misc fixes

Fixes
* Allow the HDF filename to be passed to main function instead
  of only io_manager instance.  Having main only accept io_manager
  broke all ipython notebooks.
* Removed "print(table)" from readUCI which I think was a
  debugging statement.
IPython Notebook Fixes
* Edited some of the ipython notebooks that tried to find an
  element time-series with an old name, for example tried to
  find "SURO" instead of the new name "SURO_sum".
* Edited some of the ipython notebooks so that filenames were
  case sensitive.
Deprecations
* The append function is no longer available for DataFrames and
  changed to pd.concat form.
* In pandas 3.0, to_hdf will require the "key" to be a keyword
  argument instead of a positional argument and made that change
  now to silence the deprecation message.
Format
* Removed trailing spaces from some files.
* Fixed not a multiple of 4 spaces indentation in at least one file.
* Renamed files with spaces in their names, replacing spaces with "_".
Documentation
* Additional edits to the README.rst.
* Reshaped some docstrings into Numpy format.

HSP2/__init__.py

@@ -2,9 +2,11 @@
 Authors: Robert Heaphy, Ph.D. and Paul Duda
 License: LGPL2
 '''
+from importlib.metadata import version
 
 from HSP2.main import main
 from HSP2.mainDoE import main as mainDoE
 from HSP2.utilities import versions, flowtype
-from _version import __version__
+
+__version__ = version("hsp2")
 

HSP2/main.py

@@ -8,28 +8,35 @@
 from pandas import DataFrame, date_range
 from pandas.tseries.offsets import Minute
 from datetime import datetime as dt
+from typing import Union
 import os
+from HSP2IO.hdf import HDF5
 from HSP2.utilities import versions, get_timeseries, expand_timeseries_names, save_timeseries, get_gener_timeseries
 from HSP2.configuration import activities, noop, expand_masslinks
 from HSP2.state import *
 
 from HSP2IO.io import IOManager, SupportsReadTS, Category
 
-def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None:
-    """Runs main HSP2 program.
+def main(io_manager:Union[str, IOManager], saveall:bool=False, jupyterlab:bool=True) -> None:
+    """
+    Run main HSP2 program.
 
     Parameters
     ----------
-   
-    saveall: Boolean - [optional] Default is False.
+    io_manager
+        An instance of IOManager class.
+    saveall: bool, default=False
         Saves all calculated data ignoring SAVE tables.
-    jupyterlab: Boolean - [optional] Default is True.
-        Flag for specific output behavior for  jupyter lab.
-    Return
-    ------------
+    jupyterlab: bool, default=True
+        Flag for specific output behavior for jupyter lab.
+
+    Returns
+    -------
     None
-    
     """
+    if isinstance(io_manager, str):
+        hdf5_instance = HDF5(io_manager)
+        io_manager = IOManager(hdf5_instance)
 
     hdfname = io_manager._input.file_path
     if not os.path.exists(hdfname):
@@ -46,12 +53,12 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
     ddext_sources = uci_obj.ddext_sources
     ddgener = uci_obj.ddgener
     uci = uci_obj.uci
-    siminfo = uci_obj.siminfo 
+    siminfo = uci_obj.siminfo
     ftables = uci_obj.ftables
     specactions = uci_obj.specactions
     monthdata = uci_obj.monthdata
     specactions = {} # placeholder till added to uci parser
-    
+
     start, stop = siminfo['start'], siminfo['stop']
 
     copy_instances = {}
@@ -64,12 +71,12 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
     state = init_state_dicts()
     state_siminfo_hsp2(uci_obj, siminfo)
     # Add support for dynamic functins to operate on STATE
-    # - Load any dynamic components if present, and store variables on objects 
+    # - Load any dynamic components if present, and store variables on objects
     state_load_dynamics_hsp2(state, io_manager, siminfo)
     # - finally stash specactions in state, not domain (segment) dependent so do it once
     state['specactions'] = specactions # stash the specaction dict in state
     #######################################################################################
-    
+
     # main processing loop
     msg(1, f'Simulation Start: {start}, Stop: {stop}')
     tscat = {}
@@ -80,7 +87,7 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
         siminfo['steps'] = len(siminfo['tindex'])
 
