import matplotlib.pyplot as plt
from matplotlib import ticker
import os
import os.path as osp
import numpy as np
import sys
import mmcv
from matplotlib.pyplot import axvline
from matplotlib.pyplot import MultipleLocator
import platform
import matplotlib
from tempfile import NamedTemporaryFile

cur_dir = osp.dirname(osp.abspath(__file__))
sys.path.insert(0, osp.join(cur_dir, "../../../../"))
from lib.vis_utils.colormap import colormap

_COLORS = colormap(rgb=True, maximum=1)
color_step = 8

dpi = 300
fig_size = (10, 10)
font_size = 15  # 20
linewidth = 2
marker_size = 8
handlelength = 1.8  # legend label line length
if platform.system() == "Darwin":
    viewer = "open"
else:
    viewer = "eog"


def get_size(fig, dpi=100):
    with NamedTemporaryFile(suffix=".png") as f:
        fig.savefig(f.name, bbox_inches="tight", dpi=dpi)
        height, width, _channels = matplotlib.image.imread(f.name).shape
        return width / dpi, height / dpi


def set_size(fig, size, dpi=100, eps=1e-2, give_up=2, min_size_px=10):
    target_width, target_height = size
    set_width, set_height = target_width, target_height  # reasonable starting point
    deltas = []  # how far we have
    while True:
        fig.set_size_inches([set_width, set_height])
        actual_width, actual_height = get_size(fig, dpi=dpi)
        set_width *= target_width / actual_width
        set_height *= target_height / actual_height
        deltas.append(abs(actual_width - target_width) + abs(actual_height - target_height))
        if deltas[-1] < eps:
            return True
        if len(deltas) > give_up and sorted(deltas[-give_up:]) == deltas[-give_up:]:
            return False
        if set_width * dpi < min_size_px or set_height * dpi < min_size_px:
            return False


# xlim = [0, 0.062]
xlim = [0, 8]

# yapf: disable
region_ids = [
    0    , 1    , 2    , 3    , 4    , 5    , 6    , 7    ,   8]
regions = [
    0    , 1    , 4    , 8    , 16   , 32   , 64   , 128  , 256]

ad_2_list = [
    33.67, 34.63, 34.46, 34.79, 35.27, 35.00, 35.51, 35.69, 33.92]
ad_5_list = [
    74.3, 75.4, 75.5, 74.8, 75.2, 74.9, 76.3, 76.0, 74.0]
ad_10_list = [
    92.98, 93.51, 93.33, 93.36, 93.61, 93.26, 93.69, 93.54, 92.14]
rete_2_list = [
    60.46, 58.91, 59.46, 60.80, 60.97, 62.05, 62.11, 62.12, 62.70]
re_2_list = [
    61.84, 60.15, 60.49, 62.00, 62.13, 63.43, 63.18, 63.41, 64.31]
te_2_list = [
    94.94, 95.22, 95.10, 95.24, 95.39, 95.10, 95.48, 95.56, 95.14]
mean_list = [
    69.7, 69.6, 69.7, 70.2, 70.4, 70.6, 71.0, 71.0, 70.4]
# yapf: enable

markers = ["o", "s", "*", "x", "v", "^"]
# labels = ["ADD(-S) 0.02d", "ADD(-S) 0.05d", "ADD(-S) 0.1d", "$(2\degree, 2$ cm)", "$2\degree$", "2 cm"]
labels = ["ADD(-S) 0.02d", "ADD(-S) 0.05d", "ADD(-S) 0.1d", "$2\degree, 2$ cm", "$2\degree$", "2 cm"]


def main_mean():
    # fig = plt.figure(figsize=(5, 5), dpi=150)
    fig = plt.figure(figsize=(10, 5), dpi=150)

    ########
    plt.subplot(1, 2, 1)
    plt.grid(True)
    plot_i = 0
    (h1,) = plt.plot(
        region_ids,
        ad_2_list,
        "--",
        # marker="s",
        marker=markers[plot_i],
        markersize=marker_size,
        markerfacecolor="none",
        # label="Single-Stage",
        label=labels[plot_i],
        linewidth=linewidth,
        color=_COLORS[plot_i * color_step],
        # color=(138 / 255.0, 150 / 255.0, 250 / 255.0),
        clip_on=False,
    )

    plot_i += 1
    (h2,) = plt.plot(
        region_ids,
        ad_5_list,
        "--",
        # marker="s",
        marker=markers[plot_i],
        markersize=marker_size,
        markerfacecolor="none",
        # label="Single-Stage",
        label=labels[plot_i],
        linewidth=linewidth,
        color=_COLORS[plot_i * color_step],
        # color=(138 / 255.0, 150 / 255.0, 250 / 255.0),
        clip_on=False,
    )

