This is the initial version.

README

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+CUPiDO - Connecting Undifferenced Points in Deformation Observations
+
+The CUPiDO software enables a standardized approach for the analysis
+and preparation of geodetic data for the use in geophysi-
+cal modeling. The approach resolves the problem of non-
+uniformity in the datasets obtained by different measurement
+techniques. 
+
+The approach is based on two main steps: uniformization
+of the data using a standardized data format (NetCDF), and
+the application of the CUPiDO conversion tool to construct
+double-difference observations.
+
+The CUPiDO software is structured in three directories:
+
+    create_netcdf
+        scripts to generate the standardized NetCDF data files
+        (currently in Matlab only).
+
+    create_double_differences
+        conversion tool to generate an optimal set of double 
+        differences based on the NetCDF data files (in Python2).
+
+    example
+        An example setup to demonstrate the CUPiDO software.
+
+
+(c) Delft University of Technology, 2017
+

create_double_differences/CHANGELOG

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+Version: 1.0, 19 September 2016
+- initial version
+
+Version: 1.1, 29 September 2016
+- enabling different benchmark classes
+- selection with or without outliers
+- polygon selection
+
+Version: 1.1.1, 7 October 2016
+- better handling of nan values in region of interest check (avoiding warning)
+
+Version: 1.1.2, 9 October 2016
+- bug fix in case SD observations of a single epoch are selected (and therefore no DD can be formed)
+
+Version: 1.1.3, 4 November 2016
+- bug fix in indexing
+
+Version: 1.1.4, 14 February 2017
+- implementation of unique benchmark list (for combined levelling/gps data)
+- detection and removal of dependent DD observations
+- removal of maximum number of allowed iteration in SD to DD transformation
+- format change of dates in default cupido.py settings
+

create_double_differences/README

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+CUPiDO - Connecting Undifferenced Points in Deformation Observations
+
+The CUPiDO conversion tool creates the optimal set of double-difference geodetic
+(GPS and leveling) measurements and its corresponding covariance matrix 
+based on the user input: Period of interest (POI), Region of interest (ROI),
+and technique of interest (TOI). 
+
+The software includes one main function and eight subfunctions:
+
+    cupido.py (main function)
+        For the detailed description of Inputs/Outputs of cupido.py, see
+            the header of cupido.py.     
+
+    construct_sd2dd_transformation_gps.py
+        This subfunction constructs the single-to-double difference transformation
+        for both leveling and GPS data.
+
+    construct_sd2dd_transformation.py	
+        This subfunction constructs the single-to-double difference transformation
+        for both leveling and leveling data.
+
+    construct_st_idealization_covmx.py
+        This subfunction constructs the covariance matrix associated with the 
+        spatio-temporally correlated component of idealization noise.
+
+    construct_t_idealization_covmx.py
+        This subfunction constructs the covariance matrix associated with the 
+        temporally correlated component of idealization noise.
+
+    csv_idealization_reading.py
+        This subfunction reads the idealization noise parameters from the database	     
+	(See the header of 'cupido.py' for more info about the input database).
+
+    csv_polygon_reading.py
+        This subfunction reads the polygon of the ROI.
+
+    netcdf_reading.py
+        This subfunction reads the geodetic observations from the database
+        (See the header of 'cupido.py' for more info about the input database)
+
+    cupido_logging.py
+        Logging subfunction.
+
+For the detailed description of Inputs/Outputs of cupido.py, see the 
+header of cupido.py.  
+
+
+(c) Delft University of Technology, 2017
+