def main(subArea, runName, chartTitlePre, ownership):
outDir = "C:\\Users\\olsenk\\Dropbox\\FPF\\Envision Runs\\keith_production\\"
varList = [' Stand Replacing FirePMG3', ' Stand Replacing FirePMG4', ' Stand Replacing FirePMG5']
yLabelText = 'Percent of PMG 3, 4, and 5 in Stand Replacing Fire (top 10%)'
chartTitle = chartTitlePre
PMG345Ha = reporterFunc.getPMG345Ha(subArea)
# list of ownerships to graphs
if ownership == 'All':
ownersToGraph = ['Federal','State','Private Non-Industrial','Private Industrial','Tribal','Homeowner']
pdfFile = PdfPages(outDir + 'report3_PMG345_in_HS_Fire_top10pct_All.pdf')
else:
ownersToGraph = [ownership]
pdfFile = PdfPages(outDir + 'report3_PMG345_in_HS_Fire_top10pct_' + ownersToGraph[0] + '.pdf')
# setup plot for all scenarios
fig = pl.figure(1, figsize=(11,8.5))
ax = fig.add_subplot(1,1,1)
for scenario in ['CurrentPolicy','NoFedTreat','Restoration']:
inDir = outDir + runName + "_" + scenario + "\\"
yearList = list(set(pd.io.parsers.read_csv(inDir + r'FireOccurance_by_OWNER_pivot.csv')[' Year']))
repList = list(set(pd.io.parsers.read_csv(inDir + r'FireOccurance_by_OWNER_pivot.csv')[' Run']))
totalArea = pd.io.parsers.read_csv(inDir + r'FireOccurance_by_OWNER_pivot.csv')
dataTable = pd.DataFrame(totalArea[totalArea[' Year'] > 0])
dataTable['key'] = dataTable[' OWNER_label'] + '_' + dataTable[' Run'].astype(str) + '_' + dataTable[' Year'].astype(str)
if scenario == 'CurrentPolicy':
scenarioTable = dataTable
else:
scenarioTable = pd.merge(scenarioTable, dataTable, how='left', on='key')
# sum over owners
scenarioTable.index = scenarioTable['key']
fireProneArea = PMG345Ha[ownersToGraph[0]]
if ownership == 'All':
for rep in range(len(repList)):
for year in range(1, len(yearList)):
for owner in ownersToGraph:
key = owner + '_' + str(rep) + '_' + str(year)
print(key)
if owner != ownersToGraph[0]:
for varName in varList:
scenarioTable.loc[ownersToGraph[0] + '_' + str(rep) + '_' + str(year),varName] += scenarioTable.loc[key,varName]
scenarioTable.loc[ownersToGraph[0] + '_' + str(rep) + '_' + str(year),varName + '_x'] += scenarioTable.loc[key,varName + '_x']
scenarioTable.loc[ownersToGraph[0] + '_' + str(rep) + '_' + str(year),varName + '_y'] += scenarioTable.loc[key,varName + '_y']
for owner in ownersToGraph:
fireProneArea += PMG345Ha[owner]
ownerArea = pd.DataFrame(scenarioTable[scenarioTable[' OWNER_label'] == ownersToGraph[0]])
# calculate percent of PMG345 area for each row
ownerArea['CP_HS_pct'] = (ownerArea[varList[0] + '_x'] + ownerArea[varList[1] + '_x'] + ownerArea[varList[2] + '_x']) / fireProneArea * 100
ownerArea['NFT_HS_pct'] = (ownerArea[varList[0] + '_y'] + ownerArea[varList[1] + '_y'] + ownerArea[varList[2] + '_y']) / fireProneArea * 100
ownerArea['Res_HS_pct'] = (ownerArea[varList[0]] + ownerArea[varList[1]] + ownerArea[varList[2]]) / fireProneArea * 100
#Sort dataTable on percent PMG345 in HS fire
dataTable = ownerArea.sort('NFT_HS_pct', ascending=False)
statsList1 = []
statsList2 = []
statsList3 = []
valueSet = []
maxValueSet = []
for i in range(int(round(len(dataTable) * 0.1))):
statsList1.append(dataTable['CP_HS_pct'].iloc[i])
statsList2.append(dataTable['NFT_HS_pct'].iloc[i])
statsList3.append(dataTable['Res_HS_pct'].iloc[i])
valueSet.append(statsList1)
valueSet.append(statsList2)
valueSet.append(statsList3)
maxValueSet.append(max(statsList1))
maxValueSet.append(max(statsList2))
maxValueSet.append(max(statsList3))
labelList = ['Current Policy','No Fed Treatment','Restoration']
reporterFunc.plotReporter3(fig, ax, ownership + ' - ' + str(len(repList)) + ' reps', pdfFile, valueSet, labelList, subArea, chartTitle, yLabelText, scenario, maxValueSet)
pdfFile.savefig()
pl.close()
pdfFile.close()
print "Done."
