# 1. 保存单个数组
numpy.save(file, arr, allow_pickle=True)

# 2. 保存多个数组
numpy.savez(file, *args, allow_pickle=True, **kwds)

# 保存时如果不指定数组名字， 默认按照 arr_0, arr_1 编号
numpy.savez(file, a1, a2) #  Arrays will be named: arr_0, arr_1 ...
# 保存时指定数组名字
numpy.savez(file, a1=a1, a2=a2) #  Arrays will be named: a1, a2 ...

# 读取 npz
npzfile = np.load('file.npz')
print(npzfile.files)

a1, a2 = [npzfile[key] for key in npzfile.files]

# 3. 保存多个数组, 保存时进行数据压缩，用法与 numpy.savez() 一样
# 压缩率一般在 10 倍以上，相应牺牲的是读取、保存时间，时间消耗大概是同样的倍率。
numpy.savez_compressed(file, *args, allow_pickle=True, **kwds)

from PIL import Image
import glob

pngs = glob.glob('temp_png/*.png')
# print(pngs)

frames = [Image.open(png) for png in pngs]

frames[0].save('z.gif', format='GIF', append_images=frames[1:], save_all=True, duration=100, loop=0)

import glob
import cv2

pngs = glob.glob('temp_png/*.png')
# print(pngs)

frames = [cv2.imread(png) for png in pngs]

h, w, l = frames[0].shape
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
video = cv2.VideoWriter(f'{pl}.mp4', fourcc, 15, (w, h))
for f in frames:
    video.write(f) 

cv2.destroyAllWindows()
video.release()

# give Python access to Blender's functionality
import bpy
# extend Python's math functionality
import math

# add a cube into the scene
bpy.ops.mesh.primitive_cube_add()
# get a reference to the currently active object
cube = bpy.context.active_object

# insert keyframe at frame one
cube.keyframe_insert("rotation_euler", frame=1)
# change the rotation of the cube around z-axis
cube.rotation_euler.z = math.radians(360)

# insert keyframe at the last frame
cube.keyframe_insert("rotation_euler", frame=90)

# change the location of the cube on the z-axis
cube.location.z = 0
cube.keyframe_insert("location", frame=100)
cube.location.z = 5
cube.keyframe_insert("location", frame=150)

# give Python access to Blender's functionality
import bpy
# extend Python's math functionality
import math
# extend Python's print functionality
import pprint

# initialize paramaters
vert_count = 32  # show with 16 and 64
angle_step = math.tau / vert_count
radius = 2

# create a list of vert coordinates
vert_coordinates = list()

# repeat code in a loop
for i in range(vert_count):

    # calculate current current_angle
    current_angle = angle_step * i

    # calculate coordinate
    x = radius * math.cos(current_angle)
    y = radius * math.sin(current_angle)

    # visualize what we are doing
    bpy.ops.mesh.primitive_ico_sphere_add(radius=0.05, location=(x, y, 0))

    # add current coordinate to list
    vert_coordinates.append((x, y, 0))

pprint.pprint(vert_coordinates)

# pip install pillow
# scoop install ghostscript

from PIL import Image

import os

for parent, dirnames, filenames in os.walk(os.getcwd()):
    for filename in filenames:
        ext = os.path.splitext(filename)[1]
        if ext != '.eps':
          continue

        eps_image = Image.open(filename)
        size = eps_image.size        
        print(filename, size)

        eps_image.load(scale=10)    # 分辨率增大到10倍
        eps_image.save(filename+'.png', quality=100)

import whisper

model = whisper.load_model("small", device="cpu")
result = model.transcribe(f"123.mp3")

print(result["text"]))

import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

for (k, v) in mcolors.BASE_COLORS.items():
    v = "#" + "".join(format(round(val * 255), "02x") for val in v)
    print(f'<font color="{v}"> {k:<10} ■  </font>')

for (k, v) in mcolors.TABLEAU_COLORS.items():
    print(f'<font color="{v}"> {k:<10} ■ </font>')

#%%
import radioactivedecay as rd
import matplotlib.pyplot as plt

# 创建一个放射性核素： Nuclide
ncld = rd.Nuclide('U-235')
half = ncld.half_life('readable')    # 半衰期
prog = ncld.progeny()                # 衰变产物
frac = ncld.branching_fractions()    # 占比
mode = ncld.decay_modes()            # 衰变射线类型

print(ncld, mode, prog, frac, half, sep='\n')

# 绘制衰变链
ncld.plot()

#%%
# 列出多个核算衰变类型
NUCs = ['U-235',
        'Pu-239']

for name in NUCs:
    ncld = rd.Nuclide(name)
    half = ncld.half_life('readable')
    prog = ncld.progeny()
    frac = ncld.branching_fractions()
    mode = ncld.decay_modes()
    print(ncld, mode, prog, frac, half, sep='\n')

    fig, ax = ncld.plot()
    fig.savefig(f'decay_chains_{name}.png', dpi=300)