def helpu():
loop()
print(" I am your assistant")
loop()
print(" Let me tell you what can I do for you")
menuexpl()
time.sleep(10000)
def welcome():
#intial welcome
print(" Hi! I am Pybot")
loop()
#taking user name
while True:
try:
name = input(" What's yours: ")
except ValueError:
pass
else:
if name.isalpha() == True:
print(f" Hi! {name}")
break
else:
print(" I can't get your name")
continue
#fuction call
helpu()
time.sleep(10000)
# here we can get introduced
def test_loop(rerun=0):
#TEST LOOPING OVER PARAMETERS, SAVING TO FOLDER HIERARCHY
#LOADING AND PLOTTING AGGREGATE MEASURES
path=Path('tests/test_loop')
try:
if not os.listdir(path):
rerun=1
except:
rerun =1
if rerun:
#If not already run before
prm={}
prm.update(dftparams)
axes=[
('community_std', [.1,1,10.] ),
('growth_std',[0,1.])
]
loop(path=path,axes=axes,check_key=1,print_msg=1,tsample=.1,**prm )
make_measures(path)
rebuild_filelist(path)
plot_data(path,axes=['community_std','growth_std'],values=['n_biomass'],style='3d',
#split_by=[]
)
def rl_train_fn(args, reporter):
for e in range(args.epochs):
dummy_accuracy = 1 - np.power(1.8, -np.random.uniform(e, 2 * e))
loop(1, training_data_loader)
reporter(epoch=e + 1,
accuracy=dummy_accuracy,
lr=args.lr,
wd=args.wd)
def main_loop() -> None:
environment = base_environment().extend()
def statement_loop(statement_text):
block = parse(statement_text)
expression_stack = MachineExpressionStack([])
interpret(block, expression_stack, environment)
return expression_stack.values
loop(statement_loop)
def test_build_marine_random():
with sc2_env.SC2Env("BuildMarines",
step_mul=step_mul,
game_steps_per_episode=steps * step_mul) as env:
env.observation_spec()
agent = random_agent.RandomAgent()
loop([agent], env, steps)
print agent.reward
def encode():
loop()
#taking input for encoding
text = input("Enter what to be encrypted: ")
text = text + "|||"
# encoding
encoded = base64.b64encode(bytes(text, 'utf-8'))
# writing text in it
encoded_text = open("E:\\PROJ.RC\\python\\pyBot\\enc_files\\enc.txt",
mode='b+a')
encoded_text.write(encoded)
encoded_text.close()
time.sleep(10000)
def encryption():
loop()
while True:
o=input(" How do you want to proceed\n (W)Encrypt text\n (S)Show encrypted text: \n")
if o=='w' or o=='W':
encrypt()
break # tell me more function
elif o=='S' or o=='s':
decrypt()
break #tell me more function
else:
print(" I can't get it")
continue
menu()
time.sleep(10000)
def panel_method(a, b, N, Z):
cz = 0.5 * (Z[1:] + Z[:-1]) # complex midpoint
L = abs(Z[1:] - Z[:-1]) # Panel length
n1 = (-Z.imag[1:] + Z.imag[:-1]) / L # x-comp normal vector
n2 = ( Z.real[1:] - Z.real[:-1]) / L # y-comp normal vector
# P*phi = Q
P = np.zeros( (N, N), order='Fortran' )
Q = np.zeros( (N, 3), order='Fortran' )
# Migrated fortran loop computes the lhs matrix P,
# and the rhs integral for surge, heave and pitch.
P, Q = loop.loop(N, Z, cz, L, n1, n2, P, Q)
# Solve the linear matrix system, P * phi = Q, yields phi on each panel
phi_i = np.linalg.solve(P, Q)
# Added mass.
m11 = np.sum( phi_i[:, 0] * n1 * L )
m22 = np.sum( phi_i[:, 1] * n2 * L )
m12 = np.sum( phi_i[:, 0] * n2 * L )
m66 = np.sum( phi_i[:, 2] * (cz.real*n2 - cz.imag*n1) * L )
return m11, m22, m12, m66
def Ricci__generate_Ccode(Ricci_exprs_list):
Ricci_SymbExpressions = Ricci_exprs_list[0]
print("Generating C code for Ricci tensor (FD_order="+str(FD_order)+") in "+par.parval_from_str("reference_metric::CoordSystem")+" coordinates.")
start = time.time()
# Store original finite-differencing order:
FD_order_orig = par.parval_from_str("finite_difference::FD_CENTDERIVS_ORDER")
# Set new finite-differencing order:
par.set_parval_from_str("finite_difference::FD_CENTDERIVS_ORDER", FD_order)
Ricci_string = fin.FD_outputC("returnstring", Ricci_SymbExpressions,
params="outCverbose=False,SIMD_enable=True,GoldenKernelsEnable=True")
filename = "BSSN_Ricci_FD_order_"+str(FD_order)+".h"
with open(os.path.join(outdir, filename), "w") as file:
file.write(lp.loop(["i2","i1","i0"],["cctk_nghostzones[2]","cctk_nghostzones[1]","cctk_nghostzones[0]"],
["cctk_lsh[2]-cctk_nghostzones[2]","cctk_lsh[1]-cctk_nghostzones[1]","cctk_lsh[0]-cctk_nghostzones[0]"],
["1","1","SIMD_width"],
["#pragma omp parallel for",
"#include \"rfm_files/rfm_struct__SIMD_outer_read2.h\"",
r""" #include "rfm_files/rfm_struct__SIMD_outer_read1.h"
#if (defined __INTEL_COMPILER && __INTEL_COMPILER_BUILD_DATE >= 20180804)
#pragma ivdep // Forces Intel compiler (if Intel compiler used) to ignore certain SIMD vector dependencies
#pragma vector always // Forces Intel compiler (if Intel compiler used) to vectorize
#endif"""],"",
"#include \"rfm_files/rfm_struct__SIMD_inner_read0.h\"\n"+Ricci_string))
# Restore original finite-differencing order:
par.set_parval_from_str("finite_difference::FD_CENTDERIVS_ORDER", FD_order_orig)
end = time.time()
print("(BENCH) Finished Ricci C codegen (FD_order="+str(FD_order)+") in " + str(end - start) + " seconds.")
def panel_method(a, b, N, Z, tau=0.5):
cz = 0.5 * (Z[1:] + Z[:-1]) # complex midpoint
L = abs(Z[1:] - Z[:-1]) # Panel length
n1 = (-Z.imag[1:] + Z.imag[:-1]) / L # x-comp normal vector
n2 = ( Z.real[1:] - Z.real[:-1]) / L # y-comp normal vector
# P*phi = Q
P = np.zeros( (N, N), order='Fortran' )
Q = np.zeros( (N, 3), order='Fortran' )
# Migrated fortran loop computes the lhs matrix P,
# and the rhs integral for surge, heave and pitch.
P, Q = loop.loop(N, Z, cz, L, n1, n2, P, Q)
# Additional term due to porosity
mu = 0.4 # Discharge coeff. (Molin p. 3)
K = (1 - tau) / (mu * tau**2) # Resistance coefficient
#P += 1j * K * Q
# Solve the linear matrix system, P * phi = Q, yields phi on each panel
phi_i = np.linalg.solve(P, Q)
# Added mass.
m11 = np.sum( phi_i[:, 0] * n1 * L )
m22 = np.sum( phi_i[:, 1] * n2 * L )
m12 = np.sum( phi_i[:, 0] * n2 * L )
m66 = np.sum( phi_i[:, 2] * (cz.real*n2 - cz.imag*n1) * L )
return m11, m22, m12, m66
def menu():
loop()
while True:
x = input(
" So what do you want to do: \n (C)Open Calculator\n (E)Encrypted vaults: "
)
if x == "C" or x == "c":
calc()
break
elif x == "E" or x == "e":
encryption()
break
else:
print(" Wrong input")
continue
time.sleep(10000)
def encrypt():
try:
# creating new directory or checking if file exist or not
os.path.exists("E:\\PROJ.RC\\python\\pyBot\\enc_files")
#if file exist if will run except code
except IOError:
#if file exist call encode function
encode()
else:
# otherwise (if there is no exception then it meas that file do not exist so create new file and call encode function)
loop()
print(" Directory does not exist")
os.makedirs("E:\\PROJ.RC\\python\\pyBot\\enc_files")
loop()
print(" Created new file")
encode()
menu()
def enforce_detgammabar_eq_detgammahat__generate_symbolic_expressions_and_C_code(
):
######################################
# START: GENERATE SYMBOLIC EXPRESSIONS
# Enable rfm_precompute infrastructure, which results in
# BSSN RHSs that are free of transcendental functions,
# even in curvilinear coordinates, so long as
# ConformalFactor is set to "W" (default).
par.set_parval_from_str("reference_metric::enable_rfm_precompute",
"True")
par.set_parval_from_str(
"reference_metric::rfm_precompute_Ccode_outdir",
os.path.join(outdir, "rfm_files/"))
import BSSN.Enforce_Detgammabar_Constraint as EGC
enforce_detg_constraint_symb_expressions = EGC.Enforce_Detgammabar_Constraint_symb_expressions(
)
# Now that we are finished with all the rfm hatted
# quantities in generic precomputed functional
# form, let's restore them to their closed-
# form expressions.
par.set_parval_from_str(
"reference_metric::enable_rfm_precompute",
"False") # Reset to False to disable rfm_precompute.
rfm.ref_metric__hatted_quantities()
# END: GENERATE SYMBOLIC EXPRESSIONS
######################################
start = time.time()
print(
"Generating optimized C code (FD_order=" + str(FD_order) +
") for gamma constraint. May take a while, depending on CoordSystem."
)
enforce_gammadet_string = fin.FD_outputC(
"returnstring",
enforce_detg_constraint_symb_expressions,
params="outCverbose=False,preindent=0,includebraces=False")
with open(os.path.join(outdir, "enforcedetgammabar_constraint.h"),
"w") as file:
file.write(
lp.loop(["i2", "i1", "i0"], ["0", "0", "0"],
["cctk_lsh[2]", "cctk_lsh[1]", "cctk_lsh[0]"],
["1", "1", "1"], [
"#pragma omp parallel for",
"#include \"rfm_files/rfm_struct__read2.h\"",
"#include \"rfm_files/rfm_struct__read1.h\""
], "", "#include \"rfm_files/rfm_struct__read0.h\"\n" +
enforce_gammadet_string))
end = time.time()
print("(BENCH) Finished gamma constraint C codegen (FD_order=" +
str(FD_order) + ") in " + str(end - start) + " seconds.")
def boost():
args = request.args
model = pickle.load(open('prediction_model.sav', 'rb'))
out = {}
out['price'] = boost_predict(model, args['model'], args['releaseDate'],
args['maxRes'], args['lowRes'],
args['effPix'], args['zoomW'], args['zoomT'],
args['normalFocus'], args['macroFocus'],
args['storage'], args['weight'],
args['dimension'])[0]
out['sentimentScore'] = loop(videos[args['model']])
return jsonify(out)
def BSSN_RHSs_Ricci__generate_Ccode(which_expressions, all_RHSs_Ricci_exprs_list):
betaU = all_RHSs_Ricci_exprs_list[0]
BSSN_RHSs_SymbExpressions = all_RHSs_Ricci_exprs_list[1]
Ricci_SymbExpressions = all_RHSs_Ricci_exprs_list[2]
if(which_expressions == "BSSN_RHSs"):
print("Generating C code for BSSN RHSs (FD_order="+str(FD_order)+",Tmunu="+str(enable_stress_energy_source_terms)+") in "+par.parval_from_str("reference_metric::CoordSystem")+" coordinates.")
start = time.time()
BSSN_RHSs_string = fin.FD_outputC("returnstring",BSSN_RHSs_SymbExpressions,
params="outCverbose=False,SIMD_enable=True",
upwindcontrolvec=betaU)
with open(os.path.join(outdir,"BSSN_RHSs_FD_order_"+str(FD_order)+"_enable_Tmunu_"+str(enable_stress_energy_source_terms)+".h"), "w") as file:
file.write(lp.loop(["i2","i1","i0"],["cctk_nghostzones[2]","cctk_nghostzones[1]","cctk_nghostzones[0]"],
["cctk_lsh[2]-cctk_nghostzones[2]","cctk_lsh[1]-cctk_nghostzones[1]","cctk_lsh[0]-cctk_nghostzones[0]"],
["1","1","SIMD_width"],
["#pragma omp parallel for",
"#include \"rfm_files/rfm_struct__SIMD_outer_read2.h\"",
"#include \"rfm_files/rfm_struct__SIMD_outer_read1.h\""],"",
"#include \"rfm_files/rfm_struct__SIMD_inner_read0.h\"\n"+BSSN_RHSs_string))
end = time.time()
print("Finished BSSN_RHS C codegen (FD_order="+str(FD_order)+",Tmunu="+str(enable_stress_energy_source_terms)+") in " + str(end - start) + " seconds.")
