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.measurement_stats()) N = len(result) x_ticks = tuple_gen.base_str(result,0) wifi_vals = tuple_gen.base_int(result,2) mobile_vals = tuple_gen.base_int(result,3) ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars fig = plt.figure() ax = fig.add_subplot(111) rects1 = ax.bar(ind, wifi_vals, width, color='r') rects2 = ax.bar(ind+width, mobile_vals, width, color='y') # add some ax.set_ylabel('Count') ax.set_title('Usage over Hour of Day') ax.set_xticks(ind+width) ax.set_xticklabels(x_ticks,rotation='vertical') ax.legend( (rects1[0], rects2[0]), ('Measurements', 'Users') )
result = database.query(query.signalstrength_count()) data = tuple_gen.group_by(result,0) plt.figure(1) # the first figure subplot_count = 811 for key in data.keys(): plt.subplot(subplot_count) #plt.ylim(0,31) plt.title(key) x_ticks = (tuple_gen.base_int(data[key],1)) y_vals = (tuple_gen.base_int(data[key],2)) N = len(x_ticks) ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars rects1 = plt.bar(ind, y_vals, width, color='r') plt.ylabel('count') plt.xticks(x_ticks) #plt.xticklabels(x_ticks) subplot_count+=1 if subplot_count>818:
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()
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) + 1, len(data2), axisNum) if row == 1: plt.title(key2) if col == 1: plt.ylabel(key) x_ticks = tuple_gen.base_int(data2[key2], 2) y_vals = tuple_gen.normalize(tuple_gen.base_int(data2[key2], 3)) y_vals_2 = tuple_gen.normalize(tuple_gen.base_int(data2[key2], 4)) plt.scatter(x_ticks, y_vals) # plt.plot(x_ticks,y_vals,label="avg") # plt.plot(x_ticks,y_vals_2,label="stddev") for tick in ax.get_xticklabels(): tick.set_visible(False) for tick in ax.get_yticklabels(): tick.set_visible(False) 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()
for key in data.keys(): 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) + 1, len(data2), axisNum) if row == 1: plt.title(key2) if col == 1: plt.ylabel(key) x_ticks = tuple_gen.base_int(data2[key2], 2) y_vals = tuple_gen.normalize(tuple_gen.base_int(data2[key2], 3)) y_vals_2 = tuple_gen.normalize(tuple_gen.base_int(data2[key2], 4)) plt.scatter(x_ticks, y_vals) #plt.plot(x_ticks,y_vals,label="avg") #plt.plot(x_ticks,y_vals_2,label="stddev") for tick in ax.get_xticklabels(): tick.set_visible(False) for tick in ax.get_yticklabels(): tick.set_visible(False) 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 import database, query, tuple_gen import pprint import numpy as np import matplotlib.pyplot as plt result = database.query(query.app_by_popularity()) pprint.pprint(result) N = len(result) x_ticks = tuple_gen.base_str(result, 2) data_vals = tuple_gen.base_int(result, 0) width = 0.35 ind = np.arange(N) # the x locations for the groups fig = plt.figure() ax = fig.add_subplot(111) rects1 = ax.bar(ind, data_vals, width, color='r') # add some ax.set_ylabel('Count') ax.set_title('Total Data by Application') ax.set_xticks(ind + width) ax.set_xticklabels(x_ticks, rotation='vertical') ax.legend((rects1[0], ), ('Application', ))
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.app_by_popularity()) pprint.pprint(result) N = len(result) x_ticks = tuple_gen.base_str(result,2) data_vals = tuple_gen.base_int(result,0) width=0.35 ind = np.arange(N) # the x locations for the groups fig = plt.figure() ax = fig.add_subplot(111) rects1 = ax.bar(ind, data_vals, width, color='r') # add some ax.set_ylabel('Count') ax.set_title('Total Data by Application') ax.set_xticks(ind+width) ax.set_xticklabels(x_ticks,rotation='vertical')
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.measurement_stats()) N = len(result) x_ticks = tuple_gen.base_str(result, 0) wifi_vals = tuple_gen.base_int(result, 2) mobile_vals = tuple_gen.base_int(result, 3) ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars fig = plt.figure() ax = fig.add_subplot(111) rects1 = ax.bar(ind, wifi_vals, width, color='r') rects2 = ax.bar(ind + width, mobile_vals, width, color='y') # add some ax.set_ylabel('Count') ax.set_title('Usage over Hour of Day') ax.set_xticks(ind + width) ax.set_xticklabels(x_ticks, rotation='vertical') ax.legend((rects1[0], rects2[0]), ('Measurements', 'Users'))
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()