# coding: utf-8
# Copyright (c) Max-Planck-Institut für Eisenforschung GmbH - Computational Materials Design (CM) Department
# Distributed under the terms of "New BSD License", see the LICENSE file.
"""
InteractiveBase class extends the Generic Job class with all the functionality to run the job object interactivley.
"""
from typing import Any, Optional
import numpy as np
from pyiron_base.database.filetable import FileTable
from pyiron_base.jobs.job.generic import GenericJob
__author__ = "Osamu Waseda, Jan Janssen"
__copyright__ = (
"Copyright 2020, Max-Planck-Institut für Eisenforschung GmbH - "
"Computational Materials Design (CM) Department"
)
__version__ = "1.0"
__maintainer__ = "Jan Janssen"
__email__ = "janssen@mpie.de"
__status__ = "production"
__date__ = "Sep 1, 2018"
[docs]
class InteractiveBase(GenericJob):
"""
InteractiveBase class extends the Generic Job class with all the functionality to run the job object interactively.
From this class all interactive Hamiltonians are derived. Therefore it should contain the properties/routines common
to all interactive jobs. The functions in this module should be as generic as possible.
Args:
project (ProjectHDFio): ProjectHDFio instance which points to the HDF5 file the job is stored in
job_name (str): name of the job, which has to be unique within the project
Attributes:
.. attribute:: job_name
name of the job, which has to be unique within the project
.. attribute:: status
execution status of the job, can be one of the following [initialized, appended, created, submitted, running,
aborted, collect, suspended, refresh, busy, finished]
.. attribute:: job_id
unique id to identify the job in the pyiron database
.. attribute:: parent_id
job id of the predecessor job - the job which was executed before the current one in the current job series
.. attribute:: master_id
job id of the master job - a meta job which groups a series of jobs, which are executed either in parallel or in
serial.
.. attribute:: child_ids
list of child job ids - only meta jobs have child jobs - jobs which list the meta job as their master
.. attribute:: project
Project instance the jobs is located in
.. attribute:: project_hdf5
ProjectHDFio instance which points to the HDF5 file the job is stored in
.. attribute:: job_info_str
short string to describe the job by it is job_name and job ID - mainly used for logging
.. attribute:: working_directory
working directory of the job is executed in - outside the HDF5 file
.. attribute:: path
path to the job as a combination of absolute file system path and path within the HDF5 file.
.. attribute:: version
Version of the hamiltonian, which is also the version of the executable unless a custom executable is used.
.. attribute:: executable
Executable used to run the job - usually the path to an external executable.
.. attribute:: library_activated
For job types which offer a Python library pyiron can use the python library instead of an external executable.
.. attribute:: server
Server object to handle the execution environment for the job.
.. attribute:: queue_id
the ID returned from the queuing system - it is most likely not the same as the job ID.
.. attribute:: logger
logger object to monitor the external execution and internal pyiron warnings.
.. attribute:: restart_file_list
list of files which are used to restart the calculation from these files.
.. attribute:: job_type
Job type object with all the available job types: ['ExampleJob', 'ParallelMaster', 'ScriptJob',
'ListMaster']
Examples:
In the default 'modal' mode calculation jobs can only be executed ones:
>>> job.run()
Still if you want to execute multiple similar calculations, you can execute them in interactive mode:
>>> with job.interactive_open() as job_int:
>>> # Do something with job_int
>>> job_int.run()
"""
[docs]
def __init__(
self, project: "pyiron_base.storage.hdfio.ProjectHDFio", job_name: str
):
super(InteractiveBase, self).__init__(project=project, job_name=job_name)
self._interactive_library = None
self._interactive_write_input_files = False
self._interactive_flush_frequency = 10000
self._interactive_write_frequency = 1
self.interactive_cache = {}
@property
def interactive_flush_frequency(self) -> int:
return self._interactive_flush_frequency
@interactive_flush_frequency.setter
def interactive_flush_frequency(self, frequency: int) -> None:
if not isinstance(frequency, int) or frequency < 1:
raise AssertionError("interactive_flush_frequency must be an integer>0")
if frequency < self._interactive_write_frequency:
raise ValueError(
"interactive_flush_frequency must be larger or equal to interactive_write_frequency"
)
self._interactive_flush_frequency = frequency
@property
def interactive_write_frequency(self) -> int:
return self._interactive_write_frequency
@interactive_write_frequency.setter
def interactive_write_frequency(self, frequency: int) -> None:
if not isinstance(frequency, int) or frequency < 1:
raise AssertionError("interactive_write_frequency must be an integer>0")
if self._interactive_flush_frequency < frequency:
self.interactive_flush_frequency = frequency
self._interactive_write_frequency = frequency
[docs]
def validate_ready_to_run(self) -> None:
"""
This should work but doesn't...