elif(which_expressions == "Ricci"):
print("Generating C code for Ricci tensor (FD_order="+str(FD_order)+") in "+par.parval_from_str("reference_metric::CoordSystem")+" coordinates.")
start = time.time()
Ricci_string = fin.FD_outputC("returnstring", Ricci_SymbExpressions,
params="outCverbose=False,SIMD_enable=True")
with open(os.path.join(outdir,"BSSN_Ricci_FD_order_"+str(FD_order)+".h"), "w") as file:
file.write(lp.loop(["i2","i1","i0"],["cctk_nghostzones[2]","cctk_nghostzones[1]","cctk_nghostzones[0]"],
["cctk_lsh[2]-cctk_nghostzones[2]","cctk_lsh[1]-cctk_nghostzones[1]","cctk_lsh[0]-cctk_nghostzones[0]"],
["1","1","SIMD_width"],
["#pragma omp parallel for",
"#include \"rfm_files/rfm_struct__SIMD_outer_read2.h\"",
"#include \"rfm_files/rfm_struct__SIMD_outer_read1.h\""],"",
"#include \"rfm_files/rfm_struct__SIMD_inner_read0.h\"\n"+Ricci_string))
end = time.time()
print("Finished Ricci C codegen (FD_order="+str(FD_order)+") in " + str(end - start) + " seconds.")
else:
print("Error: unexpected argument, "+str(which_expressions)+" to BSSN_RHSs_Ricci__generate_Ccode()")
def bfield(P):
B_LAB = np.array([0, 0, 0])
# % The location P is defined as the segment OP, where O is the origin of the
#% laboratory reference frame. The vector is expressed in the Lab reference
#% frame.
oplab = P
#% Iterated over all the loops (ie., lines of the 'CurrentLoops' matrix),
#% and sum the contribution of each loop at the location P
for ii in range(0, cfg.CurrentLoops.shape[0]):
# % Keep data of the Current Loop of index 'ii'
oclab = cfg.CurrentLoops[ii][0:3]
nh = cfg.CurrentLoops[ii][3:6]
I0 = cfg.CurrentLoops[ii][6]
Ra = cfg.CurrentLoops[ii][7]
Nw = cfg.CurrentLoops[ii][8]
# % Rotation matrix
ROT_LAB_LOOP = roto.ROT(nh)
# % Roto-traslation of the P point
variable2 = oplab - oclab
P_LOOP = ROT_LAB_LOOP.dot(variable2)
R = P_LOOP[2]
Z = P_LOOP[1]
# % Field contribution from the current Loop 'ii'
# % (for the analytical solution see Jackson Chap. 5)
Br, Bz = lp.loop(R, Z, I0, Ra, Nw)
# % Magnitude of the magnetic field
variable1 = Br * Br + Bz * Bz
Bnorm = np.sqrt(variable1)
# % B-field vector, expressed in the 'LOOP' reference frame
B_LOOP = [Br, 0.0, Bz]
# % Rotate the b-field in the LAB frame and sum to the
# % the total cumulative vector
B_LAB = B_LAB + ROT_LAB_LOOP.dot(B_LOOP)
return B_LAB
def output_C__MomentumConstraint_h(outdir="BSSN/",
add_T4UUmunu_source_terms=False,
enable_verbose=True):
# Step 0: Check if outdir is string; error out if not.
check_if_string__error_if_not(outdir, "outdir")
# Calling BSSN_constraints() (defined above) computes H and MU:
BSSN_constraints(add_T4UUmunu_source_terms)
if add_T4UUmunu_source_terms == True:
print(
"ERROR: MOMENTUM CONSTRAINT DOES NOT YET ADD T4UUmunu source terms."
)
exit(1)
import time
start = time.time()
if enable_verbose:
print(
"Generating optimized C code for Momentum constraint. May take a while, depending on CoordSystem."
)
MomentumConstraintString = fin.FD_outputC("returnstring", [
lhrh(lhs=gri.gfaccess("aux_gfs", "MU0"), rhs=MU[0]),
lhrh(lhs=gri.gfaccess("aux_gfs", "MU1"), rhs=MU[1]),
lhrh(lhs=gri.gfaccess("aux_gfs", "MU2"), rhs=MU[2])
],
params="outCverbose=False")
end = time.time()
if enable_verbose:
print("Finished in " + str(end - start) + " seconds.")
import loop as lp
with open(outdir + "MomentumConstraint.h", "w") as file:
file.write(
lp.loop(["i2", "i1", "i0"], ["NGHOSTS", "NGHOSTS", "NGHOSTS"], [
"NGHOSTS+Nxx[2]", "NGHOSTS+Nxx[1]", "NGHOSTS+Nxx[0]"
], ["1", "1", "1"], [
"const REAL invdx0 = 1.0/dxx[0];\n" +
"const REAL invdx1 = 1.0/dxx[1];\n" +
"const REAL invdx2 = 1.0/dxx[2];\n" +
"#pragma omp parallel for", " const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "", "const REAL xx0 = xx[0][i0];\n" + MomentumConstraintString))
print("Output C implementation of Momentum constraint to " + outdir +
"MomentumConstraint.h")
def evaluate():
data = request.get_json()
logging.info("data sent for evaluation {}".format(data))
# print(type(data))
result = []
for case in data:
n = case['n']
# cleaning text
patterns = [r'\w+']
for p in patterns:
match = re.findall(p, case['text'])
txt = ''.join(match)
txt = txt.upper()
# encrypting...
answer = loop(txt, n)
result = [""] * len(txt)
# first one
result[0] = txt[0]
txt = txt[1:]
counter = 0
# start encrypting
while "" in result:
for i in range(len(result)):
# result[i] = txt[0]
# txt = txt[1:]
# result divisible by n
if (i + counter) % n == 0:
# empty cell
if result[i] == '':
result[i] = txt[0]
txt = txt[1:]
counter += 1
else:
pass
else:
pass
logging.info("My result :{}".format(''.join(result)))
return json.dumps(result)
def BSSN_constraints__generate_symbolic_expressions_and_C_code():
######################################
# START: GENERATE SYMBOLIC EXPRESSIONS
# Define the Hamiltonian constraint and output the optimized C code.
import BSSN.BSSN_constraints as bssncon
bssncon.BSSN_constraints(add_T4UUmunu_source_terms=False)
if T4UU != None:
import BSSN.BSSN_stress_energy_source_terms as Bsest
Bsest.BSSN_source_terms_for_BSSN_RHSs(T4UU)
Bsest.BSSN_source_terms_for_BSSN_constraints(T4UU)
bssncon.H += Bsest.sourceterm_H
for i in range(3):
bssncon.MU[i] += Bsest.sourceterm_MU[i]
# END: GENERATE SYMBOLIC EXPRESSIONS
######################################
# Store original finite-differencing order:
FD_order_orig = par.parval_from_str("finite_difference::FD_CENTDERIVS_ORDER")
# Set new finite-differencing order:
par.set_parval_from_str("finite_difference::FD_CENTDERIVS_ORDER", FD_order)
start = time.time()
print("Generating optimized C code for Ham. & mom. constraints. May take a while, depending on CoordSystem.")
Ham_mom_string = fin.FD_outputC("returnstring",
[lhrh(lhs=gri.gfaccess("aux_gfs", "H"), rhs=bssncon.H),
lhrh(lhs=gri.gfaccess("aux_gfs", "MU0"), rhs=bssncon.MU[0]),
lhrh(lhs=gri.gfaccess("aux_gfs", "MU1"), rhs=bssncon.MU[1]),
lhrh(lhs=gri.gfaccess("aux_gfs", "MU2"), rhs=bssncon.MU[2])],
params="outCverbose=False")
with open(os.path.join(outdir,"BSSN_constraints_enable_Tmunu_"+str(enable_stress_energy_source_terms)+"_FD_order_"+str(FD_order)+".h"), "w") as file:
file.write(lp.loop(["i2","i1","i0"],["cctk_nghostzones[2]","cctk_nghostzones[1]","cctk_nghostzones[0]"],
["cctk_lsh[2]-cctk_nghostzones[2]","cctk_lsh[1]-cctk_nghostzones[1]","cctk_lsh[0]-cctk_nghostzones[0]"],
["1","1","1"],["#pragma omp parallel for","",""], "", Ham_mom_string))
# Restore original finite-differencing order:
par.set_parval_from_str("finite_difference::FD_CENTDERIVS_ORDER", FD_order_orig)
end = time.time()
print("(BENCH) Finished Hamiltonian & momentum constraint C codegen (FD_order="+str(FD_order)+",Tmunu="+str(enable_stress_energy_source_terms)+") in " + str(end - start) + " seconds.")
def panel_method(a, b, N, Z, tau=0.5, d=1, rho=1, w=1):
#
cz = 0.5 * (Z[1:] + Z[:-1]) # complex midpoint
L = abs(Z[1:] - Z[:-1]) # Panel length
n1 = (-Z.imag[1:] + Z.imag[:-1]) / L # x-comp normal vector
n2 = ( Z.real[1:] - Z.real[:-1]) / L # y-comp normal vector
# Parameters for fluid and porous media
mu = 0.4 # Discharge coefficient (Molin p. 3)
K = (1 - tau) / (mu*tau**2) # Resistance coefficient (Molin p. 3)
KC = d / (2.*a) # Keulegan-Carpenter number
b = 1 / (K * KC) # Porosity coefficient from Chwang
w = 1.0 # Frequency omega
#
theta = np.zeros((N, N), dtype=complex, order='Fortran')
intLog = np.zeros((N, N), dtype=complex, order='Fortran')
A = np.pi * np.eye(2*N, dtype=complex)
B = np.zeros(2*N, dtype=complex, order='Fortran')
#
B = loop.loop(N, Z, cz, L, n1, theta, intLog, A, B, mu, tau, a, d, w, rho)
# Psi and Phi on each panel
Phi = B[:N]
Psi = B[N:]
# Inner and outer potential
phi_e = 0.5 * (Phi + Psi)
phi_i = 0.5 * (Phi - Psi)
# Added mass
m11 = np.sum(phi_e.real * n1 * L) + np.sum(phi_i.real * n1 * L)
# Damping coefficient
b11 = np.sum(phi_e.imag * n1 * L / w) + np.sum(phi_i.imag * n1 * L / w)
return m11, b11
def output_Enforce_Detgammabar_Constraint_Ccode(outdir="BSSN/"):
# Step 0: Check if outdir is string; error out if not.
check_if_string__error_if_not(outdir,"outdir")
enforce_detg_constraint_symb_expressions = Enforce_Detgammabar_Constraint_symb_expressions()
enforce_gammadet_string = fin.FD_outputC("returnstring", enforce_detg_constraint_symb_expressions,
params="outCverbose=False,preindent=0,includebraces=False")
with open(outdir+"enforce_detgammabar_constraint.h", "w") as file:
indent = " "
file.write(
"void enforce_detgammabar_constraint(const int Nxx_plus_2NGHOSTS[3],REAL *xx[3], REAL *in_gfs) {\n\n")
file.write(lp.loop(["i2", "i1", "i0"], ["0", "0", "0"],
["Nxx_plus_2NGHOSTS[2]", "Nxx_plus_2NGHOSTS[1]", "Nxx_plus_2NGHOSTS[0]"],
["1", "1", "1"], ["#pragma omp parallel for",
" const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"], "",
"const REAL xx0 = xx[0][i0];\n" + enforce_gammadet_string))
file.write("}\n")
print("Output C implementation of det(gammabar) constraint to file "+outdir+"enforce_detgammabar_constraint.h")
def output_C__Hamiltonian_h(add_T4UUmunu_source_terms=False,
enable_verbose=True):
# Calling BSSN_constraints() (defined above) computes H and MU:
BSSN_constraints(add_T4UUmunu_source_terms)
import time
start = time.time()
if enable_verbose:
print(
"Generating optimized C code for Hamiltonian constraint. May take a while, depending on CoordSystem."
