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mali-plotter.py
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mali-plotter.py
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import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import matplotlib
import sys
import datamanager.handle_refugee_data as handle_refugee_data
def set_margins(l=0.13,b=0.13,r=0.96,t=0.96):
#adjust margins.
fig = plt.gcf()
fig.subplots_adjust(bottom=b,top=t,left=l,right=r)
def plotme(out_dir, data, name):
plt.clf()
data_x = []
data_y = []
d = handle_refugee_data.DataTable("mali2012/refugees.csv", csvformat="mali-portal")
for day in range(0, len(data["%s data" % name])):
if d.is_interpolated(name, day) == False:
#draw a point
data_x.append(day)
data_y.append(data.at[day,"%s data" % name])
# data.loc[:,["%s sim" % name,"%s data" % name]]).as_matrix()
y1 = data["%s sim" % name].as_matrix()
y2 = data["%s data" % name].as_matrix()
days = np.arange(len(y1))
#plt.ylabel("Number of refugees")
plt.xlabel("Days elapsed")
#matplotlib.rc('xtick', labelsize=16)
#matplotlib.rc('ytick', labelsize=16)
matplotlib.rcParams.update({'font.size': 22})
country = {"Bobo-Dioulasso":"(BF)","Mentao":"(BF)","Mbera":"(MAU)","Fassala":"(MAU)","Abala":"(NI)","Mangaize":"(NI)","Niamey":"(NI)","Tabareybarey":"(NI)"}
labelsim, = plt.plot(days,y1, linewidth=10, label="%s %s simulation" % (name.title(), country[name.title()]))
labeldata, = plt.plot(days,y2, linewidth=10, label="%s %s UNHCR data" % (name.title(), country[name.title()]))
plt.plot(data_x,data_y,'ob')
plt.legend(handles=[labelsim, labeldata],loc=4,prop={'size':20})
fig = matplotlib.pyplot.gcf()
fig.set_size_inches(12, 8)
#adjust margins.
set_margins()
fig.savefig("%s/%s.png" % (out_dir, name))
def plotme_minimal(out_dir, data, name):
plt.clf()
data_x = []
data_y = []
d = handle_refugee_data.DataTable("mali2012/refugees.csv", csvformat="mali-portal")
for day in range(0, len(data["%s data" % name])):
if d.is_interpolated(name, day) == False:
#draw a point
data_x.append(day)
data_y.append(data.at[day,"%s data" % name])
# data.loc[:,["%s sim" % name,"%s data" % name]]).as_matrix()
y1 = data["%s sim" % name].as_matrix()
y2 = data["%s data" % name].as_matrix()
days = np.arange(len(y1))
#plt.ylabel("Number of refugees")
#plt.xlabel("Days elapsed")
#matplotlib.rc('xtick', labelsize=16)
#matplotlib.rc('ytick', labelsize=16)
matplotlib.rcParams.update({'font.size': 28})
country = {"Bobo-Dioulasso":"(BF)","Mentao":"(BF)","Mbera":"(MAU)","Fassala":"(MAU)","Abala":"(NI)","Mangaize":"(NI)","Niamey":"(NI)","Tabareybarey":"(NI)"}
max_val = max([max(y1),max(y2)])
plt.xticks([])
plt.yticks([2000,5000])
plt.ylim([0, 1.1*max_val])
labelsim, = plt.plot(days,y1, linewidth=10, label="%s %s simulation" % (name.title(), country[name.title()]))
labeldata, = plt.plot(days,y2, linewidth=10, label="%s %s UNHCR data" % (name.title(), country[name.title()]))
plt.plot(data_x,data_y,'ob')
#plt.legend(handles=[labelsim, labeldata],loc=4,prop={'size':20})
plt.gca().legend_ = None
plt.text(295, 0.02*plt.ylim()[1], "%s %s" % (name.title(), country[name.title()]), size=24, ha='right')
#plt.text(200, 0.02*plt.ylim()[1], "Max: %s" % (max(y1)), size=24)
fig = matplotlib.pyplot.gcf()
fig.set_size_inches(8, 6)
#adjust margins.
set_margins(l=0.14,b=0.13,r=0.96,t=0.96)
fig.savefig("%s/min-%s.png" % (out_dir, name))
if __name__ == "__main__":
if len(sys.argv)>1:
out_dir = sys.argv[1]
else:
out_dir = "out"
matplotlib.style.use('ggplot')
#figsize=(15, 10)
refugee_data = pd.read_csv("%s/out.csv" % (out_dir), sep=',', encoding='latin1',index_col='Day')
for i in ["Mbera","Fassala","Mentao","Bobo-Dioulasso","Abala","Mangaize","Niamey","Tabareybarey"]:
plotme(out_dir, refugee_data,i)
plotme_minimal(out_dir, refugee_data,i)
matplotlib.rcParams.update({'font.size': 20})
plt.clf()
diffdata = refugee_data.loc[:,["Total error"]].as_matrix()
plt.plot(np.arange(len(diffdata)), diffdata, linewidth=5)
#plt.legend(handles=[labeldiff],loc=2,prop={'size':14})
fig = matplotlib.pyplot.gcf()
fig.set_size_inches(12, 8)
plt.ylabel("Averaged relative difference")
plt.xlabel("Days elapsed")
set_margins()
plt.savefig("%s/error.png" % out_dir)
refugee_data.loc[:,["refugees in camps (simulation)","refugees in camps (UNHCR)"]].plot(linewidth=5)
fig = matplotlib.pyplot.gcf()
fig.set_size_inches(12, 8)
set_margins()
plt.savefig("%s/numagents.png" % out_dir)
#plt.show()
# ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))
# ts = ts.cumsum()
# ts.plot()