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3fa9374bd4
This merges the three packages, matrix, mat64, and cmat128. It then renames this big package to mat. It fixes the import statements and corresponding code
123 lines
4.2 KiB
Go
123 lines
4.2 KiB
Go
// Copyright ©2017 The gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package mat_test
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import "gonum.org/v1/gonum/mat"
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// FAO is a dataset extracted from Food and Agriculture Organization of the
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// United Nations "FAO Statistical Pocketbook: World Food and Agriculture 2015".
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// pp49-52.
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var FAO = struct {
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Africa *mat.Dense
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Asia *mat.Dense
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LatinAmericaCaribbean *mat.Dense
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Oceania *mat.Dense
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}{
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Africa: mat.NewDense(21, 3, []float64{
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// 1990, 2000, 2014
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35.3, 38, 30.7, // Employment in agriculture (%)
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9.2, 20.3, 25.2, // Employment in agriculture, female (%)
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3163, 14718, 20667, // Energy consump, power irrigation (mln kWh)
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2597, 2717, 2903, // Dietary energy supply (kcal/pc/day)
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113, 116, 123, // Average dietary energy supply adequacy (%)
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58, 55, 52, // Dietary en supp, cereals/roots/tubers (%)
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18.6, 15, 10.8, // Prevalence of undernourishment (%)
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8832, 10241, 13915, // GDP per capita (US$, PPP)
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-0.4, -0.2, 50.7, // Cereal import dependency ratio (%)
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78.5, 83, 88.7, // Improved water source (% pop)
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// Production indices (2004-06=100)
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73, 90, 121, // Net food
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72, 89, 123, // Net crops
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82, 92, 123, // Cereals
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51, 77, 141, // Vegetable oils
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74, 94, 119, // Roots and tubers
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58, 86, 127, // Fruit and vegetables
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86, 93, 132, // Sugar
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76, 92, 115, // Livestock
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83, 89, 114, // Milk
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74, 91, 118, // Meat
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72, 92, 119, // Fish
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}),
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Asia: mat.NewDense(21, 3, []float64{
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// 1990, 2000, 2014
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30.9, 24.5, 27.6, // Employment in agriculture (%)
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40.9, 29.4, 31.1, // Employment in agriculture, female (%)
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7614, 38316, 82411, // Energy consump, power irrigation (mln kWh)
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2320, 2402, 2581, // Dietary energy supply (kcal/pc/day)
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107, 110, 117, // Average dietary energy supply adequacy (%)
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66, 65, 63, // Dietary en supp, cereals/roots/tubers (%)
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27.6, 25.7, 19.8, // Prevalence of undernourishment (%)
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3315, 3421, 4575, // GDP per capita (US$, PPP)
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25.9, 28.1, 42, // Cereal import dependency ratio (%)
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55.5, 61.1, 68.7, // Improved water source (% pop)
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// Production indices (2004-06=100)
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60, 82, 129, // Net food
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59, 82, 127, // Net crops
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66, 79, 131, // Cereals
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58, 79, 128, // Vegetable oils
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50, 80, 133, // Roots and tubers
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58, 82, 124, // Fruit and vegetables
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76, 94, 114, // Sugar
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65, 84, 126, // Livestock
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59, 77, 125, // Milk
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67, 87, 127, // Meat
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65, 90, 119, // Fish
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}),
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LatinAmericaCaribbean: mat.NewDense(14, 3, []float64{
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// 1990, 2000, 2014
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19.5, 14.2, 15.8, // Employment in agriculture (%)
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13.7, 6.2, 7.6, // Employment in agriculture, female (%)
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2669, 2787, 3069, // Dietary energy supply (kcal/pc/day)
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117, 120, 129, // Average dietary energy supply adequacy (%)
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42, 41, 40, // Dietary en supp, cereals/roots/tubers (%)
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14.7, 12.1, 5.5, // Prevalence of undernourishment (%)
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9837, 10976, 13915, // GDP per capita (US$, PPP)
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13, 12, 49.7, // Cereal import dependency ratio (%)
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85.1, 89.8, 94, // Improved water source (% pop)
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// Production indices (2004-06=100)
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60, 83, 129, // Net food
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64, 83, 131, // Net crops
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62, 88, 139, // Cereals
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58, 84, 123, // Livestock
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82, 107, 71, // Fish
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}),
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Oceania: mat.NewDense(21, 3, []float64{
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// 1990, 2000, 2014
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6.2, 17.1, 3.8, // Employment in agriculture (%)
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4.5, 3.9, 4.4, // Employment in agriculture, female (%)
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415, 1028, 8667, // Energy consump, power irrigation (mln kWh)
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2454, 2436, 2542, // Dietary energy supply (kcal/pc/day)
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113, 112, 114, // Average dietary energy supply adequacy (%)
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49, 50, 48, // Dietary en supp, cereals/roots/tubers (%)
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15.7, 16.1, 14.2, // Prevalence of undernourishment (%)
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2269, 2536, 3110, // GDP per capita (US$, PPP)
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95.2, 95.9, 95.4, // Cereal import dependency ratio (%)
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49.7, 53.2, 55.5, // Improved water source (% pop)
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// Production indices (2004-06=100)
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72, 99, 116, // Net food
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69, 105, 126, // Net crops
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77, 113, 117, // Cereals
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41, 122, 215, // Vegetable oils
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80, 90, 110, // Roots and tubers
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66, 88, 104, // Fruit and vegetables
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70, 104, 71, // Sugar
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79, 97, 107, // Livestock
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56, 92, 113, // Milk
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79, 96, 105, // Meat
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51, 78, 85, // Fish
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}),
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}
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