import json
from logging import getLogger
from cam_server.pipeline.data_processing import functions
import numpy as np
import os

_logger = getLogger(__name__)
curvature = np.loadtxt('configuration/user_scripts/data/curvature.txt')

def process_image(image, pulse_id, timestamp, x_axis, y_axis, parameters, bsdata=None):
    global curvature 
    # Add return values
    return_value = dict()
    prefix = parameters["camera_name"]+":"
    #(min_value, max_value) = functions.get_min_max(image)
    (x_profile, y_profile) = functions.get_x_y_profile(image)
    # Could be also y_profile.sum() -> it should give the same result.
    intensity = x_profile.sum()
    # Add return values
    return_value[prefix+"timestamp"] = timestamp
    #return_value[prefix+"min_value"] = min_value
    #return_value[prefix+"max_value"] = max_value
    return_value[prefix+"x_profile"] = x_profile
    return_value[prefix+"y_profile"] = y_profile
    return_value[prefix+"intensity"] = intensity
    
    try:
          # 1 Apply Threshold
          low, high = 125, 300
          mask = (image<high)*(image>low) #image is the single frame from the camera
          mask= np.logical_not(mask)
          image[mask] = 0
          # 2 Correct Curvature
          image_corr = np.zeros(image.shape)
          for j in range(image.shape[0]):
               image_corr[j] = np.roll(image[j],-int(curvature[j]))   
          # 3 Binning
          spectrum = np.sum(image_corr,axis=0).astype('float32')
    except: 
          spectrum = None
    return_value[prefix+"spectrum"] = spectrum
    
    return return_value