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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def compute_function_aligned(funct, data_collections, data_type, unit):
 """Compute a function with a list of aligned data collections or individual values. Args: funct: A function with a single numerical value as output and one or more numerical values as input. data_collections: A list with a length equal to the number of arguments for the function. Items of the list can be either Data Collections or individual values to be used at each datetime of other collections. data_type: An instance of a Ladybug data type that describes the results of the funct. unit: The units of the funct results. Return: A Data Collection with the results function. If all items in this list of data_collections are individual values, only a single value will be returned. Usage: from ladybug.datacollection import HourlyContinuousCollection from ladybug.epw import EPW from ladybug.psychrometrics import humid_ratio_from_db_rh from ladybug.datatype.percentage import HumidityRatio epw_file_path = './epws/denver.epw' denver_epw = EPW(epw_file_path) pressure_at_denver = 85000 hr_inputs = [denver_epw.dry_bulb_temperature, denver_epw.relative_humidity, pressure_at_denver] humid_ratio = HourlyContinuousCollection.compute_function_aligned( humid_ratio_from_db_rh, hr_inputs, HumidityRatio(), 'fraction') # humid_ratio will be a Data Colleciton of humidity ratios at Denver """

        # check that all inputs are either data collections or floats
        data_colls = []
        for i, func_input in enumerate(data_collections):
            if isinstance(func_input, BaseCollection):
                data_colls.append(func_input)
            else:
                try:
                    data_collections[i] = float(func_input)
                except ValueError:
                    raise TypeError('Expected a number or a Data Colleciton. '
                                    'Got {}'.format(type(func_input)))

        # run the function and return the result
        if len(data_colls) == 0:
            return funct(*data_collections)
        else:
            BaseCollection.are_collections_aligned(data_colls)
            val_len = len(data_colls[0].values)
            for i, col in enumerate(data_collections):
                data_collections[i] = [col] * val_len if isinstance(col, float) else col
            result = data_colls[0].get_aligned_collection(data_type=data_type, unit=unit)
            for i in xrange(val_len):
                result[i] = funct(*[col[i] for col in data_collections])
            return result