Numeric Library Methods

getTopo
wxMask/discreteMask
sortUglyStr
getIndex
encodeEditArea
decodeEditArea
getindicies
offset
agradient
diff2
getGridShape

getTopo

def getTopo(self):
# Return the numeric topo grid

wxMask

def wxMask(self, wx, query, isreg=0):
       # Returns a numeric mask i.e. a grid of 0's and 1's
       # where the value is 1 if the given query succeeds
       # Arguments:
       #     wx -- a 2-tuple:
       #         wxValues : numerical grid of byte values
       #         keys : list of "ugly strings" where the index of
       #             the ugly string corresponds to the byte value in
       #             the wxValues grid.
       #     query -- a text string representing a query
       #     isreg -- if 1, the query is treated as a regular expression
       #         otherwise as a literal string
       # Examples:
       #     # Here we want to treat the query as a regular expression
       #     PoP = where(self.wxMask(wxTuple, "^Chc:", 1), maximum(40, PoP), PoP)
       #     # Here we want to treat the query as a literal
       #     PoP = where(self.wxMask(wxTuple, ":L:") maximum(5, PoP), PoP)
       #
      # See the Smart Tool Training Guide -- Numerical Tools and Working with Weather Section for more information.

discreteMask

def wxMask(self, wx, query, isreg=0):
       # Returns a numeric mask i.e. a grid of 0's and 1's
       # where the value is 1 if the given query succeeds
       # Arguments:
       #     wx -- a 2-tuple:
       #         values : numerical grid of byte values
       #         keys : list of "ugly strings" where the index of
       #             the ugly string corresponds to the byte value in
       #             the discreteValues grid.
       #     query -- a text string representing a query
       #     isreg -- if 1, the query is treated as a regular expression
       #         otherwise as a literal string
       # Examples:
       #     # Here we want to treat the query as a regular expression
       #     PoP = where(self.wxMask(wxTuple, "BlzrdWRN", 1), maximum(40, PoP), PoP)
       #     # Here we want to treat the query as a literal
       #     PoP = where(self.wxMask(wxTuple, "WintStmWRN") maximum(5, PoP), PoP)
       #

sortUglyStr

def sortUglyStr(self, uglyStr):
       # Sort the subkeys of uglyStr alphabetically.
       #
       # @param uglyStr: A key with "^"s separating subkeys
       # @type uglyStr: string
       # @return: uglyStr with alpha sorted subkeys.
       # @rtype: string

getIndex

def getIndex(self, uglyStr, keys):
       #     Returns the byte value that corresponds to the
       #     given ugly string. If the ugly string is not found a new key will be added
       #     and the index to the new entry will be returned. This method works for grids
       #     of type weather and discrete.
       # Arguments:
       #     uglyStr: a string representing a weather value or a discrete value
       #     keys: a list of ugly strings.
       #         A Wx argument represents a 2-tuple:
       #         wxValues : numerical grid of byte values
       #         keys : list of "ugly strings" where the index of
       #          the ugly string corresponds to the byte value in the wxValues grid.
       #         For example, if our keys are:
       #             "Sct:RW:-::"
       #             "Chc:T:-::"
       #             "Chc:SW:-::"
       #         Then, the wxValues grid will have byte values of 0 where
       #          there is "Sct:RW:-::", 1 where there is "Chc:T:-::"
       #          and 2 where there is "Chc:SW:-::"
       #
      # See the Smart Tool Training Guide -- Numerical Tools and Working with Weather Section for more information.

encodeEditArea

def encodeEditArea(self, editArea):
# Returns a numpy mask for the edit area
# "editArea" can be a named area or a ReferenceData object

decodeEditArea

def decodeEditArea(self, mask):
# Returns a ReferenceData object for the given mask

getindicies

def getindicies(self, o, l):

offset

def offset(self, a, x, y):
# Gives an offset grid for array, a, by x and y points

agradient

def agradient(self, a):
# Gives offset grids in the "forward" x and "up" y directions

diff2

def diff2(self, x, n=1, axis=-1):
      # diff2(x,n=1,axis=-1) calculates the first-order, discrete
      # center difference approximation to the derivative along the axis
      # specified. array edges are padded with adjacent values.

getGridShape

def getGridShape(self):
      # Get the grid shape from the GridLocation stored in the parm manager.
      #
      # @return: The number of data points in the X and Y directions.
      # @rtype: 2-tuple of int