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Update __init__.py #528

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ec69080
Update __init__.py
tomburnley Sep 16, 2020
277bc69
Update __init__.py
tomburnley Sep 18, 2020
7704564
Update __init__.py
tomburnley Sep 22, 2020
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190 changes: 150 additions & 40 deletions mmtbx/refinement/ensemble_refinement/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,12 +2,14 @@
from __future__ import absolute_import, division, print_function
import mmtbx.solvent.ensemble_ordered_solvent as ensemble_ordered_solvent
from mmtbx.refinement.ensemble_refinement import ensemble_utils
from mmtbx.refinement import refinement_flags
from mmtbx.dynamics import ensemble_cd
import mmtbx.tls.tools as tls_tools
import mmtbx.command_line
import mmtbx.utils
import mmtbx.model
import mmtbx.maps
from mmtbx.den import den_restraints
from iotbx.option_parser import iotbx_option_parser
from iotbx import pdb
import iotbx.phil
Expand All @@ -29,15 +31,19 @@
import random
import gzip
import math
import time, os
import time
import os
import sys
from six.moves import range

# these supersede the defaults in included scopes
# Revert to defaults
# ensemble_refinement.mask.ignore_hydrogens = False
# ensemble_refinement.mask.n_radial_shells = 1
# ensemble_refinement.mask.radial_shell_width = 1.5

customization_params = iotbx.phil.parse("""
ensemble_refinement.mask.ignore_hydrogens = False
ensemble_refinement.mask.n_radial_shells = 1
ensemble_refinement.mask.radial_shell_width = 1.5
ensemble_refinement.den.kappa_burn_in_cycles = 0
ensemble_refinement.cartesian_dynamics.number_of_steps = 10
ensemble_refinement.ensemble_ordered_solvent.b_iso_min = 0.0
ensemble_refinement.ensemble_ordered_solvent.b_iso_max = 100.0
Expand Down Expand Up @@ -65,6 +71,13 @@
.type = bool
.help = Use protein atoms thermostat
}
den_restraints = True
.type = bool
.help = 'Use DEN restraints'
den
{
include scope mmtbx.den.den_params
}
update_sigmaa_rfree = 0.001
.type = float
.help = test function
Expand Down Expand Up @@ -133,6 +146,11 @@
.help = 'The fraction of atoms to include in TLS fitting'
.short_caption = Fraction of atoms to include in TLS fitting
.style = bold
import_tls_pdb = None
.type = str
.help = 'PDB path to import TLS from external structure'
.short_caption = PDB path to import TLS from external structure
.style = bold
max_ptls_cycles = 25
.type = int
.help = 'Maximum cycles to use in TLS fitting; TLS will stop prior to this if convergence is reached'
Expand Down Expand Up @@ -320,8 +338,6 @@ def __init__(self, fmodel,
ptls,
run_number=None):
adopt_init_args(self, locals())
# self.params = params.extract().ensemble_refinement

if self.params.target_name in ['ml', 'mlhl'] :
self.fix_scale = False
else:
Expand Down Expand Up @@ -369,6 +385,7 @@ def __init__(self, fmodel,
* self.cdp.number_of_steps * self.cdp.time_step, file=log)
#
print("\nAcquisition block", file=log)
print(" Number blocks : ", self.params.number_of_acquisition_periods, file=log)
print(" Number Tx periods : ", self.params.acquisition_block_n_tx, file=log)
print(" Number macro cycles : ", self.acquisition_block_macro_cycles, file=log)
print(" Time (ps) : ", self.acquisition_block_macro_cycles \
Expand Down Expand Up @@ -426,7 +443,7 @@ def __init__(self, fmodel,
max_number_of_bins = 999).show_rfactors_targets_in_bins(out = self.log)

if self.params.target_name in ['ml', 'mlhl'] :
#Must be called before reseting ADPs
# Must be called before reseting ADPs
if self.params.scale_wrt_n_calc_start:
make_header("Calculate Ncalc and restrain to scale kn", out = self.log)
self.fmodel_running.n_obs_n_calc(update_nobs_ncalc = True)
Expand All @@ -446,30 +463,40 @@ def __init__(self, fmodel,
self.target_k1 = self.fmodel_running.scale_k1()
self.update_normalisation_factors()
else:
make_header("Calculate and fix scale of Ncalc", out = self.log)
self.fmodel_running.n_obs_n_calc(update_nobs_ncalc = True)
make_header("Calculate and fix scale of Ncalc", out=self.log)
self.fmodel_running.n_obs_n_calc(update_nobs_ncalc=True)
print("Fix Ncalc scale : True", file=self.log)
print("Sum current Ncalc : {0:5.3f}".format(sum(self.fmodel_running.n_calc)), file=self.log)

