"""
    Model dictionary:
    ----------------

    List all OCMIP models with their attributes.
    Graphical attributes for displaying each model when plot: letter and color.

    Plus same thing for other variables plot along with models.
    """


#
#   Here is the table of 1-letter codes(*) that should be used to designate the
#   OCMIP-2 models:

#   Code   Model
#   ----   -----
#   A     AWI    (Germany, Bremerhaven))
#   C     CSIRO  (Australia)
#   J     IGCR   (Japan)
#   I     IPSL   (France, Paris)
#   Ih    IPSL.DM1/GEO (same as IPSL.DM1(Hor) )
#   L     LLNL   (USA, Livermore)
#   M     MIT    (USA, Boston)
#   H     MPIM   (Germany, Hamburg)
#   N     NCAR   (USA, Colorado)
#   B     NERSC  (Norway, Bergen)
#   Z     PIUB   (Switzerland, Bern)
#   P     PRINCE (USA, Princeton Univeristy)
#   P2    PRINC2 (USA, Princeton University)
#   S     SOC    (UK, Southampton)
#   U     UL     (Belgium, Universite de Liege, Universite de Louvain)

#   Other:
#   F     PISCES (France, new model from IPSL -- Olivier Aumont)
#   X     Mean
#   Y     Median
#   D     Data (2nd data "reference", if it exists)

#   Note:
#   -----
#   All the original OCMIP-2 models have a 1-letter code.  Two-letter codes (Ih
#   and P2) are used to designate sensitivity tests with two of the OCMIP models
#   (I and P).



model_dictionary  = {\
"AWI":        { "code_letter": "A",  "color": 241 },  \
"CSIRO":      { "code_letter": "C",  "color": 242 },  \
"IGCR":       { "code_letter": "J",  "color": 243 },  \
"IPSL":       { "code_letter": "I",  "color": 244 },  \
"IPSL.DM1":   { "code_letter": "Ih", "color": 245 },  \
"LLNL":       { "code_letter": "L",  "color": 246 },  \
"MIT":        { "code_letter": "M",  "color": 247 },  \
"MPIM":       { "code_letter": "H",  "color": 248 },  \
"NCAR":       { "code_letter": "N",  "color": 249 },  \
"NERSC":      { "code_letter": "B",  "color": 250 },  \
"PIUB":       { "code_letter": "Z",  "color": 251 },  \
"PRINCE":     { "code_letter": "P",  "color": 252 },  \
"PRINC2":     { "code_letter": "P2", "color": 253 },  \
"SOC":        { "code_letter": "S",  "color": 254 },  \
"UL":         { "code_letter": "U",  "color": 255 },  \
"PISCES":     { "code_letter": "F",  "color": 241 },  \
}

other_dictionary  = {\
"Mean":       { "code_letter": "X",  "color": 242 },  \
"Median":     { "code_letter": "Y",  "color": 243 },  \
"Data_2":     { "code_letter": "D",  "color": 244 },  \
}