.diff_data.Da_sim[0], Da)
self.assertEqual(self.diff_data.theta_sim[0], theta)
self.assertEqual(self.diff_data.phi_sim[0], phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso_sim[0], Diso)
self.assertEqual(self.diff_data.Dpar_sim[0], Dpar)
self.assertEqual(self.diff_data.Dper_sim[0], Dper)
self.assertEqual(self.diff_data.Dratio_sim[0], Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit_sim[0].tostring(), Dpar_unit.tostring())
# Test the matrices.
self.assertEqual(self.diff_data.tensor_diag_sim[0].tostring(), tensor_diag.tostring())
self.assertEqual(self.diff_data.rotation_sim[0].tostring(), rotation.tostring())
self.assertEqual(self.diff_data.tensor_sim[0].tostring(), tensor.tostring())
def test_set_tm(self):
"""Test the setting of the tm parameter.
The tm parameter will be set to 10 ns. The setting of tm should automatically create the
Diso parameter.
"""
# Set the diffusion type.
self.diff_data.set(param='type', value='sphere')
# Set the tm value to 10 ns.
self.diff_data.set(param='tm', value=1e-8)
# Test that the tm parameter has been set correctly.
self.assert_(hasattr(self.diff_data, 'tm'))
self.assertEqual(self.diff_data.tm, 1e-8)
# Test that the Diso parameter has been set correctly.
self.assert_(hasattr(self.diff_data, 'Diso'))
self.assertEqual(self.diff_data.Diso, 1/(6*1e-8))
def setUp(self):
"""Set 'self.diff_data' to an empty instance of the DiffTensorData class."""
self.diff_data = DiffTensorData()
class Test_diff_tensor(TestCase):
"""Unit tests for the data.diff_tensor relax module."""
def calc_spheroid_objects(self, tm, Da, theta, phi):
"""Function for calculating the spheroidal diffusion tensor objects."""
# The parameter values.
Diso = 1 / (6 * tm)
Dpar = Diso + 2.0 / 3.0 * Da
Dper = Diso - 1.0 / 3.0 * Da
Dratio = Dpar / Dper
# Vectors.
Dpar_unit = array(
[sin(theta) * cos(phi),
sin(theta) * sin(phi),
cos(theta)])
# Matrices.
if Dpar > Dper:
axis = array([0, 0, 1], float64)
tensor_diag = array([[Dper, 0.0, 0.0], [0.0, Dper, 0.0],
[0.0, 0.0, Dpar]])
else:
axis = array([1, 0, 0], float64)
tensor_diag = array([[Dpar, 0.0, 0.0], [0.0, Dper, 0.0],
[0.0, 0.0, Dper]])
# The rotation.
rotation = zeros((3, 3), float64)
two_vect_to_R(Dpar_unit, axis, rotation)
# The diffusion tensor.
tensor = dot(rotation, dot(tensor_diag, transpose(rotation)))
# Return the objects.
return Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor
def setUp(self):
"""Set 'self.diff_data' to an empty instance of the DiffTensorData class."""
self.diff_data = DiffTensorData()
def test_append_spheroid_sim(self):
"""Test the appending of Monte Carlo simulation spheroidal diffusion tensor parameters.
The following parameters will be appended to empty lists:
- tm: 8 ns
- Da: -1e7
- theta: 150 degrees
- phi: 30 degrees
"""
# The MC sim parameter values.
tm = 8e-9
Da = -1e7
theta = (150 / 360.0) * 2.0 * pi
phi = (30 / 360.0) * 2.0 * pi
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='oblate')
# Set the number of MC sims.
self.diff_data.set_sim_num(1)
