Merge pull request #87 from RAMP-project/hotfix/hidden-result-files-c…

…ommand-cli

Hotfix/hidden result files command cli

CHANGELOG.md

@@ -1,13 +1,17 @@
 Release History
 ===============
 
-0.4.1 (dev)
+0.4.2 (dev)
 ------------------
 
 **|fixed|**     installation options have been debugged and the documentation updated accordingly
 
 **|fixed|**     automated download of example applications via the `download_example` functions now includes previously missing .csv files
 
+0.4.1 (2023-10-XX)
+------------------
+
+**|hotfix|**    added option `-o` to the terminal command line interface to enable the user to provide output path to save ramp results. This option is also accessible to python users using `ofname` argument of the `ramp/ramp_run.py::run_usecase` or the `ramp/post_process/post_process.py::export_series` functions. 
 
 0.4.0 (2023-02-17)
 ------------------

README.rst

@@ -148,7 +148,11 @@ need to run the ``ramp`` command with the option ``-i``:
 
    ramp -i <path to .xlsx input file>
 
-If you already know how many profile you want to simulate, you can indicate it with the
+
+.. note:: You can input several files, separated from each others by a single blank space
+
+If you already know
+how many profile you want to simulate you can indicate it with the
 ``-n`` option:
 
 .. code-block:: bash
@@ -160,7 +164,16 @@ providing a ``.xlsx`` input file with the ``-i`` option, this will then
 be equivalent to running ``python ramp_run.py`` from the ``ramp`` folder
 without being prompted for the number of profile within the console.
 
-Other options are documented in the helper of `ramp`, which you access with the ``-h`` option
+
+If you want to save ramp results to a custom file, you can provide it with the option `-o`
+
+.. code-block:: bash
+
+   ramp -i <path to .xlsx input file> -o <path where to save RAMP outputs>
+
+.. note:: You can provide a number of output files, separated from each others by a single blank space, matching the number of input files.
+
+Other options are documented in the help of `ramp`, which you access with the ``-h`` option
 
 .. code-block:: bash
 

ramp/_version.py

@@ -1,2 +1,2 @@
 
-__version__ = "0.4.0"
+__version__ = "0.4.1"

ramp/cli.py

@@ -19,6 +19,13 @@
     type=str,
     help="path to the (xlsx) input files (including filename). If not provided, then legacy .py input files will be fetched",
 )
+parser.add_argument(
+    "-o",
+    dest="ofname_path",
+    nargs="+",
+    type=str,
+    help=f"path to the csv output files (including filename). If not provided, default output will be provided in {os.path.join(BASE_PATH, 'results')}",
+)
 parser.add_argument(
     "-n",
     dest="num_profiles",
@@ -72,6 +79,7 @@ def main():
 
     args = vars(parser.parse_args())
     fnames = args["fname_path"]
+    ofnames = args["ofname_path"]
     num_profiles = args["num_profiles"]
     # Define which input files should be considered and run.
     date_start = args["date_start"]
@@ -120,6 +128,9 @@ def main():
     else:
         days = None
 
+    if ofnames is None:
+        ofnames = [None]
+
     if fnames is None:
         print("Please provide path to input file with option -i, \n\nDefault to old version of RAMP input files\n")
         # Files are specified as numbers in a list (e.g. [1,2] will consider input_file_1.py and input_file_2.py)
@@ -135,8 +146,20 @@ def main():
         else:
             num_profiles = [None] * len(input_files_to_run)
 
