PythonNumPy创建数组方法

np.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0)

import numpy as np

# 如果不指定数据类型，就会根据object参数自动选择合适的数据类型
a = np.array([[1, 2, 3], [4, 5, 6]])
# 也可以在创建数组时，指定元素的数据类型
b = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.uint8)

np.zeros(shape, dtype=float, order='C')
np.ones(shape, dtype=float, order='C')
np.empty(shape, dtype=float, order='C')
np.eye(N, M=None, k=0, dtype=float, order='C')

import numpy as np

print(np.zeros(6))
print(np.zeros((2, 3)))
print(np.ones((2, 3), dtype=int))
print(np.empty((2, 3)))
print(np.eye(3, dtype=np.uint8))

import numpy as np

a = np.empty((3, 4), dtype=np.uint8)
a.fill(255)
print(a)

np.random.random(size=None)
np.random.randint(low, high=None, size=None)
np.random.nORMal(loc=0.0, scale=1.0, size=None)

import numpy as np

print(np.random.random(3))
print(np.random.random((2, 3)))
print(np.random.randint(5))
print(np.random.randint(1, 5, size=(2, 3)))

import numpy as np
# 导入绘图模块
import matplotlib.pyplot as plt

# 生成正态分布数据
tall = np.random.normal(170, 4, 1000)
# 从156厘米到190厘米，每2厘米一个分段
bins = np.arange(156, 190, 2)
# 绘制柱状图
plt.hist(tall, bins)
# 显示图形
plt.show()

import numpy as np

np.arange(start, stop, step, dtype=None)
np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)

import numpy as np

print(np.arange(5))
print(np.arange(5, 11))
print(np.arange(5, 11, 2))
print(np.arange(5.5, 11, 1.5))
print(np.arange(3, 15).reshape(3, 4))

import numpy as np

# 返回0到5之间的5个等距数值，包括0和5
print(np.linspace(0, 5, 5))
# 返回5个等距数值，包括0但不包括5
print(np.linspace(0, 5, 5, endpoint=False))

import numpy as np

a = np.arange(5)
print(a)
# 重复一维数组元素3次
print(np.repeat(a, 3))
a = np.arange(6).reshape((2, 3))
print(a)
# 重复二维数组元素3次，不指定轴
print(np.repeat(a, 3))
# 重复二维数组元素3次，指定0轴
print(np.repeat(a, 3, axis=0))
# 重复二维数组元素3次，指定1轴
print(np.repeat(a, 3, axis=1))

import numpy as np

a = np.arange(5)
print(a)
# 重复一维数组3次
print(np.tile(a, 3))
# 重复一维数组3行2列
print(np.tile(a, (3, 2)))
a = np.arange(6).reshape((2, 3))
print(a)
# 重复二维数组3次
print(np.tile(a, 3))
# 重复二维数组2行3列
print(np.tile(a, (2, 3)))

import numpy as np

# 精度为10°，共计37个经度点
lon = np.linspace(-180, 180, 37)
# 精度为10°，共计19个纬度点
lat = np.linspace(90, -90, 19)

import numpy as np

# 精度为10°，共计37个经度点
lon = np.linspace(-180, 180, 37)
# 精度为10°，共计19个纬度点
lat = np.linspace(90, -90, 19)

lons, lats = np.meshgrid(lon, lat)
print(lons.shape)
print(lats.shape)
print(lons[:,0])
print(lons[0])

import numpy as np

# 使用实数指定网格经度为5°
lats, lons = np.mgrid[90:-91:-5, -180:181:5]
print(lons.shape, lats.shape)
# 也可以用虚数指定分隔点数
lats, lons = np.mgrid[90:-90:37j, -180:180:73j]
print(lons.shape, lats.shape)

import numpy as np

print(np.array(['Anne', 1.70, 55]).dtype)

import numpy as np

mytype = np.dtype([('name', 'S32'), ('tall', np.float), ('bw', np.int)])
print(np.array([('Anne', 1.70, 55)], dtype=mytype))