# Set the initial values.
self.diff_data.set(param='tm', value=tm, category='sim', sim_index=0)
self.diff_data.set(param='Da', value=Da, category='sim', sim_index=0)
self.diff_data.set(param='theta',
value=theta,
category='sim',
sim_index=0)
self.diff_data.set(param='phi', value=phi, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm_sim[0], tm)
self.assertEqual(self.diff_data.Da_sim[0], Da)
self.assertEqual(self.diff_data.theta_sim[0], theta)
self.assertEqual(self.diff_data.phi_sim[0], phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(
tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso_sim[0], Diso)
self.assertEqual(self.diff_data.Dpar_sim[0], Dpar)
self.assertEqual(self.diff_data.Dper_sim[0], Dper)
self.assertEqual(self.diff_data.Dratio_sim[0], Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit_sim[0].tostring(),
Dpar_unit.tostring())
# Test the matrices.
self.assertEqual(self.diff_data.tensor_diag_sim[0].tostring(),
tensor_diag.tostring())
self.assertEqual(self.diff_data.rotation_sim[0].tostring(),
rotation.tostring())
self.assertEqual(self.diff_data.tensor_sim[0].tostring(),
tensor.tostring())
def test_display(self):
"""Test that the contents of the diffusion tensor object can be displayed."""
print(self.diff_data)
def test_set_Diso(self):
"""Test that the Diso parameter cannot be set."""
# Assert that a RelaxError occurs when Diso is set (to the tm value of 10 ns).
self.assertRaises(RelaxError, setattr, self.diff_data, 'Diso',
1 / (6 * 1e-8))
# Make sure that the Diso parameter has not been set.
self.assert_(not hasattr(self.diff_data, 'Diso'))
def test_set_spheroid_errors(self):
"""Test the setting of spheroidal diffusion tensor parameter errors.
The following parameter errors will be set:
- tm: 1 ns
- Da: 1e3
- theta: 3 degrees
- phi: 5 degrees
"""
# The parameter errors.
tm = 1e-8
Da = 1e3
theta = (3 / 360.0) * 2.0 * pi
phi = (5 / 360.0) * 2.0 * pi
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='prolate')
# Set the diffusion parameter errors.
self.diff_data.set(param='tm', value=tm, category='err')
self.diff_data.set(param='Da', value=Da, category='err')
self.diff_data.set(param='theta', value=theta, category='err')
self.diff_data.set(param='phi', value=phi, category='err')
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm_err, tm)
self.assertEqual(self.diff_data.Da_err, Da)
self.assertEqual(self.diff_data.theta_err, theta)
self.assertEqual(self.diff_data.phi_err, phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(
tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso_err, Diso)
self.assertEqual(self.diff_data.Dpar_err, Dpar)
self.assertEqual(self.diff_data.Dper_err, Dper)
self.assertEqual(self.diff_data.Dratio_err, Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit_err.tostring(),
Dpar_unit.tostring())
def test_set_spheroid_params(self):
"""Test the setting of spheroidal diffusion tensor parameters.
The following parameters will be set:
- tm: 20 ns
- Da: 2e6
- theta: 60 degrees
- phi: 290 degrees
"""
# The parameter values.
tm = 2e-8
Da = 2e6
theta = (60 / 360.0) * 2.0 * pi
phi = (290 / 360.0) * 2.0 * pi
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='prolate')
# Set the diffusion parameters.
self.diff_data.set(param='tm', value=tm)
self.diff_data.set(param='Da', value=Da)
self.diff_data.set(param='theta', value=theta)
self.diff_data.set(param='phi', value=phi)
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm, tm)
self.assertEqual(self.diff_data.Da, Da)
self.assertEqual(self.diff_data.theta, theta)
self.assertEqual(self.diff_data.phi, phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(
tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso, Diso)
self.assertEqual(self.diff_data.Dpar, Dpar)
self.assertEqual(self.diff_data.Dper, Dper)
self.assertEqual(self.diff_data.Dratio, Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit.tostring(),
Dpar_unit.tostring())
# Test the matrices.
self.assertEqual(self.diff_data.tensor_diag.tostring(),
tensor_diag.tostring())
self.assertEqual(self.diff_data.rotation.tostring(),
rotation.tostring())
self.assertEqual(self.diff_data.tensor.tostring(), tensor.tostring())
def test_set_spheroid_sim(self):
"""Test the setting of Monte Carlo simulation spheroidal diffusion tensor parameters.
