diff --git a/outputHightMap.py b/outputHightMap.py
index 2c47025..a085a0b 100755
--- a/outputHightMap.py
+++ b/outputHightMap.py
@@ -5,13 +5,14 @@
 #    --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 os.path
 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)
+logging.basicConfig(format='%(asctime)s:%(levelname)s:%(message)s', level=logging.INFO)
 
 def sort(array):
     #sort by zDim column, first to last.
@@ -43,14 +44,16 @@ def scale(array, xRange, yRange, maxX, maxY):
 def isInxyRange(xMin, xMax, yMin, yMax, xVal, yVal):
     return (xMin<=xVal) and (xVal<xMax) and (yMin<=yVal) and (yVal<yMax)
 
-imgX=100
-imgY=100
+imgX=1000
+imgY=1000
 
 #TODO: make it iterate over multiple files.
-inFile = sys.argv[1]
+inFile = os.path.realpath(sys.argv[1])
 lasFile = laspy.file.File(inFile, mode = "r")
 
-outFile = f'{imgX}*{imgY}{inFile}.png'
+outFile = f'{os.path.dirname(inFile)}/{imgX}*{imgY}{os.path.basename(inFile)}.png'
+
+print(f'outputing to {outFile}')
 
 #import each dimention scaled.
 x = lasFile.x
@@ -76,7 +79,9 @@ points = np.stack((x,y,z,intensity), axis=-1)
 # [x,y,z,intensity]]
 
 logging.debug(f'points is\n{points}')
-logging.info(f'{points.shape[0]} points in LIDAR file.')
+print(f'{points.shape[0]} points in LIDAR file.')
+#found experimentally.
+print(f'estimated worst-case time is {points.shape[0]*7.77e-07*imgX*imgY} sec')
 
 xRange = maxes[xDim]-mins[xDim]
 yRange = maxes[yDim]-mins[yDim]
@@ -107,7 +112,7 @@ for x in range(imgX):
                 zVal = scaledArray[i,zDim]
                 break;
         imageArray[x,y]=zVal
-        logging.info(f'zVal at {x},{y} is {zVal}')
+        print(f'zVal at {x},{y} is {zVal}')
 
 logging.debug(f'imageArray is {imageArray}')