Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

rewrite refresh_vars for real parameters #40

Open
wants to merge 7 commits into
base: dev
Choose a base branch
from
Open

rewrite refresh_vars for real parameters #40

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
81f5fef
rewrite refresh_vars for real parameters
Yinrui-Liu Apr 7, 2021
8b35d62
Merge branch 'dev' of github.com:jiangyi15/tf-pwa into dev
Yinrui-Liu Apr 28, 2021
0a9ddd1
updates from Yinrui Liu
Yinrui-Liu Apr 28, 2021
5e34926
updates
Yinrui-Liu Apr 28, 2021
b40e524
Merge branch 'dev' of github.com:jiangyi15/tf-pwa into dev
Yinrui-Liu Apr 28, 2021
8391e53
Merge remote-tracking branch 'upstream/dev' into dev
Yinrui-Liu May 27, 2021
f354b50
Merge remote-tracking branch 'upstream/dev' into dev
Yinrui-Liu Jun 8, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
31 changes: 24 additions & 7 deletions fit.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,7 @@ def load_config(config_file="config.yml", total_same=False):
return MultiConfig(config_files, total_same=total_same)


def fit(config, init_params="", method="BFGS", loop=1, maxiter=500):
def fit(config, vm, init_params="", method="BFGS", loop=1, maxiter=500):
"""
simple fit script
"""
Expand All @@ -59,6 +59,8 @@ def fit(config, init_params="", method="BFGS", loop=1, maxiter=500):
print("\nusing RANDOM parameters", flush=True)
# try to fit
try:
# vm.rp2xy_all()
vm.std_polar_all()
fit_result = config.fit(
batch=65000, method=method, maxiter=maxiter
)
Expand Down Expand Up @@ -139,6 +141,7 @@ def write_some_results_combine(config, fit_result, save_root=False):

for it, config_i in enumerate(config.configs):
print("########## fit fractions {}:".format(it))
print(f"nll{it}", config_i.get_fcn()({}).numpy())
mcdata = config_i.get_phsp_noeff()
fit_frac, err_frac = fit_fractions(
config_i.get_amplitude(),
Expand Down Expand Up @@ -186,16 +189,24 @@ def main():
parser.add_argument(
"--no-GPU", action="store_false", default=True, dest="has_gpu"
)
parser.add_argument("-c", "--config", default="config.yml", dest="config")
parser.add_argument(
"-c", "--config", default="config.yml", dest="config"
)
parser.add_argument(
"-i", "--init_params", default="init_params.json", dest="init"
)
parser.add_argument("-m", "--method", default="BFGS", dest="method")
parser.add_argument("-l", "--loop", type=int, default=1, dest="loop")
parser.add_argument(
"-m", "--method", default="BFGS", dest="method"
)
parser.add_argument(
"-l", "--loop", type=int, default=1, dest="loop"
)
parser.add_argument(
"-x", "--maxiter", type=int, default=2000, dest="maxiter"
)
parser.add_argument("-r", "--save_root", default=False, dest="save_root")
parser.add_argument(
"-r", "--save_root", default=False, dest="save_root"
)
parser.add_argument(
"--total-same", action="store_true", default=False, dest="total_same"
)
Expand All @@ -206,11 +217,17 @@ def main():
devices = "/device:CPU:0"
with tf.device(devices):
config = load_config(results.config, results.total_same)
try:
vm = config.get_amplitudes()[0].vm
except:
vm = config.get_amplitude().vm
fit_result = fit(
config, results.init, results.method, results.loop, results.maxiter
config, vm, results.init, results.method, results.loop, results.maxiter
)
if isinstance(config, ConfigLoader):
write_some_results(config, fit_result, save_root=results.save_root)
write_some_results(
config, fit_result, save_root=results.save_root
)
else:
write_some_results_combine(
config, fit_result, save_root=results.save_root
Expand Down
2 changes: 1 addition & 1 deletion state_cache.sh
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@ do
done
echo "using ${new_json_file} as params file"