)
Hamiltonianstring = fin.FD_outputC("returnstring",
lhrh(lhs=gri.gfaccess("aux_gfs", "H"),
rhs=H),
params="outCverbose=False")
end = time.time()
if enable_verbose:
print("Finished in " + str(end - start) + " seconds.")
import loop as lp
with open("BSSN/Hamiltonian.h", "w") as file:
file.write(
lp.loop(["i2", "i1", "i0"], ["NGHOSTS", "NGHOSTS", "NGHOSTS"],
["NGHOSTS+Nxx[2]", "NGHOSTS+Nxx[1]", "NGHOSTS+Nxx[0]"],
["1", "1", "1"], [
"const REAL invdx0 = 1.0/dxx[0];\n" +
"const REAL invdx1 = 1.0/dxx[1];\n" +
"const REAL invdx2 = 1.0/dxx[2];\n" +
"#pragma omp parallel for",
" const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "",
"const REAL xx0 = xx[0][i0];\n" + Hamiltonianstring))
print(
"Output C implementation of Hamiltonian constraint to BSSN/Hamiltonian.h"
)
def decaptcha(filenames):
print("In Progress...")
numChars, codes = loop.loop(filenames)
return (numChars, codes)
def driver_C_codes(Csrcdict,
ThornName,
rhs_list,
evol_gfs_list,
aux_gfs_list,
auxevol_gfs_list,
LapseCondition="OnePlusLog",
enable_stress_energy_source_terms=False):
# First the ETK banner code, proudly showing the NRPy+ banner
import NRPy_logo as logo
outstr = """
#include <stdio.h>
void BaikalETK_Banner()
{
"""
logostr = logo.print_logo(print_to_stdout=False)
outstr += "printf(\"BaikalETK: another Einstein Toolkit thorn generated by\\n\");\n"
for line in logostr.splitlines():
outstr += " printf(\"" + line + "\\n\");\n"
outstr += "}\n"
# Finally add C code string to dictionaries (Python dictionaries are immutable)
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list("Banner.c")] = outstr.replace(
"BaikalETK", ThornName)
# Then the RegisterSlicing() function, needed for other ETK thorns
outstr = """
#include "cctk.h"
#include "Slicing.h"
int BaikalETK_RegisterSlicing (void)
{
Einstein_RegisterSlicing ("BaikalETK");
return 0;
}"""
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"RegisterSlicing.c")] = outstr.replace("BaikalETK", ThornName)
# Next BaikalETK_Symmetry_registration(): Register symmetries
full_gfs_list = []
full_gfs_list.extend(evol_gfs_list)
full_gfs_list.extend(auxevol_gfs_list)
full_gfs_list.extend(aux_gfs_list)
outstr = """
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
#include "Symmetry.h"
void BaikalETK_Symmetry_registration(CCTK_ARGUMENTS)
{
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
// Stores gridfunction parity across x=0, y=0, and z=0 planes, respectively
int sym[3];
// Next register parities for each gridfunction based on its name
// (to ensure this algorithm is robust, gridfunctions with integers
// in their base names are forbidden in NRPy+).
"""
outstr += ""
for gf in full_gfs_list:
# Do not add T4UU gridfunctions if enable_stress_energy_source_terms==False:
if not (enable_stress_energy_source_terms == False and "T4UU" in gf):
outstr += """
// Default to scalar symmetry:
sym[0] = 1; sym[1] = 1; sym[2] = 1;
// Now modify sym[0], sym[1], and/or sym[2] as needed
// to account for gridfunction parity across
// x=0, y=0, and/or z=0 planes, respectively
"""
# If gridfunction name does not end in a digit, by NRPy+ syntax, it must be a scalar
if gf[len(gf) - 1].isdigit() == False:
pass # Scalar = default
elif len(gf) > 2:
# Rank-1 indexed expression (e.g., vector)
if gf[len(gf) - 2].isdigit() == False:
if int(gf[-1]) > 2:
print("Error: Found invalid gridfunction name: " + gf)
sys.exit(1)
symidx = gf[-1]
outstr += " sym[" + symidx + "] = -1;\n"
# Rank-2 indexed expression
elif gf[len(gf) - 2].isdigit() == True:
if len(gf) > 3 and gf[len(gf) - 3].isdigit() == True:
print("Error: Found a Rank-3 or above gridfunction: " +
gf + ", which is at the moment unsupported.")
print("It should be easy to support this if desired.")
sys.exit(1)
symidx0 = gf[-2]
outstr += " sym[" + symidx0 + "] *= -1;\n"
symidx1 = gf[-1]
outstr += " sym[" + symidx1 + "] *= -1;\n"
else:
print(
"Don't know how you got this far with a gridfunction named "
+ gf + ", but I'll take no more of this nonsense.")
print(
" Please follow best-practices and rename your gridfunction to be more descriptive"
)
sys.exit(1)
outstr += " SetCartSymVN(cctkGH, sym, \"BaikalETK::" + gf + "\");\n"
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list("Symmetry_registration_oldCartGrid3D.c")] = \
outstr.replace("BaikalETK",ThornName)
# Next set RHSs to zero
outstr = """
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
#include "Symmetry.h"
void BaikalETK_zero_rhss(CCTK_ARGUMENTS)
{
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
"""
set_rhss_to_zero = ""
for gf in rhs_list:
set_rhss_to_zero += gf + "[CCTK_GFINDEX3D(cctkGH,i0,i1,i2)] = 0.0;\n"
outstr += lp.loop(["i2", "i1", "i0"], ["0", "0", "0"],
["cctk_lsh[2]", "cctk_lsh[1]", "cctk_lsh[0]"],
["1", "1", "1"], [
"#pragma omp parallel for",
"",
"",
], "", set_rhss_to_zero)
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list("zero_rhss.c")] = outstr.replace(
"BaikalETK", ThornName)
# Next registration with the Method of Lines thorn
outstr = """
//--------------------------------------------------------------------------
// Register with the Method of Lines time stepper
// (MoL thorn, found in arrangements/CactusBase/MoL)
// MoL documentation located in arrangements/CactusBase/MoL/doc
//--------------------------------------------------------------------------
#include <stdio.h>
#include "cctk.h"
#include "cctk_Parameters.h"
#include "cctk_Arguments.h"
#include "Symmetry.h"
void BaikalETK_MoL_registration(CCTK_ARGUMENTS)
{
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
CCTK_INT ierr = 0, group, rhs;
// Register evolution & RHS gridfunction groups with MoL, so it knows
group = CCTK_GroupIndex("BaikalETK::evol_variables");
rhs = CCTK_GroupIndex("BaikalETK::evol_variables_rhs");
ierr += MoLRegisterEvolvedGroup(group, rhs);
if (ierr) CCTK_ERROR("Problems registering with MoL");
}
"""
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"MoL_registration.c")] = outstr.replace("BaikalETK", ThornName)
# Next register with the boundary conditions thorns.
# PART 1: Set BC type to "none" for all variables
# Since we choose NewRad boundary conditions, we must register all
# gridfunctions to have boundary type "none". This is because
# NewRad is seen by the rest of the Toolkit as a modification to the
# RHSs.
# This code is based on Kranc's McLachlan/ML_BSSN/src/Boundaries.cc code.
outstr = """
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
#include "cctk_Faces.h"
#include "util_Table.h"
#include "Symmetry.h"
// Set `none` boundary conditions on BSSN RHSs, as these are set via NewRad.
void BaikalETK_BoundaryConditions_evolved_gfs(CCTK_ARGUMENTS)
{
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
CCTK_INT ierr CCTK_ATTRIBUTE_UNUSED = 0;
"""
for gf in evol_gfs_list:
outstr += """
ierr = Boundary_SelectVarForBC(cctkGH, CCTK_ALL_FACES, 1, -1, "BaikalETK::""" + gf + """", "none");
if (ierr < 0) CCTK_ERROR("Failed to register BC for BaikalETK::""" + gf + """!");
"""
outstr += """
}
// Set `flat` boundary conditions on BSSN constraints, similar to what Lean does.
void BaikalETK_BoundaryConditions_aux_gfs(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
CCTK_INT ierr CCTK_ATTRIBUTE_UNUSED = 0;
"""
for gf in aux_gfs_list:
outstr += """
ierr = Boundary_SelectVarForBC(cctkGH, CCTK_ALL_FACES, cctk_nghostzones[0], -1, "BaikalETK::""" + gf + """", "flat");
if (ierr < 0) CCTK_ERROR("Failed to register BC for BaikalETK::""" + gf + """!");
"""
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"BoundaryConditions.c")] = outstr.replace("BaikalETK", ThornName)
# PART 2: Set C code for calling NewRad BCs
# As explained in lean_public/LeanBSSNMoL/src/calc_bssn_rhs.F90,
# the function NewRad_Apply takes the following arguments:
# NewRad_Apply(cctkGH, var, rhs, var0, v0, radpower),
# which implement the boundary condition:
# var = var_at_infinite_r + u(r-var_char_speed*t)/r^var_radpower
# Obviously for var_radpower>0, var_at_infinite_r is the value of
# the variable at r->infinity. var_char_speed is the propagation
# speed at the outer boundary, and var_radpower is the radial
# falloff rate.
outstr = """
#include <math.h>
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_NewRad(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
"""
for gf in evol_gfs_list:
var_at_infinite_r = "0.0"
var_char_speed = "1.0"
var_radpower = "1.0"
if gf == "alpha":
var_at_infinite_r = "1.0"
if LapseCondition == "OnePlusLog":
var_char_speed = "sqrt(2.0)"
else:
pass # 1.0 (default) is fine
if "aDD" in gf or "trK" in gf: # consistent with Lean code.
var_radpower = "2.0"
outstr += " NewRad_Apply(cctkGH, " + gf + ", " + gf.replace(
"GF", ""
) + "_rhsGF, " + var_at_infinite_r + ", " + var_char_speed + ", " + var_radpower + ");\n"
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"BoundaryCondition_NewRad.c")] = outstr.replace(
"BaikalETK", ThornName)
# First we convert from ADM to BSSN, as is required to convert initial data
# (given using) ADM quantities, to the BSSN evolved variables
import BSSN.ADM_Numerical_Spherical_or_Cartesian_to_BSSNCurvilinear as atob
IDhDD,IDaDD,IDtrK,IDvetU,IDbetU,IDalpha,IDcf,IDlambdaU = \
atob.Convert_Spherical_or_Cartesian_ADM_to_BSSN_curvilinear("Cartesian","DoNotOutputADMInputFunction",os.path.join(ThornName,"src"))
# Store the original list of registered gridfunctions; we'll want to unregister
# all the *SphorCart* gridfunctions after we're finished with them below.
orig_glb_gridfcs_list = []
for gf in gri.glb_gridfcs_list:
orig_glb_gridfcs_list.append(gf)
alphaSphorCart = gri.register_gridfunctions("AUXEVOL", "alphaSphorCart")
betaSphorCartU = ixp.register_gridfunctions_for_single_rank1(
"AUXEVOL", "betaSphorCartU")
BSphorCartU = ixp.register_gridfunctions_for_single_rank1(
"AUXEVOL", "BSphorCartU")
gammaSphorCartDD = ixp.register_gridfunctions_for_single_rank2(
"AUXEVOL", "gammaSphorCartDD", "sym01")
KSphorCartDD = ixp.register_gridfunctions_for_single_rank2(
"AUXEVOL", "KSphorCartDD", "sym01")
# ADM to BSSN conversion, used for converting ADM initial data into a form readable by this thorn.
# ADM to BSSN, Part 1: Set up function call and pointers to ADM gridfunctions
outstr = """
#include <math.h>
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_ADM_to_BSSN(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
CCTK_REAL *alphaSphorCartGF = alp;
"""
