def build(cls, data_handler, matrix_creation_parameters):
"""
Generates a matrix with the method used in the handler creation.
@param trajectory_handler:
@param matrix_creation_parameters:
@return: The created matrix.
"""
calculator_type = matrix_creation_parameters.get_value("calculator_type",
default_value = "QTRFIT_OMP_CALCULATOR")
calculator_options = matrix_creation_parameters.get_value("calculator_options",
default_value = ProtocolParameters({"number_of_threads":8,
"blocks_per_grid":8,
"threads_per_block":32}))
calculator_options = ProtocolParameters(calculator_options)
structure = data_handler.get_data()
fit_selection_coordsets = structure.getFittingCoordinates()
calc_selection_coordsets = structure.getCalculationCoordinates()
if calc_selection_coordsets is None:
calculator = RMSDCalculator(calculatorType = calculator_type,
fittingCoordsets = fit_selection_coordsets)
else:
symm_groups = []
if "symmetries" in matrix_creation_parameters:
# Then prepare it to handle calculation symmetries
# Description of equivalences must have the same number of atoms
symm_groups = cls.process_symm_groups(matrix_creation_parameters,
structure,
calc_selection_coordsets)
print "Using symmetries", symm_groups
calculator = RMSDCalculator(calculatorType = calculator_type,
fittingCoordsets = fit_selection_coordsets,
calculationCoordsets = calc_selection_coordsets,
calcSymmetryGroups = symm_groups)
try:
calculator.setNumberOfOpenMPThreads(calculator_options.get_value("number_of_threads",
default_value = 8))
except KeyError:
pass
try:
calculator.setCUDAKernelThreadsPerBlock(calculator_options.get_value("threads_per_block",
default_value = 32),
calculator_options.get_value("blocks_per_grid",
default_value = 8))
except KeyError:
pass
rmsds = calculator.pairwiseRMSDMatrix()
return CondensedMatrix(rmsds)
def pairwise_rmsd(coords):
"""
Returns vector with all pairwise backbone RMSDs from given coordinates
coords = numpy array of coordinates generated using ProDy
"""
calculator = RMSDCalculator("QCP_SERIAL_CALCULATOR", fittingCoordsets = coords)
t1 = time.time()
rmsds = calculator.pairwiseRMSDMatrix()
t2 = time.time()
print "With QCP Serial calculator it took: ", t2-t1 ,"s."
sys.stdout.flush()
#rmsd_matrix = CondensedMatrix(rmsds)
return rmsds
def build(cls, trajectory_handler, matrix_creation_parameters):
"""
Generates a matrix with the method used in the handler creation.
@param trajectory_handler:
@param matrix_creation_parameters:
@return: The created matrix.
"""
fit_selection_string = matrix_creation_parameters["fit_selection"]
fit_selection_coordsets = trajectory_handler.getSelection(
fit_selection_string)
trajectory_handler.setWorkingCoordinates(fit_selection_string)
calculator_type = matrix_creation_parameters[
"calculator_type"] if "calculator_type" in matrix_creation_parameters else "QTRFIT_OMP_CALCULATOR"
calculator = RMSDCalculator(calculatorType=calculator_type,
fittingCoordsets=fit_selection_coordsets)
# Apply calculation selection if needed
calc_selection_string = matrix_creation_parameters[
"calc_selection"] if "calc_selection" in matrix_creation_parameters else ""
if calc_selection_string != "" and calc_selection_string != fit_selection_string:
calc_selection_coordsets = trajectory_handler.getSelection(
calc_selection_string)
trajectory_handler.setWorkingCoordinates(calc_selection_string)
symm_groups = []
if "symmetries" in matrix_creation_parameters:
# Then prepare it to handle calculation symmetries
# Description of equivalences must have the same number of atoms
symm_groups = cls.process_symm_groups(
matrix_creation_parameters, trajectory_handler,
calc_selection_coordsets)
print "Using symmetries", symm_groups
calculator = RMSDCalculator(
calculatorType=calculator_type,
fittingCoordsets=fit_selection_coordsets,
calculationCoordsets=calc_selection_coordsets,
calcSymmetryGroups=symm_groups)
rmsds = calculator.pairwiseRMSDMatrix()
return CondensedMatrix(rmsds)
def build(cls, trajectory_handler, matrix_creation_parameters):
"""
Generates a matrix with the method used in the handler creation.
@param trajectory_handler:
@param matrix_creation_parameters:
@return: The created matrix.
