0.3.6

Updates between September 9, 2019 and December 1, 2019.

Changes to Codebase

Cloud

1. Added .from_pdal class method which converts a PDAL python.filter ins argument to a Cloud object.

Collection

1. ._build_polygons is now multithreaded.
2. .create_index is now multithreaded. Closes #65
3. from_dir now supports glob strings. Closes #66
4. par_apply accepts optional keyword arguments using the args parameter. These are passed to the applying function.
5. Added date-time parsing to collections.

GISExport

1. Removed some deprecated functions that were only used for tree segmentation

Ground Filter

1. Fixed a bug where KrausPfeifer1998.classify was throwing a key error. Closes #62.

Metrics

1. Added all_returns metric, that counts the number of returns in a cell.

Rasterizer

1. Gridding of points has been simplified. Closes #67.

Testing Suite

1. Modified .travis.yml for Windows testing environment.
2. Added additional checks for number of .lax files produced and length of tile change on retile_raster for collection testing. Removed printing statements.

Installation

1. 0.3.6 now officially supports conda installation! Dancing in the streets. Check the README for instructions.

Other

1. Version numbers must now be set in both setup.py and __init__.py for compatibility with conda-forge

0.3.5

Updates between April 20, 2019 and September 9, 2019

A few small maintenance updates and implementation of metrics.

Cloud

1. .normalize wrapper now allows for using already classified ground points with the classified argument.

Metrics

1. Added metrics computations for grid objects
2. Finalized the standard set of metrics for both cloud and grid objects via standard_metrics_grid and standard_metrics_cloud

Raster

1. .watershed_seg and .local_maxima were removed. Please see treeseg for new implementations of these methods.

Testing Suite

1. Added tests for Cloud.subtract, Raster.force_extent.

0.3.4 - Hotfixes

Hotixes applied directly to master between April 20, 2019 and 0.4.0 release.

Raster

1. Fixed bug in force_extent when appending empty arrays to bottom or top dimensions (May 3, 2019)

Collection

1. Restructured _construct_tile

0.3.4

Updates between February 10, 2019 and April 20, 2019.

In addition to the new features below, the documentation and user manual have been unified into one website located here. The pyfor_manual repository will be deprecated and deleted in the coming months. All of its content has been transferred to the new website.

Raster

1. Added force_extent function that allows users to force a specific output bounding box for a raster.

CloudDataFrame

1. Revamped par_apply to take advantage of .lax files if they are present.
2. Added a .crs attribute to set a collection level coordinate reference system.

Retile

1. Added a class (collection.Retiler) and wrapper functions (CloudDataFrame.retile_raster, etc) to assist in setting tile extents for a particular collection. This allows for flexibility when outputting summary rasters and reduced clutter in the CloudDataFrame class.

Other

1. Removed plotly dependencies and functions. These were not essential to the package, and created a lot of dependencies for the conda installation that are no longer present.
2. Removed detection module. This module was poorly maintained and implemented an unoptimized tree detection function. In the coming months I plan to start implementing detection tasks again, but in a more optimized way.

Testing Suite

1. Added tests for new par_apply
2. Testing for commonly loaded .las and .laz fields.

0.3.3

Updates between December 4th, 2018 and February 10, 2019. 0.3.3 implements a few structural changes and bug fixes. Its release will be followed by a major restructuring to implement in-memory .laz support in 0.3.4.

Cloud

1. Added warning to .clip when no points are present after the clip. #38
2. Minor restructuring to accommodate for a file write bug, addresses #40

Collection

1. Parallelized CloudDataFrame.clip

CrownSegments

1. Fixed a bug where crown segments were misprojected. #37

Ground Filter

1. For both Zhang2003 and KrausPfeifer1998, changed filter instantiation to reflect scikit-learn type instantiation.

Other

1. Implemented single sourcing for package versioning. #43
2. Minor adjustments to environment.yml to ensure Travis success. #41

0.3.2

Updates between October 25th, 2018 and December 4th, 2018. Note: some of these were applied directly to master before the merging of this branch. 0.3.2 represents many bug fixes and the addition of a few (relatively performant, your mileage may very) functions to collection. A shoutout to Ben Weinstein, whos diligent bug reporting has made pyfor a friendlier package during this update.