         if operation == 'COPY':
-            copy_instances[segment] = activities[operation](io_manager, siminfo, ddext_sources[(operation,segment)]) 
+            copy_instances[segment] = activities[operation](io_manager, siminfo, ddext_sources[(operation,segment)])
         elif operation == 'GENER':
             try:
                 ts = get_timeseries(io_manager, ddext_sources[(operation, segment)], siminfo)
@@ -102,7 +109,7 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
                     flags['ADNHFG'] = uci[(operation, 'NUTRX', segment)]['FLAGS']['ADNHFG']
                     flags['PO4FG'] = uci[(operation, 'NUTRX', segment)]['FLAGS']['PO4FG']
                     flags['ADPOFG'] = uci[(operation, 'NUTRX', segment)]['FLAGS']['ADPOFG']
-                
+
                 get_flows(io_manager, ts, flags, uci, segment, ddlinks, ddmasslinks, siminfo['steps'], msg)
 
             for activity, function in activities[operation].items():
@@ -118,7 +125,7 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
                 msg(3, f'{activity}')
                 # Set context for dynamic executables.
                 state_context_hsp2(state, operation, segment, activity)
-                
+
                 ui = uci[(operation, activity, segment)]   # ui is a dictionary
                 if operation == 'PERLND' and activity == 'SEDMNT':
                     # special exception here to make CSNOFG available
@@ -182,7 +189,7 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
                         elif flags['PLANK']:
                             if 'CFSAEX' in uci[(operation, 'PLANK', segment)]['PARAMETERS']:
                                 ui['PARAMETERS']['CFSAEX'] = uci[(operation, 'PLANK', segment)]['PARAMETERS']['CFSAEX']
-                    
+
                     if activity == 'RQUAL':
                         # RQUAL inputs:
                         ui['advectData'] = uci[(operation, 'ADCALC', segment)]['adcalcData']
@@ -202,12 +209,12 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
                                     ui['PARAMETERS']['NCONS'] = uci[(operation, 'CONS', segment)]['PARAMETERS']['NCONS']
 
                         # OXRX module inputs:
-                        ui_oxrx = uci[(operation, 'OXRX', segment)] 
-                        
+                        ui_oxrx = uci[(operation, 'OXRX', segment)]
+
                         if flags['HYDR']:
                             ui_oxrx['PARAMETERS']['LEN'] = uci[(operation, 'HYDR', segment)]['PARAMETERS']['LEN']
                             ui_oxrx['PARAMETERS']['DELTH'] = uci[(operation, 'HYDR', segment)]['PARAMETERS']['DELTH']
-                        
+
                         if flags['HTRCH']:
                             ui_oxrx['PARAMETERS']['ELEV'] = uci[(operation, 'HTRCH', segment)]['PARAMETERS']['ELEV']
 
@@ -221,17 +228,17 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
                             ui['PARAMETERS']['CFSAEX'] = uci[(operation, 'HTRCH', segment)]['PARAMETERS']['CFSAEX']
 
                         # NUTRX, PLANK, PHCARB module inputs:
-                        ui_nutrx = uci[(operation, 'NUTRX', segment)] 
-                        ui_plank = uci[(operation, 'PLANK', segment)] 
-                        ui_phcarb = uci[(operation, 'PHCARB', segment)] 
+                        ui_nutrx = uci[(operation, 'NUTRX', segment)]
+                        ui_plank = uci[(operation, 'PLANK', segment)]
+                        ui_phcarb = uci[(operation, 'PHCARB', segment)]
 
                 ############ calls activity function like snow() ##############
                 if operation not in ['COPY','GENER']:
                     if (activity == 'HYDR'):
                         errors, errmessages = function(io_manager, siminfo, ui, ts, ftables, state)
                     elif (activity != 'RQUAL'):
                         errors, errmessages = function(io_manager, siminfo, ui, ts)
-                    else:                    
+                    else:
                         errors, errmessages = function(io_manager, siminfo, ui, ui_oxrx, ui_nutrx, ui_plank, ui_phcarb, ts, monthdata)
                 ###############################################################
 
