""":module XMDYNDemoPhotonMatterInteractor: Module that holds the XMDYNDemoPhotonMatterInteractor class. """
##########################################################################
# #
# Copyright (C) 2015-2018 Carsten Fortmann-Grote #
# Contact: Carsten Fortmann-Grote <carsten.grote@xfel.eu> #
# #
# This file is part of simex_platform. #
# simex_platform is free software: you can redistribute it and/or modify #
# it under the terms of the GNU General Public License as published by #
# the Free Software Foundation, either version 3 of the License, or #
# (at your option) any later version. #
# #
# simex_platform is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License for more details. #
# #
# You should have received a copy of the GNU General Public License #
# along with this program. If not, see <http://www.gnu.org/licenses/>. #
# #
##########################################################################
import h5py
import numpy
import os
import random
from SimEx.Calculators.AbstractPhotonInteractor import AbstractPhotonInteractor
from SimEx.Utilities import IOUtilities
[docs]class XMDYNDemoPhotonMatterInteractor(AbstractPhotonInteractor):
"""
:class XMDYNDemoPhotonMatterInteractor: Interface class for photon-matter interaction calculations using the demo version of the XMDYN code.
"""
def __init__(self, parameters=None, input_path=None, output_path=None, sample_path=None):
"""
:param parameters: Parameters that govern the PMI calculation.
:type parameters: dict
:param input_path: Location of data needed by the PMI calculation (Laser source wavefront data).
:type input_path: str
:param output_path: Where to store the data generated by the PMI calculation.
:type output_path: str
:param sample_path: Location of the sample/target geometry file. Can be either a simS2E sample file or a pdb file. Specifying a pdb will first check if it's present in a database, if not, it will issue a query for the basename of the file to the RCSB protein data bank.
:type sample_path: str
"""
# Initialize base class.
super(XMDYNDemoPhotonMatterInteractor, self).__init__(parameters,input_path,output_path)
# Check sample path.
if sample_path is None:
raise ValueError( "A target/sample must be specified through the 'sample_path' argument." )
if not os.path.isfile( sample_path):
print("Sample file %s was not found. Will attempt to query from RCSB protein data bank." % ( sample_path))
self.__sample_path = sample_path
self.__provided_data = ['/data/snp_<7 digit index>/ff',
'/data/snp_<7 digit index>/halfQ',
'/data/snp_<7 digit index>/Nph',
'/data/snp_<7 digit index>/r',
'/data/snp_<7 digit index>/T',
'/data/snp_<7 digit index>/Z',
'/data/snp_<7 digit index>/xyz',
'/data/snp_<7 digit index>/Sq_halfQ',
'/data/snp_<7 digit index>/Sq_bound',
'/data/snp_<7 digit index>/Sq_free',
'/history/parent/detail',
'/history/parent/parent',
'/info/package_version',
'/info/contact',
'/info/data_description',
'/info/method_description',
'/version']
self.__expected_data = ['/data/arrEhor',
'/data/arrEver',
'/params/Mesh/nSlices',
'/params/Mesh/nx',
'/params/Mesh/ny',
'/params/Mesh/qxMax',
'/params/Mesh/qxMin',
'/params/Mesh/qyMax',
'/params/Mesh/qyMin',
'/params/Mesh/sliceMax',
'/params/Mesh/sliceMin',
'/params/Mesh/xMax',
'/params/xMin',
'/params/yMax',
'/params/yMin',
'/params/zCoord',
'/params/beamline/printout',
'/params/Rx',
'/params/Ry',
'/params/dRx',
'/params/dRy',
'/params/nval',
'/params/photonEnergy',
'/params/wDomain',
'/params/wEFieldUnit',
'/params/wFloatType',
'/params/wSpace',
'/params/xCentre',
'/params/yCentre',
'/info/package_version',
'/info/contact',
'/info/data_description',
'/info/method_description',
'/misc/xFWHM',
'/misc/yFWHM',
'/version',
]
if (self.parameters is None) or ('number_of_trajectories' not in list(self.parameters.keys())):
self.parameters = {'number_of_trajectories' : 1,
}
if self.parameters['number_of_trajectories'] != 1:
print("\n WARNING: Number of trajectories != 1 not supported for this demo version of the PMI module. Falling back to 1 trajectory.\n")
self.parameters['number_of_trajectories'] = 1
if "random_rotation" not in list(self.parameters.keys()):
self.parameters["random_rotation"] = False
[docs] def expectedData(self):
""" Query for the data expected by the Interactor. """
return self.__expected_data
[docs] def providedData(self):
""" Query for the data provided by the Interactor. """
return self.__provided_data
[docs] def backengine(self):
""" This method drives the backengine code."""