def main(subArea, runName, chartTitlePre, ownership):
outDir = "C:\\Users\\olsenk\\Dropbox\\FPF\\Envision Runs\\keith_production\\"
varList = [' Total Merch Harvest (m3)']
yLabelText = 'Merchantable Volume Harvested (m3)'
chartTitle = chartTitlePre
PMG345Ha = {'Federal':422702, 'State':22622, 'Private Non-Industrial':23372, 'Private Industrial':51911, 'Tribal':101160, 'Homeowner':3176}
# list of ownerships to graphs
if ownership == 'All':
ownersToGraph = ['Federal','State','Private Non-Industrial','Private Industrial','Tribal','Homeowner']
pdfFile = PdfPages(outDir + 'report3_Merch_Volume_All.pdf')
else:
ownersToGraph = [ownership]
pdfFile = PdfPages(outDir + 'report3_Merch_Volume_' + ownersToGraph[0] + '.pdf')
# setup plot for all scenarios
fig = pl.figure(1, figsize=(11,8.5))
ax = fig.add_subplot(1,1,1)
# Current policy required
for scenario in ['CurrentPolicy','NoFedTreat','Restoration']:
inDir = outDir + runName + "_" + scenario + "\\"
if os.path.isdir(inDir):
yearList = list(set(pd.io.parsers.read_csv(inDir + r'WoodProducts_by_OWNER_pivot.csv')[' Year']))
repList = list(set(pd.io.parsers.read_csv(inDir + r'WoodProducts_by_OWNER_pivot.csv')[' Run']))
totalArea = pd.io.parsers.read_csv(inDir + r'WoodProducts_by_OWNER_pivot.csv')
dataTable = pd.DataFrame(totalArea[totalArea[' Year'] > 0])
dataTable['key'] = dataTable[' OWNER_label'] + '_' + dataTable[' Run'].astype(str) + '_' + dataTable[' Year'].astype(str)
if scenario == 'CurrentPolicy':
scenarioTable = dataTable
else:
scenarioTable = pd.merge(scenarioTable, dataTable, how='left', on='key')
# sum over owners
scenarioTable.index = scenarioTable['key']
fireProneArea = PMG345Ha[ownersToGraph[0]]
if ownership == 'All':
for rep in range(len(repList)):
for year in range(1, len(yearList)):
for owner in ownersToGraph:
key = owner + '_' + str(rep) + '_' + str(year)
print(key)
if owner != ownersToGraph[0]:
for varName in varList:
scenarioTable.loc[ownersToGraph[0] + '_' + str(rep) + '_' + str(year),varName] += scenarioTable.loc[key,varName]
scenarioTable.loc[ownersToGraph[0] + '_' + str(rep) + '_' + str(year),varName + '_x'] += scenarioTable.loc[key,varName + '_x']
scenarioTable.loc[ownersToGraph[0] + '_' + str(rep) + '_' + str(year),varName + '_y'] += scenarioTable.loc[key,varName + '_y']
for owner in ownersToGraph:
fireProneArea += PMG345Ha[owner]
ownerArea = pd.DataFrame(scenarioTable[scenarioTable[' OWNER_label'] == ownersToGraph[0]])
#Sort dataTable on percent PMG345 in HS fire
## dataTable = ownerArea.sort('NFT_HS_pct', ascending=False)
# subset table for specific year
valueSet = []
maxValueSet = []
labelList = []
for yearVal in [24,49]:
yearTable = ownerArea[ownerArea[' Year'] == yearVal]
statsList1 = []
statsList2 = []
statsList3 = []
for i in range(int(round(len(yearTable)))):
statsList1.append(yearTable[varList[0] + '_x'].iloc[i])
statsList2.append(yearTable[varList[0] + '_y'].iloc[i])
statsList3.append(yearTable[varList[0]].iloc[i])
valueSet.append(statsList1)
valueSet.append(statsList2)
valueSet.append(statsList3)
maxValueSet.append(max(statsList1))
maxValueSet.append(max(statsList2))
maxValueSet.append(max(statsList3))
labelList += ['CP Year ' + str(yearVal),'NFT Year ' + str(yearVal),'Res Year ' + str(yearVal)]
reporterFunc.plotReporter3(fig, ax, ownership + ' - ' + str(len(repList)) + ' reps', pdfFile, valueSet, labelList, subArea, chartTitle, yLabelText, 'CurrentPolicy', maxValueSet)
pdfFile.savefig()
pl.close()
pdfFile.close()
print "Done."
