#
# scenario with modified sources for calibration of average pollutant from the sources
#
# lines with a hash-sign are ignored
#
# input for 1d pollution model
#
# grid
x = [0.0, 60.0, 3600.0] 
# stationary flow
u = [1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0]
# cross sectional area
a = [1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0]
# initial concentrations
c = [0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
# simulation timespan
refdate = '01 dec 1999'
#unit is always seconds
unit = 'seconds'
# step is 1min=60seconds total 5hours=18000seconds, while a particle travels through domain in 1hour
time = [ 0,60,15000]
# sources mass/m^3/s 
source_locations = [5, 30]
source_labels = ['factory1','factory2']
# generated as 
source_values['factory1'] = [155.00, 125.27, 135.33, 139.29, 117.52, 118.14, 130.15, 129.47, 123.16, 122.99, 132.20, 135.35, 134.03, 156.76, 160.72, 163.72, 159.19, 146.05, 152.32, 141.05, 145.72, 127.23, 139.15, 156.72, 155.77, 154.73, 160.93, 153.98, 131.60, 131.09, 119.74, 131.25, 149.50, 157.64, 161.88, 168.36, 174.99, 155.61, 156.94, 156.93, 137.66, 135.09, 125.60, 138.09, 124.02, 123.71, 123.11, 125.08, 122.37, 133.32, 132.26, 138.78, 142.45, 142.24, 144.04, 141.55, 145.04, 129.60, 126.29, 130.44, 124.94, 114.34, 122.95, 119.55, 119.47, 131.76, 130.77, 133.05, 128.68, 144.82, 155.27, 139.56, 135.65, 137.33, 115.37, 112.97, 109.91, 115.99, 120.53, 117.19, 120.16, 114.15, 117.48, 105.39, 107.47, 106.48, 85.26, 90.35, 111.37, 111.35, 109.71, 111.00, 102.78, 102.19, 95.54, 100.67, 110.97, 121.30, 126.72, 108.72, 95.92, 78.84, 88.13, 85.03, 90.50, 89.05, 88.39, 80.26, 83.15, 77.35, 62.48, 52.40, 65.12, 62.98, 66.28, 72.87, 69.82, 58.77, 61.63, 81.59, 65.53, 81.70, 71.55, 67.30, 72.67, 69.08, 47.20, 41.21, 45.59, 36.03, 28.81, 32.17, 22.98, 22.62, 18.98, 36.65, 33.02, 39.81, 37.03, 36.69, 37.59, 27.09, 26.52, 42.96, 47.54, 52.86, 49.96, 59.14, 68.60, 78.29, 74.27, 92.72, 96.22, 92.64, 97.32, 92.31, 101.80, 119.39, 103.34, 72.84, 80.34, 67.67, 76.62, 86.89, 86.11, 93.68, 94.79, 78.06, 91.59, 101.90, 120.36, 123.23, 110.20, 129.01, 128.76, 125.97, 124.14, 117.82, 107.71, 97.80, 88.85, 98.73, 115.76, 142.25, 126.03, 100.63, 111.20, 103.43, 79.26, 85.42, 100.88, 111.40, 124.73, 123.07, 136.09, 128.92, 123.54, 135.26, 146.36, 141.79, 162.81, 153.84, 164.68, 154.75, 149.65, 115.45, 93.82, 95.85, 89.38, 98.13, 83.97, 71.69, 64.70, 68.66, 75.39, 69.48, 71.12, 54.71, 39.72, 44.13, 49.92, 50.15, 53.17, 61.26, 53.54, 46.51, 72.20, 73.19, 73.00, 77.01, 80.01, 94.56, 91.78, 113.41, 139.59, 143.57, 142.88, 152.73, 153.08, 141.33, 152.83, 144.06, 138.35, 145.72, 154.71, 141.79, 150.46, 142.74, 134.75, 114.81, 120.06, 102.21, 93.43, 91.06, 99.07, 97.16, 97.00, 90.69, 90.40, 88.96, 91.87, 69.39, 73.85, 65.67, 69.61, 56.87, 48.16, 54.45, 66.29, 60.01, 53.23, 56.11, 51.50, 65.20, 56.66, 56.22, 48.88, 38.70, 43.28, 50.70, 49.29, 41.89, 32.89, 38.76, 34.15, 33.48, 44.05, 47.50, 54.26, 61.52, 58.45, 60.13, 87.49, 88.39, 87.47, 101.92, 102.53, 97.20, 96.16, 101.85, 94.67]