status = 0
input_files = []
if os.path.isfile(self.input_path):
input_files = [self.input_path]
elif os.path.isdir(self.input_path):
input_files = [ os.path.join( self.input_path, f) for f in os.listdir( self.input_path ) if f.split('.')[-1] == 'h5' and f.split('.')[-2] != 'opmd' ]
input_files.sort()
else:
raise IOError("Input file %s does not exist or cannot be read." % (self.input_path) )
# Create output directory if not existing yet.
if not os.path.isdir( self.output_path ):
os.mkdir( self.output_path )
elif os.path.isfile( self.output_path ):
raise IOError( "Output file %s already exists, cowardly refusing to overwrite." % (self.output_path) )
# Generate formatted output files (i.e. attach history to output file).
for i,input_file in enumerate(input_files):
tail = input_file.split( 'prop' )[-1]
output_file = os.path.join( self.output_path , 'pmi_out_%07d.h5' % (i+1) )
f_h5_out2in( input_file, output_file)
# Get the backengine calculator.
pmi_demo = PMIDemo()
# Transfer some parameters.
pmi_demo.g_s2e['prj'] = ''
pmi_demo.g_s2e['id'] = tail.split('_')[-1].split('.')[0]
pmi_demo.g_s2e['prop_out'] = input_file
pmi_demo.g_s2e['setup'] = dict()
pmi_demo.g_s2e['sys'] = dict()
pmi_demo.g_s2e['setup']['num_digits'] = 7
if 'number_of_steps' in list(self.parameters.keys()):
pmi_demo.g_s2e['steps'] = self.parameters['number_of_steps']
else:
pmi_demo.g_s2e['steps'] = 100
pmi_demo.g_s2e['maxZ'] = 100
pmi_demo.g_s2e['random_rotation'] = self.parameters['random_rotation']
pmi_demo.g_s2e['setup']['pmi_out'] = output_file
# Setup the database.
pmi_demo.f_dbase_setup()
# Go through the pmi workflow.
pmi_demo.f_init_random()
pmi_demo.f_save_info()
pmi_demo.f_load_pulse( pmi_demo.g_s2e['prop_out'] )
# Get file extension.
extension = self.__sample_path.split(".")[-1]
if extension.lower() == "h5":
h5 = h5py.File(self.__sample_path, 'r')
h5.close()
pmi_demo.f_load_sample(self.__sample_path)
elif extension.lower() == "pdb":
atoms_dict = IOUtilities.loadPDB(self.__sample_path)
pmi_demo.g_s2e['sample'] = atoms_dict
elif extension.lower() == "xyz":
atoms_dict = IOUtilities.loadXYZ(self.__sample_path)
pmi_demo.g_s2e['sample'] = atoms_dict
else:
raise IOError("Sample file is in an unsupported format (supported are h5, pdb, xyz).")
pmi_demo.f_rotate_sample()
pmi_demo.f_system_setup()
# Perform the trajectories for this pulse and orientation.
for traj in range( self.parameters['number_of_trajectories'] ):
pmi_demo.f_time_evolution()
return status
@property
def data(self):
""" Query for the field data. """
return self.__data
def _readH5(self):
""" """
""" Private method for reading the hdf5 input and extracting the parameters and data relevant to initialize the object. """
pass # Nothing to be done since IO happens in backengine.
[docs] def saveH5(self):
""" """
"""
Private method to save the object to a file.
:param output_path: The file where to save the object's data.
:type output_path: str
"""
pass # No action required since output is written in backengine.
