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generated bokeh dests graph
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@Aphexis
Aphexis committed Mar 29, 2020
1 parent 4b133d5 commit 3c1bb87
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55 changes: 38 additions & 17 deletions data_analytics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,11 @@
import matplotlib.pyplot as plt
from basic_tests import dorchester_arr, malden_arr, totten_arr
from day_aggregate import plot_any, plot_one
import pandas_bokeh

plt.close('all')

pd.set_option('plotting.backend', 'pandas_bokeh')

intersections = [dorchester_arr, malden_arr, totten_arr]
agg_i = []
Expand All @@ -27,37 +32,37 @@ def destination_traffic(dest):
df['N Huron Church-D'] = agg_i[0][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['N Huron Church-T'] = agg_i[1][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['N Huron Church-M'] = agg_i[2][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['N Huron Church-All'] = df[['N Huron Church-D', 'N Huron Church-M', 'N Huron Church-T']].sum(axis=1)
df['N Huron Church'] = df[['N Huron Church-D', 'N Huron Church-M', 'N Huron Church-T']].sum(axis=1)
elif dest == 1:
#dest 1: dnr, det, dwu, dsl, tnt, tel, twr, tsu, mnt, mel, mwr, msu
df['E Dorch-D'] = agg_i[0][['Right', 'Thru.1', 'U-Turn.3', 'Left.2']].sum(axis=1)
df['E Dorch-T'] = agg_i[0][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['E Dorch-M'] = agg_i[0][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['E Dorch-All'] = df[['E Dorch-D', 'E Dorch-M', 'E Dorch-T']].sum(axis=1)
df['E Dorchester'] = df[['E Dorch-D', 'E Dorch-M', 'E Dorch-T']].sum(axis=1)
elif dest == 2:
#dest 2: tnr, tet, twu, tsl, dnu, der, dwl, dst, mnt, mel, mwr, msu
df['E Totten-D'] = agg_i[0][['U-Turn', 'Right.1', 'Left.3', 'Thru.2']].sum(axis=1)
df['E Totten-T'] = agg_i[0][['Right', 'Thru.1', 'U-Turn.3', 'Left.2']].sum(axis=1)
df['E Totten-M'] = agg_i[0][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['E Totten-All'] = df[['E Totten-D', 'E Totten-M', 'E Totten-T']].sum(axis=1)
df['E Totten'] = df[['E Totten-D', 'E Totten-M', 'E Totten-T']].sum(axis=1)
elif dest == 3:
#dest3: mnu, mer, mwl, mst, tnu, ter, twl, tst, dnu, der, dwl, dst
df['S Huron Church-D'] = agg_i[0][['U-Turn', 'Right.1', 'Left.3', 'Thru.2']].sum(axis=1)
df['S Huron Church-T'] = agg_i[1][['U-Turn', 'Right.1', 'Left.3', 'Thru.2']].sum(axis=1)
df['S Huron Church-M'] = agg_i[2][['U-Turn', 'Right.1', 'Left.3', 'Thru.2']].sum(axis=1)
df['S Huron Church-All'] = df[['S Huron Church-D', 'S Huron Church-M', 'S Huron Church-T']].sum(axis=1)
df['S Huron Church'] = df[['S Huron Church-D', 'S Huron Church-M', 'S Huron Church-T']].sum(axis=1)
elif dest == 4:
#dest 4: mnl, meu, mwt, msr, tnu, ter, twl, tst, dnu, der, dwl, dst
df['W Malden-D'] = agg_i[0][['U-Turn', 'Right.1', 'Left.3', 'Thru.2']].sum(axis=1)
df['W Malden-T'] = agg_i[0][['U-Turn', 'Right.1', 'Left.3', 'Thru.2']].sum(axis=1)
df['W Malden-M'] = agg_i[0][['Left', 'U-Turn.1', 'Thru.3', 'Right.2']].sum(axis=1)
df['W Malden-All'] = df[['W Malden-D', 'W Malden-M', 'W Malden-T']].sum(axis=1)
df['W Malden'] = df[['W Malden-D', 'W Malden-M', 'W Malden-T']].sum(axis=1)
elif dest == 5:
#dnl, deu, dwt, dsr, tnl, teu, twt, tsr, mnt, mel, mwr, msu
df['W Dorch-D'] = agg_i[0][['Left', 'U-Turn.1', 'Thru.3', 'Right.2']].sum(axis=1)
df['W Dorch-T'] = agg_i[0][['Left', 'U-Turn.1', 'Thru.3', 'Right.2']].sum(axis=1)
df['W Dorch-M'] = agg_i[0][['Thru', 'Left.1', 'Right.3', 'U-Turn.2']].sum(axis=1)
df['W Dorch-All'] = df[['W Dorch-D', 'W Dorch-M', 'W Dorch-T']].sum(axis=1)
df['W Dorchester'] = df[['W Dorch-D', 'W Dorch-M', 'W Dorch-T']].sum(axis=1)
return df

