petitRADTRANS.utils

petitRADTRANS.utils#

Stores useful generic functions.

Classes#

LockedDict

Derivative of dict with a lock.

Functions#

`check_all_close`(a, b, **kwargs)
`class_init_args2class_args`(string)	Convenience code-writing function to convert a series of arguments into lines of initialization for a class.
`class_init_args2dict`(string)	Convenience code-writing function to convert a series of arguments into a dictionary.
`class2hdf5`(obj[, filename])	Convert an instance of a class into a HDF5 dataset.
`dataset2obj`(obj)	Convert a HDF5 dataset into a list of objects (float, int or str).
`dict2hdf5`(dictionary, hdf5_file[, group])	Convert a dictionary into a HDF5 dataset.
`copy_array_like`(array)	Copy a numpy or masked array without recursive Python deepcopy overhead.
`copy_mask_array`(array)	Copy the boolean mask associated with a masked array-like object.
`copy_parameter_value`(value)	Copy nested parameter values while leaving immutable scalars untouched.
`fill_object`(array, value)	Fill a numpy object array with a value.
`flatten_object`(array)	Flatten a numpy object array.
`hdf52dict`(hdf5_file)
`intersection_indices`(array1, array2)	Get the indices of the intersection between two sorted arrays in increasing order.
`list_str2str`(list_str[, separator])	Convert a list of strings into a string in which each input string is quoted and separated by 'separator'.
`load_csv`(file, **kwargs)
`remove_mask`(data, data_uncertainties)	Remove masked values of 3D data and linked uncertainties. TODO generalize this
`savez_compressed_record`(file, numpy_record_array)	Apply numpy.savez_compressed on a record array.
`topological_sort`(source)	Perform topological sort on a dictionary.
`tuple_init`(arg)
`user_input`(→ str \| int \| None)

Module Contents#

class petitRADTRANS.utils.LockedDict#

Bases: dict

Derivative of dict with a lock. Can be used to ensure that no new key is added once the lock is on, to prevent errors due to key typos.

_locked = False#

__copy__()#: Override the copy.copy method. Necessary to allow locked LockedDict to be copied.

__deepcopy__(memo)#: Override the copy.deepcopy method. Necessary to allow locked LockedDict to be copied.

__setitem__(key, value)#: Prevent a key to be added if the lock is on.

classmethod build_and_lock(dictionary=None, **kwargs)#: Instantiate a LockedDict and lock it.

lock()#

update(__m=None, **kwargs) → None#: Ensure that update takes the lock into account and do not remove keys.

unlock()#

tree_flatten()#

classmethod tree_unflatten(aux_data, children)#

petitRADTRANS.utils.check_all_close(a, b, **kwargs)#

petitRADTRANS.utils.class_init_args2class_args(string)#

Convenience code-writing function to convert a series of arguments into lines of initialization for a class. Useful to quickly write the __init__ function of a class from its arguments. Example:

>>> s = "arg1, arg2=0.3, arg3='a'"
>>> print(class_init_args2class_args(s))
output:
    self.arg1 = arg1
    self.arg2 = arg2
    self.arg3 = arg3

petitRADTRANS.utils.class_init_args2dict(string)#

Convenience code-writing function to convert a series of arguments into a dictionary. Useful to quickly write a dictionary from a long list of arguments. Example:

>>> s = "arg1, arg2=0.3, arg3='a'"
>>> print(class_init_args2class_args(s))
output:
    {
        'arg1': ,
        'arg2': ,
        'arg3': ,
    }

petitRADTRANS.utils.class2hdf5(obj, filename=None)#: Convert an instance of a class into a HDF5 dataset.

petitRADTRANS.utils.dataset2obj(obj)#: Convert a HDF5 dataset into a list of objects (float, int or str).

petitRADTRANS.utils.dict2hdf5(dictionary, hdf5_file, group='/')#: Convert a dictionary into a HDF5 dataset.

petitRADTRANS.utils.copy_array_like(array)#: Copy a numpy or masked array without recursive Python deepcopy overhead.

petitRADTRANS.utils.copy_mask_array(array)#: Copy the boolean mask associated with a masked array-like object.

petitRADTRANS.utils.copy_parameter_value(value)#: Copy nested parameter values while leaving immutable scalars untouched.

petitRADTRANS.utils.fill_object(array, value)#: Fill a numpy object array with a value.

petitRADTRANS.utils.flatten_object(array)#: Flatten a numpy object array.

petitRADTRANS.utils.hdf52dict(hdf5_file)#

petitRADTRANS.utils.intersection_indices(array1: numpy.typing.NDArray, array2: numpy.typing.NDArray)#

Get the indices of the intersection between two sorted arrays in increasing order.

For example, if array1 is [0.1, …, 0.3, …, 3] and array2 is interval [0.3, …, 3, …, 28], then the output indices will be the indices corresponding to [0.3, …, 3] in both arrays.

Args:: array1: the first array array2: the second array
Returns:: The indices of the intersection between both arrays, for the first and the second array.

petitRADTRANS.utils.list_str2str(list_str, separator: str = ', ')#

Convert a list of strings into a string in which each input string is quoted and separated by ‘separator’. Example:

>>> list_str2str(('AA', 'BBB', 'C'))
>>> "'AA', 'BBB', 'C'"

petitRADTRANS.utils.load_csv(file, **kwargs)#

petitRADTRANS.utils.remove_mask(data, data_uncertainties)#

Remove masked values of 3D data and linked uncertainties. TODO generalize this An array of objects is created if the resulting array is jagged.

Args:: data: 3D masked array data_uncertainties: 3D masked array
Returns:: The data and errors without the data masked values, and the mask of the original data array.

petitRADTRANS.utils.savez_compressed_record(file, numpy_record_array)#: Apply numpy.savez_compressed on a record array.

petitRADTRANS.utils.topological_sort(source)#

Perform topological sort on a dictionary.

Source: https://stackoverflow.com/questions/11557241/python-sorting-a-dependency-list

Args:: source: dictionary of {name: [list of dependencies]} pairs
Returns:: list of names, with dependencies listed first

petitRADTRANS.utils.tuple_init(arg)#

petitRADTRANS.utils.user_input(introduction_message: str, input_message: str, failure_message: str, cancel_message: str, mode: str, max_attempts: int = 5, list_length: int = None) → str | int | None#