def main(subArea, runName, chartTitlePre, ownership):
outDir = "C:\\Users\\olsenk\\Dropbox\\FPF\\Envision Runs\\keith_production\\"
varList = [' White-headed Woodpecker Good (ha)']
yLabelText = 'White-headed Woodpecker Good Habitat (ha)'
chartTitle = chartTitlePre
PMG345Ha = {
'Federal': 422702,
'State': 22622,
'Private Non-Industrial': 23372,
'Private Industrial': 51911,
'Tribal': 101160,
'Homeowner': 3176
}
# list of ownerships to graphs
if ownership == 'All':
ownersToGraph = [
'Federal', 'State', 'Private Non-Industrial', 'Private Industrial',
'Tribal', 'Homeowner'
]
pdfFile = PdfPages(outDir + 'report3_WHWO_iLAP_All.pdf')
else:
ownersToGraph = [ownership]
pdfFile = PdfPages(outDir + 'report3_WHWO_iLAP_' + ownersToGraph[0] +
'.pdf')
# setup plot for all scenarios
fig = pl.figure(1, figsize=(11, 8.5))
ax = fig.add_subplot(1, 1, 1)
for scenario in ['CurrentPolicy', 'NoFedTreat', 'Restoration']:
inDir = outDir + runName + "_" + scenario + "\\"
yearList = list(
set(
pd.io.parsers.read_csv(
inDir + r'ILAP_wildlife_models_pivot.csv')[' Year']))
repList = list(
set(
pd.io.parsers.read_csv(
inDir + r'ILAP_wildlife_models_pivot.csv')[' Run']))
totalArea = pd.io.parsers.read_csv(inDir +
r'ILAP_wildlife_models_pivot.csv')
dataTable = pd.DataFrame(totalArea[totalArea[' Year'] > 0])
dataTable['key'] = 'key_' + dataTable[' Run'].astype(
str) + '_' + dataTable[' Year'].astype(str)
if scenario == 'CurrentPolicy':
scenarioTable = dataTable
else:
scenarioTable = pd.merge(scenarioTable,
dataTable,
how='left',
on='key')
# subset table for specific year
valueSet = []
maxValueSet = []
labelList = []
for yearVal in [24, 49]:
yearTable = scenarioTable[scenarioTable[' Year'] == yearVal]
statsList1 = []
statsList2 = []
statsList3 = []
for i in range(int(round(len(yearTable)))):
statsList1.append(yearTable[varList[0] + '_x'].iloc[i])
statsList2.append(yearTable[varList[0] + '_y'].iloc[i])
statsList3.append(yearTable[varList[0]].iloc[i])
valueSet.append(statsList1)
valueSet.append(statsList2)
valueSet.append(statsList3)
maxValueSet.append(max(statsList1))
maxValueSet.append(max(statsList2))
maxValueSet.append(max(statsList3))
labelList += [
'CP Year ' + str(yearVal), 'NFT Year ' + str(yearVal),
'Res Year ' + str(yearVal)
]
reporterFunc.plotReporter3(fig, ax,
ownership + ' - ' + str(len(repList)) + ' reps',
pdfFile, valueSet, labelList, subArea,
chartTitle, yLabelText, 'CurrentPolicy',
maxValueSet)
pdfFile.savefig()
pl.close()
pdfFile.close()
print "Done."
