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‎pdal/test/data/from-module.json‎

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{
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"pipeline":[
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"./1.2-with-color.las",
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"./pdal/test/data/1.2-with-color.las",
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{
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"type": "filters.python",
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"script": "./test1.py",
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"script": "./pdal/test/data/test1.py",
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"module": "anything",
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"function": "fff"
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}

‎pdal/test/pipeline/crop_wkt_2d.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/las/1.2-with-color.las",
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{
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"type":"filters.crop",
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"polygon":"POLYGON ((636889.4129512392682955 851528.5122932585654780, 636899.1423342394409701 851475.0006867571501061, 636899.1423342394409701 851475.0006867571501061, 636928.3304832403082401 851494.4594527576118708, 636928.3304832403082401 851494.4594527576118708, 636928.3304832403082401 851494.4594527576118708, 636976.9773982415208593 851513.9182187581900507, 636976.9773982415208593 851513.9182187581900507, 637069.4065367440925911 851475.0006867571501061, 637132.6475262457970530 851445.8125377562828362, 637132.6475262457970530 851445.8125377562828362, 637336.9645692512858659 851411.7596972554456443, 637336.9645692512858659 851411.7596972554456443, 637473.1759312548674643 851158.7957392486277968, 637589.9285272579872981 850711.2441212366102263, 637244.5354307487141341 850511.7917697312077507, 636758.0662807356566191 850667.4618977354839444, 636539.1551632297923788 851056.6372177458833903, 636889.4129512392682955 851528.5122932585654780))",
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"outside":true
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},
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{
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"filename":"/Users/acbell/pdal/test/temp/autzen-colorized-1.2.3-hole.las",
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"compression":false
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}
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]
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}

‎pdal/test/pipeline/crop_wkt_2d_classification.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/las/1.2-with-color.las",
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{
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"type":"filters.crop",
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"polygon":"POLYGON ((636889.4129512392682955 851528.5122932585654780, 636899.1423342394409701 851475.0006867571501061, 636899.1423342394409701 851475.0006867571501061, 636928.3304832403082401 851494.4594527576118708, 636928.3304832403082401 851494.4594527576118708, 636928.3304832403082401 851494.4594527576118708, 636976.9773982415208593 851513.9182187581900507, 636976.9773982415208593 851513.9182187581900507, 637069.4065367440925911 851475.0006867571501061, 637132.6475262457970530 851445.8125377562828362, 637132.6475262457970530 851445.8125377562828362, 637336.9645692512858659 851411.7596972554456443, 637336.9645692512858659 851411.7596972554456443, 637473.1759312548674643 851158.7957392486277968, 637589.9285272579872981 850711.2441212366102263, 637244.5354307487141341 850511.7917697312077507, 636758.0662807356566191 850667.4618977354839444, 636539.1551632297923788 851056.6372177458833903, 636889.4129512392682955 851528.5122932585654780))",
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"outside":false
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},
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{
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"type":"filters.python",
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"function":"filter",
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"source":"import numpy as np\n\ndef filter(ins,outs):\n\tcls = ins['Classification']\n\n\tkeep_classes = [1,2]\n\n\t# Use the first test for our base array.\n\tkeep = np.equal(cls, keep_classes[0])\n\n\t# For 1:n, test each predicate and join back\n\t# to our existing predicate array\n\tfor k in range(1,len(keep_classes)):\n\t\tt = np.equal(cls, keep_classes[k])\n\t\tkeep = keep + t\n\n\touts['Mask'] = keep\n\treturn True",
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"module":"anything"
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},
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{
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"filename":"/Users/acbell/pdal/test/temp/crop-wkt-2d-classification.las",
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"compression":false
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}
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]
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}

‎pdal/test/pipeline/from-module.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/las/1.2-with-color.las",
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{
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"type": "filters.python",
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"script": "/Users/acbell/pdal/test/data/plang/test1.py",
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"module": "anything",
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"function": "fff"
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}
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]
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}