[docs]class PMIDemo(object):
def __init__(self):
self.g_s2e = {}
self.g_dbase = {}
self.f_s2e_setup()
[docs] def f_s2e_setup(self) :
self.g_s2e['setup'] = dict()
self.g_s2e['sys'] = dict()
self.g_s2e['setup']['num_digits'] = 7
self.g_s2e['steps'] = 100
self.g_s2e['maxZ'] = 100
##############################################################################
[docs] def f_save_info(self):
pmi_file = self.g_s2e['setup']['pmi_out']
grp = '/info'
### print pmi_file , grp
xfp = h5py.File( pmi_file , "a" )
try:
grp_hist_parent = xfp.create_group( grp )
except:
1
# xfp[ grp + '/Sq_free' ] = g_dbase['Sq_free']
xfp.close()
##############################################################################
[docs] def f_init_random(self) :
random.seed( self.g_s2e['id'] )
##############################################################################
[docs] def f_dbase_Zq2id(self, a_Z , a_q ) :
return ( a_Z * ( a_Z + 1 ) ) // 2 - 1*1 + a_q
##############################################################################
[docs] def f_dbase_setup(self) :
#print ' Update database!!!'
xdbase = load_ff_database()
g_dbase = dict()
# q -> sin(theta/2)/lambda
# au, exp(i*q*r) -> 1/Angstrom, exp( 2*pi*q*r)
g_dbase['halfQ'] = xdbase[:,0] = xdbase[:,0] / ( 2.0 * numpy.pi * 0.529177206 * 2.0 )
maxZ = self.g_s2e['maxZ'] #99
numQ = len( g_dbase['halfQ'] )
g_dbase['ff'] = numpy.zeros( ( self.f_dbase_Zq2id( maxZ , maxZ ) + 1 , numQ ) )
ii = 0
for ZZ in range( 1 , maxZ+1 ) :
for qq in range( ZZ+1 ) :
g_dbase['ff'][ ii , : ] = xdbase[:,ZZ] * ( ZZ - qq ) / ( ZZ * 1.0 ) ;
ii = ii + 1
g_dbase['Sq_halfQ'] = g_dbase['halfQ'] ;
g_dbase['Sq_bound'] = numpy.zeros( (numQ,) ) ;
g_dbase['Sq_free'] = numpy.zeros( (numQ,) ) ;
self.g_dbase = g_dbase
# g_dbase['ph_sigma'] ;
## g_dbase['halfQ'] = numpy.array( [ 0 , 1 , 2 ] ) ;
## maxZ = g_s2e['maxZ'] #99
## g_dbase['ff'] = numpy.zeros( ( f_dbase_Zq2id( maxZ , maxZ ) + 1 , len( g_dbase['halfQ'] ) ) )
## ii = 0
## for ZZ in range( 1 , maxZ+1 ) :
## for qq in range( ZZ+1 ) :
## g_dbase['ff'][ ii , : ] = numpy.array( [ 1.0 , 0.5 , 0.25 ] ) * ( ZZ - qq ) ;
##### print ZZ, qq, ii
##### print g_dbase['ff'][ ii , : ]
## ii = ii + 1
## g_dbase['Sq_halfQ'] = numpy.array( [ 0 , 0 , 0 ] ) ;
## g_dbase['Sq_bound'] = numpy.array( [ 0 , 0 , 0 ] ) ;
## g_dbase['Sq_free'] = numpy.array( [ 0 , 0 , 0 ] ) ;
### g_dbase['ph_sigma'] ;
[docs] def f_load_snp_content(self, a_fp , a_snp ) :
dbase_root = "/data/snp_" + str( a_snp ).zfill(self.g_s2e['setup']['num_digits']) + "/"
xsnp = dict()
xsnp['Z'] = a_fp.get( dbase_root + 'Z' ) .value
xsnp['T'] = a_fp.get( dbase_root + 'T' ) .value
xsnp['ff'] = a_fp.get( dbase_root + 'ff' ) .value
xsnp['xyz'] = a_fp.get( dbase_root + 'xyz' ) .value
xsnp['r'] = a_fp.get( dbase_root + 'r' ) .value
N = xsnp['Z'].size
xsnp['q'] = numpy.array( [ xsnp['ff'][ numpy.nonzero( xsnp['T'] == x )[0] , 0 ] for x in xsnp['xyz'] ] ) .reshape(N,)
xsnp['snp'] = a_snp ;
return xsnp
[docs] def f_load_snp_xxx(self, a_real , a_snp ) :
xfp = h5py.File( self.g_s2e['prj'] + '/pmi/pmi_out_' + str( a_real ).zfill(self.g_s2e['setup']['num_digits']) + '.h5' , "r" )
xsnp = self.f_load_snp_content( xfp , a_snp )
xfp.close()
return xsnp
[docs] def f_load_snp_from_dir(self, path_to_snapshot) :
""" Load xmdyn output from an xmdyn directory.
