1 | import numpy as np |
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2 | import math |
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3 | |
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4 | n_dims = 3 |
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5 | n_bins = 4 |
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6 | |
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7 | def make_nd_array(n_dims, n_bins): |
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8 | base_array = np.arange(0, int(math.pow(n_bins, n_dims))) |
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9 | |
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10 | shape = [] |
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11 | for i in range(0, n_dims): |
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12 | shape.append(n_bins) |
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13 | as_grid = base_array.reshape(shape) |
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14 | return as_grid |
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15 | |
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16 | |
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17 | def get_indexes_from_linear(index, grid): |
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18 | out_indexes = list() |
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19 | shape = grid.shape |
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20 | nBins = shape[0] |
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21 | # first index |
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22 | ind = index%nBins |
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23 | |
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24 | out_indexes.append(ind) |
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25 | |
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26 | #what left in linear index after first was removed |
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27 | |
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28 | rest = index/nBins; |
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29 | for d in range(1, len(shape)): |
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30 | nBins = shape[d] |
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31 | ind = rest%nBins; |
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32 | out_indexes.append( ind ) |
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33 | rest = rest/nBins |
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34 | |
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35 | return out_indexes |
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36 | |
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37 | #as_grid = np.array([[0, 1, 2, 3], [4,5,6,7], [8,9,10,11], [12, 13, 14, 15]]) # 2D |
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38 | |
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39 | #as_grid = as_grid.flatten() # 1D |
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40 | |
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41 | as_grid = make_nd_array(n_dims, n_bins) |
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42 | |
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43 | |
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44 | def get_neighbours(grid, i): |
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45 | |
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46 | n_dims = len(grid.shape) |
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47 | offset = 1 |
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48 | back = i - offset |
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49 | forward =i + offset |
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50 | |
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51 | |
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52 | if forward/grid.shape[0] == i/grid.shape[0]: |
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53 | print forward |
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54 | if back >= 0 and back/grid.shape[0] == i/grid.shape[0]: |
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55 | print back |
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56 | |
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57 | |
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58 | for j in range(1, n_dims): |
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59 | offset = offset * grid.shape[j-1] |
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60 | |
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61 | offset_next = offset * grid.shape[j] |
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62 | |
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63 | back = i - offset |
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64 | forward = i + offset |
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65 | |
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66 | |
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67 | if forward/offset_next == i/offset_next: |
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68 | print forward |
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69 | if back >= 0 and back/offset_next == i/offset_next: |
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70 | print back |
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71 | |
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72 | |
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73 | def is_within_boundaries(neigh_index, current_indexes, grid): |
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74 | neigh_indexes = get_indexes_from_linear(neigh_index, grid) |
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75 | for index in range(len(current_indexes)): |
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76 | i = current_indexes[index] |
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77 | j = neigh_indexes[index] |
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78 | abs_diff = math.fabs(i-j) |
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79 | if abs_diff < 0 or abs_diff > 1 : |
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80 | return False |
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81 | return True |
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82 | |
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83 | |
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84 | def get_neighbours_all_touching(grid, i): |
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85 | |
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86 | n_dims = len(grid.shape) |
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87 | offset = 1 |
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88 | |
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89 | |
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90 | back = i - offset |
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91 | forward =i + offset |
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92 | |
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93 | indexes = get_indexes_from_linear(i, grid) |
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94 | |
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95 | permitations = list() |
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96 | permitations.append(0) |
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97 | |
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98 | dim_min = [None] |
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99 | dim_max = [None] |
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100 | |
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101 | permitations.append(1) |
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102 | permitations.append(-1) |
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103 | |
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104 | if forward/grid.shape[0] != i/grid.shape[0]: |
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105 | dim_max[0] = indexes[0] |
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106 | if back >= 0 and back/grid.shape[0] != i/grid.shape[0]: |
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107 | dim_min[0] = indexes[0] |
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108 | |
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109 | |
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110 | for j in range(1, n_dims): |
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111 | |
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112 | dim_min.append(None) |
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113 | dim_max.append(None) |
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114 | |
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115 | offset = offset * grid.shape[j-1] |
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116 | offset_next = offset * grid.shape[j] |
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117 | |
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118 | back = i - offset |
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119 | forward = i + offset |
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120 | |
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121 | if forward/offset_next != i/offset_next: |
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122 | dim_max[j] = indexes[j] |
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123 | if back >= 0 and back/offset_next != i/offset_next: |
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124 | dim_min[j] = indexes[j] |
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125 | |
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126 | |
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127 | |
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128 | extended_perms = list() |
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129 | for perm in permitations: |
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130 | |
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131 | extended_perms.append(perm + offset) |
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132 | extended_perms.append(-1*(perm+offset)) |
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133 | |
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134 | permitations.extend(extended_perms) |
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135 | |
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136 | print "n perms", len(permitations) |
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137 | print permitations |
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138 | |
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139 | |
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140 | for perm in permitations: |
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141 | if perm == 0: |
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142 | continue |
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143 | |
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144 | neigh_index = i + perm |
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145 | |
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146 | if is_within_boundaries(neigh_index, indexes, grid): |
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147 | print neigh_index |
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148 | |
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149 | |
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150 | |
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151 | index = 1 |
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152 | |
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153 | print as_grid |
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154 | |
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155 | get_neighbours_all_touching(as_grid, index) |
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156 | |
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157 | |
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158 | |
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159 | |
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160 | |
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161 | |
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162 | |
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163 | |
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164 | |
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