# It's ugly if we output code in the following ordering, so we'll first
# output to a string and then sort the string to beautify the code a bit.
outstrtmp = []
for i in range(3):
outstrtmp.append(" CCTK_REAL *betaSphorCartU" + str(i) +
"GF = beta" + chr(ord('x') + i) + ";\n")
outstrtmp.append(" CCTK_REAL *BSphorCartU" + str(i) +
"GF = dtbeta" + chr(ord('x') + i) + ";\n")
for j in range(i, 3):
outstrtmp.append(" CCTK_REAL *gammaSphorCartDD" + str(i) +
str(j) + "GF = g" + chr(ord('x') + i) +
chr(ord('x') + j) + ";\n")
outstrtmp.append(" CCTK_REAL *KSphorCartDD" + str(i) + str(j) +
"GF = k" + chr(ord('x') + i) + chr(ord('x') + j) +
";\n")
outstrtmp.sort()
for line in outstrtmp:
outstr += line
# ADM to BSSN, Part 2: Set up ADM to BSSN conversions for BSSN gridfunctions that do not require
# finite-difference derivatives (i.e., all gridfunctions except lambda^i (=Gamma^i
# in non-covariant BSSN)):
# h_{ij}, a_{ij}, trK, vet^i=beta^i,bet^i=B^i, cf (conformal factor), and alpha
all_but_lambdaU_expressions = [
lhrh(lhs=gri.gfaccess("in_gfs", "hDD00"), rhs=IDhDD[0][0]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD01"), rhs=IDhDD[0][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD02"), rhs=IDhDD[0][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD11"), rhs=IDhDD[1][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD12"), rhs=IDhDD[1][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD22"), rhs=IDhDD[2][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "aDD00"), rhs=IDaDD[0][0]),
lhrh(lhs=gri.gfaccess("in_gfs", "aDD01"), rhs=IDaDD[0][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "aDD02"), rhs=IDaDD[0][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "aDD11"), rhs=IDaDD[1][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "aDD12"), rhs=IDaDD[1][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "aDD22"), rhs=IDaDD[2][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "trK"), rhs=IDtrK),
lhrh(lhs=gri.gfaccess("in_gfs", "vetU0"), rhs=IDvetU[0]),
lhrh(lhs=gri.gfaccess("in_gfs", "vetU1"), rhs=IDvetU[1]),
lhrh(lhs=gri.gfaccess("in_gfs", "vetU2"), rhs=IDvetU[2]),
lhrh(lhs=gri.gfaccess("in_gfs", "betU0"), rhs=IDbetU[0]),
lhrh(lhs=gri.gfaccess("in_gfs", "betU1"), rhs=IDbetU[1]),
lhrh(lhs=gri.gfaccess("in_gfs", "betU2"), rhs=IDbetU[2]),
lhrh(lhs=gri.gfaccess("in_gfs", "alpha"), rhs=IDalpha),
lhrh(lhs=gri.gfaccess("in_gfs", "cf"), rhs=IDcf)
]
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
all_but_lambdaU_outC = fin.FD_outputC("returnstring",
all_but_lambdaU_expressions,
outCparams)
outstr += lp.loop(["i2", "i1", "i0"], ["0", "0", "0"],
["cctk_lsh[2]", "cctk_lsh[1]", "cctk_lsh[0]"],
["1", "1", "1"], ["#pragma omp parallel for", "", ""],
" ", all_but_lambdaU_outC)
# ADM to BSSN, Part 3: Set up ADM to BSSN conversions for BSSN gridfunctions defined from
# finite-difference derivatives: lambda^i, which is Gamma^i in non-covariant BSSN):
outstr += """
const CCTK_REAL invdx0 = 1.0/CCTK_DELTA_SPACE(0);
const CCTK_REAL invdx1 = 1.0/CCTK_DELTA_SPACE(1);
const CCTK_REAL invdx2 = 1.0/CCTK_DELTA_SPACE(2);
"""
path = os.path.join(ThornName, "src")
BSSN_RHS_FD_orders_output = []
for root, dirs, files in os.walk(path):
for file in files:
if "BSSN_RHSs_FD_order" in file:
array = file.replace(".", "_").split("_")
BSSN_RHS_FD_orders_output.append(int(array[4]))
for current_FD_order in BSSN_RHS_FD_orders_output:
# Store original finite-differencing order:
orig_FD_order = par.parval_from_str(
"finite_difference::FD_CENTDERIVS_ORDER")
# Set new finite-differencing order:
par.set_parval_from_str("finite_difference::FD_CENTDERIVS_ORDER",
current_FD_order)
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
lambdaU_expressions = [
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU0"), rhs=IDlambdaU[0]),
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU1"), rhs=IDlambdaU[1]),
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU2"), rhs=IDlambdaU[2])
]
lambdaU_expressions_FDout = fin.FD_outputC("returnstring",
lambdaU_expressions,
outCparams)
lambdafile = "ADM_to_BSSN__compute_lambdaU_FD_order_" + str(
current_FD_order) + ".h"
with open(os.path.join(ThornName, "src", lambdafile), "w") as file:
file.write(
lp.loop(["i2", "i1", "i0"], [
"cctk_nghostzones[2]", "cctk_nghostzones[1]",
"cctk_nghostzones[0]"
], [
"cctk_lsh[2]-cctk_nghostzones[2]",
"cctk_lsh[1]-cctk_nghostzones[1]",
"cctk_lsh[0]-cctk_nghostzones[0]"
], ["1", "1", "1"], ["#pragma omp parallel for", "", ""], "",
lambdaU_expressions_FDout))
outstr += " if(FD_order == " + str(current_FD_order) + ") {\n"
outstr += " #include \"" + lambdafile + "\"\n"
outstr += " }\n"
# Restore original FD order
par.set_parval_from_str("finite_difference::FD_CENTDERIVS_ORDER",
orig_FD_order)
outstr += """
ExtrapolateGammas(cctkGH,lambdaU0GF);
ExtrapolateGammas(cctkGH,lambdaU1GF);
ExtrapolateGammas(cctkGH,lambdaU2GF);
}
"""
# Unregister the *SphorCartGF's.
gri.glb_gridfcs_list = orig_glb_gridfcs_list
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list("ADM_to_BSSN.c")] = outstr.replace(
"BaikalETK", ThornName)
import BSSN.ADM_in_terms_of_BSSN as btoa
import BSSN.BSSN_quantities as Bq
btoa.ADM_in_terms_of_BSSN()
Bq.BSSN_basic_tensors() # Gives us betaU & BU
outstr = """
#include <math.h>
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_BSSN_to_ADM(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
"""
btoa_lhrh = []
for i in range(3):
for j in range(i, 3):
btoa_lhrh.append(
lhrh(lhs="g" + chr(ord('x') + i) + chr(ord('x') + j) +
"[CCTK_GFINDEX3D(cctkGH,i0,i1,i2)]",
rhs=btoa.gammaDD[i][j]))
for i in range(3):
for j in range(i, 3):
btoa_lhrh.append(
lhrh(lhs="k" + chr(ord('x') + i) + chr(ord('x') + j) +
"[CCTK_GFINDEX3D(cctkGH,i0,i1,i2)]",
rhs=btoa.KDD[i][j]))
btoa_lhrh.append(
lhrh(lhs="alp[CCTK_GFINDEX3D(cctkGH,i0,i1,i2)]", rhs=Bq.alpha))
for i in range(3):
btoa_lhrh.append(
lhrh(lhs="beta" + chr(ord('x') + i) +
"[CCTK_GFINDEX3D(cctkGH,i0,i1,i2)]",
rhs=Bq.betaU[i]))
for i in range(3):
btoa_lhrh.append(
lhrh(lhs="dtbeta" + chr(ord('x') + i) +
"[CCTK_GFINDEX3D(cctkGH,i0,i1,i2)]",
rhs=Bq.BU[i]))
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
bssn_to_adm_Ccode = fin.FD_outputC("returnstring", btoa_lhrh, outCparams)
outstr += lp.loop(["i2", "i1", "i0"], ["0", "0", "0"],
["cctk_lsh[2]", "cctk_lsh[1]", "cctk_lsh[0]"],
["1", "1", "1"], ["#pragma omp parallel for", "", ""],
"", bssn_to_adm_Ccode)
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list("BSSN_to_ADM.c")] = outstr.replace(
"BaikalETK", ThornName)
# Next, the driver for computing the Ricci tensor:
outstr = """
#include <math.h>
#include "SIMD/SIMD_intrinsics.h"
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_driver_pt1_BSSN_Ricci(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
const CCTK_INT *FD_order = CCTK_ParameterGet("FD_order","BaikalETK",NULL);
const CCTK_REAL NOSIMDinvdx0 = 1.0/CCTK_DELTA_SPACE(0);
const REAL_SIMD_ARRAY invdx0 = ConstSIMD(NOSIMDinvdx0);
const CCTK_REAL NOSIMDinvdx1 = 1.0/CCTK_DELTA_SPACE(1);
const REAL_SIMD_ARRAY invdx1 = ConstSIMD(NOSIMDinvdx1);
const CCTK_REAL NOSIMDinvdx2 = 1.0/CCTK_DELTA_SPACE(2);
const REAL_SIMD_ARRAY invdx2 = ConstSIMD(NOSIMDinvdx2);
"""
path = os.path.join(ThornName, "src")
for root, dirs, files in os.walk(path):
for file in files:
if "BSSN_Ricci_FD_order" in file:
array = file.replace(".", "_").split("_")
outstr += " if(*FD_order == " + str(array[4]) + ") {\n"
outstr += " #include \"" + file + "\"\n"
outstr += " }\n"
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"driver_pt1_BSSN_Ricci.c")] = outstr.replace("BaikalETK", ThornName)
def SIMD_declare_C_params():
SIMD_declare_C_params_str = ""
for i in range(len(par.glb_Cparams_list)):
# keep_param is a boolean indicating whether we should accept or reject
# the parameter. singleparstring will contain the string indicating
# the variable type.
keep_param, singleparstring = ccl.keep_param__return_type(
par.glb_Cparams_list[i])
if (keep_param) and ("CCTK_REAL" in singleparstring):
parname = par.glb_Cparams_list[i].parname
SIMD_declare_C_params_str += " const "+singleparstring + "*NOSIMD"+parname+\
" = CCTK_ParameterGet(\""+parname+"\",\"BaikalETK\",NULL);\n"
SIMD_declare_C_params_str += " const REAL_SIMD_ARRAY " + parname + " = ConstSIMD(*NOSIMD" + parname + ");\n"
return SIMD_declare_C_params_str
# Next, the driver for computing the BSSN RHSs:
outstr = """
#include <math.h>
#include "SIMD/SIMD_intrinsics.h"
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_driver_pt2_BSSN_RHSs(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
const CCTK_INT *FD_order = CCTK_ParameterGet("FD_order","BaikalETK",NULL);
const CCTK_REAL NOSIMDinvdx0 = 1.0/CCTK_DELTA_SPACE(0);
const REAL_SIMD_ARRAY invdx0 = ConstSIMD(NOSIMDinvdx0);
const CCTK_REAL NOSIMDinvdx1 = 1.0/CCTK_DELTA_SPACE(1);
const REAL_SIMD_ARRAY invdx1 = ConstSIMD(NOSIMDinvdx1);
const CCTK_REAL NOSIMDinvdx2 = 1.0/CCTK_DELTA_SPACE(2);
const REAL_SIMD_ARRAY invdx2 = ConstSIMD(NOSIMDinvdx2);
""" + SIMD_declare_C_params()
path = os.path.join(ThornName, "src")
for root, dirs, files in os.walk(path):
for file in files:
if "BSSN_RHSs_FD_order" in file:
array = file.replace(".", "_").split("_")
outstr += " if(*FD_order == " + str(array[4]) + ") {\n"
outstr += " #include \"" + file + "\"\n"
outstr += " }\n"
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"driver_pt2_BSSN_RHSs.c")] = outstr.replace("BaikalETK", ThornName)
# Next, the driver for enforcing detgammabar = detgammahat constraint:
outstr = """
#include <math.h>
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_enforce_detgammabar_constraint(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
"""
path = os.path.join(ThornName, "src")
for root, dirs, files in os.walk(path):
for file in files:
if "enforcedetgammabar_constraint_FD_order" in file:
array = file.replace(".", "_").split("_")
outstr += " if(FD_order == " + str(array[4]) + ") {\n"
outstr += " #include \"" + file + "\"\n"
outstr += " }\n"
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list("driver_enforcedetgammabar_constraint.c")] = \
outstr.replace("BaikalETK",ThornName)
# Next, the driver for computing the BSSN Hamiltonian & momentum constraints
outstr = """
#include <math.h>
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
void BaikalETK_BSSN_constraints(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
const CCTK_REAL invdx0 = 1.0/CCTK_DELTA_SPACE(0);
const CCTK_REAL invdx1 = 1.0/CCTK_DELTA_SPACE(1);
const CCTK_REAL invdx2 = 1.0/CCTK_DELTA_SPACE(2);
"""
path = os.path.join(ThornName, "src")
for root, dirs, files in os.walk(path):
for file in files:
if "BSSN_constraints_FD_order" in file:
array = file.replace(".", "_").split("_")
outstr += " if(FD_order == " + str(array[4]) + ") {\n"
outstr += " #include \"" + file + "\"\n"
outstr += " }\n"
outstr += "}\n"
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"driver_BSSN_constraints.c")] = outstr.replace("BaikalETK", ThornName)
if enable_stress_energy_source_terms == True:
