Add option to change config path and correct tiff generation

src/lisfloodutilities/gridding/configuration/1arcmin/config_pr.txt

@@ -11,6 +11,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = precipitation_amount
 LONG_NAME = Daily Accumulated Precipitation
+KIWIS_FILTER_PLUGIN_CLASSES = {'ObservationsKiwisFilter': {'1303': 100.0}}
 
 [VAR_TIME]
 

src/lisfloodutilities/gridding/configuration/1arcmin/config_pr6.txt

@@ -11,6 +11,8 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = precipitation_amount
 LONG_NAME = 6 Hourly Accumulated Precipitation
+KIWIS_FILTER_PLUGIN_CLASSES = {'DowgradedObservationsKiwisFilter': {'1295': 1.0}, 'ObservationsKiwisFilter': {'1303': 100.0}}
+
 
 [VAR_TIME]
 

src/lisfloodutilities/gridding/configuration/1arcmin/config_pr6x4.txt

@@ -11,6 +11,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = precipitation_amount
 LONG_NAME = 6 Hourly Accumulated Precipitation per Day
+KIWIS_FILTER_PLUGIN_CLASSES = {'DowgradedObservationsKiwisFilter': {'1295': 1.0}, 'ObservationsKiwisFilter': {'1303': 100.0}}
 
 [VAR_TIME]
 

src/lisfloodutilities/gridding/configuration/1arcmin/default.txt

@@ -23,6 +23,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = DUMMY_STANDARD_NAME
 LONG_NAME = DUMMY LONG NAME
+KIWIS_FILTER_PLUGIN_CLASSES = {'KiwisFilter': {}}
 
 [DIMENSION]
 

src/lisfloodutilities/gridding/configuration/5x5km/config_pr.txt

@@ -11,6 +11,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = precipitation_amount
 LONG_NAME = Daily Accumulated Precipitation
+KIWIS_FILTER_PLUGIN_CLASSES = {'ObservationsKiwisFilter': {'1303': 100.0}}
 
 [VAR_TIME]
 

src/lisfloodutilities/gridding/configuration/5x5km/config_pr6.txt

@@ -11,6 +11,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = precipitation_amount
 LONG_NAME = 6 Hourly Accumulated Precipitation
+KIWIS_FILTER_PLUGIN_CLASSES = {'DowgradedObservationsKiwisFilter': {'1295': 1.0}, 'ObservationsKiwisFilter': {'1303': 100.0}}
 
 [VAR_TIME]
 

src/lisfloodutilities/gridding/configuration/5x5km/config_pr6x4.txt

@@ -11,6 +11,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = precipitation_amount
 LONG_NAME = 6 Hourly Accumulated Precipitation per Day
+KIWIS_FILTER_PLUGIN_CLASSES = {'DowgradedObservationsKiwisFilter': {'1295': 1.0}, 'ObservationsKiwisFilter': {'1303': 100.0}}
 
 [VAR_TIME]
 

src/lisfloodutilities/gridding/configuration/5x5km/default.txt

@@ -24,6 +24,7 @@ VALUE_OFFSET = 0.0
 DATA_TYPE_PACKED = i2
 STANDARD_NAME = DUMMY_STANDARD_NAME
 LONG_NAME = DUMMY LONG NAME
+KIWIS_FILTER_PLUGIN_CLASSES = {'KiwisFilter': {}}
 
 [DIMENSION]
 

src/lisfloodutilities/gridding/generate_grids.py

@@ -21,7 +21,7 @@
 from pathlib import Path
 from argparse import ArgumentParser, ArgumentTypeError
 from datetime import datetime, timedelta
-from lisfloodutilities.gridding.lib.utils import Printable, Dem, Config, FileUtils, GriddingUtils
+from lisfloodutilities.gridding.lib.utils import Printable, Dem, Config, FileUtils, GriddingUtils # , KiwisLoader
 from lisfloodutilities.gridding.lib.writers import NetCDFWriter, GDALWriter
 