+        if len(ofnames) == 1:
+            ofnames = ofnames * len(input_files_to_run)
+        elif len(input_files_to_run) != len(ofnames):
+            raise ValueError(
+                f"The number of output file paths({len(ofnames)}) should match the number of input files paths ({len(input_files_to_run)})"
+            )
+
         for i, j in enumerate(input_files_to_run):
-            run_usecase(j=j, num_profiles=num_profiles[i], parallel=parallel_processing)
+            run_usecase(
+                j=j,
+                ofname=ofnames[i],
+                num_profiles=num_profiles[i],
+                parallel=parallel_processing,
+            )
     else:
         if num_profiles is not None:
             if len(num_profiles) == 1:
@@ -173,10 +196,23 @@ def main():
             #TODO add more columns with other resampled functions (do this in Jupyter)
             resampled.to_csv(os.path.join(BASE_PATH, 'yearly_profile_hourly_resolution.csv'))
         else:
+            if len(ofnames) == 1:
+                ofnames = ofnames * len(fnames)
+            elif len(fnames) != len(ofnames):
+                raise ValueError(
+                    f"The number of output file paths({len(ofnames)}) should match the number of input files paths ({len(fnames)})"
+                )
+
             for i, fname in enumerate(fnames):
-                run_usecase(fname=fname, num_profiles=num_profiles[i], days=days, parallel=parallel_processing)
+                run_usecase(
+                    fname=fname,
+                    ofname=ofnames[i],
+                    num_profiles=num_profiles[i],
+                    days=days,
+                    parallel=parallel_processing,
+                )
 
 
 if __name__ == "__main__":
 
-    main()
+    main()

ramp/post_process/post_process.py

@@ -68,9 +68,25 @@ def Profile_series_plot(stoch_profiles_series):
 
 # Export Profiles
 
-def export_series(stoch_profiles_series, j=None, fname=None):
+def export_series(stoch_profiles_series, j=None, fname=None, ofname=None):
     series_frame = pd.DataFrame(stoch_profiles_series)
-    if j is not None:
-        series_frame.to_csv(os.path.join(BASE_PATH, 'results', 'output_file_%d.csv' % (j)))
-    if fname is not None:
-        series_frame.to_csv(os.path.join(BASE_PATH, 'results', f'output_file_{os.path.split(fname)[-1]}.csv'))
+    path_to_write = None
+    if ofname is not None:
+        path_to_write = ofname
+    else:
+        if j is not None:
+            path_to_write = os.path.join(
+                BASE_PATH, "results", "output_file_%d.csv" % (j)
+            )
+        if fname is not None:
+            path_to_write = os.path.join(
+                BASE_PATH,
+                "results",
+                f'output_file_{os.path.split(fname)[-1].replace(".", "_")}.csv',
+            )
+
+    if path_to_write is not None:
+        print(f"Writing RAMP results to {path_to_write}")
+        series_frame.to_csv(path_to_write)
+    else:
+        print("No path to a file was provided to write the results")

ramp/ramp_run.py

@@ -39,7 +39,8 @@
     from post_process import post_process as pp
 
 
-def run_usecase(j=None, fname=None, num_profiles=None, days=None, plot=True, parallel=False):
+def run_usecase(j=None, fname=None, ofname=None, num_profiles=None, days=None, plot=True, parallel=False):
+
     # Calls the stochastic process and saves the result in a list of stochastic profiles
     if days is None:
         Profiles_list = stochastic_process(j=j, fname=fname, num_profiles=num_profiles, day_type=yearly_pattern(), parallel=parallel)
@@ -48,7 +49,7 @@ def run_usecase(j=None, fname=None, num_profiles=None, days=None, plot=True, par
         Profiles_avg, Profiles_list_kW, Profiles_series = pp.Profile_formatting(Profiles_list)
         pp.Profile_series_plot(Profiles_series)  # by default, profiles are plotted as a series
 
-        pp.export_series(Profiles_series, j, fname)
+        pp.export_series(Profiles_series, j, fname, ofname)
 
         if len(Profiles_list) > 1:  # if more than one daily profile is generated, also cloud plots are shown
             pp.Profile_cloud_plot(Profiles_list, Profiles_avg)
@@ -67,7 +68,7 @@ def run_usecase(j=None, fname=None, num_profiles=None, days=None, plot=True, par
             Profiles_avg, Profiles_list_kW, Profiles_series = pp.Profile_formatting(Profiles_list)
             pp.Profile_series_plot(Profiles_series)  # by default, profiles are plotted as a series
 
-            pp.export_series(Profiles_series, j, fname)
+            pp.export_series(Profiles_series, j, fname, ofname)
 
             if len(Profiles_list) > 1:  # if more than one daily profile is generated, also cloud plots are shown
                 pp.Profile_cloud_plot(Profiles_list, Profiles_avg)