#
# scenario with true sources for generating observations
#
# 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 total 5hours, while a particle travels through domain in 1hour
time = [ 0,60,18000]
# sources mass/m^3/s 
source_locations = [5, 30]
source_labels = ['factory1','factory2']
# generated as 
source_values['factory1'] = [115.42, 103.41, 104.57, 106.88, 98.77, 107.72, 116.51, 116.27, 118.68, 119.95, 118.57, 123.83, 119.48, 135.27, 134.01, 134.58, 142.04, 142.08, 141.00, 134.60, 136.47, 126.50, 131.54, 143.08, 137.67, 143.56, 152.23, 140.13, 129.34, 133.30, 130.16, 134.96, 140.60, 145.39, 154.29, 158.54, 166.51, 157.01, 156.23, 154.47, 142.26, 143.73, 135.66, 145.63, 139.35, 142.84, 144.02, 136.93, 120.90, 120.43, 113.08, 117.62, 121.32, 133.53, 137.56, 132.59, 135.11, 127.53, 127.24, 126.74, 126.61, 124.17, 132.01, 118.22, 121.32, 127.76, 132.91, 136.85, 136.84, 141.45, 145.19, 142.90, 139.76, 137.27, 126.27, 124.45, 125.21, 127.38, 137.69, 134.83, 139.08, 144.52, 150.91, 143.19, 144.32, 145.61, 137.87, 132.17, 139.79, 138.48, 140.98, 141.25, 136.27, 131.92, 134.91, 127.76, 133.27, 137.15, 130.89, 128.76, 119.99, 104.02, 111.40, 107.76, 110.31, 112.14, 112.40, 105.23, 98.59, 96.21, 87.99, 80.85, 92.14, 92.98, 84.58, 84.85, 77.23, 68.14, 67.09, 74.84, 76.50, 81.95, 74.09, 71.49, 70.37, 62.38, 53.75, 61.57, 62.59, 58.84, 65.66, 68.22, 61.88, 72.52, 75.38, 86.80, 95.57, 90.99, 82.09, 82.17, 80.37, 74.89, 79.22, 90.65, 87.15, 81.54, 80.37, 85.80, 80.16, 72.09, 71.99, 72.29, 76.57, 72.95, 72.62, 70.23, 70.45, 82.37, 78.57, 69.47, 73.68, 67.88, 68.98, 65.25, 70.01, 74.82, 74.07, 59.92, 61.85, 74.33, 82.43, 71.58, 71.79, 67.63, 61.05, 53.06, 56.23, 54.15, 55.62, 54.00, 51.70, 55.49, 61.81, 78.04, 68.88, 62.30, 70.74, 68.71, 59.53, 62.79, 74.96, 80.81, 95.61, 99.64, 113.46, 111.08, 102.95, 101.68, 110.58, 102.63, 107.49, 103.32, 107.56, 99.78, 100.71, 86.49, 83.45, 87.37, 85.56, 95.06, 90.88, 74.50, 66.30, 74.81, 74.72, 78.19, 85.69, 70.88, 67.00, 62.75, 56.30, 56.01, 68.06, 68.61, 78.33, 73.95, 74.74, 69.80, 74.85, 73.76, 77.97, 83.48, 83.50, 90.52, 107.70, 111.68, 111.71, 118.44, 118.85, 110.82, 114.47, 114.50, 112.56, 121.91, 135.35, 131.29, 131.82, 125.76, 130.56, 113.24, 120.50, 122.05, 123.89, 132.59, 130.37, 129.21, 119.83, 107.76, 102.84, 105.14, 101.44, 92.06, 100.27, 95.42, 95.72, 96.09, 94.65, 97.92, 96.35, 84.66, 77.77, 80.21, 71.74, 70.00, 63.98, 56.38, 50.01, 48.23, 50.65, 50.94, 59.76, 58.96, 48.95, 50.17, 51.82, 55.21, 59.88, 70.11, 66.94, 69.68, 70.39, 66.99, 83.31, 82.03, 72.42, 86.01, 88.90, 81.29, 86.40, 96.12, 90.00]