# Declare T4DD as a set of gridfunctions. These won't
# actually appear in interface.ccl, as interface.ccl
# was set above. Thus before calling the code output
# by FD_outputC(), we'll have to set pointers
# to the actual gridfunctions they reference.
# (In this case the eTab's.)
T4DD = ixp.register_gridfunctions_for_single_rank2("AUXEVOL",
"T4DD",
"sym01",
DIM=4)
import BSSN.ADMBSSN_tofrom_4metric as AB4m
AB4m.g4UU_ito_BSSN_or_ADM("BSSN")
T4UUraised = ixp.zerorank2(DIM=4)
for mu in range(4):
for nu in range(4):
for delta in range(4):
for gamma in range(4):
T4UUraised[mu][nu] += AB4m.g4UU[mu][delta] * AB4m.g4UU[
nu][gamma] * T4DD[delta][gamma]
T4UU_expressions = [
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU00"), rhs=T4UUraised[0][0]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU01"), rhs=T4UUraised[0][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU02"), rhs=T4UUraised[0][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU03"), rhs=T4UUraised[0][3]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU11"), rhs=T4UUraised[1][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU12"), rhs=T4UUraised[1][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU13"), rhs=T4UUraised[1][3]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU22"), rhs=T4UUraised[2][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU23"), rhs=T4UUraised[2][3]),
lhrh(lhs=gri.gfaccess("in_gfs", "T4UU33"), rhs=T4UUraised[3][3])
]
outCparams = "outCverbose=False,includebraces=False,preindent=2,SIMD_enable=True"
T4UUstr = fin.FD_outputC("returnstring", T4UU_expressions, outCparams)
T4UUstr_loop = lp.loop(["i2", "i1", "i0"], ["0", "0", "0"],
["cctk_lsh[2]", "cctk_lsh[1]", "cctk_lsh[0]"],
["1", "1", "SIMD_width"],
["#pragma omp parallel for", "", ""], "",
T4UUstr)
outstr = """
#include <math.h>
#include "cctk.h"
#include "cctk_Arguments.h"
#include "cctk_Parameters.h"
#include "SIMD/SIMD_intrinsics.h"
void BaikalETK_driver_BSSN_T4UU(CCTK_ARGUMENTS) {
DECLARE_CCTK_ARGUMENTS;
DECLARE_CCTK_PARAMETERS;
const CCTK_REAL *restrict T4DD00GF = eTtt;
const CCTK_REAL *restrict T4DD01GF = eTtx;
const CCTK_REAL *restrict T4DD02GF = eTty;
const CCTK_REAL *restrict T4DD03GF = eTtz;
const CCTK_REAL *restrict T4DD11GF = eTxx;
const CCTK_REAL *restrict T4DD12GF = eTxy;
const CCTK_REAL *restrict T4DD13GF = eTxz;
const CCTK_REAL *restrict T4DD22GF = eTyy;
const CCTK_REAL *restrict T4DD23GF = eTyz;
const CCTK_REAL *restrict T4DD33GF = eTzz;
""" + T4UUstr_loop + """
}\n"""
# Add C code string to dictionary (Python dictionaries are immutable)
Csrcdict[append_to_make_code_defn_list(
"driver_BSSN_T4UU.c")] = outstr.replace("BaikalETK", ThornName)
'id1': id1,
'class0': class0,
'class1': class1
})
snapshots = []
start_time = links[0]['time']
end_time = links[len(links)-1]['time']
flag = 0
link_number = 0
interval_time = 360
snapshot_time = 3600
while start_time + flag * interval_time - interval_time <= end_time - snapshot_time:
if link_number >= len(links):
break
link_graph, link_number = loop(links, link_number, start_time, flag, interval_time, snapshot_time)
snapshots.append(link_graph)
flag += 1
nodes = Nodes(snapshots)
graphs = []
graphs_nodes = []
for snapshot in snapshots:
graph, graph_nodes = network(snapshot, nodes)
graphs.append(graph)
graphs_nodes.append(graph_nodes)
vectors = []
for num in range(len(graphs)):
vector = matrix(graphs, num)
vectors.append(vector)
import loop
# Are we on the right host machine?
hostname = socket.gethostname()
if not ("psexport" in hostname or "login" == hostname):
sys.exit("ERROR: Cannot submit jobs from this host. You are logged in to %s but you need to be logged in to psexport or davinci (login node) to submit jobs to the queue." % hostname)
# Read configuration
if len(sys.argv) < 2:
sys.exit("Usage: cheman_server.py cheman_server.cfg")
#debug = False
#if len(sys.argv) >= 3:
# if sys.argv[2] == "DEBUG":
# debug = True
configfilename = sys.argv[1]
#print "Gmail login"
#email = raw_input("Email address: ")
#password = getpass.getpass("Password: "******"WARNING: loop() crashed, restarting..."
#this is the size of the chunks which are used for faster scene loading
const.CHUNK_SIZE = 40
#odds WHO doctors will spawn
# for example: 10 will give one in ten
const.WHO_ODDS = 100
const.NOG_ODDS = 10
#getting the users home directory
from os.path import expanduser
const.HOME = expanduser("~")
##############################################
gameloop = loop.loop()
if __name__=="__main__":
gameloop.run()
geigerPower = pyb.Pin('Y9', pyb.Pin.OUT_PP) #relay for power geiger
geigerPower.high() #turn off
geigerIn = pyb.Pin('Y10', pyb.Pin.IN)
#pitido inicial en salida Y8
tim12 = pyb.Timer(12, freq=3500)
ch2=tim12.channel(2, pyb.Timer.PWM, pin=pyb.Pin.board.Y8, pulse_width=12000)
pyb.delay(100) #in msecs
ch2.pulse_width(0)
#uart6 a wixel, pins Y1 y Y2
uart = UART(6,9600)
uart.init(9600,bits=8,stop=1,parity=None)
pyb.repl_uart(uart)
#initalize fram
fr = fram.fram()
frt = fram_t.fram_t(fr)
#rtc
rtc = pyb.RTC()
#initialize am2302
a = am2302.am2302(ch2, frt)
#initialize loop
l = loop.loop(geigerPower, a, fr, frt, ch2, uart, wixel)
#initialize commands
cms = commands.commands(rtc, fr, frt)
import getpass
import loop
# Are we on the right host machine?
hostname = socket.gethostname()
if not ("psexport" in hostname or "login" == hostname):
sys.exit("ERROR: Cannot submit jobs from this host. You are logged in to %s but you need to be logged in to psexport or davinci (login node) to simultaneously submit jobs to the queue and communicate with the google spreadsheet." % hostname)
# Read configuration
if len(sys.argv) < 2:
sys.exit("Usage: cheetah_manager.py cheetah_manager.cfg")
debug = False
if len(sys.argv) >= 3:
if sys.argv[2] == "DEBUG":
debug = True
configfilename = sys.argv[1]
print "Gmail login"
password = getpass.getpass()
if debug:
loop.loop(configfilename,password)
else:
while True:
try:
loop.loop(configfilename,password)
except:
print "WARNING: loop() crashed, restarting..."
def run_loops_generation(self):
ranks = list(set(map(lambda x: x.rank, self.callstacks)))
# First one loop per rank is done. After the generation step, the
# rank merge step is done.
#
ranks_loops=[]
# If aliasing is detected, every subloop will be an independent loop
# object. After generation, the cluster is divided into sub-clusters
#
ranks_subloops=[]
loops_id = 0
for rank in ranks:
callstacks = list(filter(lambda x: x.rank == rank, self.callstacks))
# Trying to remove aliasing by a new clustering dimension...
# On that case, just code after the "else" is needed
aliasing_detector=tmatrix.from_callstacks_obj(callstacks)
if aliasing_detector.aliased():
callstack_parts = aliasing_detector.get_subloops()
subloops = []
for x in callstack_parts:
new_loop = loop(callstacks=x,id=loops_id)
new_loop.cluster_id = self.cluster_id
subloops.append(new_loop)
loops_id += 1
ranks_subloops.append(subloops)
else:
new_loop = loop(callstacks=callstacks, id=loops_id)
new_loop.cluster_id = self.cluster_id
ranks_loops.append(new_loop)
loops_id += 1
if len(ranks_loops) > 0:
self.loops.append(self.__ranks_level_merge(ranks_loops))
self.nloops = 1
elif len(ranks_subloops) > 0:
# Here i am assuming that all subloops of all ranks are related
# between them in function of the order they appear in the ranks_
# subloop.
# ranks_subloops = [ [loop1.1, loop1.2, loop1.3],
# [loop2.1, loop2.2, loop2.3]]
# | | |
# merged merged merged
ssubloops = []
nsubloops = 0
for i in range(len(max(ranks_subloops))):
loops_to_merge = []
for subloops in ranks_subloops:
if len(subloops) > i: loops_to_merge.append(subloops[i])
merged_ranks_loop = self.__ranks_level_merge(loops_to_merge)
ssubloops.append(merged_ranks_loop)
nsubloops += 1
# self.loops.append(merged_ranks_loop)
# self.nloops += 1
if aliasing_detector.is_hidden_superloop():
superloop = loop(callstacks=[], id=-1) # Void loop
superloop.cluster_id = self.cluster_id
superloop.iterations = aliasing_detector\
.get_hidden_superloop_its()
superloop.original_iterations = superloop.iterations
superloop.set_hidden_loop()
logging.debug("Cluster {0}: Superloop detected ({1} its)"
.format(self.cluster_id, superloop.iterations))
for sl in ssubloops:
superloop.merge_with_subloop(sl)
self.loops.append(superloop)
self.nloops = 1
else:
self.loops.extend(ssubloops)
self.nloops = nsubloops
else:
assert False, "Not managed situation."
self.loops_generation_done = True
const.OFFSET_X = 0
const.OFFSET_Y = 0
#this is the size of the screen in tiles, by multiplying LENGTH with SCALE you get the total screen size in pixels
#I forget why I have LENGTH WIDE X/Y, marked for removal
const.LENGTH_X = 40
const.LENGTH_Y = 30
const.LARGE_X = const.SCALE * LENGTH_X
const.LARGE_Y = const.SCALE * LENGHT_Y
#this is the size of the chunks which are used for faster scene loading
const.CHUNK_SIZE = 40
#odds WHO doctors will spawn
# for example: 10 will give one in ten
const.WHO_ODDS = 100
const.NOG_ODDS = 10
#getting the users home directory
from os.path import expanduser
const.HOME = expanduser("~")
##############################################
gameloop = loop.loop()
if __name__ == "__main__":
gameloop.run()
def Tmunu_Numerical_Spherical_or_Cartesian_to_BSSNCurvilinear(
CoordType_in, Tmunu_input_function_name, pointer_to_ID_inputs=False):
# The ADM & BSSN formalisms only work in 3D; they are 3+1 decompositions of Einstein's equations.
# To implement axisymmetry or spherical symmetry, simply set all spatial derivatives in
# the relevant angular directions to zero; DO NOT SET DIM TO ANYTHING BUT 3.
# Step 0: Set spatial dimension (must be 3 for BSSN)
DIM = 3
# Step 1: Define the input variables: the 4D stress-energy tensor, and the ADM 3-metric, lapse, & shift:
T4SphorCartUU = ixp.declarerank2("T4SphorCartUU", "sym01", DIM=4)
gammaSphorCartDD = ixp.declarerank2("gammaSphorCartDD", "sym01")
alphaSphorCart = sp.symbols("alphaSphorCart")
betaSphorCartU = ixp.declarerank1("betaSphorCartU")
# Step 2: All Tmunu initial data quantities are functions of xx0,xx1,xx2, but
# in the Spherical or Cartesian basis.
# We first define the BSSN stress-energy source terms in the Spherical
# or Cartesian basis, respectively.
# To get \gamma_{\mu \nu} = gammabar4DD[mu][nu], we'll need to construct the 4-metric, using Eq. 2.122 in B&S:
# S_{ij} = \gamma_{i \mu} \gamma_{j \nu} T^{\mu \nu}
# S_{i} = -\gamma_{i\mu} n_\nu T^{\mu\nu}
# S = \gamma^{ij} S_{ij}
# rho = n_\mu n_\nu T^{\mu\nu},
# where
# \gamma_{\mu\nu} = g_{\mu\nu} + n_\mu n_\nu
# and
# n_mu = {-\alpha,0,0,0},
# Step 2.1: Construct the 4-metric based on the input ADM quantities.
# This is provided by Eq 4.47 in [Gourgoulhon](https://arxiv.org/pdf/gr-qc/0703035.pdf):
# g_{tt} = -\alpha^2 + \beta^k \beta_k
# g_{ti} = \beta_i
# g_{ij} = \gamma_{ij}
# Eq. 2.121 in B&S
betaSphorCartD = ixp.zerorank1()
for i in range(DIM):
for j in range(DIM):
betaSphorCartD[i] += gammaSphorCartDD[i][j] * betaSphorCartU[j]
# Now compute the beta contraction.
beta2 = sp.sympify(0)
for i in range(DIM):
beta2 += betaSphorCartU[i] * betaSphorCartD[i]
# Eq. 2.122 in B&S
g4SphorCartDD = ixp.zerorank2(DIM=4)
g4SphorCartDD[0][0] = -alphaSphorCart**2 + beta2
for i in range(DIM):
g4SphorCartDD[i + 1][0] = g4SphorCartDD[0][i + 1] = betaSphorCartD[i]
for i in range(DIM):
for j in range(DIM):
g4SphorCartDD[i + 1][j + 1] = gammaSphorCartDD[i][j]
# Step 2.2: Construct \gamma_{mu nu} = g_{mu nu} + n_mu n_nu:
n4SphorCartD = ixp.zerorank1(DIM=4)
n4SphorCartD[0] = -alphaSphorCart
gamma4SphorCartDD = ixp.zerorank2(DIM=4)
for mu in range(4):
for nu in range(4):
gamma4SphorCartDD[mu][nu] = g4SphorCartDD[mu][
nu] + n4SphorCartD[mu] * n4SphorCartD[nu]
# Step 2.3: We now have all we need to construct the BSSN source
# terms in the current basis (Spherical or Cartesian):
# S_{ij} = \gamma_{i \mu} \gamma_{j \nu} T^{\mu \nu}
# S_{i} = -\gamma_{i\mu} n_\nu T^{\mu\nu}
# S = \gamma^{ij} S_{ij}
# rho = n_\mu n_\nu T^{\mu\nu},
SSphorCartDD = ixp.zerorank2()
SSphorCartD = ixp.zerorank1()
SSphorCart = sp.sympify(0)
rhoSphorCart = sp.sympify(0)
for i in range(DIM):
for j in range(DIM):
for mu in range(4):
for nu in range(4):
SSphorCartDD[i][j] += gamma4SphorCartDD[
i + 1][mu] * gamma4SphorCartDD[
j + 1][nu] * T4SphorCartUU[mu][nu]
for i in range(DIM):
for mu in range(4):
for nu in range(4):
SSphorCartD[i] += -gamma4SphorCartDD[
i + 1][mu] * n4SphorCartD[nu] * T4SphorCartUU[mu][nu]
gammaSphorCartUU, gammaDET = ixp.symm_matrix_inverter3x3(gammaSphorCartDD)
for i in range(DIM):
for j in range(DIM):
SSphorCart += gammaSphorCartUU[i][j] * SSphorCartDD[i][j]
for mu in range(4):
for nu in range(4):
rhoSphorCart += n4SphorCartD[mu] * n4SphorCartD[
nu] * T4SphorCartUU[mu][nu]
# Step 3: Perform basis conversion to
# Make sure that rfm.reference_metric() has been called.
# We'll need the variables it defines throughout this module.
if rfm.have_already_called_reference_metric_function == False:
print(
"Error. Called Tmunu_Numerical_Spherical_or_Cartesian_to_BSSNCurvilinear() without"
)
print(
" first setting up reference metric, by calling rfm.reference_metric()."