:param path: The directory path to xmdyn output.
:type path: str
:param snapshot_index: Which snapshot to load.
:type snapshot_index: int
:returns: The snapshot data.
:rtype: dict
"""
xsnp = dict()
xsnp['Z'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'Z.dat' )) # Atom numbers
xsnp['T'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'T.dat' )) # Atom type
xsnp['uid'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'uid.dat' )) #Unique atom ID.
xsnp['r'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'r.dat' )) # Cartesian coordinates.
xsnp['v'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'v.dat' )) # Cartesian velocities.
xsnp['m'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'm.dat' )) # Masses.
xsnp['q'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'q.dat' )) # Ion charge
xsnp['ff'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'f0.dat' )) # Form factors of each atom type.
xsnp['Q'] = numpy.loadtxt(os.path.join(path_to_snapshot, 'Q.dat' )) # Wavenumber grid for form factors.
return xsnp
[docs] def f_load_sample( self, sample_path ) :
sample = dict()
xfp = h5py.File( sample_path, 'r' )
xxx = xfp.get( 'Z' ) ; sample['Z'] = xxx.value
xxx = xfp.get( 'r' ) ; sample['r'] = xxx.value
xfp.close()
sample['selZ'] = dict()
for sel_Z in numpy.unique( sample['Z'] ) :
sample['selZ'][sel_Z] = numpy.nonzero( sample['Z'] == sel_Z )
sample['N'] = len( sample['Z'] )
self.g_s2e['sample'] = sample
[docs] def f_save_data(self, dset , data ) :
xfp = h5py.File( self.g_s2e['setup']['pmi_out'] , "a" )
try:
xfp.create_group( os.path.dirname( dset ) )
except:
1
xfp[ dset ] = data
xfp.close()
[docs] def f_rotate_sample( self ) :
# Init quaternion for rotation.
self.g_s2e['sample']['rot_quaternion'] = numpy.array([0,0,0,0])
# Set to random if desired.
if self.g_s2e['random_rotation'] is True:
self.g_s2e['sample']['rot_quaternion'] = numpy.random.rand( 4 )
self.g_s2e['sample']['rotmat'] = numpy.zeros((9,))
s2e_gen_randrot_quat( self.g_s2e['sample']['rot_quaternion'] , self.g_s2e['sample']['rotmat'] ) ;
s2e_rand_orient( self.g_s2e['sample']['r'] , self.g_s2e['sample']['rotmat'] ) ;
self.f_save_data( '/data/angle' , self.g_s2e['sample']['rot_quaternion'] .reshape((1,4)) )
[docs] def f_system_setup( self ) :
self.g_s2e['sys']['r'] = self.g_s2e['sample']['r'].copy()
self.g_s2e['sys']['q'] = numpy.zeros( self.g_s2e['sample']['Z'].shape )
self.g_s2e['sys']['NE'] = self.g_s2e['sample']['Z'].copy()
self.g_s2e['sys']['Z'] = self.g_s2e['sample']['Z']
self.g_s2e['sys']['Nph'] = 1e99
#print ' NOTE: Nph is uniform.'