"""
if self._interactive_flush_frequency < self._interactive_write_frequency:
raise ValueError(
"interactive_write_frequency must be smaller or equal to interactive_flush_frequency"
)
def _run_if_running(self) -> None:
"""
Run the job if it is in the running state.
Returns:
None
"""
if self.server.run_mode.interactive:
self.run_if_interactive()
elif self.server.run_mode.interactive_non_modal:
self.run_if_interactive_non_modal()
else:
super(InteractiveBase, self)._run_if_running()
def _check_if_input_should_be_written(self) -> bool:
"""
Check if the input should be written.
Returns:
bool: True if the input should be written, False otherwise.
"""
return (
super(InteractiveBase, self)._check_if_input_should_be_written()
or self._interactive_write_input_files
)
[docs]
def interactive_is_activated(self) -> bool:
"""
Check if the interactive library is activated.
Returns:
bool: True if the interactive library is activated, False otherwise.
"""
if self._interactive_library is None:
return False
else:
return True
@staticmethod
def _extend_hdf(
h5: "pyiron_base.storage.hdfio.ProjectHDFio", path: str, key: str, data: Any
) -> None:
"""
Extend an existing HDF5 dataset with new data.
Args:
h5 (pyiron_base.storage.hdfio.ProjectHDFio): HDF5 file object.
path (str): Path to the dataset within the HDF5 file.
key (str): Name of the dataset.
data (Union[list, np.ndarray]): Data to be added to the dataset.
Returns:
None
"""
if path in h5.list_groups() and key in h5[path].list_nodes():
current_hdf = h5[path + "/" + key]
if isinstance(data, list):
entry = current_hdf.tolist() + data
else:
entry = current_hdf.tolist() + data.tolist()
data = np.array(entry)
h5[path + "/" + key] = data
@staticmethod
def _include_last_step(
array: np.ndarray, step: int = 1, include_last: bool = False
) -> np.ndarray:
"""
Returns a new array with elements selected at a given step size.
Args:
array (np.ndarray): The input array.
step (int, optional): The step size for selecting elements. Defaults to 1.
include_last (bool, optional): Whether to include the last element in the new array. Defaults to False.
Returns:
np.ndarray: The new array with selected elements.
"""
if step == 1:
return array
if len(array) > 0:
if len(array) > step:
new_array = array[::step]
index_lst = list(range(len(array)))
if include_last and index_lst[-1] != index_lst[::step][-1]:
new_array.append(array[-1])
return new_array
else:
if include_last:
return [array[-1]]
else:
return []
return []
[docs]
def interactive_flush(
self, path: str = "interactive", include_last_step: bool = False
) -> None:
"""
Flushes the interactive cache to the HDF5 file.
Args:
path (str): The path within the HDF5 file to store the flushed data.
include_last_step (bool): Whether to include the last step of the cache in the flushed data.
Returns:
None
"""
with self.project_hdf5.open("output") as h5:
for key in self.interactive_cache.keys():
if len(self.interactive_cache[key]) == 0:
continue
data = self._include_last_step(
array=self.interactive_cache[key],
step=self.interactive_write_frequency,
include_last=include_last_step,
)
try:
if (
len(data) > 0
and isinstance(data[0], list)
and len(np.shape(data)) == 1
):
self._extend_hdf(h5=h5, path=path, key=key, data=data)
elif np.array(data).dtype == np.dtype("O"):
self._extend_hdf(h5=h5, path=path, key=key, data=data)
else:
self._extend_hdf(h5=h5, path=path, key=key, data=np.array(data))
except ValueError:
self._extend_hdf(
h5=h5, path=path, key=key, data=np.array(data, dtype="object")
)
self.interactive_cache[key] = []
[docs]
def interactive_open(self) -> "pyiron_base.jobs.job.interactive.InteractiveBase":
"""
Set the run mode to interactive.
