import matplotlib.pyplot as plt import database,query,tuple_gen import pprint import numpy as np import matplotlib.pyplot as plt result = database.query(query.signalstrength_over_hour_of_day()) data = tuple_gen.group_by(result,0) plt.figure(1) # the first figure subplot_count = 511 for key in data.keys(): plt.subplot(subplot_count) #plt.ylim(0,31) plt.title(key) x_ticks = tuple_gen.hour_minute_period(data[key],1,2,10) y_vals = (tuple_gen.base_float(data[key],3)) plt.plot(x_ticks,y_vals) subplot_count+=1 plt.show()
import numpy as np
import matplotlib.pyplot as plt
import database,query,tuple_gen
import pprint
import numpy as np
import matplotlib.pyplot as plt
result={}
result['morning'] = database.query(query.wifi_favorite_count_over_time(0,6))
result['afternoon'] = database.query(query.wifi_favorite_count_over_time(12,16))
result['night'] = database.query(query.wifi_favorite_count_over_time(20,24))
plt.title("Favorite wifi router count over time for different time of days")
plt.ylabel('count')
plt.xlabel('time of day')
for key in result:
x_ticks = tuple_gen.hour_minute_period(result[key],0,1,10)
y_vals = tuple_gen.base_int(result[key],2)
plt.plot(x_ticks,y_vals,label=key)
plt.legend()
plt.show()
data2 = tuple_gen.group_by(data[key], 1) list_keys = data2.keys() row += 1 col = 0 for key2 in sorted(list_keys): axisNum += 1 col += 1 ax = plt.subplot(len(data), len(data2), axisNum) if row == 1 : plt.title(key2) if col == 1 : plt.ylabel(key) x_ticks = tuple_gen.hour_minute_period(data2[key2], 2, 3, 10) #y_vals = tuple_gen.normalize(tuple_gen.base_int(data2[key2], 4)) y_vals = tuple_gen.base_int(data2[key2], 4) plt.plot(x_ticks, y_vals) for tick in ax.get_xticklabels(): tick.set_visible(False) for tick in ax.get_yticklabels(): tick.set_visible(True) plt.show()
import numpy as np
import matplotlib.pyplot as plt
import database, query, tuple_gen
import pprint
import numpy as np
import matplotlib.pyplot as plt
result = database.query(query.connectiontype_over_time_of_day())
data = tuple_gen.group_by(result, 0)
wifi_ticks = tuple_gen.hour_minute_period(data['True'], 1, 2, 10)
wifi_vals = (tuple_gen.base_int(data['True'], 3))
mobile_ticks = tuple_gen.hour_minute_period(data['False'], 1, 2, 10)
mobile_vals = (tuple_gen.base_int(data['False'], 3))
plt.figure(1)
plt.plot(wifi_ticks, wifi_vals, label='Wifi')
plt.plot(mobile_ticks, mobile_vals, label='Mobile')
plt.ylabel('Count')
plt.title('Connection Type over day')
plt.legend()
plt.show()
import numpy as np
import matplotlib.pyplot as plt
import database,query,tuple_gen
import pprint
import numpy as np
import matplotlib.pyplot as plt
result = database.query(query.connectiontype_over_time_of_day())
data = tuple_gen.group_by(result,0)
wifi_ticks = tuple_gen.hour_minute_period(data['True'],1,2,10)
wifi_vals =(tuple_gen.base_int(data['True'],3))
mobile_ticks = tuple_gen.hour_minute_period(data['False'],1,2,10)
mobile_vals =(tuple_gen.base_int(data['False'],3))
plt.figure(1)
plt.plot(wifi_ticks,wifi_vals,label='Wifi')
plt.plot(mobile_ticks,mobile_vals,label='Mobile')
plt.ylabel('Count')
plt.title('Connection Type over day')
plt.legend()
plt.show()
import numpy as np
import matplotlib.pyplot as plt
result = database.query(query.throughput_over_time())
data = tuple_gen.group_by(result, 0)
plt.figure(1) # the first figure
axisNum = len(data) * 100 + 10
for key in data.keys():
data2 = tuple_gen.group_by(data[key], 1)
axisNum += 1
ax = plt.subplot(axisNum)
plt.title(key)
x_ticks_up = tuple_gen.hour_minute_period(data2["9912"], 2, 3, 10)
y_vals_up = (tuple_gen.base_int(data2["9912"], 4))
x_ticks_down = tuple_gen.hour_minute_period(data2["9710"], 2, 3, 10)
y_vals_down = (tuple_gen.base_int(data2["9710"], 4))
plt.ylabel('bps')
plt.plot(x_ticks_up, y_vals_up, label='Upload')
plt.plot(x_ticks_down, y_vals_down, label='Download')
plt.legend()
plt.show()
import numpy as np import matplotlib.pyplot as plt result = database.query(query.signalstrength_over_hour_of_day()) data = tuple_gen.group_by(result,0) plt.figure(1) # the first figure subplot_count = 511 for key in data.keys(): plt.subplot(subplot_count) #plt.ylim(0,31) N = len(data.keys()) ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars plt.title(key) x_ticks = tuple_gen.hour_minute_period(data[key],1,2,10) y_vals = (tuple_gen.base_float(data[key],3)) plt.plot(x_ticks,y_vals) subplot_count+=1 plt.show()
data = tuple_gen.group_by(result,0)
plt.figure(1) # the first figure
axisNum = len(data)*100 + 10
for key in data.keys():
data2 = tuple_gen.group_by(data[key],1)
axisNum += 1
ax = plt.subplot(axisNum)
plt.title(key)
x_ticks_up = tuple_gen.hour_minute_period(data2["9912"],2,3,10)
y_vals_up = (tuple_gen.base_int(data2["9912"],4))
x_ticks_down = tuple_gen.hour_minute_period(data2["9710"],2,3,10)
y_vals_down = (tuple_gen.base_int(data2["9710"],4))
plt.ylabel('bps')
plt.plot(x_ticks_up,y_vals_up,label='Upload')
plt.plot(x_ticks_down,y_vals_down,label='Download')
plt.legend()
plt.show()
