Python使用np.linspace生成均匀分布点的注意事项
本文介绍Python中numpy库的linspace函数用法。通过对比201个点与200个点的生成结果,详解起始值、终止值与点数对输出序列的影响,特别是闭区间包含两端数据的特性及非整数步长的情况,帮助开发者避免常见误区。
Python使用np.linspace生成均匀分布点的注意事项
实现方法如下所示:
import numpy as np
print(np.linspace(-100,100,201)
使用np.linspace()函数,指定起始位置和终止位置,中间包含0,总共需要生成201个点。
由于区间[-100, 100]包含两端数据,即数学上的闭区间,因此共生成201个点。
运行结果如下:
-100. -99. -98. -97. -96. -95. -94. -93. -92. -91. -90. -89.
-88. -87. -86. -85. -84. -83. -82. -81. -80. -79. -78. -77.
-76. -75. -74. -73. -72. -71. -70. -69. -68. -67. -66. -65.
-64. -63. -62. -61. -60. -59. -58. -57. -56. -55. -54. -53.
-52. -51. -50. -49. -48. -47. -46. -45. -44. -43. -42. -41.
-40. -39. -38. -37. -36. -35. -34. -33. -32. -31. -30. -29.
-28. -27. -26. -25. -24. -23. -22. -21. -20. -19. -18. -17.
-16. -15. -14. -13. -12. -11. -10. -9. -8. -7. -6. -5.
-4. -3. -2. -1. 0. 1. 2. 3. 4. 5. 6. 7.
8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.
20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31.
32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43.
44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55.
56. 57. 58. 59. 60. 61. 62. 63. 64. 65. 66. 67.
68. 69. 70. 71. 72. 73. 74. 75. 76. 77. 78. 79.
80. 81. 82. 83. 84. 85. 86. 87. 88. 89. 90. 91.
92. 93. 94. 95. 96. 97. 98. 99. 100.]
然而,如果你未计算两个数之间应包含多少个点,
例如在区间(-100, 100)中直接指定生成200个点,结果可能与预期不符:
实际输出结果:
[-100. -98.99497487 -97.98994975 -96.98492462 -95.9798995
-94.97487437 -93.96984925 -92.96482412 -91.95979899 -90.95477387
-89.94974874 -88.94472362 -87.93969849 -86.93467337 -85.92964824
-84.92462312 -83.91959799 -82.91457286 -81.90954774 -80.90452261
-79.89949749 -78.89447236 -77.88944724 -76.88442211 -75.87939698
-74.87437186 -73.86934673 -72.86432161 -71.85929648 -70.85427136
-69.84924623 -68.84422111 -67.83919598 -66.83417085 -65.82914573
-64.8241206 -63.81909548 -62.81407035 -61.80904523 -60.8040201
-59.79899497 -58.79396985 -57.78894472 -56.7839196 -55.77889447
-54.77386935 -53.76884422 -52.7638191 -51.75879397 -50.75376884
-49.74874372 -48.74371859 -47.73869347 -46.73366834 -45.72864322
-44.72361809 -43.71859296 -42.71356784 -41.70854271 -40.70351759
-39.69849246 -38.69346734 -37.68844221 -36.68341709 -35.67839196
-34.67336683 -33.66834171 -32.66331658 -31.65829146 -30.65326633
-29.64824121 -28.64321608 -27.63819095 -26.63316583 -25.6281407
-24.62311558 -23.61809045 -22.61306533 -21.6080402 -20.60301508
-19.59798995 -18.59296482 -17.5879397 -16.58291457 -15.57788945
-14.57286432 -13.5678392 -12.56281407 -11.55778894 -10.55276382
-9.54773869 -8.54271357 -7.53768844 -6.53266332 -5.52763819
-4.52261307 -3.51758794 -2.51256281 -1.50753769 -0.50251256
0.50251256 1.50753769 2.51256281 3.51758794 4.52261307
5.52763819 6.53266332 7.53768844 8.54271357 9.54773869
10.55276382 11.55778894 12.56281407 13.5678392 14.57286432
15.57788945 16.58291457 17.5879397 18.59296482 19.59798995
20.60301508 21.6080402 22.61306533 23.61809045 24.62311558
25.6281407 26.63316583 27.63819095 28.64321608 29.64824121
30.65326633 31.65829146 32.66331658 33.66834171 34.67336683
35.67839196 36.68341709 37.68844221 38.69346734 39.69849246
40.70351759 41.70854271 42.71356784 43.71859296 44.72361809
45.72864322 46.73366834 47.73869347 48.74371859 49.74874372
50.75376884 51.75879397 52.7638191 53.76884422 54.77386935
55.77889447 56.7839196 57.78894472 58.79396985 59.79899497
60.8040201 61.80904523 62.81407035 63.81909548 64.8241206
65.82914573 66.83417085 67.83919598 68.84422111 69.84924623
70.85427136 71.85929648 72.86432161 73.86934673 74.87437186
75.87939698 76.88442211 77.88944724 78.89447236 79.89949749
80.90452261 81.90954774 82.91457286 83.91959799 84.92462312
85.92964824 86.93467337 87.93969849 88.94472362 89.94974874
90.95477387 91.95979899 92.96482412 93.96984925 94.97487437
95.9798995 96.98492462 97.98994975 98.99497487 100. ]
因此,使用此函数时,需仔细考虑两端数据是否包含以及具体需要的点数。
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