This is the same as setting :attr:`.server.run_mode.interactive`.
Must be called before :meth:`.run()` is called.
"""
self.server.run_mode.interactive = True
return _WithInteractiveOpen(self)
[docs]
def interactive_close(self) -> None:
"""
Stop interactive execution and sync interactive output cache.
Sets the job status to :attr:`~.JobStatus.finished`, :meth:`.run()` cannot be called after this.
"""
if (
len(list(self.interactive_cache.keys())) > 0
and len(self.interactive_cache[list(self.interactive_cache.keys())[0]]) != 0
):
self.interactive_flush(path="interactive", include_last_step=True)
self.project_hdf5.rewrite_hdf5()
self.status.finished = True
if not isinstance(self.project.db, FileTable):
self.run_time_to_db()
else:
self._hdf5["status"] = self.status.string
self._interactive_library = None
for key in self.interactive_cache.keys():
self.interactive_cache[key] = []
[docs]
def interactive_store_in_cache(self, key: str, value: Any) -> None:
"""
Store a value in the interactive cache.
Args:
key (str): The key to store the value under.
value (Any): The value to be stored.
Returns:
None
"""
self.interactive_cache[key] = value
[docs]
def run_if_interactive(self) -> None:
raise NotImplementedError("run_if_interactive() is not implemented!")
[docs]
def run_if_interactive_non_modal(self) -> None:
raise NotImplementedError("run_if_interactive_non_modal() is not implemented!")
[docs]
def to_hdf(
self,
hdf: Optional["pyiron_base.storage.hdfio.ProjectHDFio"] = None,
group_name: Optional[str] = None,
):
"""
Store the InteractiveBase object in the HDF5 File
Args:
hdf (ProjectHDFio): HDF5 group object - optional
group_name (str): HDF5 subgroup name - optional
"""
super(InteractiveBase, self).to_hdf(hdf=hdf, group_name=group_name)
with self.project_hdf5.open("input") as hdf5_input:
hdf5_input["interactive"] = {
"interactive_flush_frequency": self._interactive_flush_frequency,
"interactive_write_frequency": self._interactive_write_frequency,
}
[docs]
def from_hdf(
self,
hdf: Optional["pyiron_base.storage.hdfio.ProjectHDFio"] = None,
group_name: Optional[str] = None,
):
"""
Restore the InteractiveBase object in the HDF5 File
Args:
hdf (ProjectHDFio): HDF5 group object - optional
group_name (str): HDF5 subgroup name - optional
"""
super(InteractiveBase, self).from_hdf(hdf=hdf, group_name=group_name)
with self.project_hdf5.open("input") as hdf5_input:
if "interactive" in hdf5_input.list_nodes():
interactive_dict = hdf5_input["interactive"]
self._interactive_flush_frequency = interactive_dict[
"interactive_flush_frequency"
]
if "interactive_write_frequency" in interactive_dict.keys():
self._interactive_write_frequency = interactive_dict[
"interactive_write_frequency"
]
else:
self._interactive_write_frequency = 1
class _WithInteractiveOpen:
def __init__(self, job: InteractiveBase):
self._job = job
def __repr__(self) -> str:
return "Interactive ready"
def __enter__(self) -> InteractiveBase:
return self._job
def __exit__(self, exc_type, exc_val, exc_tb):
job_status = self._job.status.string
job_closed = self._job.interactive_close()
if job_status in ["aborted"]:
self._job.status.string = job_status
return job_closed
def __getattr__(self, attr):
error_message = (
"Syntax:\n"
+ "`your_job.interactive_open()`\n"
+ "`your_job.run()`\n"
+ "Alternatively you can use the `with`-statement:\n"
+ "`with your_job.interactive_open() as job_int:`\n"
+ "` job_int.run()`\n"
)
raise ValueError(error_message)
