Index: trunk/tests/test_output_data.py
===================================================================
diff -u -r40 -r41
--- trunk/tests/test_output_data.py	(.../test_output_data.py)	(revision 40)
+++ trunk/tests/test_output_data.py	(.../test_output_data.py)	(revision 41)
@@ -87,7 +87,7 @@
         output_data = extract_wave.subset_era_5(dir_test_data, 1981, 1982)
 
         try:
-            netcdf_filepath = output_data.generate_wave_netcdf(
+            netcdf_filepath = output_data.generate_netcdf(
                 dir_path=output_test_data,
                 base_name='test_wave',
                 dataset_code=None,
@@ -105,7 +105,59 @@
 
 class Test_generate_output:
 
+    @pytest.mark.unittest
+    def test_when_no_arguments_given_no_valid_data_dict_then_raises(self):
+        # 1. Given
+        input_data = data_acquisition.InputData()
+        input_data.input_dict = test_wave_variable_dict
+        input_data.coord_list = [(4.2, 2.4), ]
+        output_data = None
+        generated_output = None
+        expected_message = output_messages.error_not_initialized_data_dict
+
+        # 2. When
+        with pytest.raises(IOError) as e_info:
+            output_data = OutputData(None)
+            generated_output = output_data.generate_output()
+
+        # 3. Then
+        assert generated_output is None
+        assert expected_message == str(e_info.value)
+
     @pytest.mark.systemtest
+    def test_when_no_arguments_given_valid_data_dict_then_returns_expected_output(self):
+        # 1. Given
+        # When using local data you can just replace the comment in these lines
+        # dir_test_data = TestUtils.get_local_test_data_dir('netCDF_Waves_data')
+        dir_test_data = 'P:\\metocean-data\\open\\ERA5\\data\\Global'
+
+        input_data = data_acquisition.InputData()
+        input_data.input_dict = test_wave_variable_dict
+        input_data.coord_list = [(4.2, 2.4), ]
+        return_value = None
+
+        # 2. When
+        extract_wave = extract_waves.ExtractWaves(input_data)
+        output_data = extract_wave.subset_era_5(dir_test_data, 1981, 1982)
+
+        try:
+            return_value = output_data.generate_output()
+        except Exception as e_info:
+            pytest.fail(
+                'Exception thrown but not expected. {}'.format(str(e_info)))
+
+        # 3. Then
+        output_xarray = output_data.get_xarray()
+        output_netcdf_filepath = output_data.get_netcdf_filepath()
+
+        assert return_value is not None
+        assert output_netcdf_filepath is not None
+        assert os.path.exists(output_netcdf_filepath)
+        assert output_xarray is not None
+
+        os.remove(output_netcdf_filepath)
+
+    @pytest.mark.systemtest
     def test_when_given_all_arguments_does_not_raise(self):
         # 1. Given
         # When using local data you can just replace the comment in these lines
Index: trunk/SDToolBox/data_acquisition.py
===================================================================
diff -u -r40 -r41
--- trunk/SDToolBox/data_acquisition.py	(.../data_acquisition.py)	(revision 40)
+++ trunk/SDToolBox/data_acquisition.py	(.../data_acquisition.py)	(revision 41)
@@ -1,8 +1,10 @@
 #! /usr/bin/env python
 from datetime import datetime
 import os
+import random
+import string
 
-import SDToolBox.outputmessages as output_messages
+import SDToolBox.outputmessages as om
 
 from netCDF4 import Dataset
 from sklearn.neighbors import BallTree as BallTree
@@ -167,7 +169,7 @@
         """
         if not var_list:
             var_list = []
-            print(output_messages.error_missing_list_of_variables)
+            print(om.error_missing_list_of_variables)
 
         values_dict = {}
         for var in var_list:
@@ -192,28 +194,42 @@
 
     def generate_output(
             self,
-            dir_path: str,
-            base_name: str,
-            dataset_code: str,
-            file_format: str):
+            dir_path: str = None,
+            base_name: str = None,
+            dataset_code: str = None):
         """Generates an unified netcdf4 file and its xarray equivalent
         from the self.__data_dict.
 
-        Arguments:
-            file_path {str} -- Target file path.
-            base_name {str} -- Base name for the output file.
-            dataset_code {str} -- Code of the dataset
-            file_format {str} -- Format for the dataset
+        Keyword Arguments:
+            dir_path {str} -- Target file path. (default: {None})
+            base_name {str} -- Base name for the output file. (default: {None})
+            dataset_code {str} -- Code of the dataset. (default: {None})
 
         Returns:
             xarray {xarray.Dataset} -- Equivalent xarray of the dict.
         """
-        netcdf_filepath = self.generate_wave_netcdf(
+        if not self.__data_dict or \
+            not self.__data_dict[self.var_lat_key] or \
+                not self.__data_dict[self.var_lon_key] or \
+                not self.__data_dict[self.var_time_key] or \
+                not self.__data_dict[self.var_val_key]:
+            raise IOError(om.error_not_initialized_data_dict)
+
+        if not dir_path or \
+            not base_name or \
+                not dataset_code:
+            # Get current directory
+            dir_path = os.getcwd()
+            # temp_generated_netcdf
+            base_name = 'temp_generated_{}'.format(self.__get_random_str(4))
+            dataset_code = 'CF'
+
+        netcdf_filepath = self.generate_netcdf(
             dir_path=dir_path,
             base_name=base_name,
-            dataset_code=dataset_code,
-            file_format=file_format
+            dataset_code=dataset_code
         )
+
         self.__output_netcdf_file = netcdf_filepath
         return self.generate_xarray_from_netcdf(netcdf_filepath)
 
