rename geotiff_play -> parseGeoTIFF.py, clean up README

Author: mkrupczak3

EIO_fetch_geotiff_example.md

@@ -17,7 +17,7 @@ The `--bounds` option accepts latitude and longitude coordinates (more precisely
 
     $ eio clip -o Rome-30m-DEM.tif --bounds 12.35 41.8 12.65 42
 
-In the preceeding example, `12.35` is the western longitude bound, `41.8` is the southern latitude bound, `12.65` is the eastern most longitude bound, and `42` is the northernmost latitude bound of the rectangular area of the desired geoTIFF file.
+In the preceeding example, `12.35` is the western longitude bound, `41.8` is the southern latitude bound, `12.65` is the eastern most longitude bound, and `42` is the northernmost latitude bound of the rectangular area of the desired GeoTIFF file.
 
 To clean up stale temporary files and fix the cache in the event of a server error use:
 
@@ -33,4 +33,4 @@ The excellent elevation data set is generated by a technique known as [Synthetic
 The dataset for the elevation API backing the `eio clip` was generated by the (Space) [Shuttle Radar Topography Mission](https://en.wikipedia.org/wiki/Shuttle_Radar_Topography_Mission#Highest_Resolution_Global_Release) conducted in the year 2000. In 2015 a high resolution global [digital elevation model](https://en.wikipedia.org/wiki/Digital_elevation_model), derived from the SRTM dataset, covering most of the world was released to the public without restriction. This DEM derived from the SRTM mission has a high resolution of 1-arc second (approx 30 meters). [Studies](https://www.sciencedirect.com/science/article/pii/S2090447917300084) have shown the vertical accuracy of the datapoints are very good, with error being observed to be within +/- 10 meters, despite the +/- 16 meters figure which was published in the SRTM data specification
 
 ## Improvement
-OpenAthena can accept DEM geoTIFF files of higher resolution or accuracy than the SRTM dataset, if provided by the user. Newer synthetic aperature radar datasets and LIDAR datasests are likely availible to those with significant resources
+OpenAthena can accept DEM GeoTIFF files of higher resolution or accuracy than the SRTM dataset, if provided by the user. Newer synthetic aperature radar datasets and LIDAR datasests are likely availible to those with significant resources

README.md

@@ -93,13 +93,13 @@ This software is in pre-alpha and results are not guaranteed to be accurate. Use
 
 [Python3](https://www.python.org/) (and the included pip package manager) must be installed first
 
-All you need to do is run `pip3 install gdal matplotlib mgrs`, then run `playground/geotiff_play.py` with python3:
+All you need to do is run `pip3 install gdal matplotlib mgrs`, then run `src/parseGeoTIFF.py` with python3:
 ```bash
 pip3 install gdal matplotlib mgrs
 # if this fails, instead install the GDAL package with your package manager (i.e. apt, yum, brew, pacman, etc.)
 git clone https://github.com/mkrupczak3/OpenAthena.git
-cd OpenAthena/playground
-python3 geotiff_play.py
+cd OpenAthena/src
+python3 parseGeoTIFF.py
 ```
 
 "pip3" and "python3" may just be called "pip" and "python" depending on the configuration of your system
@@ -110,16 +110,16 @@ This software is in pre-alpha and results are not guaranteed to be accurate. Use
 
 ### parseImage.py
 
-[parseImage.py](./playground/parseImage.py) can perform automatic extraction and use of EXIF/XMP sensor information from drone photos. This allows for the automatic extraction and use of data including the aircraft camera's lat/lon, altitude, azimuth, and angle of declenation (theta). OpenAthena (if provided [terrain elevation data](./EIO_fetch_geotiff_example.md)) will extract and use these values automaticaly to find the location on the ground in the exact center of the image
+[parseImage.py](./src/parseImage.py) can perform automatic extraction and use of EXIF/XMP sensor information from drone photos. This allows for the automatic extraction and use of data including the aircraft camera's lat/lon, altitude, azimuth, and angle of declenation (theta). OpenAthena (if provided [terrain elevation data](./EIO_fetch_geotiff_example.md)) will extract and use these values automaticaly to find the location on the ground in the exact center of the image
 
 [![image of command line on MacOS, command python3 parseImage.py bartow.tif, output and prompting user for drone image filename](./assets/parseImage_interactive_example2.png)](drone_sensor_data_blurb.md)
 
 
 More info [**here**](drone_sensor_data_blurb.md)
 