source_values['factory2'] = [104.23, 98.75, 100.97, 103.57, 108.01, 102.21, 90.64, 82.54, 86.65, 101.14, 115.24, 109.95, 129.45, 131.14, 115.77, 106.50, 100.04, 97.41, 98.75, 107.82, 114.54, 123.48, 126.61, 116.07, 120.39, 123.54, 120.03, 112.00, 120.30, 124.37, 125.77, 128.35, 116.86, 99.85, 90.20, 69.56, 74.69, 77.55, 64.59, 65.44, 61.21, 71.98, 71.43, 69.40, 62.41, 67.90, 74.99, 72.03, 101.86, 103.80, 116.06, 97.88, 85.79, 78.14, 77.95, 63.24, 58.27, 37.81, 45.50, 46.09, 53.16, 66.68, 56.52, 55.48, 46.90, 52.61, 43.72, 22.95, 15.54, 34.31, 50.86, 63.39, 54.98, 50.07, 63.05, 64.23, 50.36, 41.85, 35.38, 43.34, 58.57, 54.74, 40.90, 43.64, 29.77, 43.66, 59.12, 68.00, 67.38, 80.54, 91.23, 97.26, 94.25, 94.59, 100.52, 91.08, 78.40, 73.04, 71.67, 72.06, 61.20, 84.95, 91.18, 76.14, 85.59, 93.25, 89.42, 93.63, 92.44, 106.19, 97.79, 94.82, 82.60, 95.18, 108.08, 108.02, 116.60, 131.37, 134.38, 143.02, 146.01, 142.17, 133.67, 155.39, 155.23, 155.97, 156.61, 140.52, 143.05, 134.90, 131.95, 125.39, 140.12, 149.18, 121.33, 123.74, 121.16, 119.72, 121.92, 117.52, 116.29, 107.00, 101.17, 106.39, 94.25, 93.95, 100.22, 98.40, 89.12, 103.91, 95.21, 94.90, 92.65, 111.40, 105.76, 117.89, 106.94, 107.22, 117.90, 104.22, 109.53, 120.35, 120.05, 135.85, 115.25, 134.08, 143.42, 149.33, 139.10, 119.46, 118.58, 119.69, 121.48, 109.33, 104.27, 82.72, 87.50, 97.85, 102.41, 86.11, 91.52, 88.21, 77.18, 64.49, 62.57, 58.48, 65.11, 64.99, 68.56, 95.00, 100.39, 86.96, 72.16, 76.80, 82.82, 75.79, 77.95, 88.39, 90.62, 81.93, 95.92, 86.24, 71.96, 67.27, 75.02, 68.20, 91.19, 104.80, 110.05, 113.27, 106.63, 98.93, 92.09, 98.86, 107.24, 114.65, 125.65, 118.19, 125.08, 125.31, 131.96, 159.97, 146.23, 152.47, 148.59, 140.46, 151.59, 156.87, 153.26, 150.65, 148.24, 150.52, 164.78, 153.82, 157.60, 158.91, 149.62, 152.60, 162.96, 158.85, 165.65, 154.67, 165.12, 170.22, 174.38, 166.44, 171.51, 164.49, 153.66, 146.24, 147.66, 133.99, 129.67, 120.41, 130.71, 131.83, 123.64, 106.61, 106.31, 117.17, 88.92, 72.90, 62.66, 66.19, 64.91, 62.41, 62.02, 34.50, 41.03, 36.02, 36.17, 46.35, 33.15, 49.62, 59.77, 56.62, 66.01, 88.22, 82.69, 86.17, 81.18, 86.34, 99.64, 102.92, 111.23, 102.54, 113.23, 116.51, 116.68, 116.73, 123.21, 134.22, 132.45, 116.29, 120.31, 105.84, 91.52, 74.52, 90.58, 96.56, 127.36]

#output (index based and 0 based)
output_file = 'pollution_model.output'
output_locations = [10, 20, 40]
output_labels = ['locA','locB','locC']
# boundaries
# only left and right at locations 0 and -1 allowed at the moment
bound_labels=['left', 'right']
bound_locations=[0, -1]
bound_values['left']=[0.01]
bound_values['right']=[0.0]