from read_chirp_data import *
#import nix_helpers as nh 
import matplotlib.pyplot as plt
import numpy as np
from IPython import embed


data_dir = "../data"
dataset = "2018-11-09-ad-invivo-1"
#data = ("2018-11-09-ad-invivo-1", "2018-11-09-ae-invivo-1", "2018-11-09-ag-invivo-1", "2018-11-13-aa-invivo-1", "2018-11-13-ac-invivo-1", "2018-11-13-ad-invivo-1", "2018-11-13-ah-invivo-1", "2018-11-13-ai-invivo-1", "2018-11-13-aj-invivo-1", "2018-11-13-ak-invivo-1", "2018-11-13-al-invivo-1", "2018-11-14-aa-invivo-1", "2018-11-14-ac-invivo-1", "2018-11-14-ad-invivo-1", "2018-11-14-af-invivo-1", "2018-11-14-ag-invivo-1", "2018-11-14-ah-invivo-1", "2018-11-14-ai-invivo-1", "2018-11-14-ak-invivo-1", "2018-11-14-al-invivo-1", "2018-11-14-am-invivo-1", "2018-11-14-an-invivo-1")
spikes = read_chirp_spikes(os.path.join(data_dir, dataset))
eod = read_chirp_eod(os.path.join(data_dir, dataset))
times = read_chirp_times(os.path.join(data_dir, dataset))


df_map = {}
for k in spikes.keys():
	df = k[1]
	if df in df_map.keys():
		df_map[df].append(k)
	else:
		df_map[df] = [k]
print(df_map.keys())

e1 = eod[0, '-50Hz', '20%', '100Hz']
#plt.plot(e1[1])
#plt.show()
plt.title('EOD chirps')
plt.xlabel('Frequency')
plt.ylabel('Amplitude')
plt.plot(e1[0],e1[1])
plt.show()

ct = times[0, '-50Hz', '20%', '100Hz']
#plt.scatter(ct*1000, np.ones(len(ct)))
plt.scatter(np.asarray(ct)*1000, np.ones(len(ct)))
plt.show()

#plt.scatter(spikes[0, '-50Hz', '20%', '100Hz'][0, 0.614])

#print(len(spikes))
#print(len(eod))
#print(len(times))