#Set ADP model
# Set ADP model
self.tls_manager = er_tls_manager()
self.setup_tls_selections(tls_group_selection_strings = self.params.tls_group_selections)
self.fit_tls(input_model = self.model)
self.assign_solvent_tls_groups()
# Fit pTLS to starting atomic model
if self.params.import_tls_pdb is None:
self.setup_tls_selections(
tls_group_selection_strings=self.params.tls_group_selections)
self.fit_tls(input_model=self.model)
self.assign_solvent_tls_groups()
# Import TLS from reference model
else:
fit_tlsos, fit_tls_strings = self.import_tls_selections()
self.setup_tls_selections(tls_group_selection_strings=fit_tls_strings)
self.model.tls_groups.tlsos = fit_tlsos
self.tls_manager.tls_operators = fit_tlsos
self.assign_solvent_tls_groups()
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#Set occupancies to 1.0
# Set occupancies to 1.0
if self.params.set_occupancies:
make_header("Set occupancies to 1.0", out = self.log)
self.model.get_xray_structure().set_occupancies(
value = 1.0)
self.model.show_occupancy_statistics(out = self.log)
#Initiates running average SFs
# Initiates running average SFs
self.er_data.f_calc_running = self.fmodel_running.f_calc().data().deep_copy()
#self.fc_running_ave = self.fmodel_running.f_calc()
self.fc_running_ave = self.fmodel_running.f_calc().deep_copy()

#Initial sigmaa array, required for ML target function
#Set eobs and ecalc normalization factors in Fmodel, required for ML
# Initial sigmaa array, required for ML target function
# Set eobs and ecalc normalization factors in Fmodel, required for ML
if self.params.target_name in ['ml', 'mlhl'] :
self.sigmaa_array = self.fmodel_running.sigmaa().sigmaa().data()
self.best_r_free = self.fmodel_running.r_free()
Expand Down Expand Up @@ -499,10 +526,9 @@ def __init__(self, fmodel,
self.update_normalisation_factors()

# Ordered Solvent Update
if self.params.ordered_solvent_update \
and (self.macro_cycle == 1\
or self.macro_cycle%self.params.ordered_solvent_update_cycle == 0):
self.ordered_solvent_update()
if self.params.ordered_solvent_update:
if self.macro_cycle == 1 or self.macro_cycle%self.params.ordered_solvent_update_cycle == 0:
self.ordered_solvent_update()

xrs_previous = self.model.get_xray_structure().deep_copy_scatterers()
assert self.fmodel_running.xray_structure is self.model.get_xray_structure()
Expand All @@ -515,6 +541,71 @@ def __init__(self, fmodel,
else:
cdp_verbose = -1

if self.params.den_restraints:
if self.macro_cycle == 1:
make_header("Create DEN restraints", out = self.log)
# Update den manager due to solvent chain changes from start model
from mmtbx.den import den_restraints
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pdb_hierarchy = self.model.get_hierarchy()
den_manager = den_restraints(
pdb_hierarchy = pdb_hierarchy,
pdb_hierarchy_ref = None,
params = self.params.den,
log = self.log)
self.model.restraints_manager.geometry.den_manager = den_manager
print(
"DEN weight : ",
self.model.restraints_manager.geometry.den_manager.weight,
file=self.log)
print(
"DEN gamma : ",
self.model.restraints_manager.geometry.den_manager.gamma,
file=self.log)
#
den_seed = self.params.random_seed
flex.set_random_seed(value=den_seed)
random.seed(den_seed)
self.model.restraints_manager.geometry.den_manager.build_den_proxies(
pdb_hierarchy=pdb_hierarchy)
self.model.restraints_manager.geometry.den_manager.build_den_restraints()
self.model.restraints_manager.geometry.den_manager.current_cycle = 1
sites_cart = self.model.get_xray_structure().sites_cart()
if self.params.verbose > 0:
print(
self.model.restraints_manager.geometry.den_manager.show_den_summary(
sites_cart=sites_cart),
file=self.log)

else:
# Reassign random pairs
if self.macro_cycle % 500 == 0:
make_header("Create DEN restraints", out = self.log)
den_seed += 1
flex.set_random_seed(value=den_seed)
from mmtbx.den import den_restraints
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pdb_hierarchy = self.model.get_hierarchy()
den_manager = den_restraints(
pdb_hierarchy = pdb_hierarchy,
pdb_hierarchy_ref = None,
params = self.params.den,
log = self.log)
self.model.restraints_manager.geometry.den_manager = den_manager
self.model.restraints_manager.geometry.den_manager.build_den_proxies(
pdb_hierarchy=pdb_hierarchy)
self.model.restraints_manager.geometry.den_manager.build_den_restraints()
self.model.restraints_manager.geometry.den_manager.current_cycle = 1
sites_cart = self.model.get_xray_structure().sites_cart()
if self.params.verbose > 0:
print(
self.model.restraints_manager.geometry.den_manager.show_den_summary(
sites_cart=sites_cart),
file=self.log)

# Update eq distances per macro cycle
self.model.restraints_manager.geometry.den_manager.current_cycle = 1
self.model.restraints_manager.geometry.den_manager.update_eq_distances(
sites_cart=self.model.get_xray_structure().sites_cart())

cd_manager = ensemble_cd.cartesian_dynamics(
structure = self.model.get_xray_structure(),
restraints_manager = self.model.restraints_manager,
Expand All @@ -540,6 +631,17 @@ def __init__(self, fmodel,
self.reset_velocities = False
self.cmremove = False