    plot_i += 1
    (h3,) = plt.plot(
        region_ids,
        ad_10_list,
        "--",
        # marker="s",
        marker=markers[plot_i],
        markersize=marker_size,
        markerfacecolor="none",
        # label="Single-Stage",
        label=labels[plot_i],
        linewidth=linewidth,
        color=_COLORS[plot_i * color_step],
        # color=(138 / 255.0, 150 / 255.0, 250 / 255.0),
        clip_on=False,
    )

    plot_i += 1
    (h4,) = plt.plot(
        region_ids,
        rete_2_list,
        "--",
        # marker="d",
        marker=markers[plot_i],
        markersize=marker_size,
        markerfacecolor="none",
        # label="Ours",
        label=labels[plot_i],
        linewidth=linewidth,
        color=_COLORS[plot_i * color_step],
        # color=(0, 112 / 255.0, 68 / 255.0),
        clip_on=False,
    )

    plot_i += 1
    (h5,) = plt.plot(
        region_ids,
        re_2_list,
        "--",
        # marker="d",
        marker=markers[plot_i],
        markersize=marker_size,
        markerfacecolor="none",
        # label="Ours",
        label=labels[plot_i],
        linewidth=linewidth,
        color=_COLORS[plot_i * color_step],
        # color=(0, 112 / 255.0, 68 / 255.0),
        clip_on=False,
    )

    plot_i += 1
    (h6,) = plt.plot(
        region_ids,
        te_2_list,
        "--",
        # marker="d",
        marker=markers[plot_i],
        markersize=marker_size,
        markerfacecolor="none",
        # label="Ours",
        label=labels[plot_i],
        linewidth=linewidth,
        color=_COLORS[plot_i * color_step],
        # color=(0, 112 / 255.0, 68 / 255.0),
        clip_on=False,
    )

    plt.xlim(xlim)
    plt.ylim([30, 100])
    # plt.ylim([50, 100])
    # plt.yscale("log")

    ax = plt.gca()
    # ax.xaxis.set_major_locator(MultipleLocator(10))
    ax.set_xlabel("number of regions", fontsize=font_size)
    ax.set_ylabel("accuracy (%)", fontsize=font_size)

    plt.xticks(region_ids, labels=[str(_r) for _r in regions])
    ax.set_yticks([30, 40, 50, 60, 70, 80, 90, 100])
    # ax.get_yaxis().set_major_formatter(ticker.ScalarFormatter())

    ax.xaxis.set_tick_params(labelsize=font_size)
    ax.yaxis.set_tick_params(labelsize=font_size)
    ########

    plt.subplot(1, 2, 2)
    plt.grid(True)
    (h7,) = plt.plot(
        region_ids,
        mean_list,
        # "-",
        marker="d",
        # marker=markers[-1],
        markersize=marker_size,
        markerfacecolor="none",
        # label="RANSAC EPnP",
        label=labels[-1],
        linewidth=linewidth,
        # color=_COLORS[plot_i*5],
        color=(0, 112 / 255.0, 68 / 255.0),
        clip_on=False,
    )

    handles = [h1, h2, h3, h4, h5, h6, h7]
    # handles = [h7]
    plt.legend(
        handles,
        labels + ["MEAN"],
        loc="lower right",
        # loc="center left",
        # bbox_to_anchor=(0.85, 0.0),
        fontsize=font_size,
        fancybox=True,
        framealpha=0.5,
        handlelength=handlelength,
    )
    plt.xlim(xlim)
    # plt.ylim([30, 100])
    plt.ylim([64, 74])
    # plt.yscale("log")

    ax = plt.gca()
    # ax.xaxis.set_major_locator(MultipleLocator(10))
    ax.set_xlabel("number of regions", fontsize=font_size)
    ax.set_ylabel("accuracy (%)", fontsize=font_size)

    plt.xticks(region_ids, labels=[str(_r) for _r in regions])
    # ax.set_yticks([60, 70, 80, 90, 100])
    # ax.get_yaxis().set_major_formatter(ticker.ScalarFormatter())

    ax.xaxis.set_tick_params(labelsize=font_size)
    ax.yaxis.set_tick_params(labelsize=font_size)
    save_path = "output/lm/ablation_regions_v4.pdf"
    mmcv.mkdir_or_exist(osp.dirname(save_path))
    # set_size(fig, fig_size, dpi=dpi)
    plt.tight_layout()
    plt.savefig(save_path, dpi=fig.dpi)  # , bbox_inches="tight")
    print("save fig path: ", save_path)
    os.system(f"{viewer} {save_path}")


if __name__ == "__main__":
    # main()
    main_mean()