)
exit(1)
# Step 1: All input quantities are in terms of r,th,ph or x,y,z. We want them in terms
# of xx0,xx1,xx2, so here we call sympify_integers__replace_rthph() to replace
# r,th,ph or x,y,z, respectively, with the appropriate functions of xx0,xx1,xx2
# as defined for this particular reference metric in reference_metric.py's
# xxSph[] or xxCart[], respectively:
r_th_ph_or_Cart_xyz_oID_xx = []
if CoordType_in == "Spherical":
r_th_ph_or_Cart_xyz_oID_xx = rfm.xxSph
elif CoordType_in == "Cartesian":
r_th_ph_or_Cart_xyz_oID_xx = rfm.xxCart
else:
print(
"Error: Can only convert ADM Cartesian or Spherical initial data to BSSN Curvilinear coords."
)
exit(1)
# Next apply Jacobian transformations to convert into the (xx0,xx1,xx2) basis
# alpha is a scalar, so no Jacobian transformation is necessary.
alpha = alphaSphorCart
Jac_dUSphorCart_dDrfmUD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
Jac_dUSphorCart_dDrfmUD[i][j] = sp.diff(
r_th_ph_or_Cart_xyz_oID_xx[i], rfm.xx[j])
Jac_dUrfm_dDSphorCartUD, dummyDET = ixp.generic_matrix_inverter3x3(
Jac_dUSphorCart_dDrfmUD)
betaU = ixp.zerorank1()
BU = ixp.zerorank1()
gammaSphorCartDD = ixp.zerorank2()
KDD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
betaU[i] += Jac_dUrfm_dDSphorCartUD[i][j] * betaSphorCartU[j]
BU[i] += Jac_dUrfm_dDSphorCartUD[i][j] * BSphorCartU[j]
for k in range(DIM):
for l in range(DIM):
gammaSphorCartDD[i][j] += Jac_dUSphorCart_dDrfmUD[k][i] * Jac_dUSphorCart_dDrfmUD[l][j] * \
gammaSphorCartDD[k][l]
KDD[i][j] += Jac_dUSphorCart_dDrfmUD[k][
i] * Jac_dUSphorCart_dDrfmUD[l][j] * KSphorCartDD[k][l]
# Step 3: All ADM quantities were input into this function in the Spherical or Cartesian
# basis, as functions of r,th,ph or x,y,z, respectively. In Steps 1 and 2 above,
# we converted them to the xx0,xx1,xx2 basis, and as functions of xx0,xx1,xx2.
# Here we convert ADM quantities to their BSSN Curvilinear counterparts:
# Step 3.1: Convert ADM $\gamma_{ij}$ to BSSN $\bar{\gamma}_{ij}$:
# We have (Eqs. 2 and 3 of [Ruchlin *et al.*](https://arxiv.org/pdf/1712.07658.pdf)):
# \bar{\gamma}_{i j} = \left(\frac{\bar{\gamma}}{\gamma}\right)^{1/3} \gamma_{ij}.
gammaSphorCartUU, gammaDET = ixp.symm_matrix_inverter3x3(gammaSphorCartDD)
gammabarDD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
gammabarDD[i][j] = (rfm.detgammahat / gammaDET)**(sp.Rational(
1, 3)) * gammaSphorCartDD[i][j]
# Step 3.2: Convert the extrinsic curvature $K_{ij}$ to the trace-free extrinsic
# curvature $\bar{A}_{ij}$, plus the trace of the extrinsic curvature $K$,
# where (Eq. 3 of [Baumgarte *et al.*](https://arxiv.org/pdf/1211.6632.pdf)):
# K = \gamma^{ij} K_{ij}, and
# \bar{A}_{ij} &= \left(\frac{\bar{\gamma}}{\gamma}\right)^{1/3} \left(K_{ij} - \frac{1}{3} \gamma_{ij} K \right)
trK = sp.sympify(0)
for i in range(DIM):
for j in range(DIM):
trK += gammaSphorCartUU[i][j] * KDD[i][j]
AbarDD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
AbarDD[i][j] = (rfm.detgammahat / gammaDET)**(sp.Rational(
1, 3)) * (KDD[i][j] -
sp.Rational(1, 3) * gammaSphorCartDD[i][j] * trK)
# Step 3.3: Set the conformal factor variable $\texttt{cf}$, which is set
# by the "BSSN_RHSs::ConformalFactor" parameter. For example if
# "ConformalFactor" is set to "phi", we can use Eq. 3 of
# [Ruchlin *et al.*](https://arxiv.org/pdf/1712.07658.pdf),
# which in arbitrary coordinates is written:
# \phi = \frac{1}{12} \log\left(\frac{\gamma}{\bar{\gamma}}\right).
# Alternatively if "BSSN_RHSs::ConformalFactor" is set to "chi", then
# \chi = e^{-4 \phi} = \exp\left(-4 \frac{1}{12} \left(\frac{\gamma}{\bar{\gamma}}\right)\right)
# = \exp\left(-\frac{1}{3} \log\left(\frac{\gamma}{\bar{\gamma}}\right)\right) = \left(\frac{\gamma}{\bar{\gamma}}\right)^{-1/3}.
#
# Finally if "BSSN_RHSs::ConformalFactor" is set to "W", then
# W = e^{-2 \phi} = \exp\left(-2 \frac{1}{12} \log\left(\frac{\gamma}{\bar{\gamma}}\right)\right) =
# \exp\left(-\frac{1}{6} \log\left(\frac{\gamma}{\bar{\gamma}}\right)\right) =
# \left(\frac{\gamma}{\bar{\gamma}}\right)^{-1/6}.
# First compute gammabarDET:
gammabarUU, gammabarDET = ixp.symm_matrix_inverter3x3(gammabarDD)
cf = sp.sympify(0)
if par.parval_from_str("ConformalFactor") == "phi":
cf = sp.Rational(1, 12) * sp.log(gammaDET / gammabarDET)
elif par.parval_from_str("ConformalFactor") == "chi":
cf = (gammaDET / gammabarDET)**(-sp.Rational(1, 3))
elif par.parval_from_str("ConformalFactor") == "W":
cf = (gammaDET / gammabarDET)**(-sp.Rational(1, 6))
else:
print("Error ConformalFactor type = \"" +
par.parval_from_str("ConformalFactor") + "\" unknown.")
exit(1)
# Step 4: Rescale tensorial quantities according to the prescription described in
# the [BSSN in curvilinear coordinates tutorial module](Tutorial-BSSNCurvilinear.ipynb)
# (also [Ruchlin *et al.*](https://arxiv.org/pdf/1712.07658.pdf)):
#
# h_{ij} &= (\bar{\gamma}_{ij} - \hat{\gamma}_{ij})/\text{ReDD[i][j]}\\
# a_{ij} &= \bar{A}_{ij}/\text{ReDD[i][j]}\\
# \lambda^i &= \bar{\Lambda}^i/\text{ReU[i]}\\
# \mathcal{V}^i &= \beta^i/\text{ReU[i]}\\
# \mathcal{B}^i &= B^i/\text{ReU[i]}\\
hDD = ixp.zerorank2()
aDD = ixp.zerorank2()
vetU = ixp.zerorank1()
betU = ixp.zerorank1()
for i in range(DIM):
vetU[i] = betaU[i] / rfm.ReU[i]
betU[i] = BU[i] / rfm.ReU[i]
for j in range(DIM):
hDD[i][j] = (gammabarDD[i][j] - rfm.ghatDD[i][j]) / rfm.ReDD[i][j]
aDD[i][j] = AbarDD[i][j] / rfm.ReDD[i][j]
# Step 5: Output all ADM-to-BSSN expressions to a C function. This function
# must first call the ID_ADM_SphorCart() defined above. Using these
# Spherical or Cartesian data, it sets up all quantities needed for
# BSSNCurvilinear initial data, *except* $\lambda^i$, which must be
# computed from numerical data using finite-difference derivatives.
with open("BSSN/ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h",
"w") as file:
file.write(
"void ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs(const REAL xx0xx1xx2[3],"
)
if pointer_to_ID_inputs == True:
file.write("ID_inputs *other_inputs,")
else:
file.write("ID_inputs other_inputs,")
file.write("""
REAL *hDD00,REAL *hDD01,REAL *hDD02,REAL *hDD11,REAL *hDD12,REAL *hDD22,
REAL *aDD00,REAL *aDD01,REAL *aDD02,REAL *aDD11,REAL *aDD12,REAL *aDD22,
REAL *trK,
REAL *vetU0,REAL *vetU1,REAL *vetU2,
REAL *betU0,REAL *betU1,REAL *betU2,
REAL *alpha, REAL *cf) {
REAL gammaSphorCartDD00,gammaSphorCartDD01,gammaSphorCartDD02,
gammaSphorCartDD11,gammaSphorCartDD12,gammaSphorCartDD22;
REAL KSphorCartDD00,KSphorCartDD01,KSphorCartDD02,
KSphorCartDD11,KSphorCartDD12,KSphorCartDD22;
REAL alphaSphorCart,betaSphorCartU0,betaSphorCartU1,betaSphorCartU2;
REAL BSphorCartU0,BSphorCartU1,BSphorCartU2;
const REAL xx0 = xx0xx1xx2[0];
const REAL xx1 = xx0xx1xx2[1];
const REAL xx2 = xx0xx1xx2[2];
REAL xyz_or_rthph[3];\n""")
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
outputC(r_th_ph_or_Cart_xyz_oID_xx[0:3],
["xyz_or_rthph[0]", "xyz_or_rthph[1]", "xyz_or_rthph[2]"],
"BSSN/ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h",
outCparams + ",CSE_enable=False")
with open("BSSN/ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h",
"a") as file:
file.write(" " + ADM_input_function_name +
"""(xyz_or_rthph, other_inputs,
&gammaSphorCartDD00,&gammaSphorCartDD01,&gammaSphorCartDD02,
&gammaSphorCartDD11,&gammaSphorCartDD12,&gammaSphorCartDD22,
&KSphorCartDD00,&KSphorCartDD01,&KSphorCartDD02,
&KSphorCartDD11,&KSphorCartDD12,&KSphorCartDD22,
&alphaSphorCart,&betaSphorCartU0,&betaSphorCartU1,&betaSphorCartU2,
&BSphorCartU0,&BSphorCartU1,&BSphorCartU2);
// Next compute all rescaled BSSN curvilinear quantities:\n""")
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
outputC([
hDD[0][0], hDD[0][1], hDD[0][2], hDD[1][1], hDD[1][2], hDD[2][2],
aDD[0][0], aDD[0][1], aDD[0][2], aDD[1][1], aDD[1][2], aDD[2][2], trK,
vetU[0], vetU[1], vetU[2], betU[0], betU[1], betU[2], alpha, cf
], [
"*hDD00", "*hDD01", "*hDD02", "*hDD11", "*hDD12", "*hDD22", "*aDD00",
"*aDD01", "*aDD02", "*aDD11", "*aDD12", "*aDD22", "*trK", "*vetU0",
"*vetU1", "*vetU2", "*betU0", "*betU1", "*betU2", "*alpha", "*cf"
],
"BSSN/ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h",
params=outCparams)
with open("BSSN/ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h",
"a") as file:
file.write("}\n")
# Step 5.A: Output the driver function for the above
# function ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs()
# Next write the driver function for ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs():
with open("BSSN/ID_BSSN__ALL_BUT_LAMBDAs.h", "w") as file:
file.write(
"void ID_BSSN__ALL_BUT_LAMBDAs(const int Nxx_plus_2NGHOSTS[3],REAL *xx[3],"
)
if pointer_to_ID_inputs == True:
file.write("ID_inputs *other_inputs,")
else:
file.write("ID_inputs other_inputs,")
file.write("REAL *in_gfs) {\n")
file.write(
lp.loop(["i2", "i1", "i0"], ["0", "0", "0"], [
"Nxx_plus_2NGHOSTS[2]", "Nxx_plus_2NGHOSTS[1]",
"Nxx_plus_2NGHOSTS[0]"
], ["1", "1", "1"], [
"#pragma omp parallel for", " const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "", """const REAL xx0 = xx[0][i0];
const int idx = IDX3(i0,i1,i2);
const REAL xx0xx1xx2[3] = {xx0,xx1,xx2};
ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs(xx0xx1xx2,other_inputs,
&in_gfs[IDX4pt(HDD00GF,idx)],&in_gfs[IDX4pt(HDD01GF,idx)],&in_gfs[IDX4pt(HDD02GF,idx)],
&in_gfs[IDX4pt(HDD11GF,idx)],&in_gfs[IDX4pt(HDD12GF,idx)],&in_gfs[IDX4pt(HDD22GF,idx)],
&in_gfs[IDX4pt(ADD00GF,idx)],&in_gfs[IDX4pt(ADD01GF,idx)],&in_gfs[IDX4pt(ADD02GF,idx)],
&in_gfs[IDX4pt(ADD11GF,idx)],&in_gfs[IDX4pt(ADD12GF,idx)],&in_gfs[IDX4pt(ADD22GF,idx)],
&in_gfs[IDX4pt(TRKGF,idx)],
&in_gfs[IDX4pt(VETU0GF,idx)],&in_gfs[IDX4pt(VETU1GF,idx)],&in_gfs[IDX4pt(VETU2GF,idx)],
&in_gfs[IDX4pt(BETU0GF,idx)],&in_gfs[IDX4pt(BETU1GF,idx)],&in_gfs[IDX4pt(BETU2GF,idx)],
&in_gfs[IDX4pt(ALPHAGF,idx)],&in_gfs[IDX4pt(CFGF,idx)]);
"""))
file.write("}\n")
