From 4daf4bcfee811437f8094c4e6b6129a6a48ab098 Mon Sep 17 00:00:00 2001
From: dcradu <dcradu@uliege.be>
Date: Mon, 25 Oct 2021 15:30:55 +0200
Subject: [PATCH] removed reading existing files in main
---
src/main.py | 42 +++++++++---------------------------------
1 file changed, 9 insertions(+), 33 deletions(-)
diff --git a/src/main.py b/src/main.py
index ccc6f2a..aa41993 100644
--- a/src/main.py
+++ b/src/main.py
@@ -1,8 +1,8 @@
import pickle
import yaml
-from os.path import join, isfile, isdir
+from os.path import join, isdir
from os import makedirs
-from numpy import sum, float64
+from numpy import float64
from time import strftime
import julia
from julia import Main
@@ -28,37 +28,13 @@ if __name__ == '__main__':
model_parameters['technologies'],
model_parameters['deployments'])
- if isfile(join(data_path, 'input/criticality_matrix.p')):
-
- custom_log(' WARNING! Instance data read from files.')
- D = pickle.load(open(join(data_path, 'input/criticality_matrix.p'), 'rb'))
- site_coordinates = pickle.load(open(join(data_path, 'input/site_coordinates.p'), 'rb'))
- capacity_factors_data = pickle.load(open(join(data_path, 'input/capacity_factors_data.p'), 'rb'))
- site_positions = pickle.load(open(join(data_path, 'input/site_positions.p'), 'rb'))
-
- r = list(site_coordinates.keys())
- d = sum(model_parameters['deployments'])
- t = model_parameters['technologies']
- ts = len(capacity_factors_data[list(site_coordinates.keys())[0]][model_parameters['technologies'][0]].time)
- custom_log(f" Reading data for a model with a spatial resolution of {float(spatial_resolution)}, "
- f"covering {r}, siting {d} {t} sites and {ts} time steps.")
-
- else:
-
- custom_log('Files not available. Starting data pre-processing.')
-
- database = read_database(data_path, spatial_resolution)
- site_coordinates = return_filtered_coordinates(database, model_parameters, tech_parameters)
- truncated_data = selected_data(database, site_coordinates, time_horizon)
- capacity_factors_data = return_output(truncated_data, data_path)
- time_windows_data = resource_quality_mapping(capacity_factors_data, siting_parameters)
- D = xarray_to_ndarray(critical_window_mapping(time_windows_data, model_parameters))
- site_positions = sites_position_mapping(time_windows_data)
-
- pickle.dump(D, open(join(data_path, 'input/criticality_matrix.p'), 'wb'), protocol=4)
- pickle.dump(site_coordinates, open(join(data_path, 'input/site_coordinates.p'), 'wb'), protocol=4)
- pickle.dump(capacity_factors_data, open(join(data_path, 'input/capacity_factors_data.p'), 'wb'), protocol=4)
- pickle.dump(site_positions, open(join(data_path, 'input/site_positions.p'), 'wb'), protocol=4)
+ database = read_database(data_path, spatial_resolution)
+ site_coordinates = return_filtered_coordinates(database, model_parameters, tech_parameters)
+ truncated_data = selected_data(database, site_coordinates, time_horizon)
+ capacity_factors_data = return_output(truncated_data, data_path)
+ time_windows_data = resource_quality_mapping(capacity_factors_data, siting_parameters)
+ D = xarray_to_ndarray(critical_window_mapping(time_windows_data, model_parameters))
+ site_positions = sites_position_mapping(time_windows_data)
output_dir = join(data_path, f"output/{strftime('%Y%m%d_%H%M%S')}/")
if not isdir(output_dir):
--
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