def plot_dests():
Expand All @@ -66,19 +71,30 @@ def plot_dests():
for i in range(6):
dests.append(destination_traffic(i))
dests_grouped.append(dests[i].groupby([dests[i].index.hour, dests[i].index.minute]).mean())
plt.ylabel('Amount of Traffic')
plt.xlabel('Date/Time')
dests_grouped[0]['N Huron Church-All'].plot(label='N Huron Church')
dests_grouped[1]['E Dorch-All'].plot(label='E Dorch')
dests_grouped[2]['E Totten-All'].plot(label='E Totten')
dests_grouped[3]['S Huron Church-All'].plot(label='S Huron Church')
dests_grouped[4]['W Malden-All'].plot(label='W Malden')
dests_grouped[5]['W Dorch-All'].plot(label='W Dorch')
plt.legend(loc="upper right")
plt.title("Traffic along destination routes")
all = pd.concat([dests_grouped[0]['N Huron Church'], dests_grouped[1]['E Dorchester'], dests_grouped[2]['E Totten'], dests_grouped[3]['S Huron Church'], dests_grouped[4]['W Malden'], dests_grouped[5]['W Dorchester']],
axis=1)
# print(all)
all.plot(title="Traffic along destination routes", xlabel='Time of day (hour, minute)', ylabel='Number of Vehicles')
# plt.legend(loc="upper right")
# plt.title("Traffic along destination routes")
plt.show()
# plt.ylabel('Amount of Traffic')
# plt.xlabel('Date/Time')

# fig = plt.figure()
# for frame in dests_grouped:
# plt.plot(frame.index, frame[[-1]])
# ax = dests_grouped[0]['N Huron Church-All'].plot()#(label='N Huron Church')
# dests_grouped[1]['E Dorch-All'].plot(ax=ax)#(label='E Dorch', ax=ax)
# dests_grouped[2]['E Totten-All'].plot(ax=ax)#(label='E Totten', ax=ax)
# dests_grouped[3]['S Huron Church-All'].plot(ax=ax)#(label='S Huron Church', ax=ax)
# dests_grouped[4]['W Malden-All'].plot(ax=ax)#(label='W Malden', ax=ax)
# dests_grouped[5]['W Dorch-All'].plot(ax=ax)#(label='W Dorch', ax=ax)
# plt.legend(loc="upper right")
# plt.title("Traffic along destination routes")
# plt.show()


# plot_dests()

# dest_1 = destination_traffic(0)
# dest_2 = destination_traffic(1)
Expand Down Expand Up @@ -116,6 +132,11 @@ def agg_dir_traffic(intersection):
plt.title("N-S vs. E-W traffic on " + intersection_dict[intersection])
plt.show()

f = open("static/views/graph" + "dests" + ".html", "wb")
pandas_bokeh.output_file("static/views/graph" + "dests" + ".html")
plot_dests()
f.close()

# agg_dir_traffic(0)
# agg_dir_traffic(1)
# agg_dir_traffic(2)
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