lowflow_index = Platypus.calcLowFlowIndex(year_data, flow_col, summerlow, winterlow, summerlowday, winterlowday, index_method="linear_scaling") # method = "min_duration" or "linear_scaling"
food_index, dispersal_index = Platypus.calcFoodDispIndex(year_data, flow_col, freshes, durations, frequencies, timing)
burrow_index = Platypus.calcBurrowIndex(year_data, flow_col, burrow_startmonth, burrow_endmonth, entrance_buffer, breeding_startmonth, breeding_endmonth)
#platypus_index = pd.DataFrame(index=["{y}/{s0}/{s1}-{y1}/{e0}/{e1}".format(y=year, y1=year+1, s0=start_time[0], s1=start_time[1], e0=end_time[0], e1=end_time[1])])
platypus_index = pd.DataFrame(index=["{y}/{s0}-{y1}/{e0}".format(y=year, y1=year+1, s0=start_time[0], e0=end_time[0])])
platypus_index['lowflow_index'] = lowflow_index
platypus_index['food_index'] = food_index
platypus_index['dispersal_index'] = dispersal_index
platypus_index['burrow_index'] = burrow_index
# platypus_index['annualflow']=annualflow
#Add to benchmark dataframe
platypusIndexes = platypusIndexes.append(platypus_index)
#End if
#End for
platypusIndexes['platypus_index']=platypusIndexes.mean(axis=1)
platypusIndexes['platypus_rolling_index']=pd.rolling_mean(platypusIndexes['platypus_index'],3)
print platypusIndexes.describe()
platypusIndexes["platypus_rolling_index"].plot(marker='o')
# platypusIndexes.index.name = 'Time'
# ggplot(platypusIndexes,aes(x='Time', y='platypus_rolling_index'))+geom_line()
FileHandle.writeCSV(platypusIndexes, "./Integrated/Modules/Ecology/Outputs", "platypus_index.csv")
FileHandle.writeCSV(flow_data, "./Integrated/Modules/Ecology/Outputs", "platypus_flowdata.csv")
platypus_index = pd.DataFrame(index=[
"{y}/{s0}-{y1}/{e0}".format(
y=year, y1=year + 1, s0=start_time[0], e0=end_time[0])
])
platypus_index['lowflow_index'] = lowflow_index
platypus_index['food_index'] = food_index
platypus_index['dispersal_index'] = dispersal_index
platypus_index['burrow_index'] = burrow_index
# platypus_index['annualflow']=annualflow
#Add to benchmark dataframe
platypusIndexes = platypusIndexes.append(platypus_index)
#End if
#End for
platypusIndexes['platypus_index'] = platypusIndexes.mean(axis=1)
platypusIndexes['platypus_rolling_index'] = pd.rolling_mean(
platypusIndexes['platypus_index'], 3)
print platypusIndexes.describe()
platypusIndexes["platypus_rolling_index"].plot(marker='o')
# platypusIndexes.index.name = 'Time'
# ggplot(platypusIndexes,aes(x='Time', y='platypus_rolling_index'))+geom_line()
FileHandle.writeCSV(platypusIndexes, "./Integrated/Modules/Ecology/Outputs",
"platypus_index.csv")
FileHandle.writeCSV(flow_data, "./Integrated/Modules/Ecology/Outputs",
"platypus_flowdata.csv")
#For development purposes only. Display index results for each species
for species in specieslist:
save_folder = "./Integrated/Modules/Ecology/Outputs/{s}/{asset}/{sp}".format(s=scen_name, asset=eco_site, sp=species)
species_index = flow_indexes[species]
all_index = species_index['gw'][['gw_suitability_index','sw_suitability_index','water_suitability_index']]
all_index_annual = all_index.resample("A", how='sum')
all_index_rolling = pd.rolling_mean(all_index_annual,3)
print scen_name,eco_site, species
all_index_annual.plot()
FileHandle.writeCSV(all_index, save_folder, "all_index_daily.csv")
FileHandle.writeCSV(all_index_annual, save_folder, "all_index_annual.csv")
FileHandle.writeCSV(all_index_rolling, save_folder, "all_index_rolling.csv")
# print species
# print "---- Groundwater ----"
# FileHandle.writeCSV(species_index['gw'], save_folder, "gw.csv")
# # print species_index['gw']
# print "---------------------"
# print "---- Surface Water ----"
# FileHandle.writeCSV(species_index['sw'], save_folder, "sw.csv")
# # print species_index['sw']
# print "---------------------"
# print "---- Water Index ----"
# FileHandle.writeCSV(species_index['water_index'], save_folder, "water_index.csv")
#End if
Manager.season_started = False
#Debugging counter
season_counter = 0
year_counter += 1
#Reset pumping costs for next timestep
for f in Manager.Farm.fields:
pumping_costs[f.name] = 0
#End if
#End if
assert pd.to_datetime(str(timestep)) == current_ts, "Somehow the timestep changed! {} - {}".format(timestep, current_ts)
timestep = loop_timestep
#End while
#print long_results
# OUTPUT RESULTS ABOVE INTO CSV FOR VISUALIZATION
for Field in Manager.Farm.fields:
long_results[Field.name].loc['Total', :] = long_results[Field.name].sum(axis=0, numeric_only=True, skipna=False)
FileHandler.writeCSV(long_results[Field.name], 'output', '2nd_phase_{f}.csv'.format(f=Field.name))
FileHandler.writeCSV(irrigation_log[Field.name], 'output', '2nd_phase_{f}_irrig_log.csv'.format(f=Field.name))
#End for
print "==== DONE ===="
])
fish_index['lowflow_index'] = lowflow_index
fish_index['spawning_index'] = spawn_index
fish_index['dispersal_index'] = dispersal_index
fish_index['washout_index'] = washout_index
# fish_index['annualflow']=annualflow
#Add to benchmark dataframe
fishIndexes = fishIndexes.append(fish_index)
#End if
#End for
fishIndexes['long_lived_fish_index'] = fishIndexes.mean(axis=1)
fishIndexes['short_lived_fish_index'] = fishIndexes['lowflow_index']
fishIndexes['short_lived_fish_rindex'] = pd.rolling_mean(
fishIndexes['short_lived_fish_index'], 2)
fishIndexes['long_lived_fish_rindex'] = pd.rolling_mean(
fishIndexes['long_lived_fish_index'], 4)
print fishIndexes.describe()
fishIndexes["short_lived_fish_rindex"].plot()
fishIndexes["long_lived_fish_rindex"].plot(color="red")
FileHandle.writeCSV(fishIndexes, "./Integrated/Modules/Ecology/Outputs",
"fish_index.csv")
#FileHandle.writeCSV(flow_data, "./Integrated/Modules/Ecology/Outputs", "fish_flowdata.csv")
Manager.season_started = False
# Debugging counter
season_counter = 0
year_counter += 1
# Reset pumping costs for next timestep
for f in Manager.Farm.fields:
pumping_costs[f.name] = 0
# End if
# End if
assert pd.to_datetime(str(timestep)) == current_ts, "Somehow the timestep changed! {} - {}".format(
timestep, current_ts
)
timestep = loop_timestep
# End while
# print long_results
# OUTPUT RESULTS ABOVE INTO CSV FOR VISUALIZATION
for Field in Manager.Farm.fields:
long_results[Field.name].loc["Total", :] = long_results[Field.name].sum(axis=0, numeric_only=True, skipna=False)
FileHandler.writeCSV(long_results[Field.name], "output", "2nd_phase_{f}.csv".format(f=Field.name))
FileHandler.writeCSV(irrigation_log[Field.name], "output", "2nd_phase_{f}_irrig_log.csv".format(f=Field.name))
# End for
print "==== DONE ===="
save_folder = "./Integrated/Modules/Ecology/Outputs/{s}/{asset}/{sp}".format(
s=scen_name, asset=eco_site, sp=species)
species_index = flow_indexes[species]
all_index = species_index['gw'][[
'gw_suitability_index', 'sw_suitability_index',
'water_suitability_index'
]]
all_index_annual = all_index.resample("A", how='sum')
all_index_rolling = pd.rolling_mean(all_index_annual, 3)
print scen_name, eco_site, species
all_index_annual.plot()
FileHandle.writeCSV(all_index, save_folder,
"all_index_daily.csv")
FileHandle.writeCSV(all_index_annual, save_folder,
"all_index_annual.csv")
FileHandle.writeCSV(all_index_rolling, save_folder,
"all_index_rolling.csv")
# print species
# print "---- Groundwater ----"
# FileHandle.writeCSV(species_index['gw'], save_folder, "gw.csv")
# # print species_index['gw']
# print "---------------------"
# print "---- Surface Water ----"
# FileHandle.writeCSV(species_index['sw'], save_folder, "sw.csv")
# # print species_index['sw']
# print "---------------------"
# print "---- Water Index ----"
#fish_index = pd.DataFrame(index=["{y}/{s0}/{s1}-{y1}/{e0}/{e1}".format(y=year, y1=year+1, s0=start_time[0], s1=start_time[1], e0=end_time[0], e1=end_time[1])])
fish_index = pd.DataFrame(index=["{y}/{s0}-{y1}/{e0}".format(y=year, y1=year+1, s0=start_time[0], e0=end_time[0])])
fish_index['lowflow_index'] = lowflow_index
fish_index['spawning_index'] = spawn_index
fish_index['dispersal_index'] = dispersal_index
fish_index['washout_index'] = washout_index
# fish_index['annualflow']=annualflow
#Add to benchmark dataframe
fishIndexes = fishIndexes.append(fish_index)
#End if
#End for
fishIndexes['long_lived_fish_index']=fishIndexes.mean(axis=1)
fishIndexes['short_lived_fish_index']=fishIndexes['lowflow_index']
fishIndexes['short_lived_fish_rindex']=pd.rolling_mean(fishIndexes['short_lived_fish_index'],2)
fishIndexes['long_lived_fish_rindex']=pd.rolling_mean(fishIndexes['long_lived_fish_index'],4)
print fishIndexes.describe()
fishIndexes["short_lived_fish_rindex"].plot()
fishIndexes["long_lived_fish_rindex"].plot(color="red")
FileHandle.writeCSV(fishIndexes, "./Integrated/Modules/Ecology/Outputs", "fish_index.csv")
#FileHandle.writeCSV(flow_data, "./Integrated/Modules/Ecology/Outputs", "fish_flowdata.csv")