@@ -233,33 +249,31 @@
         # so basically an importer.
         return self.__output_xarray
 
-    def generate_wave_netcdf(
+    def generate_netcdf(
             self,
             dir_path: str,
             base_name: str,
-            dataset_code: str,
-            file_format: str):
+            dataset_code: str):
         """Generates an unified netcdf4 file from the self.__data_dict.
 
         Arguments:
             file_path {str} -- Target file path.
             base_name {str} -- Base name for the output file.
             dataset_code {str} -- Code of the dataset
-            file_format {str} -- Format for the dataset
 
         Returns:
             nc_filename {str} -- Filepath to the generated dataset.
         """
-        file_name = '{}_{}_{}.nc'.format(
-            base_name, file_format, dataset_code)
+        file_name = '{}_{}.nc'.format(
+            base_name, dataset_code)
         nc_filename = os.path.join(dir_path, file_name)
         print('Writing {}'.format(nc_filename))
         self.__cleanup_data_dict()
         with Dataset(nc_filename, mode='w', format="NETCDF4") as netcdf:
             self.__set_dataset_structure(netcdf)
             self.__set_wave_variables(netcdf, dataset_code)
             self.__set_wave_data(netcdf, dataset_code)
-            self.__set_global_data(netcdf, file_format, dataset_code)
+            self.__set_global_data(netcdf, dataset_code)
 
         self.__output_netcdf_file = nc_filename
 
@@ -276,6 +290,11 @@
         for key in remove_keys:
             del self.__data_dict[self.var_val_key][key]
 
+    def __get_random_str(self, length: int = 10):
+        """Generate a random string of fixed length """
+        letters = string.ascii_lowercase
+        return ''.join(random.choice(letters) for i in range(length))
+
     def __get_station_number(self):
         lon_keys = self.__data_dict[self.var_lon_key]
         lat_keys = self.__data_dict[self.var_lat_key]
@@ -291,7 +310,7 @@
         return self.__data_dict[self.var_time_key]
 
     def __set_global_data(
-            self, netcdf: Dataset, output_format: str, dataset_code: str):
+            self, netcdf: Dataset, dataset_code: str):
         """Sets the global data for our new output dataset.
         see: http://www.unidata.ucar.edu/software/thredds/current/
         netcdf-java/formats/DataDiscoveryAttConvention.html
@@ -305,7 +324,7 @@
         netcdf.Conventions = 'CF-1.4'
         netcdf.standard_name_vocabulary = 'CF Standard Name Table vNN'
 
-        netcdf.title = '{} {}'.format(dataset_code, output_format) + \
+        netcdf.title = '{}'.format(dataset_code) + \
             ' data North Sea Dutch coast'
         netcdf.summary = '' + \
             'North Sea Water Level data in coastal gauges for the Dutch coast'
Index: trunk/SDToolBox/outputmessages.py
===================================================================
diff -u -r40 -r41
--- trunk/SDToolBox/outputmessages.py	(.../outputmessages.py)	(revision 40)
+++ trunk/SDToolBox/outputmessages.py	(.../outputmessages.py)	(revision 41)
@@ -12,3 +12,6 @@
     'Not enough coordinates were provided as InputData.coord_list.'
 error_no_valid_dict_of_vars = '' + \
     'A dictionary of variables (key: value) should be provided.'
+error_not_initialized_data_dict = '' + \
+    'Data dictionary has not been initialized, ' + \
+        'no xarray or netCDF can be created.'
\ No newline at end of file
Index: trunk/SDToolBox/extract_waves.py
===================================================================
diff -u -r40 -r41
--- trunk/SDToolBox/extract_waves.py	(.../extract_waves.py)	(revision 40)
+++ trunk/SDToolBox/extract_waves.py	(.../extract_waves.py)	(revision 41)
@@ -169,11 +169,6 @@
         nn_lon_idx = []
         nn_lat_idx = []
 
-        # ref_file_path = self.find_default_file(directory_path)
-        # Hardcoded:
-        # base_file_name = 'Hs\\era5_Global_Hs_1981.nc'
-        # ref_file_path = os.path.join(directory_path, base_file_name)
-
         # Extract index and value for all input lat, lon.
         with Dataset(ref_file_path, 'r', self.__ds_format) \
                 as ref_dataset:
@@ -194,13 +189,6 @@
         return nn_lon_idx, nn_lat_idx
 
     @staticmethod
-    def find_default_file(dir: str):
-        for root, dirs, files in os.walk(dir):
-            for file in files:
-                if file.endswith('.nc'):
-                    return os.path.join(root, file)
-
-    @staticmethod
     def get_case_subset(dataset, variable_name, lon, lat):
         return dataset[variable_name][:, lat, lon]