[docs] def f_save_snp( self, a_snp ) :
self.g_s2e['sys']['xyz'] = self.f_dbase_Zq2id( self.g_s2e['sys']['Z'] , self.g_s2e['sys']['q'] )
self.g_s2e['sys']['T'] = numpy.sort( numpy.unique( self.g_s2e['sys']['xyz'] ) )
ff = numpy.zeros( ( len( self.g_s2e['sys']['T'] ) , len( self.g_dbase['halfQ'] ) ) )
for ii in range( len( self.g_s2e['sys']['T'] ) ) :
ff[ii,:] = self.g_dbase['ff'][self.g_s2e['sys']['T'][ii].astype(int),:].copy()
### print self.g_s2e['sys']['T'][ii].astype(int) , ff[ii,:]
pmi_file = self.g_s2e['setup']['pmi_out']
grp = '/data/snp_' + str( a_snp ).zfill( self.g_s2e['setup']['num_digits'] )
### print pmi_file , grp
xfp = h5py.File( pmi_file , "a" )
try:
grp_hist_parent = xfp.create_group( '/data' )
except:
1
grp_hist_parent = xfp.create_group( grp )
xfp[ grp + '/Z' ] = self.g_s2e['sys']['Z']
xfp[ grp + '/T' ] = self.g_s2e['sys']['T'] .astype(numpy.int32)
xfp[ grp + '/xyz' ] = self.g_s2e['sys']['xyz'] .astype(numpy.int32)
xfp[ grp + '/r' ] = self.g_s2e['sys']['r'] .astype(numpy.float32)
xfp[ grp + '/Nph' ] = numpy.array( [self.g_s2e['pulse']['sel_int'][a_snp-1]] )
xfp[ grp + '/halfQ' ] = self.g_dbase['halfQ'] .astype(numpy.float32)
xfp[ grp + '/ff' ] = ff .astype(numpy.float32)
xfp[ grp + '/Sq_halfQ' ] = self.g_dbase['Sq_halfQ'] .astype(numpy.float32)
xfp[ grp + '/Sq_bound' ] = self.g_dbase['Sq_bound'] .astype(numpy.float32)
xfp[ grp + '/Sq_free' ] = self.g_dbase['Sq_free'] .astype(numpy.float32)
xfp.close()
##############################################################################
[docs] def f_num_snp_xxx( self, all_real ) :
xfp = h5py.File( self.g_s2e['prj'] + '/pmi/pmi_out_' + str( all_real[0] ).zfill(self.g_s2e['setup']['num_digits']) + '.h5' , "r" )
cc = 1
while 1 :
if not xfp.get( "/data/snp_" + str( cc ).zfill(self.g_s2e['setup']['num_digits']) ) :
xfp.close()
return cc - 1
cc = cc + 1
# try:
# if type( a_fp.get( "/data/snp_" + str( cc ).zfill(NUM_DIGITS) + '/Nph' ) ) == 'NoneType' :
# print 'N'
# else :
# print 1
#
# except:
# return cc
##############################################################################
[docs] def f_load_pulse(self, a_prop_out ) :
xfp = h5py.File( a_prop_out , "r" )
self.g_s2e['pulse'] = dict()
self.g_s2e['pulse']['xFWHM'] = xfp.get( '/misc/xFWHM' ) .value
self.g_s2e['pulse']['yFWHM'] = xfp.get( '/misc/yFWHM' ) .value
self.g_s2e['pulse']['nSlices'] = xfp.get( 'params/Mesh/nSlices' ) .value
self.g_s2e['pulse']['nx'] = xfp.get( 'params/Mesh/nx' ) .value
self.g_s2e['pulse']['ny'] = xfp.get( 'params/Mesh/ny' ) .value
self.g_s2e['pulse']['sliceMax'] = xfp.get( 'params/Mesh/sliceMax' ) .value
self.g_s2e['pulse']['sliceMin'] = xfp.get( 'params/Mesh/sliceMin' ) .value
self.g_s2e['pulse']['xMax'] = xfp.get( 'params/Mesh/xMax' ) .value
self.g_s2e['pulse']['xMin'] = xfp.get( 'params/Mesh/xMin' ) .value
self.g_s2e['pulse']['yMax'] = xfp.get( 'params/Mesh/yMax' ) .value
self.g_s2e['pulse']['yMin'] = xfp.get( 'params/Mesh/yMin' ) .value
self.g_s2e['pulse']['photonEnergy'] = xfp.get( 'params/photonEnergy' ) .value
self.g_s2e['pulse']['arrEver'] = xfp.get( 'data/arrEver' ) .value
self.g_s2e['pulse']['arrEhor'] = xfp.get( 'data/arrEhor' ) .value
#g_s2e['pulse'][''] = xfp.get( '' ) .value
xfp.close()
