diff --git a/docs/Examples.rst b/docs/Examples.rst index 64ec27e..b44f725 100644 --- a/docs/Examples.rst +++ b/docs/Examples.rst @@ -2,4 +2,112 @@ ================ Examples ================ -lars lars + +Several examples of how to use the carra2py modules and methods, and the utility scripts. +All the examples assume that the user has installed the package correctly, has activated the python environemt and is in the correct folder (/user/carra2py). + + +carra2py.AVHRR() +================ + +These examples are executed in a python console, the chosen date is 6th of May, 1994 + +**First import the carra2py package** + ``import carra2py`` + +**and then input the date in the carra2py.AVHRR() module** + ``avhrr = carra2py.AVHRR("19940506")`` + +How to get the raw data +------------------------ + +**get the data in EPSG:4326 using the get_data() method** + ``rawdata = avhrr.get_data()`` + +**or get the data in EPSG:3413 using the get_data() method** + ``rawdata = avhrr.get_data(polar=True)`` + +How to process data +-------------------- +the default settings is set to process for all regions with a resolution of 2500 meters. +Note that the region names have the same spelling as in the table in the introduction section. + +**Process with default settings** + ``output = avhrr.proc()`` + +**Process for Greenland, Iceland and AlaskaYukon, with a 1000 m resolution** + ``output = avhrr.proc(area = ["Greenland","Iceland","AlaskaYukon"],res=1000)`` + +**Process with rawdata from user, see "carra2py Modules and Methods" for input specifications** + ``output = avhrr.proc(raw_data=rawdata)`` + +How to export data +-------------------- +the default export settings is set to process for all regions with a resolution of 2500 meters. + +**Export as tif with default settings** + ``avhrr.export_to_tif()`` + +**Export as csv with default settings** + ``avhrr.export_to_csv()`` + +**Export as netcdf with default settings** + ``avhrr.export_to_nc()`` + +**Export user defined processed data as tif** + ``avhrr.export_to_tif(output=output)`` + +**Export user defined processed data as netcdf in specfic folder** + ``avhrr.export_to_nc(output=output,path="home/carra2py/john/statoil")`` + +multiexec.py +================ + +These examples are executed as command lines in a terminal, in your carra2py environment. +The default settings is set to process for all regions with a resolution of 2500 meters using 4 CPU cores and then export as tif files. +Please note, the user must input a start and end date for the processing. +These examples are all exectued with the time period 1st of January, 1982 - 31th of December, 2022. + +How to process several dates +----------------------------- +**Process with default settings** + ``python multiexec.py -st 19820101 -en 20221231`` + + **Process with 1000 meter resolution** + ``python multiexec.py -st 19820101 -en 20221231 -re 1000`` + +How to process specific areas +------------------------------ +**Process for Svalbard, NorthernArcticCanada and SevernayaZemlya** + ``python multiexec.py -st 19820101 -en 20221231 -ar [Svalbard,NorthernArcticCanada,SevernayaZemlya]`` + +**Process for Greenland and Iceland with 1000 meter resolution** + ``python multiexec.py -st 19820101 -en 20221231 -ar [Greenland,Iceland] -re 1000`` + +How to change output format +----------------------------- + +**Process with default settings and then export as netcdf files** + ``python multiexec.py -st 19820101 -en 20221231 -o nc`` + +**Process with default settings and then export as csv files** + ``python multiexec.py -st 19820101 -en 20221231 -o csv`` + +How to change the number of cores used +-------------------------------------- + +**Process using 8 cores** + ``python multiexec.py -st 19820101 -en 20221231 -c 8`` + +**Process using 1 core** + ``python multiexec.py -st 19820101 -en 20221231 -c 1`` + + +Example with all arguments +-------------------------------------- + +**Process using 6 cores, for Norway and NovayaZemlya, with a 5000 meter resolution, and then export as netcdf** + ``python multiexec.py -st 19820101 -en 20221231 -ar [Norway,NovayaZemlya] -c 6 -re 5000 -o nc`` + + + diff --git a/docs/Introduction.rst b/docs/Introduction.rst index 5701034..da3f656 100644 --- a/docs/Introduction.rst +++ b/docs/Introduction.rst @@ -13,6 +13,8 @@ Installation **Clone the repository:** ``git clone git@github.com:RasmusBahbah/carra2py.git`` +**Or download from https://github.com/RasmusBahbah/carra2py:** + **Change into the top-level directory:** ``cd carra2py`` @@ -27,3 +29,32 @@ Dependencies ================ Python 3.5 or up + + +Processing Regions +================ + +The latest carra2py version can process 9 different Regions: + ++----------------------+-------------+ +| Region | area [km^2] | ++======================+=============+ +| Greenland | 1,744,666 | ++----------------------+-------------+ +| Norway | 34,018 | ++----------------------+-------------+ +| Svalbard | 32,506 | ++----------------------+-------------+ +| Iceland | 11,489 | ++----------------------+-------------+ +| NorthernArcticCanada | 100,691 | ++----------------------+-------------+ +| SouthernArcticCanada | 40,970 | ++----------------------+-------------+ +| AlaskaYukon | 96,909 | ++----------------------+-------------+ +| NovayaZemlya | 21,506 | ++----------------------+-------------+ +| SevernayaZemlya | 15,842 | ++----------------------+-------------+ + diff --git a/docs/Processing scripts.rst b/docs/Processing scripts.rst index 69745cd..5741a8c 100644 --- a/docs/Processing scripts.rst +++ b/docs/Processing scripts.rst @@ -3,4 +3,25 @@ Processing Scripts ================ -hkllh +Description of utility scripts for carra2py. + + +multiexec.py: +================ + +An executable script used for processing and exporting albedo data over multiple dates in a defined time period. It is also possible to use multiple CPU cores to speed the process. + +Arguments: +---------------- + +**-st: the start date of the process period in the format "yyyymmdd"** + +**-en: the end date of the process period in the format "yyyymmdd"** + +**-re: the wanted ouput resolution in meters, there are three choices [1000,2500,5000], default is set to 2500** + +**-ar: the wanted areas to process, default is set to process for all areas** + +**-o: the wanted output format, there are three choices ["tif","csv","nc"], the default is set to "tif"** + +**-c: number of CPU cores the user want to use. The default is set to 4** diff --git a/docs/carra2py methods.rst b/docs/carra2py methods.rst index ab3229e..f198a4b 100644 --- a/docs/carra2py methods.rst +++ b/docs/carra2py methods.rst @@ -8,7 +8,7 @@ Description of the carra2py modules and its methods. class carra2py.AVHRR(date): ================ -Parameter: date: str +Attributes: date: str ---------------- the processed date, only in 'yyyymmdd' format @@ -84,8 +84,7 @@ Export the processed data to tif files in ESPG:3413 AVHRR.export_to_csv(output=None, path='default') ~~~~~~~~~~~~~~~~ -Export the processed data to csv files in ESPG:3413, the format will be - +Export the processed data to csv files in ESPG:3413, the files will include three columns "x", "y" and "albedo" with length m*n **Parameter: output: dict** @@ -104,7 +103,7 @@ Export the processed data to csv files in ESPG:3413, the format will be AVHRR.export_to_nc(output=None, path='default') ~~~~~~~~~~~~~~~~ -Export the processed data to netcdf4 files in ESPG:3413, the format will be +Export the processed data to netcdf4 files in ESPG:3413, the files will include three variables "x", "y" and "albedo" with shape (m,n) **Parameter: output: dict**