def main(subArea, runName, chartTitlePre, ownership):
outDir = "C:\\Users\\olsenk\\Dropbox\\FPF\\Envision Runs\\keith_production\\"
varList = [
' Stand Replacing FirePMG3', ' Stand Replacing FirePMG4',
' Stand Replacing FirePMG5'
]
yLabelText = 'Percent of PMG 3, 4, and 5 in Stand Replacing Fire'
chartTitle = chartTitlePre
PMG345Ha = reporterFunc.getPMG345Ha(subArea)
# list of ownerships to graphs
if ownership == 'All':
ownersToGraph = [
'Federal', 'State', 'Private Non-Industrial', 'Private Industrial',
'Tribal', 'Homeowner'
]
pdfFile = PdfPages(outDir + 'report3_PMG345_in_HS_Fire_All.pdf')
else:
ownersToGraph = [ownership]
pdfFile = PdfPages(outDir + 'report3_PMG345_in_HS_Fire_' +
ownersToGraph[0] + '.pdf')
# setup plot for all scenarios
fig = pl.figure(1, figsize=(11, 8.5))
ax = fig.add_subplot(1, 1, 1)
valueSet1 = []
valueSet2 = []
maxValueSet1 = []
maxValueSet2 = []
for scenario in ['CurrentPolicy', 'NoFedTreat', 'Restoration']:
inDir = outDir + runName + "_" + scenario + "\\"
yearList = list(
set(
pd.io.parsers.read_csv(
inDir + r'FireOccurance_by_OWNER_pivot.csv')[' Year']))
repList = list(
set(
pd.io.parsers.read_csv(
inDir + r'FireOccurance_by_OWNER_pivot.csv')[' Run']))
totalArea = pd.io.parsers.read_csv(inDir +
r'FireOccurance_by_OWNER_pivot.csv')
# get stats from multiple reps
statsList1 = []
statsList2 = []
for year in range(1, max(yearList) + 1):
yearArea = totalArea[totalArea[' Year'] == year]
dataList = []
for rep in repList:
repArea = yearArea[yearArea[' Run'] == rep]
# sum output over selected ownerships
for ownerToGraph in ownersToGraph:
if ownerToGraph == ownersToGraph[0]:
ownerArea = pd.DataFrame(
repArea[repArea[' OWNER_label'] == ownerToGraph])
fireProneArea = PMG345Ha[ownerToGraph]
else:
tempArea = repArea[repArea[' OWNER_label'] ==
ownerToGraph]
for varName in varList:
# totalArea.loc[list(ownerArea.index)[0],varName] += tempArea[varName].iloc[0]
ownerArea[varName].iloc[0] += tempArea[
varName].iloc[0]
fireProneArea += PMG345Ha[ownerToGraph]
ownerToGraph = 'All'
if fireProneArea > 0:
dataList.append(
(ownerArea[varList[0]].iloc[0] +
ownerArea[varList[1]].iloc[0] +
ownerArea[varList[2]].iloc[0]) / fireProneArea * 100)
else:
dataList.append(0.0)
# add year data to dictionary
if year < 25:
statsList1 += dataList
else:
statsList2 += dataList
valueSet1.append(statsList1)
valueSet2.append(statsList2)
maxValueSet1.append(max(statsList1))
maxValueSet2.append(max(statsList2))
labelList = [
'CP 0-24', 'NFT 0-24', 'Res 0-24', 'CP 25-50', 'NFT 25-50', 'Res 25-50'
]
reporterFunc.plotReporter3(
fig, ax, ownerToGraph + ' - ' + str(len(repList)) + ' reps', pdfFile,
valueSet1 + valueSet2, labelList, subArea, chartTitle, yLabelText,
scenario, maxValueSet1 + maxValueSet2)
pdfFile.savefig()
pl.close()
pdfFile.close()
print "Done."