Plugin Template With Detailed Notes 1ΒΆ
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# Copyright 2014 Diamond Light Source Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# the information below is used in the auto-API creation for documentation
# and the synopsis appears in the configurator.
"""
.. module:: plugin_template1_with_detailed_notes
:platform: Unix
:synopsis: A template to create a simple plugin that takes one dataset as\
input and returns a similar dataset as output.
.. moduleauthor:: Developer Name <email@address.ac.uk>
"""
from savu.plugins.plugin import Plugin
from savu.plugins.driver.cpu_plugin import CpuPlugin
from savu.plugins.utils import register_plugin
# this decorator is required for the configurator to recognise the plugin
@register_plugin
class PluginTemplate1WithDetailedNotes(Plugin, CpuPlugin):
# Each class must inherit from the Plugin class and a driver
def __init__(self):
super(PluginTemplate1WithDetailedNotes, self).__init__('PluginTemplate1WithDetailedNotes')
def nInput_datasets(self):
# Called immediately after the plugin is loaded in to the framework
return 1
def nOutput_datasets(self):
# Called immediately after the plugin is loaded in to the framework
return 1
def setup(self):
# This method is called after the number of in/out datasets associated
# with the plugin has been established. It tells the framework all
# the information it needs to know about the data transport to-and-from
# the plugin.
#================== Input and output datasets =========================
# in_datasets and out_datasets are instances of the Data class.
# in_datasets were either created in the loader or as output from
# previous plugins. out_datasets objects have already been created at
# this point, but they are empty and need to be populated.
# Get the Data instances associated with this plugin
in_dataset, out_dataset = self.get_datasets()
# see https://savu.readthedocs.io/en/latest/api/savu.data.data_structures.data_create/
# for more information on creating datasets.
# Populate the output dataset(s)
out_dataset[0].create_dataset(in_dataset[0])
#================== Input and output plugin datasets ==================
# in_pData and out_pData are instances of the PluginData class.
# All in_datasets and out_datasets above have an in/out_pData object
# attached to them temporarily for the duration of the plugin,
# giving access to additional plugin-specific dataset details. At this
# point they have been created but not yet populated.
# Get the PluginData instances attached to the Data instances above
in_pData, out_pData = self.get_plugin_datasets()
# Each plugin dataset must call this method and define the data access
# pattern and number of frames required.
in_pData[0].plugin_data_setup('SINOGRAM', 'single')
# 'single', 'multiple' or an int (should only be used if essential)
out_pData[0].plugin_data_setup('SINOGRAM', 'single')
# All dataset information can be accessed via the Data and PluginData
# instances
def pre_process(self):
# This method is called once before any processing has begun.
# Access parameters from the doc string in the parameters dictionary
# e.g. self.parameters['example']
pass
def process_frames(self, data):
# This function is called in a loop by the framework until all the
# data has been processed.
# Each iteration of the loop will receive a list of numpy arrays
# (data) containing nInput_datasets with the data sliced as requested
# in the setup method (SINOGRAM in this case). If 'multiple' or an
# integer number of max_frames are requested the array with have an
# extra dimension.
# This plugin has one output dataset, so a single numpy array (a
# SINOGRAM in this case) should be returned to the framework.
return data[0]
def post_process(self):
# This method is called once after all processing has completed
# (after an MPI barrier).
pass
from savu.plugins.plugin_tools import PluginTools
# Each plugin consists of two Python modules
# - A plugin containing the processing
# - A tools file containing the parameter and citation details
# Each plugin must have a complementary plugin file of the same name
# concatenated with "_tools.py"
class PluginTemplate1WithDetailedNotesTools(PluginTools):
"""
A description of the plugin - the synopsis from the main plugin
file appears as the short plugin description in the configurator
and anything written here appears as the longer description (-vv flag).
"""
def define_parameters(self):
"""
example:
visibility: basic
dtype: [None, str]
description: Example of a plugin parameter
default: None
"""