# Step 6: Compute $\bar{\Lambda}^i$ (Eqs. 4 and 5 of
# [Baumgarte *et al.*](https://arxiv.org/pdf/1211.6632.pdf)),
# from finite-difference derivatives of rescaled metric
# quantities $h_{ij}$:
# \bar{\Lambda}^i = \bar{\gamma}^{jk}\left(\bar{\Gamma}^i_{jk} - \hat{\Gamma}^i_{jk}\right).
# The reference_metric.py module provides us with analytic expressions for
# $\hat{\Gamma}^i_{jk}$, so here we need only compute
# finite-difference expressions for $\bar{\Gamma}^i_{jk}$, based on
# the values for $h_{ij}$ provided in the initial data. Once
# $\bar{\Lambda}^i$ has been computed, we apply the usual rescaling
# procedure:
# \lambda^i = \bar{\Lambda}^i/\text{ReU[i]},
# and then output the result to a C file using the NRPy+
# finite-difference C output routine.
# We will need all BSSN gridfunctions to be defined, as well as
# expressions for gammabarDD_dD in terms of exact derivatives of
# the rescaling matrix and finite-difference derivatives of
# hDD's.
gammabarDD = bssnrhs.gammabarDD
gammabarUU, gammabarDET = ixp.symm_matrix_inverter3x3(gammabarDD)
gammabarDD_dD = bssnrhs.gammabarDD_dD
# Next compute Christoffel symbols \bar{\Gamma}^i_{jk}:
GammabarUDD = ixp.zerorank3()
for i in range(DIM):
for j in range(DIM):
for k in range(DIM):
for l in range(DIM):
GammabarUDD[i][j][k] += sp.Rational(
1,
2) * gammabarUU[i][l] * (gammabarDD_dD[l][j][k] +
gammabarDD_dD[l][k][j] -
gammabarDD_dD[j][k][l])
# Next evaluate \bar{\Lambda}^i, based on GammabarUDD above and GammahatUDD
# (from the reference metric):
LambdabarU = ixp.zerorank1()
for i in range(DIM):
for j in range(DIM):
for k in range(DIM):
LambdabarU[i] += gammabarUU[j][k] * (
GammabarUDD[i][j][k] - rfm.GammahatUDD[i][j][k])
# Finally apply rescaling:
# lambda^i = Lambdabar^i/\text{ReU[i]}
lambdaU = ixp.zerorank1()
for i in range(DIM):
lambdaU[i] = LambdabarU[i] / rfm.ReU[i]
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
lambdaU_expressions = [
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU0"), rhs=lambdaU[0]),
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU1"), rhs=lambdaU[1]),
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU2"), rhs=lambdaU[2])
]
lambdaU_expressions_FDout = fin.FD_outputC("returnstring",
lambdaU_expressions,
outCparams)
with open("BSSN/ID_BSSN_lambdas.h", "w") as file:
file.write("""
void ID_BSSN_lambdas(const int Nxx[3],const int Nxx_plus_2NGHOSTS[3],REAL *xx[3],const REAL dxx[3],REAL *in_gfs) {\n"""
)
file.write(
lp.loop(["i2", "i1", "i0"], ["NGHOSTS", "NGHOSTS", "NGHOSTS"],
["NGHOSTS+Nxx[2]", "NGHOSTS+Nxx[1]", "NGHOSTS+Nxx[0]"],
["1", "1", "1"], [
"const REAL invdx0 = 1.0/dxx[0];\n" +
"const REAL invdx1 = 1.0/dxx[1];\n" +
"const REAL invdx2 = 1.0/dxx[2];\n" +
"#pragma omp parallel for",
" const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "", "const REAL xx0 = xx[0][i0];\n" +
lambdaU_expressions_FDout))
file.write("}\n")
import sys
import os
import signal
from loop import loop
def handle_pdb(sig, frame):
import pdb
pdb.Pdb().set_trace(frame)
if __name__ == '__main__':
signal.signal(signal.SIGUSR1, handle_pdb)
sys.stdout.write(str(os.getpid()))
sys.stdout.flush()
loop()
import evaluate as e
# 读取一张图片,做灰度化处理,转为二维矩阵。虽然原图是灰度图,但仍需此步骤,不然会是三维矩阵
peppers = cv2.imread('raw_peppers.png', 0)
# 使用高斯滤波消除噪声
# (5,5)是高斯核的大小,0是sigmaX,0的意思是让方程自己给你算对应的sigma
peppers_b = cv2.GaussianBlur(peppers, (5, 5), 0)
peppers_t = copy.deepcopy(peppers_b)
# 返回的是经过非极大值抑制后的矩阵
peppers_g = g.gradient(peppers_t)
# 返回的是迭代后的最优阈值
peppers_T = l.loop(peppers_g)
# ret是返回的最优阈值,image是处理后的图
# THRESH_BINARY就是三角法（这句话存疑,忘记哪里看来的了,但实际使用起来似乎使用的阈值是传入的阈值）
# THRESH_OTSU是大津法
# 这一个函数会根据直方图选择最优的阈值,即otus或传入的阈值,可以从返回值ret中获取
# peppers_ret, new1 = cv2.threshold(peppers_b, peppers_T, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
# 这一条就只会使用大津法算出的阈值,但大津有缺点,直方图没有明显双峰时效果可能不好
peppers_ret, image = cv2.threshold(peppers_b, peppers_T, 255, cv2.THRESH_OTSU)
# 因为想要有更多的边被画出来,所以取更小的（我自己一厢情愿的,可能没有理论依据）
peppers_T = min(peppers_ret, peppers_T)
peppers = cv2.Canny(peppers_b, peppers_T / 2, peppers_T)
# 这是自适应阈值的边缘切割,用高斯核做窗口去给每一个像素一个自适应阈值
# 最后一个参数会影响切割质量,具体原理请参考文档
from output import output_class from input import input_class from translator import translator_class from loop import loop output = output_class() input = input_class() translator = translator_class(output) output.finalize() loop(output, input, translator)
def Convert_Spherical_or_Cartesian_ADM_to_BSSN_curvilinear(
CoordType_in,
ADM_input_function_name,
Ccodesdir="BSSN",
pointer_to_ID_inputs=False):
# The ADM & BSSN formalisms only work in 3D; they are 3+1 decompositions of Einstein's equations.
# To implement axisymmetry or spherical symmetry, simply set all spatial derivatives in
# the relevant angular directions to zero; DO NOT SET DIM TO ANYTHING BUT 3.
# Step 0: Set spatial dimension (must be 3 for BSSN)
DIM = 3
# Step 1: All ADM initial data quantities are now functions of xx0,xx1,xx2, but
# they are still in the Spherical or Cartesian basis. We can now directly apply
# Jacobian transformations to get them in the correct xx0,xx1,xx2 basis:
# All input quantities are in terms of r,th,ph or x,y,z. We want them in terms
# of xx0,xx1,xx2, so here we call sympify_integers__replace_rthph() to replace
# r,th,ph or x,y,z, respectively, with the appropriate functions of xx0,xx1,xx2
# as defined for this particular reference metric in reference_metric.py's
# xxSph[] or xxCart[], respectively:
# Define the input variables:
gammaSphorCartDD = ixp.declarerank2("gammaSphorCartDD", "sym01")
KSphorCartDD = ixp.declarerank2("KSphorCartDD", "sym01")
alphaSphorCart = sp.symbols("alphaSphorCart")
betaSphorCartU = ixp.declarerank1("betaSphorCartU")
BSphorCartU = ixp.declarerank1("BSphorCartU")
# Make sure that rfm.reference_metric() has been called.
# We'll need the variables it defines throughout this module.
if rfm.have_already_called_reference_metric_function == False:
print(
"Error. Called Convert_Spherical_ADM_to_BSSN_curvilinear() without"
)
print(
" first setting up reference metric, by calling rfm.reference_metric()."
)
sys.exit(1)
r_th_ph_or_Cart_xyz_oID_xx = []
if CoordType_in == "Spherical":
r_th_ph_or_Cart_xyz_oID_xx = rfm.xxSph
elif CoordType_in == "Cartesian":
r_th_ph_or_Cart_xyz_oID_xx = rfm.xxCart
else:
print(
"Error: Can only convert ADM Cartesian or Spherical initial data to BSSN Curvilinear coords."
)
sys.exit(1)
# Step 2: All ADM initial data quantities are now functions of xx0,xx1,xx2, but
# they are still in the Spherical or Cartesian basis. We can now directly apply
# Jacobian transformations to get them in the correct xx0,xx1,xx2 basis:
# alpha is a scalar, so no Jacobian transformation is necessary.
alpha = alphaSphorCart
Jac_dUSphorCart_dDrfmUD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
Jac_dUSphorCart_dDrfmUD[i][j] = sp.diff(
r_th_ph_or_Cart_xyz_oID_xx[i], rfm.xx[j])
Jac_dUrfm_dDSphorCartUD, dummyDET = ixp.generic_matrix_inverter3x3(
Jac_dUSphorCart_dDrfmUD)
betaU = ixp.zerorank1()
BU = ixp.zerorank1()
gammaDD = ixp.zerorank2()
KDD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
betaU[i] += Jac_dUrfm_dDSphorCartUD[i][j] * betaSphorCartU[j]
BU[i] += Jac_dUrfm_dDSphorCartUD[i][j] * BSphorCartU[j]
for k in range(DIM):
for l in range(DIM):
gammaDD[i][j] += Jac_dUSphorCart_dDrfmUD[k][i] * Jac_dUSphorCart_dDrfmUD[l][j] * \
gammaSphorCartDD[k][l]
KDD[i][j] += Jac_dUSphorCart_dDrfmUD[k][
i] * Jac_dUSphorCart_dDrfmUD[l][j] * KSphorCartDD[k][l]
# Step 3: All ADM quantities were input into this function in the Spherical or Cartesian
# basis, as functions of r,th,ph or x,y,z, respectively. In Steps 1 and 2 above,
# we converted them to the xx0,xx1,xx2 basis, and as functions of xx0,xx1,xx2.
# Here we convert ADM quantities in the "rfm" basis to their BSSN Curvilinear
# counterparts, for all BSSN quantities *except* lambda^i:
import BSSN.BSSN_in_terms_of_ADM as BitoA
BitoA.gammabarDD_hDD(gammaDD)
BitoA.trK_AbarDD_aDD(gammaDD, KDD)
BitoA.cf_from_gammaDD(gammaDD)
BitoA.betU_vetU(betaU, BU)