@@ -256,7 +263,7 @@ def main(io_manager:IOManager, saveall:bool=False, jupyterlab:bool=True) -> None
 
                 if 'SAVE' in ui:
                     save_timeseries(io_manager,ts,ui['SAVE'],siminfo,saveall,operation,segment,activity,jupyterlab,outstep)
-    
+
                 if (activity == 'RQUAL'):
                     if 'SAVE' in ui_oxrx:   save_timeseries(io_manager,ts,ui_oxrx['SAVE'],siminfo,saveall,operation,segment,'OXRX',jupyterlab,outstep_oxrx)
                     if 'SAVE' in ui_nutrx and flags['NUTRX'] == 1:   save_timeseries(io_manager,ts,ui_nutrx['SAVE'],siminfo,saveall,operation,segment,'NUTRX',jupyterlab,outstep_nutrx)

HSP2IO/hdf.py

@@ -1,12 +1,12 @@
+from typing import Any, Union
+
 import pandas as pd
-from pandas.io.pytables import read_hdf
-from HSP2IO.protocols import Category
-from collections import defaultdict
-from typing import Union, Any
 
 from HSP2.uci import UCI
+from HSP2IO.protocols import Category
 
-class HDF5():
+
+class HDF5:
 
 	def __init__(self, file_path:str) -> None:
 		self.file_path = file_path
@@ -24,9 +24,9 @@ def __exit__(self, exc_type, exc_value, trace):
 
 	def read_uci(self) -> UCI:
 		"""Read UCI related tables
-		
+
 		Parameters: None
-		
+
 		Returns: UCITuple
 
 		"""
@@ -78,44 +78,44 @@ def read_uci(self) -> UCI:
 				uci.monthdata[f'{op}/{module}'] = self._store[path]
 		return uci
 
-	def read_ts(self, 
+	def read_ts(self,
 			category:Category,
-			operation:Union[str,None]=None, 
-			segment:Union[str,None]=None, 
+			operation:Union[str,None]=None,
+			segment:Union[str,None]=None,
 			activity:Union[str,None]=None) -> pd.DataFrame:
 		try:
 			path = ''
 			if category == category.INPUTS:
 				path = f'TIMESERIES/{segment}'
 			elif category == category.RESULTS:
 				path = f'RESULTS/{operation}_{segment}/{activity}'
-			return read_hdf(self._store, path)
+			return pd.read_hdf(self._store, path)
 		except KeyError:
 			return pd.DataFrame()
 
-	def write_ts(self, 
-			data_frame:pd.DataFrame, 
+	def write_ts(self,
+			data_frame:pd.DataFrame,
 			category: Category,
-			operation:str, 
-			segment:str, 
-			activity:str, 
-			*args:Any, 
+			operation:str,
+			segment:str,
+			activity:str,
+			*args:Any,
 			**kwargs:Any) -> None:
 		"""Saves timeseries to HDF5"""
 		path=f'{operation}_{segment}/{activity}'
 		if category:
 			path = 'RESULTS/' + path
-		complevel = None 
+		complevel = None
 		if 'compress' in kwargs:
 			if kwargs['compress']:
 				complevel = 9
-		data_frame.to_hdf(self._store, path, format='t', data_columns=True, complevel=complevel)
-		#data_frame.to_hdf(self._store, path)
+		data_frame.to_hdf(self._store, key=path, format='t', data_columns=True, complevel=complevel)
+		#data_frame.to_hdf(self._store, key=path)
 
 	def write_log(self, hsp2_log:pd.DataFrame) -> None:
-		hsp2_log.to_hdf(self._store, 'RUN_INFO/LOGFILE', data_columns=True, format='t')
+		hsp2_log.to_hdf(self._store, key='RUN_INFO/LOGFILE', data_columns=True, format='t')
 
 	def write_versioning(self, versioning:pd.DataFrame) -> None:
-		versioning.to_hdf(self._store, 'RUN_INFO/VERSIONS', data_columns=True, format='t')
+		versioning.to_hdf(self._store, key='RUN_INFO/VERSIONS', data_columns=True, format='t')