Source code for hbp_nrp_cleserver.bibi_config.bibi_configuration_script

# This file is part of the Neurorobotics Platform software
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# The Human Brain Project is a European Commission funded project
# in the frame of the Horizon2020 FET Flagship plan.
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# of the License, or (at your option) any later version.
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Script to run CLE from BIBI Configuration File
from hbp_nrp_commons.generated import bibi_api_gen
# We use many of the bibi helper functions here and newly added helper functions should be
# visible to the template(s) immediate, thus the wildcard-import
# pylint: disable=wildcard-import, unused-wildcard-import
from hbp_nrp_commons.bibi_functions import *

__author__ = 'GeorgHinkel'

import os
import re
import logging
import warnings

logger = logging.getLogger(__name__)

tf_name_regex = re.compile(r'^.*def\s+(\w+)\s*\(.*', flags=re.MULTILINE)

[docs]def deprecated(func): # pragma: no cover """This is a decorator which can be used to mark functions as deprecated. It will result in a warning being emmitted when the function is used.""" def newFunc(*args, **kwargs): """ Deprecation warning """ message = "Call to deprecated function %s." % func.__name__ warnings.warn(message, category=DeprecationWarning) logger.warning(message) return func(*args, **kwargs) newFunc.__name__ = func.__name__ newFunc.__doc__ = func.__doc__ newFunc.__dict__.update(func.__dict__) return newFunc
FOUR_SPACES = " " * 4
[docs]def correct_indentation(text, first_line_indent_level, indent_string=FOUR_SPACES): """ Adapts the indentation of the given code in order to paste it into the generated script. The indentation of the given text is determined based on the first content line (first line which consists not only of white spaces). The indentation must either use four spaces or a tab character. :param text: the original input to adapt :param first_line_indent_level: the target indentation level of the entire block :type first_line_indent_level: int :param indent_string: (Optional): the pattern for one level of indentation :return: the adapted text """ text.replace("\t", indent_string) lines = text.split("\n") result = [] first_line_indent = None for line in lines: if line.lstrip(): if first_line_indent is None and line: first_line_stripped = line.lstrip() first_line_indent = line[:len(line) - len(first_line_stripped)] result.append(indent_string * first_line_indent_level + line[len(first_line_indent):]) else: result.append("\n") return "\n".join(result)
[docs]def get_tf_name(tf_code): """ Returns the function name of transfer function code @param tf_code: string with transfer function code @return: function name """ ret = re.findall(tf_name_regex, tf_code) return ret[0] if ret else None
[docs]def generate_tf(tf, external_tf_path=None): """ Generates the code for the given transfer function :param tf: The transfer function to generate code for :param external_tf_path: Base folder where external python TFs are stored :return: A unicode string with the generated code """ if hasattr(tf, "src") and tf.src: # If the "src" tag is specified, ignore embedded code (if present) assert isinstance(tf, bibi_api_gen.PythonTransferFunction) assert external_tf_path is not None del tf.orderedContent()[:] with open(os.path.join(external_tf_path, tf.src)) as f: tf_source = correct_indentation(, 0) else: tf_source = '\n'.join(correct_indentation(cont.value, 0) for cont in tf.orderedContent()) return ''.join(line for line in tf_source.splitlines(True) if not line.isspace())