# Take central pixel values.
sel_x = self.g_s2e['pulse']['nx'] // 2 ;
sel_y = self.g_s2e['pulse']['ny'] // 2 ;
# note: the data order in the HDF5 file is not x,y but y,x
sel_pixV = self.g_s2e['pulse']['arrEver'] [sel_y,sel_x,:,:]
sel_pixH = self.g_s2e['pulse']['arrEhor'] [sel_y,sel_x,:,:]
dt = ( self.g_s2e['pulse']['sliceMax'] - self.g_s2e['pulse']['sliceMin'] ) / ( self.g_s2e['pulse']['nSlices'] * 1.0 )
dx = ( self.g_s2e['pulse']['xMax'] - self.g_s2e['pulse']['xMin'] ) / ( self.g_s2e['pulse']['nx'] * 1.0 )
dy = ( self.g_s2e['pulse']['yMax'] - self.g_s2e['pulse']['yMin'] ) / ( self.g_s2e['pulse']['ny'] * 1.0 )
Eph = self.g_s2e['pulse']['photonEnergy'] * 1.0 ;
NPH = 0
for tt in range( self.g_s2e['pulse']['nSlices'] ) :
NPH += ( sel_pixV[tt,0]**2 + sel_pixV[tt,1]**2 + sel_pixH[tt,0]**2 + sel_pixH[tt,1]**2 )
NPH *= 1e6 * dt * self.g_s2e['pulse']['xFWHM'] * self.g_s2e['pulse']['yFWHM'] / ( Eph * 1.6022e-19 )
self.g_s2e['pulse']['sel_int'] = numpy.ones( (self.g_s2e['steps'],) ) * ( NPH / (1.0*self.g_s2e['steps']) )
# print self.g_s2e['pulse']['arrEhor'].shape , dt , dx , dy , NPH
# print self.g_s2e['pulse']['sel_int']
# self.g_s2e_pulse['sliceMax'] = self.g_s2e_pulse[''] - self.g_s2e_pulse['']
# self.g_s2e_pulse['sliceMin'] = 0
# self.g_s2e_pulse['sliceDelta'] = self.g_s2e_pulse[''] / ( self.g_s2e_pulse[''] - 1.0 )
# self.g_s2e_pulse['slices'] =
# self.g_s2e_pulse['xMax'] = ( self.g_s2e_pulse[''] - self.g_s2e_pulse[''] ) / 2.0
# self.g_s2e_pulse['xMin'] = - self.g_s2e_pulse['']
# self.g_s2e_pulse['xDelta'] = ( self.g_s2e_pulse[''] - self.g_s2e_pulse[''] ) / ( self.g_s2e_pulse[''] - 1.0 )
# self.g_s2e_pulse['sel_pix_x'] = ( self.g_s2e_pulse[''] + 1 ) / 2
# self.g_s2e_pulse['sel_pix_y'] = ( self.g_s2e_pulse[''] + 1 ) / 2
return
# /** Some transformation and derived useful parameters */
# data_prop_out.sliceMax = data_prop_out.sliceMax - data_prop_out.sliceMin ;
# data_prop_out.sliceMin = 0 ;
#
# data_prop_out.sliceDelta = data_prop_out.sliceMax / (double) (data_prop_out.nSlices-1) ;
# data_prop_out.slices = calloc( data_prop_out.nSlices , sizeof(double) ) ;
# for ( ii = 0 ; ii < data_prop_out.nSlices ; ii++ )
# {
# data_prop_out.slices[ii] = data_prop_out.sliceDelta * ii ;
# }
# data_prop_out.xMax = ( data_prop_out.xMax - data_prop_out.xMin ) / 2.0 ;
# data_prop_out.xMin = - data_prop_out.xMax ;
# data_prop_out.xDelta = ( data_prop_out.xMax - data_prop_out.xMin ) /
# (double) (data_prop_out.nx - 1 ) ;
# data_prop_out.yMax = ( data_prop_out.yMax - data_prop_out.yMin ) / 2.0 ;
#
# data_prop_out.yMin = - data_prop_out.yMax ;
# data_prop_out.yDelta = ( data_prop_out.yMax - data_prop_out.yMin ) /
# (double) ( data_prop_out.ny - 1 ) ;
# /** Selecting center (ot highest fluence) pixel */
# data_prop_out.sel_pix_x = ( data_prop_out.nx + 1 ) / 2 ;
# data_prop_out.sel_pix_y = ( data_prop_out.ny + 1 ) / 2 ;
##############################################################################
[docs] def f_time_evolution(self) :
for step in range( 1 , self.g_s2e['steps'] + 1 ) :
self.f_save_snp( step )
##############################################################################
