Changeset 991df6a in flex_extract.git for python/Disagg.py


Ignore:
Timestamp:
May 14, 2018, 10:11:29 PM (6 years ago)
Author:
Anne Philipp <anne.philipp@…>
Branches:
master, ctbto, dev
Children:
812283d
Parents:
efdb01a
Message:

finished documentation (except plot_retrieved)

File:
1 edited

Legend:

Unmodified
Added
Removed
  • python/Disagg.py

    refdb01a r991df6a  
    33#************************************************************************
    44# TODO AP
    5 # - make a class out of this ???
    6 # - write a test class
     5# - check alist of size 4 ?
     6# - write a test, IMPORTANT
    77#************************************************************************
    8 """
    9 @Author: Anne Philipp (University of Vienna)
     8#*******************************************************************************
     9# @Author: Anne Philipp (University of Vienna)
     10#
     11# @Date: March 2018
     12#
     13# @Change History:
     14#    November 2015 - Leopold Haimberger (University of Vienna):
     15#        - migration of the methods dapoly and darain from Fortran
     16#          (flex_extract_v6 and earlier) to Python
     17#
     18#    April 2018 - Anne Philipp (University of Vienna):
     19#        - applied PEP8 style guide
     20#        - added structured documentation
     21#        - outsourced the disaggregation functions dapoly and darain
     22#          to a new module named Disagg
     23#
     24# @License:
     25#    (C) Copyright 2015-2018.
     26#
     27#    This software is licensed under the terms of the Apache Licence Version 2.0
     28#    which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
     29#
     30# @Module Description:
     31#    Disaggregation of deaccumulated flux data from an ECMWF model FG field.
     32#    Initially the flux data to be concerned are:
     33#    - large-scale precipitation
     34#    - convective precipitation
     35#    - surface sensible heat flux
     36#    - surface solar radiation
     37#    - u stress
     38#    - v stress
     39#    Different versions of disaggregation is provided for rainfall
     40#    data (darain, modified linear) and the surface fluxes and
     41#    stress data (dapoly, cubic polynomial).
     42#
     43# @Module Content:
     44#    - dapoly
     45#    - darain
     46#
     47#*******************************************************************************
    1048
    11 @Date: March 2018
    12 
    13 @ChangeHistory:
    14     November 2015 - Leopold Haimberger (University of Vienna):
    15         - integrated methods dapoly and darain from Fortran to Python
    16 
    17     April 2018 - Anne Philipp (University of Vienna):
    18         - applied PEP8 style guide
    19         - added structured documentation
    20         - outsourced the disaggregation functions dapoly and darain
    21           to a new module named Disagg
    22 
    23 @License:
    24     (C) Copyright 2015-2018.
    25 
    26     This software is licensed under the terms of the Apache Licence Version 2.0
    27     which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
    28 
    29 @Requirements:
    30     A standard python 2.6 or 2.7 installation
    31 
    32 @Description:
    33     Further documentation may be obtained from www.flexpart.eu.
    34 
    35     Functionality provided:
    36         Disaggregation of deaccumulated flux data from an ECMWF model FG field.
    37         Initially the flux data to be concerned are:
    38         - large-scale precipitation
    39         - convective precipitation
    40         - surface sensible heat flux
    41         - surface solar radiation
    42         - u stress
    43         - v stress
    44 
    45         Different versions of disaggregation is provided for rainfall
    46         data (darain, modified linear) and the surface fluxes and
    47         stress data (dapoly, cubic polynomial).
    48 
    49 """
    5049# ------------------------------------------------------------------------------
    5150# MODULES
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