import json
from logging import getLogger
from cam_server.pipeline.data_processing import functions
from collections import deque

_logger = getLogger(__name__)

Nbg=10
bg = deque([],Nbg)

#pattern = [1, 1, 1, 1, 0]
pix_min =  750
pix_max = 1750

x_profile_BG = []



def _interpolate_row(y_known, x_known, x_interp):
    y_interp = np.interp(x_interp, x_known, y_known)
    return y_interp



def find_edge(data, step_length=100, edge_type="rising", refinement=1):
    # refine data
    data_length = data.shape[0]
    refined_data = np.apply_along_axis(
        _interpolate_row,
        axis=0,
        arr=data,
        x_known=np.arange(data_length),
        x_interp=np.arange(0, data_length - 1, refinement),
    )

    # prepare a step function and refine it
    step_waveform = np.ones(shape=(step_length,))
    if edge_type == "rising":
        step_waveform[: int(step_length / 2)] = -1
    elif edge_type == "falling":
        step_waveform[int(step_length / 2) :] = -1

    step_waveform = np.interp(
        x=np.arange(0, step_length - 1, refinement), xp=np.arange(step_length), fp=step_waveform
    )

    # find edges
    xcorr = np.apply_along_axis(np.correlate, 0, refined_data, v=step_waveform, mode="valid")
    edge_position = np.argmax(xcorr, axis=0).astype(float) * refinement
    xcorr_amplitude = np.amax(xcorr, axis=0)

    # correct edge_position for step_length
    edge_position += np.floor(step_length / 2)

    return {"edge_pos": edge_position, "xcorr": xcorr, "xcorr_ampl": xcorr_amplitude, "signal":data}









def process_image(image, pulse_id, timestamp, x_axis, y_axis, parameters, bsdata=None):
    # 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.
    # Add return values
    intensity = x_profile.sum()
    

    
     sig = x_profile / x_profile_BG -1
     edge_pos= find_edge(sig[ pix_min : pix_max ])["edge_pos"] + pix_min
     xcorr= find_edge(sig[ pix_min : pix_max ])["xcorr"]
    
    #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
    return_value[prefix+"sig"] = sig
    return_value[prefix+"edge_pos"] = edge_pos
    return_value[prefix+"xcorr"] = xcorr
    
    return return_value