shapepipe.pipeline.str_handler
shapepipe.pipeline.str_handler¶
STRING HANDLER.
This module defines a class for handling string operations.
- Author
Axel Guinot
- class StrInterpreter(string, catalogue, make_compare=False, mask_dict=None)[source]¶
Bases:
objectString Interpreter Class.
Class to handle operation/comparison in a string.
- Parameters
string (str) – String to interpret
catralog (dict, recarray or str) – If type(catalogue) == str : assume a SExtractor fits catalogue and read parameter in it else : assume the catalogue is already open and look into it
make_compare (bool) – If true assume a comparison in the string
mask_dict (dict) – Dictionary containing mask usable for the operation
autorun (bool) – If true return directly the result
- interpret(string, make_compare=False, make_func=True, make_operate=True)[source]¶
Interpret.
This function handles the different possible operations
- Parameters
- Returns
Result of the current operation.
- Return type
array or float
Notes
This is a recursive function.
- _compare(string)[source]¶
Handle Comparison in a String.
This function transform condition in a string to real condition.
- Parameters
string (str) – strind containing the comparison.
- _apply_func(string)[source]¶
Parse Input String for Function Name and Apply Function.
- Parameters
str (string) – input string
- Returns
result of the function
- Return type
- _init_stat_function()[source]¶
Initialise Available Stat Functions.
Create a dictionary containing the functions.
- _mean(input)[source]¶
Get Mean.
Compute the mean of a distribution.
- Parameters
input (numpy.ndarray) – Numpy array containing the data.
- Returns
mean, if input array has size > 0; -1, otherwise
- Return type
- _mode(input, eps=0.001, iter_max=1000)[source]¶
Get Mode.
Compute the mode, the most frequent value of a continuous distribution.
- Parameters
input (numpy.ndarray) – Numpy array containing the data.
eps (float, optional) – Accuracy to achieve (default is 0.001)
iter_max (int, optional) – Maximum number of iterations
- Returns
mode, if input array has 10 or more elements; median, if input array has >0 and <10 elements; -1, if input array has 0 elements
- Return type
- _sigma_mad(input)[source]¶
Get Mean Absolute Deviation.
Compute median absolute deviation (MAD).
- Parameters
input (numpy.ndarray) – input data
- Returns
MAD, if input size > 0; -1 if input size is 0
- Return type
- _test_homogeneity(*args)[source]¶
Test Homogeneity.
Test homogeneity on 1D or 2D space.
- Parameters
param1 (numpy.ndarray) – Array on which the homogeneity test is performed
param2 (numpy.ndarray, optional) – Array on which the homogeneity test is performed
nb_cells (int) – Number of cells in the space. (note : has to be a square number)
- Returns
Percentage of inhomogeneity compared to worse possible case (based on the standard deviation)
- Return type
- _operate(string, string_split)[source]¶
Handle Operation in a String.
Make operation between catalogue’s parameters and/or numbers.
- Parameters
- Returns
Result of the operation
- Return type
Notes
It’s used as a recursive function
- _string_op_func(string_op, string_split, op, tmp)[source]¶
Perform a Specified Operation.
This function handle the posible operation between parameters.
- Parameters
string_op (list) – List of parameters to operate.
string_split (list) – The different parameter splitted using ‘*|/|\-|+s*(?![^()]*))’ as delimiter.
op (func) – The kind of operation provided as an operator function (Example : operator.sub).
tmp (str or float) – Temporary result of the global operation or value to initiate operation.
- Returns
Result of the operation or ‘pass’ if there are remaining operations
- Return type