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environment,worker_db: mutate datasets from experiments via dedicated method instead of Notifier. Closes #345

This commit is contained in:
Sebastien Bourdeauducq 2016-03-29 16:26:14 +08:00
parent 1884b22528
commit ac0f62628d
4 changed files with 40 additions and 22 deletions

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@ -9,6 +9,8 @@ unreleased
* The CPU speed in the pipistrello gateware has been reduced from 83 1/3 MHz to
75 MHz. This will reduce the achievable sustained pulse rate and latency
accordingly. ISE was intermittently failing to meet timing (#341).
* set_dataset in broadcast mode no longer returns a Notifier. Mutating datasets
should be done with mutate_dataset instead (#345).
1.0rc1

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@ -221,13 +221,11 @@ class HasEnvironment:
broadcast=False, persist=False, save=True):
"""Sets the contents and handling modes of a dataset.
If the dataset is broadcasted, it must be PYON-serializable.
If the dataset is saved, it must be a scalar (``bool``, ``int``,
``float`` or NumPy scalar) or a NumPy array.
Datasets must be scalars (``bool``, ``int``, ``float`` or NumPy scalar)
or NumPy arrays.
:param broadcast: the data is sent in real-time to the master, which
dispatches it. Returns a Notifier that can be used to mutate the
dataset.
dispatches it.
:param persist: the master should store the data on-disk. Implies
broadcast.
:param save: the data is saved into the local storage of the current
@ -238,7 +236,19 @@ class HasEnvironment:
return
if self.__dataset_mgr is None:
raise ValueError("Dataset manager not present")
return self.__dataset_mgr.set(key, value, broadcast, persist, save)
self.__dataset_mgr.set(key, value, broadcast, persist, save)
def mutate_dataset(self, key, index, value):
"""Mutate an existing dataset at the given index (e.g. set a value at
a given position in a NumPy array)
If the dataset was created in broadcast mode, the modification is
immediately transmitted."""
if self.__parent is not None:
self.__parent.mutate_dataset(key, index, value)
if self.__dataset_mgr is None:
raise ValueError("Dataset manager not present")
self.__dataset_mgr.mutate(key, index, value)
def get_dataset(self, key, default=NoDefault):
"""Returns the contents of a dataset.

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@ -218,20 +218,26 @@ class DatasetManager:
def set(self, key, value, broadcast=False, persist=False, save=True):
if persist:
broadcast = True
r = None
if broadcast:
self.broadcast[key] = (persist, value)
r = self.broadcast[key][1]
self.broadcast[key] = persist, value
if save:
self.local[key] = value
return r
def mutate(self, key, index, value):
target = None
if key in self.local:
target = self.local[key]
if key in self.broadcast.read:
target = self.broadcast[key][1]
if target is None:
raise KeyError("Cannot mutate non-existing dataset")
target[index] = value
def get(self, key):
try:
if key in self.local:
return self.local[key]
except KeyError:
pass
return self.ddb.get(key)
else:
return self.ddb.get(key)
def write_hdf5(self, f):
result_dict_to_hdf5(f, self.local)

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@ -38,19 +38,19 @@ class FloppingF(EnvExperiment):
def run(self):
l = len(self.frequency_scan)
frequency = self.set_dataset("flopping_f_frequency",
np.full(l, np.nan),
broadcast=True, save=False)
brightness = self.set_dataset("flopping_f_brightness",
np.full(l, np.nan),
broadcast=True)
self.set_dataset("flopping_f_frequency",
np.full(l, np.nan),
broadcast=True, save=False)
self.set_dataset("flopping_f_brightness",
np.full(l, np.nan),
broadcast=True)
self.set_dataset("flopping_f_fit", np.full(l, np.nan),
broadcast=True, save=False)
for i, f in enumerate(self.frequency_scan):
m_brightness = model(f, self.F0) + self.noise_amplitude*random.random()
frequency[i] = f
brightness[i] = m_brightness
self.mutate_dataset("flopping_f_frequency", i, f)
self.mutate_dataset("flopping_f_brightness", i, m_brightness)
time.sleep(0.1)
self.scheduler.submit(self.scheduler.pipeline_name, self.scheduler.expid,
self.scheduler.priority, time.time() + 20, False)