Cloud

1. Fixed a bug with the name attribute that returned the entire directory instead of just the filename (without extension)
2. Added .subtract function, this allows a user to provide their own (properly referenced) DEM for use in normalizing the parent cloud object.
3. Cloud.clip now resets the index of the points dataframe Cloud.data.points
4. Resolved issues instantiating Cloud objects using .laz files.
5. Changed the default normalization algorithm back to Zhang2003 now that it is working properly again (see below).
6. Cloud.convex_hull now returns a single shapely.geometry.Polygon instead of geopandas.GeoSeries

Collection

1. Added bounding_box attribute that retrieves the bounding box of the entire collection, used in retiling.
2. Added retile function to split large acquisitions into smaller tile sizes, for now this just splits into quadrants.
3. Added clip function to make memory-optimized spatial queries of collections, for example: clipping a collection of field plots.
4. Made CloudDataFrame.index_las and CloudDataFrame.from_dir into internal functions: CloudDataFrame._index_las and CloudDataFrame._from_dir respectively.

*Data

1. Added a check for empty dataframe before writing to file.
2. Improved the structure of LASData to prevent writing non-existant columns to file.

Ground Filter

1. Added normalize function to Zhang2003.
2. Fixed an issue where KrausPfeifer1998 was producing non-sensical normalizations.

Rasterizer

1. Grid now computes bins starting from the top left of an input Cloud. This fixes a lot of unnecessary array flipping further downstream. A UserWarning was added and will remain in effect until 0.3.3.

General Adjustments

1. Now testing multiple file types, .ply, .laz and .las
2. Added lastools and laxpy to the dependency stack.
3. Edited ~60% of the docstrings to reflect recent changes. Added cross referenced links and other small improvements.
4. Updated the samples to reflect recent changes. Added a few sections to the Normalization and Collections samples.

0.3.1

Updates between October 11th, 2018 and October 25th, 2018

Detection

1. Refactored LayerStacking to Ayrey2017 to cohere more with the citation format.

Documentation

1. Updated docstrings with 0.3.0 changes.

Rasterizer

1. Removed Grid.normalize, a deprecated function
2. Added a UserWarning in the case of undefined coordinate reference system of the Cloud object when writing a Raster

Testing Suite

1. Added many tests to achieve 90% coverage

0.3.0

Updates between September 5, 2018 and October 10th, 2018

Collection

1. Added 'CloudDataFrame', an inherited class from GeoDataFrame used to manage large LiDAR acquisitions.

Samples

1. Added Collections sample
2. Adjusted normalization/bem/etc sample with new updates.

Windows Compatibility

1. Addressed issues with plotting on Windows 10 - an up-to-date version of PyCharm should work well.

Cloud

1. Added support for .ply files
2. Changed default normalization algorithm to ground_filter.KrausPfeifer1998 while I debug and restructure ground_filter.zhang
3. Made CloudData a base class for the new LASDAta and PLYData classes.

Rasterizer

1. Changed Grid.raster to allow for keyword arguments for passed functions.
2. Added DeprecationWarning to rasterizer.Grid.normalize, will be replaced with standalone ground filters in 3.1.
3. Added DetectedTops object, used for visualizing detected tops from CHM.

Filter

1. Moved filter to ground_filter

KrausPfeif

Ground_Filter

1. Restructued filters into their own Classes, each with .bem, .classify() and .normalize. Fits better with the structure of the package.
2. Added Kraus and Pfeifer (1998) ground filter after having some issues with zhang. This filter is a much simpler ground filter but provides reasonable results.

environment.yml

1. Enforcing rasterio > 1.0 requirement which thereby requires use of conda-forge channel.
2. Added plyfile requirement (see above)

0.2.3

Updates between August 5, 2018 and September 5, 2018. These updates are minor improvements to set up for 0.3.0 release.

