inital commit. basic heatmap generator. still have to make many options configurable.

.gitignore

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+*.png
+
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outputHightMap.py

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+#! /usr/bin/env python3
+#command line arguments:
+#    --help, -h, outputs usage of the program
+#    -x, -y, outputs width and hight of the output image
+#    --output, -o, name of output file. if there are multiple input files, there will be a number prepended to this.
+#    after all comamnd line arguments, file or files(space seperated) to process.
+
+import numpy as np
+import sys, argparse, laspy, logging
+import seaborn as sns; sns.set_theme()
+import matplotlib.pyplot as plt
+from PIL import Image
+
+logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO)
+
+imgX=100
+imgY=100
+
+#TODO: make it iterate over multiple files.
+inFile = sys.argv[1]
+lasFile = laspy.file.File(inFile, mode = "r")
+#import each dimention scaled.
+x = lasFile.x
+y = lasFile.y
+z = lasFile.z
+maxes = np.array(lasFile.header.max)*np.array(lasFile.header.scale)
+mins = np.array(lasFile.header.min)*np.array(lasFile.header.scale)
+logging.debug(f'max values is {maxes}')
+logging.debug(f'min values is {mins}')
+intensity = lasFile.intensity
+
+#dimention that will be z(top down) dimention in final heatmap. TODO: auto detect this based on dimention with least variance.
+zDim=0
+xDim=1
+yDim=2
+
+points = np.stack((x,y,z,intensity), axis=-1)
+#points should now look like
+#[[x,y,z,intensity]
+# [x,y,z,intensity]
+# ...
+# [x,y,z,intensity]
+# [x,y,z,intensity]]
+
+logging.debug(f'points is\n{points}')
+
+xRange = maxes[xDim]-mins[xDim]
+yRange = maxes[yDim]-mins[yDim]
+zRange = maxes[zDim]-mins[zDim]
+def sort(array):
+    #sort by zDim column, first to last.
+    logging.debug(f'zDim sliced points is\n{array[:,zDim]}')
+    #the [::-1] reverses the resulting array, so that sortedPoints will be from biggest to smallest.
+    ind = np.argsort(array[:,zDim])[::-1]
+    sortedPoints = array[ind]
+    logging.debug(f'sortedPoints is\n{sortedPoints}')
+    return sortedPoints
+
+sortedPoints = sort(points)
+
+imageArray = np.zeros((imgX, imgY))
+
+def scale(array, xRange, yRange, maxX, maxY):
+    logging.debug(f'xRange is {xRange} and yRange is {yRange}')
+    xScale = maxX/xRange
+    yScale = maxY/yRange
+
+    scaledArray = sortedPoints[:, 0:3]
+    scaledArray[:,xDim]=scaledArray[:,xDim]-mins[xDim]
+    scaledArray[:,xDim]=scaledArray[:,xDim]*xScale
+    logging.debug(f'xmin in scaledArray is {scaledArray[:,xDim].min()}')
+    logging.debug(f'xmin in scaledArray is {scaledArray[:,xDim].max()}')
+
+    scaledArray[:,yDim]=scaledArray[:,yDim]-mins[yDim]
+    scaledArray[:,yDim]=scaledArray[:,yDim]*yScale
+    logging.debug(f'ymin in scaledArray is {scaledArray[:,yDim].min()}')
+    logging.debug(f'ymin in scaledArray is {scaledArray[:,yDim].max()}')
+    logging.debug(f'scaledArray is\n{scaledArray}')
+    return scaledArray
+
+scaledArray = scale(points, xRange, yRange, imgX, imgY)
+
+def isInxyRange(xMin, xMax, yMin, yMax, xVal, yVal):
+    return (xMin<=xVal) and (xVal<xMax) and (yMin<=yVal) and (yVal<yMax)
+
+for x in range(imgX):
+    for y in range(imgY):
+        if x==imgX:
+            xMax=x+2
+        else:
+            xMax=x+1
+
+        if y==imgY:
+            yMax=y+2
+        else:
+            yMax=y+1
+
+        zVal=0
+        logging.debug(f'yMax is {yMax} and xMax is {xMax}')
+        for i in range(scaledArray.shape[0]):
+            if isInxyRange(x, xMax, y, yMax, scaledArray[i,xDim], scaledArray[i,yDim]):
+                zVal = scaledArray[i,zDim]
+                break;
+        imageArray[x,y]=zVal
+        logging.info(f'zVal at {x},{y} is {zVal}')
+
+logging.debug(f'imageArray is {imageArray}')
+
+heatMap = sns.heatmap(imageArray, center=((maxes[zDim]+mins[zDim])/2), square=True)
+heatMapFig = heatMap.get_figure()
+heatMapFig.savefig("output.png")