Firstly the following parameters will be appended to empty lists:
- tm: 2 ns
- Da: 1e5
- theta: 0 degrees
- phi: 360 degrees
These MC sim values will then be explicity overwritten by setting the first elements of the
lists to:
- tm: 0.5 ns
- Da: 3e5
- theta: 2 degrees
- phi: 0 degrees
"""
# Set the diffusion type.
self.diff_data.set(param='type', value='spheroid')
self.diff_data.set(param='spheroid_type', value='prolate')
# Set the number of MC sims.
self.diff_data.set_sim_num(1)
# Set the initial values.
self.diff_data.set(param='tm', value=2e-9, category='sim', sim_index=0)
self.diff_data.set(param='Da', value=1e5, category='sim', sim_index=0)
self.diff_data.set(param='theta',
value=0.0,
category='sim',
sim_index=0)
self.diff_data.set(param='phi',
value=2.0 * pi,
category='sim',
sim_index=0)
# The new MC sim parameter values.
tm = 0.5e-9
Da = 3e5
theta = (2 / 360.0) * 2.0 * pi
phi = 0.0
# Set the MC sim parameter values (overwriting the initial values).
self.diff_data.set(param='tm', value=tm, category='sim', sim_index=0)
self.diff_data.set(param='Da', value=Da, category='sim', sim_index=0)
self.diff_data.set(param='theta',
value=theta,
category='sim',
sim_index=0)
self.diff_data.set(param='phi', value=phi, category='sim', sim_index=0)
# Test the set values.
self.assertEqual(self.diff_data.type, 'spheroid')
self.assertEqual(self.diff_data.tm_sim[0], tm)
self.assertEqual(self.diff_data.Da_sim[0], Da)
self.assertEqual(self.diff_data.theta_sim[0], theta)
self.assertEqual(self.diff_data.phi_sim[0], phi)
# Calculate the diffusion tensor objects.
Diso, Dpar, Dper, Dratio, Dpar_unit, tensor_diag, rotation, tensor = self.calc_spheroid_objects(
tm, Da, theta, phi)
# Test the automatically created values.
self.assertEqual(self.diff_data.Diso_sim[0], Diso)
self.assertEqual(self.diff_data.Dpar_sim[0], Dpar)
self.assertEqual(self.diff_data.Dper_sim[0], Dper)
self.assertEqual(self.diff_data.Dratio_sim[0], Dratio)
# Test the vectors.
self.assertEqual(self.diff_data.Dpar_unit_sim[0].tostring(),
Dpar_unit.tostring())
# Test the matrices.
self.assertEqual(self.diff_data.tensor_diag_sim[0].tostring(),
tensor_diag.tostring())
self.assertEqual(self.diff_data.rotation_sim[0].tostring(),
rotation.tostring())
self.assertEqual(self.diff_data.tensor_sim[0].tostring(),
tensor.tostring())
def test_set_tm(self):
"""Test the setting of the tm parameter.
The tm parameter will be set to 10 ns. The setting of tm should automatically create the
Diso parameter.
"""
# Set the diffusion type.
self.diff_data.set(param='type', value='sphere')
# Set the tm value to 10 ns.
self.diff_data.set(param='tm', value=1e-8)
# Test that the tm parameter has been set correctly.
self.assert_(hasattr(self.diff_data, 'tm'))
self.assertEqual(self.diff_data.tm, 1e-8)
# Test that the Diso parameter has been set correctly.
self.assert_(hasattr(self.diff_data, 'Diso'))
self.assertEqual(self.diff_data.Diso, 1 / (6 * 1e-8))