Documentation

1. Moved documentation from ReadTheDocs to brycefrank.com/pyfor
2. Updated documentation main page and internal structure

Testing Suite

1. Fixed broken clip polygons

Samples

1. Fixed clip sample (from above)
2. Added LayerStacking sample

Detection

1. Several improvements to detection.LayerStacking

GISExport

1. Added a project indices function, mostly for internal use.

0.2.2

Updates between May 9, 2018 and August 5, 2018.

Cloud

1. Fixed pandas SettingWithCopyWarning after clip + plot, still needs to be tested for performance (i.e. is this copy necessary?)
2. Added plotting for custom dimensions for Cloud.plot3d()
3. Moved pyqtgraph import statements witin Cloud.plot3d() to improve import perormance
4. Added functionality for plotting detected trees. Very rough but functional.
5. Added summary functionality, use print(some_cloud_object) to view.

Rasterizer

1. Watershed segmentation output was oriented incorrectly, fixed. (Actually was fixed via master, putting here for reference).
2. Fixed a bug that produced the wrong axes tick mark labels after modification of the Cloud object.
3. Reworked the behavior of rasterizer.Raster.local_maxima
   • By default only produces one pixel per detected top, whereas before it was possible to produce many pixels per top. This occurred if the detected top pixels were all equal in height.
   • If you prefer this type of behavior, you can set the argument multi_top to True
   • The other major rework here is that the function now returns a properly geo-referenced Raster, instead of a raw array. This is much more useful w/r/t I/O.

Detection

1. Added dedicated detection module
2. Added early version of LayerStacking (Ayrey et al. 2017)
   • This gets as far as the "Overlap map" in their paper
   • Sample forthcoming

Testing Suite

1. Added an second feature to the testing shapefile.
2. Adjusted testing suite to NEON data set for simplicity.
3. Test fixes for the above changes.

Environment

1. Enforcing rasterio version >= 1.0.2 in the environment for use of MemoryFiles (involved with LayerStacking)

0.2.1

Update merged to master: May 9th, 2018

This update was meant to implement features and bug fixes on the tile processing capabilities as well as improve some of the visualization functions. More samples and documentation were added, along with ~90% code coverage. Although the 0.3.0-specific voxelizer.py was added, it is not officially supported in this release.

Samples

1. Added a watershed segmentation sample.
2. Added a clipping sample.
3. Improved normalization sample
4. Added grid metrics sample with the new as_raster argument (see below)

Voxelizer

1. Added basic VoxelGrid class with a 3D version of raster

Rasterizer

Raster

1. Added a plot argument to the rasterizer.Raster.watershed_seg() function. This will plot the segment polygons over the raster object.
2. Fixed a bug in rasterizer.Raster.iplot3d that prevented plotting
3. Added rasterizer.Raster._convex_hull_mask, this helps plot interpolated rasters correctly by setting values outside of the convex hull to nan. This will help with future plotting and writing function to be written. columns that describe which dimension and which metric were calculated for the raster in that row. More details can be seen in the Grid_Metrics sample.

Grid

1. Removed the plot function from rasterizer.Grid, did not seem to fit with the philosophy of the object.
2. Added as_raster argument to rasterizer.Grid.metrics, this returns a pandas dataframe of the Raster objects that has

Cloud

1. Added cloud.Cloud.convex_hull, returns the convex hull of the two dimensional plane.
2. Reduced cloud.Cloud.clip to handle only shapely polygons for maintainability.

clip_funcs

1. clip_funcs.poly_clip now returns the indices of the original input cloud object. This is a cleaner approach than previously implemented.
2. Some slight adjustments to the other functions to accommodate (1).

General Maintenance

1. More tests were added.
2. Added a sample polygon shapefile: pyfortest/data/clip.shp, this will be used to test the clipping function.
3. Moved some import statements to their respective functions to reduce import time of the package.
4. Changed the theme of the documentation to something a bit more readable.