30 Second Functions

When is it faster to write the function than to even find out how to do it in the help.  Well ok, I did actually search and didn't find out how, but here is what would have been faster.

I use handwheels,  I wanted an easy way to switch the z input from the footdisk to the right handwheel and back.  There is probably a way to pass an argument into a macro but I couldn't find it so enter....

zhand.py

print 'z handwheel'
VrCfg().SetHwLocZ (2)

The beauty of VrCfg is that it modifies the environment in real time just like calling any of the functions that would do the same thing via a dialog box.

Saying anything else would just not have a point, except, always be thinking of ways to extend the usefulness of existing processes.

Note to self: Step backward through LiDAR when removing, and repr ( round ( a number )) is awsome

First, apparently I never noticed this before but while trying to step though a bunch of LiDAR points to remove a certain class it apparently changes something dynamically (like the point number in the buffer).  I noticed this because I was doing a

    for PointNum in range(Punt.GetCount()):
        if Punt.Cla(PointNum) == Whatever:
            Punt.DelPunt(PointNum)

To get rid of a certain type of point, in this case based on class.  What I noticed though was that each time it ran there were a bunch of points left over (half??).  I decided that even though I wasn't doing a record until the loop was done, the point number in the buffer must change as points are deleted.  So what to do?  How about starting at the last point and removing them from the top end of the buffer so as you work backwards the previous point numbers would not have changed.  I came up with

for PointNum in range(Punt.GetCount(),-1,-1):

and it seems to work fine.

Second and totally unrelated I needed to rebuild a tile naming structure for a local dataset.  There is a tile scheme that is based on 5000 foot tiles that is easy enough to get the names of.  The problem is that there is also a subset of 1250 foot tiles that starts from the corner of each 5k block but the names are based on 1000 foot increments.  When you digitize a random point in a block you can't necessarily round down to the lower 1000 because they just truncate the thousands from a rounded 1250.  Ok hard to imagine but the corners would be 0, 1250, 2500, 3750 so a number 3749 would fall in a 2500 block and truncate to 2000 meaning the tile would have 2 in the name, not to mention dropping a million off one of the coordinates.  Now for the why I love python part!

repr(round(1773691/1250)*1250)[1:4]

yields '772' just like is necessary to build the proper tile name. 

Note to self: Find a reason to use geopy

Full disclosure; This has nothing to do with anything except that I was playing with a really cool module today and need to make sure I remember what I just learned.  The module is geopy (which by the way I installed using pip for the first time ever ) which can be used to geocode natural language addresses using a variety of APIs.  Don't know when, how, or why I'll use it but I'm certain I will.

Info can be found at https://pypi.python.org/pypi/geopy
Doc at http://geopy.readthedocs.org/en/latest/

Here is what I just did (using my current address)

>>> import geopy
>>> geopy.geocoders.GoogleV3().geocode("4090 weaver ct s 43026")
Location((40.035917, -83.144145, 0.0))
>>> geopy.geocoders.GoogleV3().geocode("4090 weaver ct s 43026").raw
{u'geometry': {u'location': {u'lat': 40.035917, u'lng': -83.144145}, u'viewport': {u'northeast': {u'lat': 40.03726598029149, u'lng': -83.1427960197085}, u'southwest': {u'lat': 40.03456801970849, u'lng': -83.1454939802915}}, u'location_type': u'ROOFTOP'}, u'formatted_address': u'4090 Weaver Court, Hilliard, OH 43026, USA', u'place_id': u'ChIJpUOLF-iTOIgRT-Vqu5rHhLo', u'address_components': [{u'long_name': u'4090', u'types': [u'street_number'], u'short_name': u'4090'}, {u'long_name': u'Weaver Court', u'types': [u'route'], u'short_name': u'Weaver Ct'}, {u'long_name': u'Northwest Industrial Complex', u'types': [u'neighborhood', u'political'], u'short_name': u'Northwest Industrial Complex'}, {u'long_name': u'Hilliard', u'types': [u'locality', u'political'], u'short_name': u'Hilliard'}, {u'long_name': u'Norwich', u'types': [u'administrative_area_level_3', u'political'], u'short_name': u'Norwich'}, {u'long_name': u'Franklin County', u'types': [u'administrative_area_level_2', u'political'], u'short_name': u'Franklin County'}, {u'long_name': u'Ohio', u'types': [u'administrative_area_level_1', u'political'], u'short_name': u'OH'}, {u'long_name': u'United States', u'types': [u'country', u'political'], u'short_name': u'US'}, {u'long_name': u'43026', u'types': [u'postal_code'], u'short_name': u'43026'}, {u'long_name': u'1197', u'types': [u'postal_code_suffix'], u'short_name': u'1197'}], u'partial_match': True, u'types': [u'street_address']}

It's all part of the process (or subprocess as the case may be)

On occasion I make the case for installing python in order to extend the usefulness of the environment in Vr, or at least getting hold of some of the most useful standard libraries.  Well here is another good reason.  This is just a snippet that I will use later but I figure this is as good a place as any to keep track of it.

Before too long I want to write a script that will depend on running an external process, then interacting with the results of the process (no spoilers yet).  In order to do that I'm going to make something similar to the following call to process some files leaving the results in the working directory. The research I did here was to make sure I had a way to not proceed until the original process was complete.  Later I'll need to make sure I can run a shell command and capture the resulting output but this will do for now.

import subprocess
process = subprocess.Popen('lasboundary -i *rgb1.las -otxt')
process.wait()
print process.returncode
print '\a'

the last line is just to beep so I knew when it was done.

Reminder snippets - liblas and reading laz files

The other thing that I used to do with this blog is post things that I wanted to remember.  At one point the Vr forums were a good place to do this because it also gave an opportunity to share and collaborate.  Since that doesn't really seem to be happening any more I suppose I could drop things here and then come back to them later if necessary.  Yes I could just do this in a document but who knows maybe a new opportunity for some kind of sharing community will pop up again.

In this case I just want to remind myself that if Vr never adopts the .LAZ LiDAR compression format for reading, it would still be possible using liblas. This is simple a little interactive session that shows it is theoretically possible using my own data.

There may indeed be other better ways, but this seems to work fine.

>>> import liblas
>>> f=liblas.file.File(r'c:\tmp\N1915250.laz',mode='r')
>>> f

>>> p=f.read(100)
>>> p.classification
5
>>> p.x
1919853.35
>>> f.header.compressed
True
>>> f.filename
'c:\\tmp\\N1915250.laz'