opengate.utility
================

.. py:module:: opengate.utility


Attributes
----------

.. autoapisummary::

   opengate.utility.git
   opengate.utility.g4_units


Classes
-------

.. autoapisummary::

   opengate.utility.LazyModuleLoader


Functions
---------

.. autoapisummary::

   opengate.utility.assert_equal_dic
   opengate.utility.ensure_directory_exists
   opengate.utility.get_material_name_variants
   opengate.utility.g4_best_unit
   opengate.utility.g4_best_unit_tuple
   opengate.utility.assert_key
   opengate.utility.assert_keys
   opengate.utility.indent
   opengate.utility.assert_unique_element_name
   opengate.utility.make_builders
   opengate.utility.read_mac_file_to_commands
   opengate.utility.ensure_filename_is_str
   opengate.utility.insert_suffix_before_extension
   opengate.utility.get_random_folder_name
   opengate.utility.get_rnd_seed
   opengate.utility.DDF
   opengate.utility.DD
   opengate.utility.print_dic
   opengate.utility.get_release_date
   opengate.utility.get_gate_folder
   opengate.utility.get_data_folder
   opengate.utility.get_tests_folder
   opengate.utility.get_contrib_path
   opengate.utility.print_opengate_info
   opengate.utility.calculate_variance
   opengate.utility.standard_error_c4_correction


Module Contents
---------------

.. py:class:: LazyModuleLoader(module_name)

   Lazy loading allows you to delay the loading of a module until it's actually needed.
   This can be useful if a module is expensive to load or if it may not be used in
   every execution of the program.
   We use it for some modules that was found to delay the startup time, in particular:
   - radioactivedecay and pandas in phidsources
   - torch and gaga in gansources (only required for some features)


   .. py:attribute:: module_name


   .. py:attribute:: module
      :value: None



   .. py:method:: __getattr__(name)


.. py:data:: git

.. py:function:: assert_equal_dic(d1, d2, name='')

.. py:function:: ensure_directory_exists(directory)

.. py:data:: g4_units

.. py:function:: get_material_name_variants(material_name)

   Get different variants of a material name, e.g. with/without prepended G4_, only first letter capital.
   Intended to bridge inconsistencies in naming conventions.


.. py:function:: g4_best_unit(value, unit_type)

.. py:function:: g4_best_unit_tuple(value, unit_type)

.. py:function:: assert_key(key: str, d: box.Box)

.. py:function:: assert_keys(keys: list, d: box.Box)

.. py:function:: indent(amount, text, ch=' ')

   Prefix the text with indent spaces
   https://stackoverflow.com/questions/8234274/how-to-indent-the-contents-of-a-multi-line-string


.. py:function:: assert_unique_element_name(elements, name)

.. py:function:: make_builders(class_names)

   Consider a list of Classname. For each, it builds a key/value, with:
   - the type of the class as key
   - and a lambda function that create an object of this class as value


.. py:function:: read_mac_file_to_commands(filename)

.. py:function:: ensure_filename_is_str(filename)

.. py:function:: insert_suffix_before_extension(file_path, suffix, suffix_separator='-')

.. py:function:: get_random_folder_name(size=8, create=True)

.. py:function:: get_rnd_seed(seed)

.. py:function:: DDF()

   Debug print current Function name


.. py:function:: DD(arg)

   Debug print variable name and its value


.. py:function:: print_dic(dic)

.. py:function:: get_release_date(opengate_version)

.. py:function:: get_gate_folder()

.. py:function:: get_data_folder()

.. py:function:: get_tests_folder()

.. py:function:: get_contrib_path()

.. py:function:: print_opengate_info()

   Print information about OpenGate and the environment


.. py:function:: calculate_variance(value_array, squared_value_array, number_of_samples)

.. py:function:: standard_error_c4_correction(n)

   Parameters
   ----------
   n : integer
       Number of subsets (of the samples).

   Returns
   -------
   c4 : double
       Factor to convert the biased standard error of the mean of subsets of the sample into an unbiased
       -  assuming a normal distribution .
       Usage: standard_error(unbiased) = standard_deviation_of_mean(=biased) / c4
       The reason is that the standard deviation of the mean of subsets of the sample X underestimates the true standard error. For n = 2 this underestimation is about 25%.

       Values for c4: n=2: 0.7979; n= 9: 0.9693