newer_file=`find -cnewer ${new_json_file} | grep -v trash | grep -E ".*\.(C|json|root|log|png|txt|pdf)"`
newer_file=`find -cnewer ${new_json_file} | grep -v trash | grep -E ".*\.(C|json|root|log|png|txt|pdf|csv)"`
for i in ${newer_file};
do
cache_file ${i}
Expand Down
22 changes: 15 additions & 7 deletions tf_pwa/config_loader/plot.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -473,13 +473,21 @@ def _plot_partial_wave(
linewidth=1,
)
else:
le3 = hist_i.draw(
ax,
color=curve_style[0],
linestyle=curve_style[1:],
label=label,
linewidth=1,
)
try:
le3 = hist_i.draw(
ax,
color=curve_style[0],
linestyle=curve_style[1:],
label=label,
linewidth=1,
)
except:
le3 = hist_i.draw(
ax,
color=curve_style,
label=label,
linewidth=1,
)
legends.append(le3[0])
legends_label.append(label)
if yscale == "log":
Expand Down
70 changes: 36 additions & 34 deletions tf_pwa/variable.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -350,42 +350,42 @@ def refresh_vars(self, init_val=None, bound_dic=None):
dtype=self.dtype,
)
)
# all_vars = set(self.trainable_vars) # real vars
# real_vars = all_vars - set(cplx_vars)
for name in set(init_val) & set(self.trainable_vars):
if hasattr(init_val[name], "__len__"):
mu = init_val[name][0]
sigma = init_val[name][1]
if name not in bound_dic:
val = tf.random.normal(
shape=[], mean=mu, stddev=sigma, dtype=self.dtype
)
else:
range_ = bound_dic[name]
while True:

# for real parameters
for name in self.trainable_vars:
if name in init_val: # given initial values, in format either {name: [mu, sigma]} or {name: value}
if hasattr(init_val[name], "__len__"):
mu = init_val[name][0]
sigma = init_val[name][1]
if name not in bound_dic:
val = tf.random.normal(
shape=[], mean=mu, stddev=sigma, dtype=self.dtype
)
if val < range_[1] and val > range_[0]:
break
self.variables[name].assign(val)
else:
if init_val[name] is not None:
self.variables[name].assign(init_val[name])

for name in set(bound_dic) - set(init_val):
_min, _max = bound_dic[name]
if _min is not None:
if _max is not None:
val = tf.random.uniform(
shape=[], minval=_min, maxval=_max, dtype=self.dtype
)
else:
range_ = bound_dic[name]
while True:
val = tf.random.normal(
shape=[], mean=mu, stddev=sigma, dtype=self.dtype
)
if val < range_[1] and val > range_[0]:
break
self.variables[name].assign(val)
else:
val = _min + np.random.chisquare(df=1)
else:
if _max is not None:
val = _max - np.random.chisquare(df=1)
self.variables[name].assign(val)
if init_val[name] is not None:
self.variables[name].assign(init_val[name])
elif name in bound_dic: # if not given init_val but the parameter has boundary
_min, _max = bound_dic[name]
if _min is not None:
if _max is not None:
val = tf.random.uniform(
shape=[], minval=_min, maxval=_max, dtype=self.dtype
)
else:
val = _min + np.random.chisquare(df=1)
else:
if _max is not None:
val = _max - np.random.chisquare(df=1)
self.variables[name].assign(val)

def set_fix(self, name, value=None, unfix=False):
"""
Expand Down Expand Up @@ -678,17 +678,19 @@ def std_polar(self, name):
phase part is between :math:`-\\pi` to :math:`\\pi`.
:param name: String
"""
self.xy2rp(name)
if self.complex_vars[name] is not True: # it is a xy complex
return
r = self.variables[name + "r"]
p = self.variables[name + "i"]
if r < 0:
r.assign(tf.abs(r))
if type(self.complex_vars[name]) == list:
print("$$$!@@!deprecated in variable.VarsManager.std_polar") # could be deprecated
for name_r in self.complex_vars[name]:
self.variables[name_r[:-1] + "i"].assign_add(np.pi)
else:
p.assign_add(np.pi)
self._std_polar_angle(p)
p.assign(self._std_polar_angle(p))

def std_polar_all(self): # std polar expression: r>0, -pi<p<pi
"""
Expand Down