 
@@ -80,6 +80,8 @@ def run(config_filename: str, infolder: str, output_file: str, processing_dates_
         output_writer_tiff = GDALWriter(conf, overwrite_output, quiet_mode)
     output_writer_netcdf = NetCDFWriter(conf, overwrite_output, quiet_mode)
     output_writer_netcdf.open(Path(outfile))
+#    file_loader = KiwisLoader(conf, overwrite_output, Path(infolder), quiet_mode)
+#    for filename in file_loader:
     for filename in sorted(Path(infolder).rglob(inwildcard)):
         file_timestamp = file_utils.get_timestamp_from_filename(filename) + timedelta(days=netcdf_offset_file_date)
         if not file_utils.processable_file(file_timestamp, dates_to_process, conf.start_date, conf.end_date):
@@ -89,6 +91,7 @@ def run(config_filename: str, infolder: str, output_file: str, processing_dates_
             outfilepath = filename.with_suffix('.tiff')
             output_writer_tiff.open(outfilepath)
         grid_data = grid_utils.generate_grid(filename)
+        print('orig: ', grid_data[1519][2250])
         output_writer_netcdf.write(grid_data, file_timestamp)
         if output_tiff:
             output_writer_tiff.write(grid_data, file_timestamp)
@@ -144,6 +147,9 @@ def main(argv):
         parser.add_argument("-c", "--conf", dest="config_type", required=True,
                             help="Set the grid configuration type to use.",
                             metavar="{5x5km, 1arcmin,...}")
+        parser.add_argument("-p", "--pathconf", dest="config_base_path", required=False, type=FileUtils.folder_type,
+                            help="Overrides the base path where the configurations are stored.",
+                            metavar="/path/to/config")
         parser.add_argument("-v", "--var", dest="variable_code", required=True,
                             help="Set the variable to be processed.",
                             metavar="{pr,pd,tn,tx,ws,rg,...}")
@@ -172,6 +178,8 @@ def main(argv):
         quiet_mode = args.quiet
 
         configuration_base_folder = os.path.join(program_path, '../src/lisfloodutilities/gridding/configuration')
+        if args.config_base_path is not None and len(args.config_base_path) > 0:
+            configuration_base_folder = args.config_base_path
 
         file_utils = FileUtils(args.variable_code, quiet_mode)
 

src/lisfloodutilities/gridding/lib/utils.py

@@ -23,10 +23,14 @@
 import pandas as pd
 from decimal import *
 from datetime import datetime, timedelta
+from collections import OrderedDict
 from scipy.spatial import cKDTree
 from pyg2p import Loggable
 from pyg2p.main.readers.netcdf import NetCDFReader
 from pyg2p.main.interpolation.scipy_interpolation_lib import ScipyInterpolation
+from numpy import delete
+import importlib
+
 
 __DECIMAL_CASES = 20
 __DECIMAL_FORMAT = '{:.20f}'
@@ -428,3 +432,106 @@ def generate_grid(self, filename: Path) -> np.ndarray:
         self.check_grid_nan(filename, result)
         grid_data = self.prepare_grid(result, grid_x.shape)
         return grid_data
+
+
+# class KiwisLoader(Printable):
+#     DATE_PATTERN_CONDENSED = '%Y%m%d%H%M%S'
+#     DATE_PATTERN_SEPARATED = '%Y-%m-%d %H:%M:%S'
+#     CSV_DELIMITER = '\t'
+#     FILES_WILDCARD = '??????????00_all.kiwis'
+#
+#     def __init__(self, conf: Config, overwrite_file: bool = False, infolder: Path, quiet_mode: bool = False):
+#         super().__init__(quiet_mode)
+#         self.conf = conf
+#         self.overwrite_file = overwrite_file
+#         self.var_code = self.conf.var_code
+#         self.var_size = len(self.var_code)
+#         self.inwildcard = self.var_code + FILES_WILDCARD
+#         self.infolder = infolder
+#         # Frequency between timesteps in hours
+#         self.time_frequency = int(self.conf.get_config_field('VAR_TIME','FREQUENCY'))
+#         self.is_daily_var = (self.time_frequency == 1)
+#         # Number of files to be read/processed simultaneously. for non daily vars time frequency is in hours
+#         self.read_files_step = 1 if self.is_daily_var else int(24 / self.time_frequency)
+#         self.files_list = OrderedDict()
+#         self.file_groups = []
+#         self.filter_classes = self.__get_filter_classes()
+#
+#     def __iter__(self):
+#         self.__load_kiwis_paths()
+#         self.file_groups = iter(self.__get_file_groups())
+#         return self
+#
+#     def __next__(self):
+#         if self.is_daily_var:
+#             for filter_class in self.filter_classes:
+#                 df_kiwis_array = filter_class.filter(self.file_groups[self.file_group_read_idx])
+#                 self.file_group_read_idx += 1
+#         raise StopIteration
+#
+#     def __get_filter_classes(self) -> array:
+#         '''
+#         TODO: Implement the class.
+#         '''
+#         plugins_array = []
+#         # Load the class dynamically
+#         plugins = self.conf.get_config_field('PROPERTIES', 'KIWIS_FILTER_PLUGIN_CLASSES')
+#         module_name = 'lisfloodutilities.gridding.lib.filters'
+#         try:
+#             for plugin in plugins:
+#                 class_name = plugin
+#                 class_args = plugins[plugin]
+#                 module = importlib.import_module(module_name)
+#                 class_instance = getattr(module, class_name)(class_args)
+#                 plugins_array.append(class_instance)
+#         except ImportError:
+#             print(f"Error: Could not import module '{module_name}'")
+#         except AttributeError:
+#             print(f"Error: Could not find class '{class_name}' in module '{module_name}'")
+#         return plugins_array
+#
+#     def __filter_kiwis(self, filename_kiwis: Path) -> pd.DataFrame:
+#         return None
+#
+#     def __get_points_filename(self, kiwis_timestamp: str, filename_kiwis: Path) -> Path:
+#         '''
+#         Returns the points file path.
+#         If the mode is overwrite tries to get the first pointfile path it finds and if it does not find generates a new file path.
+#         Otherwise generates a new file path.
+#         '''
+#         if self.overwrite_file:
+#             for points_path in sorted(filename_kiwis.parent.rglob(f'{self.var_code}{kiwis_timestamp_str}_??????????????.txt')):
+#                 if points_path.is_file():
+#                     return points_path
+#         pointfile_timestamp = datetime.now().strftime('%Y%m%d%H%M%S')
+#         return Path(filename_kiwis.parent, f'{self.var_code}{kiwis_timestamp_str}_{pointfile_timestamp}.txt')
+#
+#     def __load_kiwis_paths(self):
+#         netcdf_offset_file_date = int(self.conf.get_config_field('VAR_TIME','OFFSET_FILE_DATE'))
+#         for filename_kiwis in sorted(self.infolder.rglob(self.inwildcard)):
+#             kiwis_timestamp = self.__get_timestamp_from_filename(filename_kiwis)
+#             file_timestamp = kiwis_timestamp + timedelta(days=netcdf_offset_file_date)
+#             if self.__processable_file(file_timestamp, self.conf.start_date, self.conf.end_date):
+#                 kiwis_timestamp_str = kiwis_timestamp.strftime(DATE_PATTERN_CONDENSED)
+#                 filename_points = self.__get_points_filename(kiwis_timestamp_str, filename_kiwis)
+#                 self.files_list[kiwis_timestamp_str] = (filename_kiwis, filename_points)
+#                 # print_msg(f'Processing file: {filename}')
+#
+#     def __get_next_file_group(self):
+#         '''
+#         TODO
+#         '''
+#         if self.is_daily_var:
+#             for kiwis_timestamp_str in self.files_list:
+#                 self.file_groups.append([kiwis_timestamp_str])
+#         else: # divide the files into groups of 4 and give exception if group is not complete
+#             for kiwis_timestamp_str in self.files_list:
+#                 self.file_groups.append([])
+#
+#     def __get_timestamp_from_filename(self, filename: Path) -> datetime:
+#         file_timestamp = filename.name[self.var_size:12+self.var_size] + '00'
+#         return datetime.strptime(file_timestamp, FileUtils.DATE_PATTERN_CONDENSED)
+#
+#     def __processable_file(self, file_timestamp: datetime, start_date: datetime = None, end_date: datetime = None) -> bool:
+#         return (start_date is not None and start_date <= file_timestamp and
+#                 end_date is not None and file_timestamp <= end_date)