hDD = BitoA.hDD
trK = BitoA.trK
aDD = BitoA.aDD
cf = BitoA.cf
vetU = BitoA.vetU
betU = BitoA.betU
# Step 4: Compute $\bar{\Lambda}^i$ (Eqs. 4 and 5 of
# [Baumgarte *et al.*](https://arxiv.org/pdf/1211.6632.pdf)),
# from finite-difference derivatives of rescaled metric
# quantities $h_{ij}$:
# \bar{\Lambda}^i = \bar{\gamma}^{jk}\left(\bar{\Gamma}^i_{jk} - \hat{\Gamma}^i_{jk}\right).
# The reference_metric.py module provides us with analytic expressions for
# $\hat{\Gamma}^i_{jk}$, so here we need only compute
# finite-difference expressions for $\bar{\Gamma}^i_{jk}$, based on
# the values for $h_{ij}$ provided in the initial data. Once
# $\bar{\Lambda}^i$ has been computed, we apply the usual rescaling
# procedure:
# \lambda^i = \bar{\Lambda}^i/\text{ReU[i]},
# and then output the result to a C file using the NRPy+
# finite-difference C output routine.
# We will need all BSSN gridfunctions to be defined, as well as
# expressions for gammabarDD_dD in terms of exact derivatives of
# the rescaling matrix and finite-difference derivatives of
# hDD's. This functionality is provided by BSSN.BSSN_unrescaled_and_barred_vars,
# which we call here to overwrite above definitions of gammabarDD,gammabarUU, etc.
Bq.gammabar__inverse_and_derivs() # Provides gammabarUU and GammabarUDD
gammabarUU = Bq.gammabarUU
GammabarUDD = Bq.GammabarUDD
# Next evaluate \bar{\Lambda}^i, based on GammabarUDD above and GammahatUDD
# (from the reference metric):
LambdabarU = ixp.zerorank1()
for i in range(DIM):
for j in range(DIM):
for k in range(DIM):
LambdabarU[i] += gammabarUU[j][k] * (GammabarUDD[i][j][k] -
rfm.GammahatUDD[i][j][k])
# Finally apply rescaling:
# lambda^i = Lambdabar^i/\text{ReU[i]}
lambdaU = ixp.zerorank1()
for i in range(DIM):
lambdaU[i] = LambdabarU[i] / rfm.ReU[i]
if ADM_input_function_name == "DoNotOutputADMInputFunction":
return hDD, aDD, trK, vetU, betU, alpha, cf, lambdaU
# Step 5.A: Output files containing finite-differenced lambdas.
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
lambdaU_expressions = [
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU0"), rhs=lambdaU[0]),
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU1"), rhs=lambdaU[1]),
lhrh(lhs=gri.gfaccess("in_gfs", "lambdaU2"), rhs=lambdaU[2])
]
lambdaU_expressions_FDout = fin.FD_outputC("returnstring",
lambdaU_expressions, outCparams)
with open(os.path.join(Ccodesdir, "ID_BSSN_lambdas.h"), "w") as file:
file.write("""
void ID_BSSN_lambdas(const int Nxx[3],const int Nxx_plus_2NGHOSTS[3],REAL *xx[3],const REAL dxx[3],REAL *in_gfs) {\n"""
)
file.write(
lp.loop(["i2", "i1", "i0"], ["NGHOSTS", "NGHOSTS", "NGHOSTS"],
["NGHOSTS+Nxx[2]", "NGHOSTS+Nxx[1]", "NGHOSTS+Nxx[0]"],
["1", "1", "1"], [
"const REAL invdx0 = 1.0/dxx[0];\n" +
"const REAL invdx1 = 1.0/dxx[1];\n" +
"const REAL invdx2 = 1.0/dxx[2];\n" +
"#pragma omp parallel for",
" const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "", "const REAL xx0 = xx[0][i0];\n" +
lambdaU_expressions_FDout))
file.write("}\n")
# Step 5: Output all ADM-to-BSSN expressions to a C function. This function
# must first call the ID_ADM_SphorCart() defined above. Using these
# Spherical or Cartesian data, it sets up all quantities needed for
# BSSNCurvilinear initial data, *except* $\lambda^i$, which must be
# computed from numerical data using finite-difference derivatives.
with open(
os.path.join(
Ccodesdir,
"ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h"),
"w") as file:
file.write(
"void ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs(const REAL xx0xx1xx2[3],"
)
if pointer_to_ID_inputs == True:
file.write("ID_inputs *other_inputs,")
else:
file.write("ID_inputs other_inputs,")
file.write("""
REAL *hDD00,REAL *hDD01,REAL *hDD02,REAL *hDD11,REAL *hDD12,REAL *hDD22,
REAL *aDD00,REAL *aDD01,REAL *aDD02,REAL *aDD11,REAL *aDD12,REAL *aDD22,
REAL *trK,
REAL *vetU0,REAL *vetU1,REAL *vetU2,
REAL *betU0,REAL *betU1,REAL *betU2,
REAL *alpha, REAL *cf) {
REAL gammaSphorCartDD00,gammaSphorCartDD01,gammaSphorCartDD02,
gammaSphorCartDD11,gammaSphorCartDD12,gammaSphorCartDD22;
REAL KSphorCartDD00,KSphorCartDD01,KSphorCartDD02,
KSphorCartDD11,KSphorCartDD12,KSphorCartDD22;
REAL alphaSphorCart,betaSphorCartU0,betaSphorCartU1,betaSphorCartU2;
REAL BSphorCartU0,BSphorCartU1,BSphorCartU2;
const REAL xx0 = xx0xx1xx2[0];
const REAL xx1 = xx0xx1xx2[1];
const REAL xx2 = xx0xx1xx2[2];
REAL xyz_or_rthph[3];\n""")
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
outputC(
r_th_ph_or_Cart_xyz_oID_xx[0:3],
["xyz_or_rthph[0]", "xyz_or_rthph[1]", "xyz_or_rthph[2]"],
os.path.join(Ccodesdir,
"ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h"),
outCparams + ",CSE_enable=False")
with open(
os.path.join(
Ccodesdir,
"ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h"),
"a") as file:
file.write(" " + ADM_input_function_name +
"""(xyz_or_rthph, other_inputs,
&gammaSphorCartDD00,&gammaSphorCartDD01,&gammaSphorCartDD02,
&gammaSphorCartDD11,&gammaSphorCartDD12,&gammaSphorCartDD22,
&KSphorCartDD00,&KSphorCartDD01,&KSphorCartDD02,
&KSphorCartDD11,&KSphorCartDD12,&KSphorCartDD22,
&alphaSphorCart,&betaSphorCartU0,&betaSphorCartU1,&betaSphorCartU2,
&BSphorCartU0,&BSphorCartU1,&BSphorCartU2);
// Next compute all rescaled BSSN curvilinear quantities:\n""")
outCparams = "preindent=1,outCfileaccess=a,outCverbose=False,includebraces=False"
outputC([
hDD[0][0], hDD[0][1], hDD[0][2], hDD[1][1], hDD[1][2], hDD[2][2],
aDD[0][0], aDD[0][1], aDD[0][2], aDD[1][1], aDD[1][2], aDD[2][2], trK,
vetU[0], vetU[1], vetU[2], betU[0], betU[1], betU[2], alpha, cf
], [
"*hDD00", "*hDD01", "*hDD02", "*hDD11", "*hDD12", "*hDD22", "*aDD00",
"*aDD01", "*aDD02", "*aDD11", "*aDD12", "*aDD22", "*trK", "*vetU0",
"*vetU1", "*vetU2", "*betU0", "*betU1", "*betU2", "*alpha", "*cf"
],
os.path.join(
Ccodesdir,
"ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h"),
params=outCparams)
with open(
os.path.join(
Ccodesdir,
"ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs.h"),
"a") as file:
file.write("}\n")
# Step 5.a: Output the driver function for the above
# function ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs()
# Next write the driver function for ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs():
with open(os.path.join(Ccodesdir, "ID_BSSN__ALL_BUT_LAMBDAs.h"),
"w") as file:
file.write(
"void ID_BSSN__ALL_BUT_LAMBDAs(const int Nxx_plus_2NGHOSTS[3],REAL *xx[3],"
)
if pointer_to_ID_inputs == True:
file.write("ID_inputs *other_inputs,")
else:
file.write("ID_inputs other_inputs,")
file.write("REAL *in_gfs) {\n")
file.write(
lp.loop(["i2", "i1", "i0"], ["0", "0", "0"], [
"Nxx_plus_2NGHOSTS[2]", "Nxx_plus_2NGHOSTS[1]",
"Nxx_plus_2NGHOSTS[0]"
], ["1", "1", "1"], [
"#pragma omp parallel for", " const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "", """const REAL xx0 = xx[0][i0];
const int idx = IDX3(i0,i1,i2);
const REAL xx0xx1xx2[3] = {xx0,xx1,xx2};
ID_ADM_xx0xx1xx2_to_BSSN_xx0xx1xx2__ALL_BUT_LAMBDAs(xx0xx1xx2,other_inputs,
&in_gfs[IDX4pt(HDD00GF,idx)],&in_gfs[IDX4pt(HDD01GF,idx)],&in_gfs[IDX4pt(HDD02GF,idx)],
&in_gfs[IDX4pt(HDD11GF,idx)],&in_gfs[IDX4pt(HDD12GF,idx)],&in_gfs[IDX4pt(HDD22GF,idx)],
&in_gfs[IDX4pt(ADD00GF,idx)],&in_gfs[IDX4pt(ADD01GF,idx)],&in_gfs[IDX4pt(ADD02GF,idx)],
&in_gfs[IDX4pt(ADD11GF,idx)],&in_gfs[IDX4pt(ADD12GF,idx)],&in_gfs[IDX4pt(ADD22GF,idx)],
&in_gfs[IDX4pt(TRKGF,idx)],
&in_gfs[IDX4pt(VETU0GF,idx)],&in_gfs[IDX4pt(VETU1GF,idx)],&in_gfs[IDX4pt(VETU2GF,idx)],
&in_gfs[IDX4pt(BETU0GF,idx)],&in_gfs[IDX4pt(BETU1GF,idx)],&in_gfs[IDX4pt(BETU2GF,idx)],
&in_gfs[IDX4pt(ALPHAGF,idx)],&in_gfs[IDX4pt(CFGF,idx)]);
"""))
file.write("}\n")
#!/usr/bin/python
from button import button
from led import led
from setup import setup
from loop import loop
# Open a file
fo = open("arduino.c", "w")
b = button(9)
le = led(12)
s = setup()
s.addComposant(b)
s.addComposant(le)
fo.write(str(s.arduino()))
lo = loop()
lo.addRead(["BUTTON9", "BUTTON10"])
lo.addActionIf(["BUTTON9", "BUTTON10"], "dualPush", ["active"], "LED12")
fo.write(str(lo.arduino()))
# Close opend file
fo.close()
def output_Enforce_Detgammabar_Constraint_Ccode():
# Set spatial dimension (must be 3 for BSSN)
DIM = 3
# Then we set the coordinate system for the numerical grid
rfm.reference_metric(
) # Create ReU, ReDD needed for rescaling B-L initial data, generating BSSN RHSs, etc.
# We will need the h_{ij} quantities defined within BSSN_RHSs
# below when we enforce the gammahat=gammabar constraint
# Step 1: All barred quantities are defined in terms of BSSN rescaled gridfunctions,
# which we declare here in case they haven't yet been declared elsewhere.
Bq.declare_BSSN_gridfunctions_if_not_declared_already()
hDD = Bq.hDD
Bq.BSSN_basic_tensors()
gammabarDD = Bq.gammabarDD
# First define the Kronecker delta:
KroneckerDeltaDD = ixp.zerorank2()
for i in range(DIM):
KroneckerDeltaDD[i][i] = sp.sympify(1)
# The detgammabar in BSSN_RHSs is set to detgammahat when BSSN_RHSs::detgbarOverdetghat_equals_one=True (default),
# so we manually compute it here:
dummygammabarUU, detgammabar = ixp.symm_matrix_inverter3x3(gammabarDD)
# Next apply the constraint enforcement equation above.
hprimeDD = ixp.zerorank2()
for i in range(DIM):
for j in range(DIM):
hprimeDD[i][j] = \
(sp.Abs(rfm.detgammahat) / detgammabar) ** (sp.Rational(1, 3)) * (KroneckerDeltaDD[i][j] + hDD[i][j]) \
- KroneckerDeltaDD[i][j]
enforce_detg_constraint_vars = [ \
lhrh(lhs=gri.gfaccess("in_gfs", "hDD00"), rhs=hprimeDD[0][0]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD01"), rhs=hprimeDD[0][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD02"), rhs=hprimeDD[0][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD11"), rhs=hprimeDD[1][1]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD12"), rhs=hprimeDD[1][2]),
lhrh(lhs=gri.gfaccess("in_gfs", "hDD22"), rhs=hprimeDD[2][2])]
enforce_gammadet_string = fin.FD_outputC(
"returnstring",
enforce_detg_constraint_vars,
params="outCverbose=False,preindent=0,includebraces=False")
with open("BSSN/enforce_detgammabar_constraint.h", "w") as file:
indent = " "
file.write(
"void enforce_detgammabar_constraint(const int Nxx_plus_2NGHOSTS[3],REAL *xx[3], REAL *in_gfs) {\n\n"
)
file.write(
lp.loop(["i2", "i1", "i0"], ["0", "0", "0"], [
"Nxx_plus_2NGHOSTS[2]", "Nxx_plus_2NGHOSTS[1]",
"Nxx_plus_2NGHOSTS[0]"
], ["1", "1", "1"], [
"#pragma omp parallel for", " const REAL xx2 = xx[2][i2];",
" const REAL xx1 = xx[1][i1];"
], "", "const REAL xx0 = xx[0][i0];\n" + enforce_gammadet_string))
file.write("}\n")
print(
"Output C implementation of det(gammabar) constraint to file BSSN/enforce_detgammabar_constraint.h"
)
