def _parseFunctionConstituents(self, function, parse_consts=True, data_scheme=None):
"""
_parseFunctionConstituents() [protected]
Purpose: Take a function string and parse out the variables and constants that the function needs for computations. If the data_scheme
variable is given, convert the list to a file-based variable names.
Parameters: function [ type=str ]
String containing the function.
parse_consts [ type=bool ] [ optional ]
Boolean value specifying whether or not to parse out the constants in the file name. Default is True.
data_scheme [ type=dict ] [ optional ]
A dictionary containing the mapping of internal variables names to the variable names in the data file.
Returns: A list of internal constant names and/or a list of internal variable names or file variable names, depending on whether or not
parse_consts was set and data_scheme was given.
"""
# Put the variable list into a regexp-like format
nc_variable_list = "(?:^|(?<=[\\W]))(?:" + "|".join(self._var_map.keys()) + ")(?:(?=[\\W])|$)"
# Find all NetCDF variables in the function, removing duplicates
var_list = uniquify(re.findall(nc_variable_list, function))
if parse_consts:
hp_const_list = "|".join([ const for const in dir(derived) if const[0] != "_" ])
# Find all the constants in the function, removing duplicates
const_list = uniquify(re.findall(hp_const_list, function))
if data_scheme is not None:
var_list = [ data_scheme[self._var_map[v]] for v in var_list ]
if parse_consts:
return var_list, const_list
else:
return var_list
def _finalizeProduct(self, plot_time, is_forecast, plot_names=[]):
"""
_finalizeProduct() [protected]
Purpose: Add final things to the product, such as the title, valid time, and border, and then save.
Parameters: forecast_hour [type=int]
Forecast hour for model products (pass in None for an observed product).
Returns: [nothing]
"""
plot_names = uniquify(plot_names)
# Modify the last plot name for joining for the title string
if len(plot_names) > 1:
plot_names[-1] = "and " + plot_names[-1]
# Create the forecast hour string according to whether or not we're passed a forecast hour.
plot_time_delta = plot_time - self._valid_time
hour = Units.convert(plot_time_delta.microseconds, 'us', 'hr') + Units.convert(plot_time_delta.seconds, 's', 'hr') + Units.convert(plot_time_delta.days, 'dy', 'hr')
file_name = self._image_file_name % { 'plot_time':hour }
if is_forecast:
fh_string = " (F%03d)" % hour
else:
fh_string = ""
if self._vertical_level in ['surface', 'sfc', "None"]:
vert_level_str = ""
else:
vert_level_str = " %s" % self._vertical_level
# Create the valid time string and assemble the title string
valid_time_string = plot_time.strftime(self._product_time_format)
title_string = "%s%s %s Valid: %s%s" % (self._product_title, vert_level_str, ", ".join(plot_names), valid_time_string, fh_string)
# Put the title on the image
pylab.title(title_string, weight="bold", size="x-small", bbox=dict(facecolor="#ffffff", alpha=0.7),x=0.5,y=0.95)
# Save the figure
try:
pylab.savefig(file_name)
except IOError:
fatalError("Couldn't save image to %s" % file_name)
print "Saved product '%s', valid at %s%s, to file %s" % (self._product_title,
valid_time_string, fh_string, file_name)
pylab.close()
return
