source: trunk/anuga_core/source/anuga/damage_modelling/exposure.py @ 8125

import csv

from anuga.anuga_exceptions import TitleValueError, \
                                    DataMissingValuesError

from anuga.file.csv_file import load_csv_as_dict

from anuga.geospatial_data.geospatial_data import Geospatial_data,\
     ensure_absolute

LAT_TITLE = 'LATITUDE'
LONG_TITLE = 'LONGITUDE'
X_TITLE = 'x'
Y_TITLE = 'y'



class Exposure:
    '''
    Class for National Exposure Database storage (NEXIS).
    Returns a csv file handle
    '''
    def __init__(self,file_name, latitude_title=LAT_TITLE,
                 longitude_title=LONG_TITLE, is_x_y_locations=None,
                 x_title=X_TITLE, y_title=Y_TITLE,
                 refine_polygon=None, title_check_list=None):
        """
        This class is for handling the exposure csv file.
        It reads the file in and converts the lats and longs to a geospatial
        data object.
        Use the methods to read and write columns.

        The format of the csv files it reads is;
           The first row is a title row.
           comma's are the delimiters
           each column is a 'set' of data

        Feel free to use/expand it to read other csv files.

        It is not for adding and deleting rows

        Can geospatial handle string attributes? It's not made for them.
        Currently it can't load and save string att's.

        So just use geospatial to hold the x, y and georef? Bad, since
        different att's are in diferent structures.  Not so bad, the info
        to write if the .csv file is saved is in attribute_dic

        The location info is in the geospatial attribute.
        """

        self._file_name = file_name
        self._geospatial = None #

        # self._attribute_dic is a dictionary.
        #The keys are the column titles.
        #The values are lists of column data

        # self._title_index_dic is a dictionary.
        #The keys are the column titles.
        #The values are the index positions of file columns.
        self._attribute_dic, self._title_index_dic = \
            load_csv_as_dict(self._file_name, \
            title_check_list=title_check_list)
        try:
            #Have code here that handles caps or lower
            lats = self._attribute_dic[latitude_title]
            longs = self._attribute_dic[longitude_title]
        except KeyError:
            # maybe a warning..
            #Let's see if this works..
            if False != is_x_y_locations:
                is_x_y_locations = True
            pass
        else:
            self._geospatial = Geospatial_data(latitudes=lats,
                                               longitudes=longs)

        if is_x_y_locations is True:
            if self._geospatial is not None:
                pass #fixme throw an error
            try:
                xs = self._attribute_dic[x_title]
                ys = self._attribute_dic[y_title]
                points = [[float(i),float(j)] for i,j in map(None,xs,ys)]
            except KeyError:
                # maybe a warning..
                msg = "Could not find location information."
                raise TitleValueError, msg
            else:
                self._geospatial = Geospatial_data(data_points=points)

        # create a list of points that are in the refining_polygon
        # described by a list of indexes representing the points

    ##
    # @brief Create a comparison method.
    # @param self This object.
    # @param other The other object.
    # @return True if objects are 'same'.
    def __cmp__(self, other):
        #check that 'other' is an instance of this class
        if isinstance(self, type(other)):
            result = cmp(self._attribute_dic, other._attribute_dic)
            if result <> 0:
                return result

            # The order of the columns is important. Therefore..
            result = cmp(self._title_index_dic, other._title_index_dic)
            if result <> 0:
                return result
            for self_ls, other_ls in map(None, self._attribute_dic,
                                         other._attribute_dic):
                result = cmp(self._attribute_dic[self_ls],
                             other._attribute_dic[other_ls])
                if result <> 0:
                    return result
            return 0
        else:
            return 1

    ##
    # @brief Get a list of column values given a column name.
    # @param column_name The name of the column to get values from.
    # @param use_refind_polygon Unused??
    def get_column(self, column_name, use_refind_polygon=False):
        """
        Given a column name return a list of the column values

        Note, the type of the values will be String!
        do this to change a list of strings to a list of floats
        time = [float(x) for x in time]

        Not implemented:
        if use_refind_polygon is True, only return values in the
        refined polygon
        """

        if not self._attribute_dic.has_key(column_name):
            msg = 'There is no column called %s!' % column_name
            raise TitleValueError, msg

        return self._attribute_dic[column_name]

    ##
    # @brief ??
    # @param value_column_name ??
    # @param known_column_name ??
    # @param known_values ??
    # @param use_refind_polygon ??
    def get_value(self, value_column_name, known_column_name,
                  known_values, use_refind_polygon=False):
        """
        Do linear interpolation on the known_colum, using the known_value,
        to return a value of the column_value_name.
        """

        pass

    ##
    # @brief Get a geospatial object that describes the locations.
    # @param use_refind_polygon Unused??
    def get_location(self, use_refind_polygon=False):
        """
        Return a geospatial object which describes the
        locations of the location file.

        Note, if there is not location info, this returns None.

        Not implemented:
        if use_refind_polygon is True, only return values in the
        refined polygon
        """

        return self._geospatial

    ##
    # @brief Add column to 'end' of CSV data.
    # @param column_name The new column name.
    # @param column_values The new column values.
    # @param overwrite If True, overwrites last column, doesn't add at end.
    def set_column(self, column_name, column_values, overwrite=False):
        """
        Add a column to the 'end' (with the right most column being the end)
        of the csv file.

        Set overwrite to True if you want to overwrite a column.

        Note, in column_name white space is removed and case is not checked.
        Precondition
        The column_name and column_values cannot have comma's in it.
        """

        # sanity checks
        value_row_count = \
                len(self._attribute_dic[self._title_index_dic.keys()[0]])
        if len(column_values) <> value_row_count:
            msg = 'The number of column values must equal the number of rows.'
            raise DataMissingValuesError, msg

        # check new column name isn't already used, and we aren't overwriting
        if self._attribute_dic.has_key(column_name):
            if not overwrite:
                msg = 'Column name %s already in use!' % column_name
                raise TitleValueError, msg
        else:
            # New title.  Add it to the title index.
            self._title_index_dic[column_name] = len(self._title_index_dic)

        self._attribute_dic[column_name] = column_values

    ##
    # @brief Save the exposure CSV  file.
    # @param file_name If supplied, use this filename, not original.
    def save(self, file_name=None):
        """
        Save the exposure csv file
        """

        if file_name is None:
            file_name = self._file_name

        fd = open(file_name, 'wb')
        writer = csv.writer(fd)

        #Write the title to a cvs file
        line = [None] * len(self._title_index_dic)
        for title in self._title_index_dic.iterkeys():
            line[self._title_index_dic[title]] = title
        writer.writerow(line)

        # Write the values to a cvs file
        value_row_count = \
                len(self._attribute_dic[self._title_index_dic.keys()[0]])
        for row_i in range(value_row_count):
            line = [None] * len(self._title_index_dic)
            for title in self._title_index_dic.iterkeys():
                line[self._title_index_dic[title]] = \
                     self._attribute_dic[title][row_i]
            writer.writerow(line)