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


from aare import RawSubFile, DetectorType, RawFile

from pathlib import Path
path = Path("/home/l_msdetect/erik/data/aare-test-data/raw/jungfrau/")
f = RawSubFile(path/"jungfrau_single_d0_f0_0.raw", DetectorType.Jungfrau, 512, 1024, 16)

# f = RawFile(path/"jungfrau_single_master_0.json")


# from aare._aare import ClusterVector_i, Interpolator

# import pickle 
# import numpy as np
# import matplotlib.pyplot as plt
# import boost_histogram as bh
# import torch
# import math
# import time



# def gaussian_2d(mx, my, sigma = 1, res=100, grid_size = 2):
#     """
#     Generate a 2D gaussian as position mx, my, with sigma=sigma. 
#     The gaussian is placed on a 2x2 pixel matrix with resolution 
#     res in one dimesion.
#     """
#     x = torch.linspace(0, pixel_size*grid_size, res)
#     x,y = torch.meshgrid(x,x, indexing="ij")
#     return 1 / (2*math.pi*sigma**2) * \
#       torch.exp(-((x - my)**2 / (2*sigma**2) + (y - mx)**2 / (2*sigma**2)))

# scale = 1000 #Scale factor when converting to integer
# pixel_size = 25 #um
# grid = 2
# resolution = 100
# sigma_um = 10
# xa = np.linspace(0,grid*pixel_size,resolution)
# ticks = [0, 25, 50]

# hit = np.array((20,20))
# etahist_fname = "/home/l_msdetect/erik/tmp/test_hist.pkl"

# local_resolution = 99
# grid_size = 3
# xaxis = np.linspace(0,grid_size*pixel_size, local_resolution)
# t = gaussian_2d(hit[0],hit[1], grid_size = grid_size, sigma = 10, res = local_resolution)
# pixels = t.reshape(grid_size, t.shape[0] // grid_size, grid_size, t.shape[1] // grid_size).sum(axis = 3).sum(axis = 1)
# pixels = pixels.numpy()
# pixels = (pixels*scale).astype(np.int32)
# v = ClusterVector_i(3,3)
# v.push_back(1,1, pixels)

# with open(etahist_fname, "rb") as f:
#         hist = pickle.load(f)
# eta = hist.view().copy()
# etabinsx = np.array(hist.axes.edges.T[0].flat)
# etabinsy = np.array(hist.axes.edges.T[1].flat)
# ebins = np.array(hist.axes.edges.T[2].flat)
# p = Interpolator(eta, etabinsx[0:-1], etabinsy[0:-1], ebins[0:-1])




# #Generate the hit




# tmp = p.interpolate(v)
# print(f'tmp:{tmp}')
# pos = np.array((tmp['x'], tmp['y']))*25


# print(pixels)
# fig, ax = plt.subplots(figsize = (7,7))
# ax.pcolormesh(xaxis, xaxis, t)
# ax.plot(*pos, 'o')
# ax.set_xticks([0,25,50,75])
# ax.set_yticks([0,25,50,75])
# ax.set_xlim(0,75)
# ax.set_ylim(0,75)
# ax.grid()
# print(f'{hit=}')
# print(f'{pos=}')