def main():
print('&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&')
client = TSDBClient()
n_add = 50
mus = np.random.uniform(low=0.0, high=1.0, size=n_add)
sigs = np.random.uniform(low=0.05, high=0.4, size=n_add)
jits = np.random.uniform(low=0.05, high=0.2, size=n_add)
for i, m, s, j in zip(range(n_add), mus, sigs, jits):
client.insert_ts("ts-{}".format(i), tsmaker(m, s, j))
for i in range(5):
client.add_vp()
_, results = client.select(fields=[])
print("RESULT TYPE: ", type(results))
for k in results:
print(k, results[k])
m = np.random.uniform(low=0.0, high=1.0)
s = np.random.uniform(low=0.05, high=0.4)
j = np.random.uniform(low=0.05, high=0.2)
query = tsmaker(m, s, j)
_, closest = client.simsearch(query)
print("CLOSEST MATCH: ", closest)
_, closest = client.sim_search_SAX(query)
print("CLOSEST MATCH: ", closest)
def main():
print('&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&')
client = TSDBClient()
n_add = 50
mus = np.random.uniform(low=0.0, high=1.0, size=n_add)
sigs = np.random.uniform(low=0.05, high=0.4, size=n_add)
jits = np.random.uniform(low=0.05, high=0.2, size=n_add)
for i, m, s, j in zip(range(n_add), mus, sigs, jits):
client.insert_ts("ts-{}".format(i), tsmaker(m, s, j))
for i in range(5):
client.add_vp()
_, results = client.select(fields=[])
print("RESULT TYPE: ", type(results))
for k in results:
print(k, results[k])
m = np.random.uniform(low=0.0, high=1.0)
s = np.random.uniform(low=0.05, high=0.4)
j = np.random.uniform(low=0.05, high=0.2)
query = tsmaker(m, s, j)
_, closest = client.simsearch(query)
print("CLOSEST MATCH: ", closest)
_, closest = client.sim_search_SAX(query)
print("CLOSEST MATCH: ", closest)
class SampleApp2(tk.Tk):
def __init__(self):
tk.Tk.__init__(self)
self.destroy()
self.switch = 0
self.switch2 = 0
self.master3 = None
self.master = tk.Tk()
self.master2 = None
self.label = tk.Label(self.master,text="""
I would like to take this opportunity to thank you for using similarity search
for time series using the iSAX index. Please complete the prompts from the
other window before moving on to this window.
""",justify = 'left')
self.button = tk.Button(self.master, text="continue", command=self.on_button)
self.label.pack()
self.button.pack()
def on_button(self):
self.client = TSDBClient()
self.client.add_trigger('junk', 'insert_ts', None, 'db:one:ts')
self.client.add_trigger('stats', 'insert_ts', ['mean', 'std'], None)
if self.master2:
self.master2.destroy()
else:
self.master.destroy()
_, results = self.client.select()
if not len(results):
self.master1 = tk.Tk()
self.label = tk.Label(self.master1,text="""
It appears you have not chosen to load any time series into the database so the
database will be automatically populated for the search.
""",justify= 'left')
self.label2 = tk.Label(self.master1,text= "How many time series would you like in the database?")
self.entry = tk.Entry(self.master1)
self.button = tk.Button(self.master1, text="continue", command=self.on_button1)
self.label.pack()
self.label2.pack()
self.entry.pack()
self.button.pack()
else:
self.switch = 1
self.on_button1()
def on_button1(self):
self.master2 = tk.Tk()
if self.switch == 1:
self.label_1 = tk.Label(self.master2, text='Do you wish to provide your own time series for the query?')
self.button1 = tk.Button(self.master2, text="yes", command=self.on_button2)
self.button2 = tk.Button(self.master2, text="no", command=self.on_button3)
self.label_1.pack()
self.button1.pack(side='right')
self.button2.pack(side='right')
else:
self.number = None
number = self.entry.get()
if number:
try:
self.number = int(number)
except:
self.number = None
if not self.number:
self.label_1 = tk.Label(self.master2,text="Please enter a number.")
self.button1 = tk.Button(self.master2, text="continue", command=self.on_button)
self.master1.destroy()
self.label_1.pack()
self.button1.pack()
else:
self.master1.destroy()
self.tsdict = tsgenerator(self.client,self.number)
self.label_1 = tk.Label(self.master2, text='Do you wish to provide your own time series for the query?')
self.button1 = tk.Button(self.master2, text="yes", command=self.on_button2)
self.button2 = tk.Button(self.master2, text="no", command=self.on_button3)
self.label_1.pack()
self.button1.pack(side='right')
self.button2.pack(side='right')
def on_button2(self):
self.switch2 = 0
if self.master3:
self.master3 = tk.Tk()
self.master4.destroy()
else:
self.master2.destroy()
self.master3 = tk.Tk()
self.label_1 = tk.Label(self.master3,text="Please enter the file name for the query (as .npy file): ")
self.entry = tk.Entry(self.master3)
self.button1 = tk.Button(self.master3, text="continue", command=self.on_button4)
self.label_1.pack()
self.entry.pack()
self.button1.pack()
def on_button3(self):
self.master2.destroy()
self.master4 = tk.Tk()
self.switch2 = 1
self.label = tk.Label(self.master4,text="A time series will be automatically generated. ")
self.button1 = tk.Button(self.master4, text="continue", command=self.on_button4)
self.label.pack()
self.button1.pack()
def on_button4(self):
if self.switch2 == 0:
self.filename = self.entry.get()
if self.filename:
try:
tsarray = np.load(self.filename)
self.arg = ts.TimeSeries(tsarray[0,:], tsarray[1,:])
self.master3.destroy()
except:
self.master4 = tk.Tk()
self.label = tk.Label(self.master4,text="Error encountered, please make sure the file name is correct.")
self.button1 = tk.Button(self.master4, text="continue", command=self.on_button2)
self.master3.destroy()
self.label.pack()
self.button1.pack()
else:
self.on_button2()
else:
mus = np.random.uniform(low=0.0, high=1.0, size=1)
sigs = np.random.uniform(low=0.05, high=0.4, size=1)
jits = np.random.uniform(low=0.05, high=0.2, size=1)
self.master4.destroy()
meta, tsrs = tsmaker(mus, sigs, jits)
self.arg = tsrs
import matplotlib.pyplot as plt
_, res = self.client.sim_search_SAX(self.arg)
if res:
_, res2 = self.client.select(metadata_dict={'pk':res}, fields=['ts'])
plt.plot(self.arg.times(), self.arg.values(),label='query')
plt.plot(res2[res]['ts'][0], res2[res]['ts'][1],label='closest match')
plt.legend(loc='best',fontsize=12)
plt.show()
else:
print('Could not find matching time series')