src/lisfloodutilities/gridding/lib/writers.py

@@ -14,6 +14,7 @@
 import time as timex
 import warnings
 import numpy as np
+import copy
 from argparse import ArgumentTypeError
 from pathlib import Path
 from datetime import datetime, timedelta
@@ -123,12 +124,14 @@ def write_timestep(self, grid: np.ndarray, timestep: int = -1):
                 raise Exception("netCDF Dataset was not initialized. If file already exists, use --force flag to append.")
             timestep_idx = int(timestep / self.time_frequency)
             self.nf.variables[self.netcdf_var_time][timestep_idx] = timestep
-            values = self.setNaN(grid)
+            print('ncdf f(grid): ', grid[1519][2250])
+            values = self.setNaN(copy.deepcopy(grid))
             values[values < self.conf.value_min_packed] = np.nan
             values[values > self.conf.value_max_packed] = np.nan
             values[values != self.conf.VALUE_NAN] *= self.conf.scale_factor
             values[values != self.conf.VALUE_NAN] += self.conf.add_offset
             values[np.isnan(values)] = self.conf.VALUE_NAN * self.conf.scale_factor + self.conf.add_offset
+            print('ncdf i(grid): ', values[1519][2250])
             self.nf.variables[self.var_code][timestep_idx, :, :] = values
 
     def opened(self) -> bool:
@@ -287,6 +290,8 @@ def write_timestep(self, grid: np.ndarray, timestep: int = -1):
             ds.GetRasterBand(1).SetScale(self.conf.scale_factor)
             ds.GetRasterBand(1).SetOffset(self.conf.add_offset)
             ds = self.setup_dataset_metadata(ds)
+            print('tiff f(grid): ', grid[1519][2250])
+            print('tiff i(grid): ', grid.astype(np.int16)[1519][2250])
             ds.GetRasterBand(1).WriteArray(grid.astype(np.int16))
             ds.FlushCache()
             ds = None