‎pdal/test/pipeline/predicate-embed.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/las/1.2-with-color.las",
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{
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"type":"filters.python",
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"module":"anything",
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"function":"fff",
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"source":"import numpy as np\ndef fff(ins,outs):\n\tX = ins['X']\n\tResult = np.equal(X, 637501.67)\n\t#print X\n\t#print Mask\n\touts['Mask'] = Result\n\treturn True"
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}
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]
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}

‎pdal/test/pipeline/predicate-keep-ground-and-unclass.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/autzen/autzen.las",
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{
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"type":"filters.python",
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"module":"anything",
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"function":"filter",
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"source":"import numpy as np\n\ndef filter(ins,outs):\n\tcls = ins['Classification']\n\n\tkeep_classes = [1,2]\n\n\t# Use the first test for our base array.\n\tkeep = np.equal(cls, keep_classes[0])\n\n\t# For 1:n, test each predicate and join back\n\t# to our existing predicate array\n\tfor k in range(1,len(keep_classes)):\n\t\tt = np.equal(cls, keep_classes[k])\n\t\tkeep = keep + t\n\n\touts['Mask'] = keep\n\treturn True"
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},
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"/Users/acbell/pdal/test/temp/out2.las"
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]
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}

‎pdal/test/pipeline/predicate-keep-last-return.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/autzen/autzen.las",
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{
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"type":"filters.stats"
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},
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{
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"type":"filters.python",
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"module":"anything",
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"function":"filter",
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"source":"import numpy as np\n\ndef filter(ins,outs):\n\tret = ins['ReturnNumber']\n\tret_no = ins['NumberOfReturns']\n\n\t# Use the first test for our base array.\n\trets = np.equal(ret, ret_no)\n\n\touts['Mask'] = rets\n\treturn True"
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},
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"/Users/acbell/pdal/test/temp/out2.las"
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]
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}

‎pdal/test/pipeline/predicate-keep-specified-returns.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/autzen/autzen.las",
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{
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"type":"filters.python",
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"module":"anything",
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"function":"filter",
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"source":"import numpy as np\n\ndef filter(ins,outs):\n\tret = ins['ReturnNumber']\n\n\tkeep_ret = [0, 1,2]\n\n\t# Use the first test for our base array.\n\tkeep = np.equal(ret, keep_ret[0])\n\n\t# For 1:n, test each predicate and join back\n\t# to our existing predicate array\n\tfor k in range(1, len(keep_ret)):\n\t\tt = np.equal(ret, keep_ret[k])\n\t\tkeep = keep + t\n\n\touts['Mask'] = keep\n\treturn True"
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},
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"/Users/acbell/pdal/test/temp/out2.las"
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]
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}

‎pdal/test/pipeline/programmable-update-y-dims.json‎

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{
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"pipeline":[
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"/Users/acbell/pdal/test/data/autzen/autzen-utm.las",
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{
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"type":"filters.python",
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"function":"myfunc",
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"module":"derive",
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"source":"import numpy as np\ndef myfunc(ins,outs):\n\tX = ins['Y']\n\tX1 = np.zeros(X.size, dtype=type(X[0])) + 314\n\touts['Y'] = X1\n\treturn True"
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}
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]
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}

‎pdal/test/pipeline/reproject.json‎

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{
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"pipeline":[
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{
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"filename":"/Users/acbell/pdal/test/data/las/1.2-with-color.las",
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"spatialreference":"EPSG:2993"
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},
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{
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"type":"filters.python",
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"function":"filter",
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"source":"import numpy as np\n\ndef filter(ins,outs):\n\tcls = ins['Classification']\n\n\tkeep_classes = [1]\n\n\t# Use the first test for our base array.\n\tkeep = np.equal(cls, keep_classes[0])\n\n\t# For 1:n, test each predicate and join back\n\t# to our existing predicate array\n\tfor k in range(1,len(keep_classes)):\n\t\tt = np.equal(cls, keep_classes[k])\n\t\tkeep = keep + t\n\n\touts['Mask'] = keep\n\treturn True",
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"module":"anything"
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},
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"/Users/acbell/pdal/test/temp/out2.las"
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]
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}

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