import requests
import matplotlib.pyplot as plt
from datetime import datetime
import json
import os

latest_history_path = "latest_history.json"

file_path = latest_history_path
history_url = "http://192.168.178.84:9587/bettwaage/history"

focus_on_latest_bed_data = False

convert_time_to_seconds = True

# Get data
data = None
if file_path is None or not os.path.exists(file_path):
    print("Fetching data ...")
    data = requests.get(history_url)
    data = data.json()

    print("Saving latest data ...")
    with open(latest_history_path, "w", encoding="UTF-8") as fp:
        json.dump(data, fp)
else:
    print("Reading data ...")
    with open(file_path, "r") as fp:
        data = json.load(fp)


print("Processing data ...")

# Get rough value for empty bed weight per leg
rough_bed_weight = 80
bed_only_weight = {}
for d in data:
    if d["total"] < rough_bed_weight:
        bed_only_weight = {
            "tl": d["tl"],
            "tr": d["tr"],
            "bl": d["bl"],
            "br": d["br"],
        }
        total_bed_only_weight = sum(bed_only_weight.values())
        break

if focus_on_latest_bed_data:
    # Collect all coherent sequences of someone being in bed
    in_bed_datas: list[list[dict]] = []
    is_in_bed_sequence = False
    threshhold = 100.0
    for d in data:
        t = d["total"]
        if t >= threshhold:
            if not is_in_bed_sequence:
                in_bed_datas.append([])
                is_in_bed_sequence = True
            in_bed_datas[-1].append(d)
        elif is_in_bed_sequence:
            is_in_bed_sequence = False

    # Pick latest with minimum length/duration
    min_length = 100
    for sequence in in_bed_datas:
        if len(sequence) >= min_length:
            data = sequence


# Prepare data for plotting
x = [d["timestamp"] for d in data]
# x = [datetime.strptime(d, "%Y-%m-%d %H:%M:%S.%f") for d in x]

# if convert_time_to_seconds:
#     max_time = max(x)
#     x = [(d - max_time).total_seconds() for d in x]

total = [d["total"] for d in data]
tl = [d["tl"] for d in data]
tr = [d["tr"] for d in data]
bl = [d["bl"] for d in data]
br = [d["br"] for d in data]
top = [l + r for l, r in zip(tl, tr)]
bottom = [l + r for l, r in zip(bl, br)]
left = [t + b for t, b in zip(tl, bl)]
right = [t + b for t, b in zip(tr, br)]


fig, ax = plt.subplots()

person_weight = [t - total_bed_only_weight for t in total]

ax.set_xlabel("Time (s)")
ax.set_ylabel("Weight (kg)")

ax.plot(x, person_weight, color="tab:blue")

plt.show()
exit()

# Experiment: Calculate position over time
bed_size = (140, 200)
left_bed_only = bed_only_weight["tl"] + bed_only_weight["bl"]
top_bed_only = bed_only_weight["tr"] + bed_only_weight["tl"]
right_bed_only = bed_only_weight["tr"] + bed_only_weight["br"]
bottom_bed_only = bed_only_weight["br"] + bed_only_weight["bl"]
position_over_time = []
for t, b, l, r in zip(top, bottom, left, right):
    horizontal_weight = l - left_bed_only + r - right_bed_only
    vertical_weight = t - top_bed_only + b - bottom_bed_only
    position_over_time.append(
        (
            bed_size[0] * (l - left_bed_only) / horizontal_weight,
            bed_size[1] * (t - top_bed_only) / vertical_weight,
        )
    )

# Plot data
fig, (ax0, ax1) = plt.subplots(nrows=2)

ax0.set_xlabel("Time (s)")
ax0.set_ylabel("Weight (kg)")

ax0.plot(x, total, color="tab:blue")
ax0.plot(x, tl, color="tab:red")
ax0.plot(x, tr, color="tab:green")
ax0.plot(x, bl, color="tab:orange")
ax0.plot(x, br, color="tab:purple")
ax0.plot(x, top, color="tab:pink")
ax0.plot(x, bottom, color="tab:grey")

ax0.legend(
    ["Total", "Top Left", "Top Right", "Bottom Left", "Bottom Right", "Top", "Bottom"]
)

# Experiment: Plot position
import math
import colorsys

segments = 100
seg_length = math.ceil(len(position_over_time) / segments)
horizontal, vertical = zip(*position_over_time)
for i in range(0, segments):
    low = int(i * seg_length)
    high = min(int((i + 1) * seg_length), len(position_over_time))
    ax1.plot(
        horizontal[low:high],
        vertical[low:high],
        color=colorsys.hsv_to_rgb(i / segments * 0.5, 1, 0.7),
        linewidth=0.3,
    )
ax1.set_xlim((0, bed_size[0]))
ax1.set_ylim((0, bed_size[1]))
ax1.invert_yaxis()


plt.show()