-### geotiff_play.py
+### parseGeoTIFF.py
 
-Run python geotiff_play.py (while in the playground directory) for a demonstration of [geoTIFF](https://en.wikipedia.org/wiki/GeoTIFF) [DEM](https://en.wikipedia.org/wiki/Digital_elevation_model) parsing. The file `Rome-30m-DEM.tif` is provided in the `playground` directory as an example. A DEM covering a customized area can be [easily obtained](./EIO_fetch_geotiff_example.md) using the python `elevation` API
+Run python parseGeoTIFF.py (while in the src directory) for a demonstration of [GeoTIFF](https://en.wikipedia.org/wiki/GeoTIFF) [DEM](https://en.wikipedia.org/wiki/Digital_elevation_model) parsing. The file `Rome-30m-DEM.tif` is provided in the `src` directory as an example. A DEM covering a customized area can be [easily obtained](./EIO_fetch_geotiff_example.md) using the python `elevation` API
 
 
 (counterintuitively, the x and y axis are backwards in the standard notation of a position via [latitude , longitude])
@@ -128,8 +128,8 @@ Run python geotiff_play.py (while in the playground directory) for a demonstrati
 
 
 ```
-user@mypc:~/projects/OpenAthena/playground$
-python geotiff_play.py
+user@mypc:~/projects/OpenAthena/src$
+python parseGeoTIFF.py
 ```
 ![render of terrain around Rome](./assets/render_cli_screenshot.png)
 
@@ -142,10 +142,10 @@ Then, exit the picture window that appears. You will now be prompted in the comm
 getTarget.py searches along the constructed line (emmitted from the camera center) for a terrain match
 
 
-To start, `cd` into the `playground` directory, then run getTarget.py:
+To start, `cd` into the `src` directory, then run getTarget.py:
 
 ```bash
-you@yourcomputer playground % python3 getTarget.py
+you@yourcomputer src % python3 getTarget.py
 ```
 
 You should then see the following prompt:
@@ -156,7 +156,7 @@ Which GeoTiff file would you like to read?
 Enter the GeoTIFF filename:
 ```
 
-You can clip [your own geoTIFF file](./playground/EIO_fetch_geotiff_example.md) from the [elevation API command line](http://elevation.bopen.eu/en/stable/quickstart.html#command-line-usage), or just use the provided example file `Rome-30m-DEM.tif` which contains the elevation data of the city of Rome, Italy and its outlying area
+You can clip [your own GeoTIFF file](./EIO_fetch_geotiff_example.md) from the [elevation API command line](http://elevation.bopen.eu/en/stable/quickstart.html#command-line-usage), or just use the provided example file `Rome-30m-DEM.tif` which contains the elevation data of the city of Rome, Italy and its outlying area
 
 
 ```bash
@@ -221,6 +221,8 @@ Target (lat, lon): 33.8352826, -84.5219971
 Google Maps: https://maps.google.com/?q=33.835283,-84.521997
 
 NATO MGRS: 16SGC2930646654
+MGRS 10m: 33TUG03953105
+MGRS 100m: 33TUG039310
 
 ```
 
@@ -246,7 +248,7 @@ The values should be tested for correctness and not totally relied upon in the c
 `Google Maps:` a link to the previous lat/lon on Google Maps. Each rounded to 6 decimal places
 
 
-`NATO MGRS: ` represents the target location in the [NATO Military Grid Reference System (MGRS)](https://en.wikipedia.org/wiki/Military_Grid_Reference_System), which is simmilar to [UTM](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system). This coordinate system does not include the altitude of the Target
+`NATO MGRS:` represents the target location in the [NATO Military Grid Reference System (MGRS)](https://en.wikipedia.org/wiki/Military_Grid_Reference_System), which is simmilar to [UTM](https://en.wikipedia.org/wiki/Universal_Transverse_Mercator_coordinate_system). This coordinate system does not include the altitude of the Target
 
 
 The program `getTarget.py` will then exit

assets/parseImage_interactive_example.png

@@ -4,7 +4,7 @@ The consumer models of some drones do not display their position, altitude, came
 
 ### parseImage.py
 
-[parseImage.py](./playground/parseImage.py) has an experimental feature for automatic extraction and use of EXIF/XMP sensor information from drone photos
+[parseImage.py](./src/parseImage.py) has an experimental feature for automatic extraction and use of EXIF/XMP sensor information from drone photos
 
 parseImage.py can be run in an **interactive** mode, or **headless** mode based on how many arguments are given after `python parseImage.py`. **Interactive** is designed for use by humans with one or more images, **headless** is designed for use by automation with one or more images. The output of **headless** mode is subject to change in future versions
 
@@ -27,7 +27,7 @@ python parseImage.py bartow.tif
 
 ![image of command line on MacOS, command python3 parseImage.py bartow.tif, output and prompting user for drone image filename](./assets/parseImage_interactive_example2.png)
 
-Enter the full file path of the drone image if it is not in the `playground` directory. Otherwise, just input the image filename and press **RETURN**
+Enter the full file path of the drone image if it is not in the `src` directory. Otherwise, just input the image filename and press **RETURN**
 
 Multiple images can be processed at once in **interactive** mode. When you're finished inputing images, type **`done`** to begin processing