source_values['factory2'] = [120.02, 119.00, 110.58, 119.29, 119.17, 123.05, 117.80, 113.07, 115.45, 116.28, 129.71, 127.54, 143.43, 153.95, 139.29, 126.78, 122.50, 121.10, 121.13, 127.15, 121.79, 116.52, 115.10, 115.02, 117.11, 124.80, 129.21, 116.36, 121.46, 127.30, 131.77, 141.05, 143.05, 137.78, 136.39, 118.37, 121.80, 122.61, 118.27, 113.54, 105.80, 105.67, 108.64, 106.42, 103.01, 103.01, 102.01, 95.36, 105.12, 108.54, 117.99, 114.40, 106.38, 112.44, 112.84, 107.47, 107.01, 92.66, 100.95, 94.14, 89.57, 99.76, 93.49, 90.92, 87.72, 99.97, 100.87, 93.34, 85.62, 98.75, 113.11, 125.05, 115.86, 114.36, 113.00, 115.33, 111.24, 104.29, 101.30, 109.43, 126.77, 128.31, 126.22, 131.19, 127.45, 140.80, 148.46, 139.08, 133.90, 143.37, 145.78, 148.18, 135.33, 136.71, 141.39, 136.41, 128.86, 127.35, 119.58, 119.05, 121.08, 130.99, 132.09, 127.95, 139.64, 145.28, 146.51, 150.93, 146.72, 152.46, 153.86, 157.81, 149.58, 160.20, 162.66, 148.06, 150.98, 159.68, 163.64, 172.90, 181.57, 173.95, 156.34, 168.68, 170.69, 169.99, 166.20, 154.31, 155.33, 144.77, 138.27, 136.44, 141.63, 143.98, 133.82, 144.31, 144.13, 157.26, 147.87, 141.73, 135.79, 134.74, 127.41, 120.29, 103.03, 97.23, 99.45, 98.45, 97.57, 97.08, 98.66, 95.37, 90.65, 94.80, 92.16, 94.26, 87.72, 87.18, 93.10, 87.08, 88.61, 87.41, 87.38, 85.31, 70.82, 70.58, 81.47, 86.81, 84.61, 80.39, 82.83, 80.65, 77.46, 78.55, 88.30, 70.56, 75.59, 69.01, 76.68, 59.82, 59.18, 60.59, 58.48, 58.01, 48.06, 41.08, 36.46, 40.48, 37.54, 50.02, 52.18, 39.79, 37.81, 34.43, 36.58, 36.34, 35.69, 31.75, 32.73, 23.70, 29.71, 21.60, 18.42, 19.02, 22.47, 23.51, 37.68, 50.77, 56.44, 58.14, 53.30, 51.04, 41.98, 40.54, 38.43, 52.45, 59.00, 60.47, 59.31, 60.90, 67.41, 84.47, 87.40, 94.18, 99.51, 103.85, 111.36, 120.61, 120.90, 118.59, 120.24, 127.44, 136.11, 131.90, 138.29, 136.73, 134.00, 137.68, 144.12, 139.57, 128.38, 127.86, 131.72, 132.12, 143.33, 140.53, 145.93, 139.80, 130.31, 134.96, 124.61, 115.09, 110.78, 100.13, 104.49, 102.72, 93.62, 87.61, 80.98, 81.09, 64.23, 60.11, 51.01, 54.52, 59.92, 61.96, 62.17, 44.03, 45.47, 40.34, 39.72, 38.66, 31.60, 37.25, 40.33, 39.09, 46.88, 59.50, 52.46, 53.37, 46.41, 53.05, 57.76, 55.03, 52.04, 47.69, 55.57, 54.82, 54.80, 46.75, 50.21, 70.83, 73.72, 64.17, 66.86, 57.33, 59.42, 48.15, 54.53, 63.86, 76.01]
#output (index based and 0 based)
output_file = 'pollution_model_generate_observations.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]