"""
fit_selection_string = matrix_creation_parameters["fit_selection"]
fit_selection_coordsets = trajectory_handler.getSelection(fit_selection_string)
trajectory_handler.setWorkingCoordinates(fit_selection_string)
calculator_type = matrix_creation_parameters["calculator_type"] if "calculator_type" in matrix_creation_parameters else "QTRFIT_OMP_CALCULATOR"
calculator = RMSDCalculator(calculatorType = calculator_type,
fittingCoordsets = fit_selection_coordsets)
# Apply calculation selection if needed
calc_selection_string = matrix_creation_parameters["calc_selection"] if "calc_selection" in matrix_creation_parameters else ""
if calc_selection_string != "" and calc_selection_string != fit_selection_string:
calc_selection_coordsets = trajectory_handler.getSelection(calc_selection_string)
trajectory_handler.setWorkingCoordinates(calc_selection_string)
symm_groups = []
if "symmetries" in matrix_creation_parameters:
# Then prepare it to handle calculation symmetries
# Description of equivalences must have the same number of atoms
symm_groups = cls.process_symm_groups(matrix_creation_parameters,
trajectory_handler,
calc_selection_coordsets)
print "Using symmetries",symm_groups
calculator = RMSDCalculator(calculatorType = calculator_type,
fittingCoordsets = fit_selection_coordsets,
calculationCoordsets = calc_selection_coordsets,
calcSymmetryGroups=symm_groups)
rmsds = calculator.pairwiseRMSDMatrix()
return CondensedMatrix(rmsds)
def parse_decoys(decoy_dir, number_of_decoys = None):
"""
Extracts backbone coordinates from first n pdbs in the given directory and
returns their coordinates as a numpy array. If not n is specified,
it considers every pdb file.
decoy_dir = directory with decoys
number_of_decoys = n (optional)
"""
decoy_list = []
for file in os.listdir(decoy_dir):
if file.endswith(".pdb"):
decoy_list.append(os.path.join(decoy_dir,file))
decoy_list = sorted(decoy_list)
#selecting first n decoys, if n is specified
if number_of_decoys != None:
decoys_considered = decoy_list[:number_of_decoys]
else:
decoys_considered = decoy_list # add pdb name to a list
#using ProDy to parse PDBs
pdb_ref = parsePDB(decoys_considered[0])
#extracting C-alpha coordinates as numpy array
coords_ref = np.array((pdb_ref.select("name CA C1").getCoordsets())) # reference pose pdb0
#####PRINT COORDS!
rmsd_out=open("all_vs_all_rmsd.txt",'w')
rmsd_out.write("ref:"+str(decoys_considered[0])+"\n")
rmsd_out.close()
for i in range(1,len(decoys_considered)):
pdb = parsePDB(decoys_considered[i])
coords_temp = np.array((pdb.select("name CA C1").getCoordsets())) # get the pose2 pdb1
coords = np.vstack((coords_ref, coords_temp))
number_of_conformations = coords.shape[0]
number_of_atoms = coords.shape[1]
calculator = RMSDCalculator("QCP_SERIAL_CALCULATOR", fittingCoordsets = coords)
rmsds = calculator.pairwiseRMSDMatrix()
sys.stdout.flush()
rmsd_out=open("all_vs_all_rmsd.txt",'a')
rmsd_out.write(str(i)+"\t"+str(rmsds)+"\n")
rmsd_out.close()
def build(cls, data_handler, matrix_creation_parameters):
"""
Generates a matrix with the method used in the handler creation.
@param trajectory_handler:
@param matrix_creation_parameters:
@return: The created matrix.
"""
calculator_type = matrix_creation_parameters.get_value(
"calculator_type", default_value="QTRFIT_OMP_CALCULATOR")
calculator_options = matrix_creation_parameters.get_value(
"calculator_options",
default_value=ProtocolParameters({
"number_of_threads": 8,
"blocks_per_grid": 8,
"threads_per_block": 32
}))
calculator_options = ProtocolParameters(calculator_options)
structure = data_handler.get_data()
fit_selection_coordsets = structure.getFittingCoordinates()
calc_selection_coordsets = structure.getCalculationCoordinates()
if calc_selection_coordsets is None:
calculator = RMSDCalculator(
calculatorType=calculator_type,
fittingCoordsets=fit_selection_coordsets)
else:
symm_groups = []
if "symmetries" in matrix_creation_parameters:
# Then prepare it to handle calculation symmetries
# Description of equivalences must have the same number of atoms
symm_groups = cls.process_symm_groups(
matrix_creation_parameters, structure,
calc_selection_coordsets)
print "Using symmetries", symm_groups
calculator = RMSDCalculator(
calculatorType=calculator_type,
fittingCoordsets=fit_selection_coordsets,
calculationCoordsets=calc_selection_coordsets,
calcSymmetryGroups=symm_groups)
try:
calculator.setNumberOfOpenMPThreads(
calculator_options.get_value("number_of_threads",
default_value=8))
except KeyError:
pass
try:
calculator.setCUDAKernelThreadsPerBlock(
calculator_options.get_value("threads_per_block",
default_value=32),
calculator_options.get_value("blocks_per_grid",
default_value=8))
except KeyError:
pass
rmsds = calculator.pairwiseRMSDMatrix()
return CondensedMatrix(rmsds)
def print_matrix(input_coordsets, output):
# Generate the matrix and print it
calculator = RMSDCalculator(calculatorType="QCP_OMP_CALCULATOR",
fittingCoordsets=input_coordsets)
matrixToImage(CondensedMatrix(calculator.pairwiseRMSDMatrix()),
output + ".png")
def print_matrix(input_coordsets, output):
# Generate the matrix and print it
calculator = RMSDCalculator(calculatorType="QCP_OMP_CALCULATOR", fittingCoordsets = input_coordsets)
matrixToImage(CondensedMatrix(calculator.pairwiseRMSDMatrix()), output + ".png")