# Update CDL restraints
from mmtbx import conformation_dependent_library as cdl
from mmtbx.conformation_dependent_library import cdl_utils, cdl_setup
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cdl_proxies = cdl_setup.setup_restraints(
self.model.restraints_manager.geometry,
verbose=True)
cdl.update_restraints(self.model.get_hierarchy(),
geometry=self.model.restraints_manager.geometry,
cdl_proxies=cdl_proxies,
verbose=True)

#Calc rolling average KE energy
self.kinetic_energy_running_average()
#Show KE stats
Expand Down Expand Up @@ -888,6 +990,16 @@ def update_sigmaa(self):
self.best_r_free = self.fmodel_running.r_free()
print("|"+"-"*77+"|\n", file=self.log)

def import_tls_selections(self):
make_header("Import External TLS", out = self.log)
print('External TLS model: ' + self.params.import_tls_pdb, file=self.log)
pdb_import_tls = self.params.import_tls_pdb
pdb_tls_inp = iotbx.pdb.hierarchy.input(file_name=pdb_import_tls)
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please use iotbx.pdb.input() instead, preferably checking if the file exists.

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Still this, with the explanation in the previous message.

tls_params = pdb_tls_inp.input.extract_tls_params(pdb_tls_inp.hierarchy)
fit_tlsos = [tls_tools.tlso(t=o.t, l=o.l, s=o.s, origin=o.origin) for o in tls_params.tls_params]
tls_strings = [o.selection_string for o in tls_params.tls_params]
return fit_tlsos, tls_strings

def setup_tls_selections(self, tls_group_selection_strings):
make_header("Generating TLS selections from input parameters (not including solvent)", out = self.log)
model_no_solvent = self.model.deep_copy()
Expand Down Expand Up @@ -948,7 +1060,6 @@ def setup_tls_selections(self, tls_group_selection_strings):
tls_no_sol_no_hd_selections = mmtbx.utils.get_atom_selections(
model = model_no_solvent,
selection_strings = tls_no_hd_selection_strings)

#
assert self.tls_manager is not None
self.tls_manager.tls_selection_strings_no_sol = tls_group_selection_strings
Expand All @@ -964,7 +1075,7 @@ def setup_tls_selections(self, tls_group_selection_strings):
selection_strings = self.tls_manager.tls_selection_strings_no_sol,
tlsos = self.tls_manager.tls_operators)

def fit_tls(self, input_model, verbose = False):
def fit_tls(self, input_model, verbose=False):
make_header("Fit TLS from reference model", out = self.log)
model_copy = input_model.deep_copy()
model_copy = model_copy.remove_solvent()
Expand Down Expand Up @@ -1135,7 +1246,8 @@ def tls_parameters_update(self):
update_f_mask = False)

def assign_solvent_tls_groups(self):
self.model.get_xray_structure().convert_to_anisotropic(selection = self.model.solvent_selection())
self.model.get_xray_structure().convert_to_anisotropic(
selection=self.model.solvent_selection())
self.fmodel_running.update_xray_structure(
xray_structure = self.model.get_xray_structure(),
update_f_calc = False,
Expand Down Expand Up @@ -1183,6 +1295,7 @@ def kinetic_energy_running_average(self):
= (self.a_prime * self.er_data.ke_protein_running) + ( (1-self.a_prime) * ke)

def ordered_solvent_update(self):
make_header("Update ordered solvent", out = self.log)
ensemble_ordered_solvent_manager = ensemble_ordered_solvent.manager(
model = self.model,
fmodel = self.fmodel_running,
Expand Down Expand Up @@ -1686,6 +1799,9 @@ def run(args, command_name = "phenix.ensemble_refinement", out=None,
new_file_object=log_file)
timer = user_plus_sys_time()
mmtbx.utils.print_programs_start_header(log=log, text=command_name)
#
make_header("Ensemble Refinement 2020", out=log)
#
make_header("Ensemble refinement parameters", out = log)
working_phil.show(out = log)
make_header("Model and data statistics", out = log)
Expand Down Expand Up @@ -1739,22 +1855,16 @@ def run(args, command_name = "phenix.ensemble_refinement", out=None,
log = log)

# Refinement flags
# Worst hack I've ever seen! No wonder ensemble refinement is semi-broken!
class rf:
def __init__(self, size):
self.individual_sites = True
self.individual_adp = False
self.sites_individual = flex.bool(size, True)
self.sites_torsion_angles = None
self.torsion_angles = None
self.adp_individual_iso = None
self.adp_individual_aniso = None
def inflate(self, **keywords): pass
def select_detached(self, **keywords): pass

refinement_flags = rf(size = model.get_number_of_atoms())

model.set_refinement_flags(refinement_flags)
rf = refinement_flags.manager(
individual_sites = True,
individual_adp = False,
sites_individual = flex.bool(model.get_number_of_atoms(), True),
sites_torsion_angles = None,
torsion_angles = None,
# den = er_params.den_restraints,
adp_individual_iso = None,
adp_individual_aniso = None)
model.set_refinement_flags(rf)
model.get_restraints_manager()

# Geometry file
Expand Down