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use f-strings everywhere

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Jan Petykiewicz 2022-11-20 21:57:54 -08:00
parent efeb29479b
commit 3d8054ba40
2 changed files with 20 additions and 19 deletions
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20
opencl_fdfd/csr.py
View File

@ -114,11 +114,11 @@ def cg(
_, err2 = rhoerr_step(r, []) _, err2 = rhoerr_step(r, [])
b_norm = numpy.sqrt(err2) b_norm = numpy.sqrt(err2)
logging.debug('b_norm check: ', b_norm) logging.debug(f'b_norm check: {b_norm}')
success = False success = False
for k in range(max_iters): for k in range(max_iters):
logging.debug('[{:06d}] rho {:.4} alpha {:4.4}'.format(k, rho, alpha)) logging.debug(f'[{k:06d}] rho {rho:.4} alpha {alpha:4.4}')
rho_prev = rho rho_prev = rho
e = xr_step(x, p, r, v, alpha, []) e = xr_step(x, p, r, v, alpha, [])
@ -126,7 +126,7 @@ def cg(
errs += [numpy.sqrt(err2) / b_norm] errs += [numpy.sqrt(err2) / b_norm]
logging.debug('err {}'.format(errs[-1])) logging.debug(f'err {errs[-1]}')
if errs[-1] < err_threshold: if errs[-1] < err_threshold:
success = True success = True
@ -136,8 +136,8 @@ def cg(
e = a_step(v, m, p, e) e = a_step(v, m, p, e)
alpha = rho / dot(p, v, e) alpha = rho / dot(p, v, e)
if verbose and k % 1000 == 0: if k % 1000 == 0:
logging.info('iteration {}'.format(k)) logger.info(f'iteration {k}')
''' '''
Done solving Done solving
@ -150,12 +150,12 @@ def cg(
logging.info('Solve success') logging.info('Solve success')
else: else:
logging.warning('Solve failure') logging.warning('Solve failure')
logging.info('{} iterations in {} sec: {} iterations/sec \ logging.info(f'{k} iterations in {time_elapsed} sec: {k / time_elapsed} iterations/sec')
'.format(k, time_elapsed, k / time_elapsed)) logging.debug(f'final error {errs[-1]}')
logging.debug('final error {}'.format(errs[-1])) logging.debug(f'overhead {start_time2 - start_time} sec')
logging.debug('overhead {} sec'.format(start_time2 - start_time))
logging.info('Final residual: {}'.format(norm(A @ x - b) / norm(b))) residual = norm(A @ x - b) / norm(b)
logging.info(f'Final residual: {residual}')
return x return x

19
opencl_fdfd/main.py
View File

@ -179,13 +179,13 @@ def cg_solver(
_, err2 = rhoerr_step(r, []) _, err2 = rhoerr_step(r, [])
b_norm = numpy.sqrt(err2) b_norm = numpy.sqrt(err2)
logging.debug('b_norm check: {}'.format(b_norm)) logging.debug(f'b_norm check: {b_norm}')
success = False success = False
for k in range(max_iters): for k in range(max_iters):
do_print = (k % 100 == 0) do_print = (k % 100 == 0)
if do_print: if do_print:
logger.debug('[{:06d}] rho {:.4} alpha {:4.4}'.format(k, rho, alpha)) logger.debug(f'[{k:06d}] rho {rho:.4} alpha {alpha:4.4}')
rho_prev = rho rho_prev = rho
e = xr_step(x, p, r, v, alpha, []) e = xr_step(x, p, r, v, alpha, [])
@ -194,7 +194,7 @@ def cg_solver(
errs += [numpy.sqrt(err2) / b_norm] errs += [numpy.sqrt(err2) / b_norm]
if do_print: if do_print:
logger.debug('err {}'.format(errs[-1])) logger.debug(f'err {errs[-1]}')
if errs[-1] < err_threshold: if errs[-1] < err_threshold:
success = True success = True
@ -205,7 +205,7 @@ def cg_solver(
alpha = rho / dot(p, v, e) alpha = rho / dot(p, v, e)
if k % 1000 == 0: if k % 1000 == 0:
logger.info('iteration {}'.format(k)) logger.info(f'iteration {k}')
''' '''
Done solving Done solving
@ -222,15 +222,16 @@ def cg_solver(
logger.info('Solve success') logger.info('Solve success')
else: else:
logger.warning('Solve failure') logger.warning('Solve failure')
logger.info('{} iterations in {} sec: {} iterations/sec \ logger.info(f'{k} iterations in {time_elapsed} sec: {k / time_elapsed} iterations/sec')
'.format(k, time_elapsed, k / time_elapsed)) logger.debug(f'final error {errs[-1]}')
logger.debug('final error {}'.format(errs[-1])) logger.debug(f'overhead {start_time2 - start_time} sec')
logger.debug('overhead {} sec'.format(start_time2 - start_time))
A0 = meanas.fdfd.operators.e_full(omega, dxes, epsilon, mu).tocsr() A0 = meanas.fdfd.operators.e_full(omega, dxes, epsilon, mu).tocsr()
if adjoint: if adjoint:
# Remember we conjugated all the contents of A earlier # Remember we conjugated all the contents of A earlier
A0 = A0.T A0 = A0.T
logger.info('Post-everything residual: {}'.format(norm(A0 @ x - b) / norm(b)))
residual = norm(A0 @ x - b) / norm(b)
logger.info(f'Post-everything residual: {residual}')
return x return x