import sys
sys.path.append('/home/l_msdetect/erik/aare/build')

#Our normal python imports
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import boost_histogram as bh
import time

from aare import File, ClusterFinder, VarClusterFinder, ClusterFile

base = Path('/mnt/sls_det_storage/matterhorn_data/aare_test_data/')

f = File(base/'Moench03new/cu_half_speed_master_4.json')


from aare._aare import ClusterFinderMT, ClusterCollector, ClusterFileSink


cf = ClusterFinderMT((400,400), (3,3), n_threads = 3)
# collector = ClusterCollector(cf)
out_file = ClusterFileSink(cf, "test.clust")

for i in range(1000):
    img = f.read_frame()
    cf.push_pedestal_frame(img)
print('Pedestal done')
cf.sync()

for i in range(100):
    img = f.read_frame()
    cf.find_clusters(img)


# time.sleep(1)
cf.stop()  
time.sleep(1)
print('Second run')
cf.start()
for i in range(100):
    img = f.read_frame()
    cf.find_clusters(img)

cf.stop()
print('Third run')
cf.start()
for i in range(129):
    img = f.read_frame()
    cf.find_clusters(img)

cf.stop()
out_file.stop()
print('Done')


cfile = ClusterFile("test.clust")
i = 0
while True:
    try:
        cv = cfile.read_frame()
        i+=1
    except RuntimeError:
        break
print(f'Read {i} frames') 




# cf = ClusterFinder((400,400), (3,3))
# for i in range(1000):
#     cf.push_pedestal_frame(f.read_frame())

# fig, ax = plt.subplots()
# im = ax.imshow(cf.pedestal())
# cf.pedestal()
# cf.noise()



# N = 500
# t0 = time.perf_counter()
# hist1 = bh.Histogram(bh.axis.Regular(40, -2, 4000))
# f.seek(0)

# t0 = time.perf_counter()
# data = f.read_n(N)
# t_elapsed = time.perf_counter()-t0


# n_bytes = data.itemsize*data.size

# print(f'Reading {N} frames took {t_elapsed:.3f}s {N/t_elapsed:.0f} FPS, {n_bytes/1024**2:.4f} GB/s')


# for frame in data:
#     a = cf.find_clusters(frame)

# clusters = cf.steal_clusters()

# t_elapsed = time.perf_counter()-t0
# print(f'Clustering {N} frames took {t_elapsed:.2f}s  {N/t_elapsed:.0f} FPS')


# t0 = time.perf_counter()
# total_clusters = clusters.size

# hist1.fill(clusters.sum())

# t_elapsed = time.perf_counter()-t0
# print(f'Filling histogram with the sum of {total_clusters} clusters took: {t_elapsed:.3f}s, {total_clusters/t_elapsed:.3g} clust/s')
# print(f'Average number of clusters per frame {total_clusters/N:.3f}')