[docs]def f_eval_disp( a_snp , a_r0 , a_sample ) :
num_Z = len( list(a_sample['selZ'].keys()) )
all_disp = numpy.zeros( ( num_Z , ) )
cc = 0 ;
for sel_Z in list(a_sample['selZ'].keys()) :
dr = a_snp['r'][a_sample['selZ'][sel_Z],:] - a_r0[a_sample['selZ'][sel_Z],:]
all_disp[cc] = numpy.mean( numpy.sqrt( numpy.sum( dr * dr , axis = 1 ) ) ) / 1e-10
cc = cc + 1
return all_disp
[docs]def s2e_gen_randrot_quat( quat , rotmat ) :
if ( 0 == quat[0] * quat[0] +
quat[1] * quat[1] +
quat[2] * quat[2] +
quat[3] * quat[3] ) :
u0,u1,u2 = numpy.random.random( 3 )
q0 = numpy.sqrt(1.-u0) * numpy.sin(2*numpy.pi*u1) ;
q1 = numpy.sqrt(1.-u0) * numpy.cos(2*numpy.pi*u1) ;
q2 = numpy.sqrt(u0) * numpy.sin(2*numpy.pi*u2) ;
q3 = numpy.sqrt(u0) * numpy.cos(2*numpy.pi*u2) ;
quat[0] = q0 ;
quat[1] = q1 ;
quat[2] = q2 ;
quat[3] = q3 ;
else :
q0 = quat[0] ;
q1 = quat[1] ;
q2 = quat[2] ;
q3 = quat[3] ;
rotmat[0] = q0*q0 + q1*q1 - q2*q2 - q3*q3 ; #// M[0][0]
rotmat[1] = 2 * ( q1*q2 - q0*q3 ) ; #// M[0][1]
rotmat[2] = 2 * ( q1*q3 + q0*q2 ) ; #// M[0][2]
rotmat[3] = 2 * ( q1*q2 + q0*q3 ) ; #// M[1][0]
rotmat[4] = q0*q0 - q1*q1 + q2*q2 - q3*q3 ; #// M[1][1]
rotmat[5] = 2 * ( q2*q3 - q0*q1 ) ; #// M[1][2]
rotmat[6] = 2 * ( q1*q3 - q0*q2 ) ; #// M[2][0]
rotmat[7] = 2 * ( q2*q3 + q0*q1 ) ; #// M[2][1]
rotmat[8] = q0*q0 - q1*q1 - q2*q2 + q3*q3 ; #// M[2][2]
# inversematrix3( (void*) (rotmat + ii) , (void*) (invmat + ii) ) ;
# for ( ii = 0 ; ii < randrot ; ii++ )
# {
# for ( jj=0 ; jj < 3 ; jj++ )
# {
# printf( "% e % e % e\n" , rotmat[ii][jj*3+0] , rotmat[ii][jj*3+1] ,
# rotmat[ii][jj*3+2] ) ;
# }
# printf("\n") ;
# for ( jj=0 ; jj < 3 ; jj++ )
# {
# printf( "% e % e % e\n" , invmat[ii][jj*3+0] , invmat[ii][jj*3+1] ,
# invmat[ii][jj*3+2] ) ;
# }
# printf("\n\n\n") ;
# }
#}
##############################################################################
[docs]def s2e_rand_orient( r ,mat ) :
N = r.shape[0]
### print N
vv = numpy.zeros((3,0))
for ii in range(N) :
vv = r[ii,:]
### print vv , vv.shape , mat.shape
r[ii,0] = mat[0] * vv[0] + mat[1] * vv[1] + mat[2] * vv[2]
r[ii,1] = mat[3] * vv[0] + mat[4] * vv[1] + mat[5] * vv[2]
r[ii,2] = mat[6] * vv[0] + mat[7] * vv[1] + mat[8] * vv[2]
##############################################################################
[docs]def f_eval_numE( a_snp , a_sample ) :
num_Z = len( list(a_sample['selZ'].keys()) )
all_numE = numpy.zeros( ( num_Z , ) )
cc = 0 ;
for sel_Z in list(a_sample['selZ'].keys()) :
all_numE[cc] = numpy.mean( a_snp['q'][a_sample['selZ'][sel_Z]] )
cc = cc + 1
return all_numE
##############################################################################
[docs]def f_md_step( r , v , m , dt ) :
r = r.copy()
v = v.copy()
a = ( force( config , param ) + external_force( config , param ) ) / m
r = r + v*dt + 0.5*a*dt**2.0
config['r'] = r
an = ( force( config , param ) + external_force( config , param ) ) / m
v = v + 0.5* (a+an) * dt
config['v'] = v
E = f_sysenergy_kin(v,m) + syspot( config , param ) + ext_syspot( config , param )
##############################################################################
[docs]def f_pmi_diagnostics_help() :
