Merge branch 'main' of https://github.com/RasmusBahbah/carra2py

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`` 
+
+
+

docs/Introduction.rst

@@ -13,6 +13,8 @@ Installation
 **Clone the repository:**
     ``git clone [email protected]: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      |
++----------------------+-------------+
+

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** 

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**