print("""
----
""")
##############################################################################
##############################################################################
##############################################################################
[docs]def load_ff_database():
# INTERNAL NOTE # ######## To get to the nice array below: ########
# INTERNAL NOTE # for x in `seq 1 100` ; do echo $x ; RES=`time xatom -Z $x -formfactor -Q 10 -N_Q 100 2>ff-$x.err` ; echo "$RES" | grep -v \# > ff-$x.dat ; echo "$RES" | grep \# > ff-$x.log ; done
# INTERNAL NOTE # cp ff-1.dat ff_all.dat
# INTERNAL NOTE # for x in `seq 2 100` ; do cat ff-${x}.dat| cut -c14-26 | paste -d" " ff_all.dat - > ff_all.xxx ; mv ff_all.xxx ff_all.dat ; done
# INTERNAL NOTE # cat ff_all.dat |while read x; do echo '[' `echo $x|sed s/\ /\ ,\ /g` '] ,'; done > ff_all.dat--numpy_array
dbase = numpy.array(
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]
)
return dbase
##############################################################################
[docs]def f_hdf5_simple_read(self, a_file , a_dataset ) :
xfp = h5py.File( a_file , "r" )
xxx = xfp.get( a_dataset ).value
xfp.close()
return xxx
##############################################################################
[docs]def f_h5_out2in( src , dest , *args ) :
file_in = h5py.File( src , "r")
file_out = h5py.File( dest , "w")
grp_hist = file_out.create_group( "history" )
grp_hist_parent = file_out.create_group( "history/parent" )
grp_hist_parent_detail = file_out.create_group( "history/parent/detail" )
pre_s2e_module = os.path.basename( os.path.dirname( os.path.abspath( src ) ) )
print('Previous module: ' , pre_s2e_module)
# Add attribute to history/parent
grp_hist_parent.attrs['name'] = "_" + pre_s2e_module
grp_srchist = file_in.get( "history/parent" ) ;
file_out.copy( grp_srchist , grp_hist_parent )
# Copy everything to history except "data" & "history"
for objname in list(file_in.keys()) :
if objname != "data" and objname != "history" :
x = file_in.get( objname )
if isinstance(x, h5py.Dataset):
mygroup = file_in['/']
file_out["history/parent/detail/"+objname] = mygroup[objname][...]
elif isinstance(x, h5py.Group):
file_out.copy( x , "history/parent/detail/" + objname)
else:
print(objname , " has been SKIPPED!!")
print(objname)
else :
print(' NOT:', objname)
print(list(file_in['data'].keys()))
print(list(file_in['data'].items()))
# Create external link to parent's data
#file_out['history/parent/detail/data'] = h5py.ExternalLink( src ,'/data')
parent_module = os.path.basename( src ) [ : os.path.basename( src ) .find( '_out' ) ]
file_out['history/parent/detail/data'] = h5py.ExternalLink( '../' + parent_module + '/' + os.path.basename( src ) , '/data' )
# Create your own groups
grp_data = file_out.create_group( "data" )
grp_param = file_out.create_group( "params" )
grp_param = file_out.create_group( "misc" )
grp_param = file_out.create_group( "info" )
# Create s2e interface version
interface = file_out.create_dataset("info/interface_version", (1,), dtype='f')
interface[0] = 1.0
file_out.close()
file_in.close()