danforthcenter/plantcv: PlantCV v3.11.0

3.11.0 updates Added a label parameter to all PlantCV functions that save observations. The label parameter can be used to set a sample name when saving observations. Multiple samples can be saved per image now, allowing for repeated measurements, which simplifies workflows that measure multiple objects or regions of interest Added a sample parameter to Outputs.add_observation. Outputs class observations are now organized under sample names so that multiple samples can be associated with a single workflow. Add function pcv.transform.warp to fuse images that have different size/scale/proportions, e.g. from two (different) cameras in different locations. The function accepts 2 images and 4 pairs of points in order to compute a perspective transformation matrix so the images overlay nicely. Update the function pcv.hyperspectral.analyze_index to be more robust to NaN values and to also only consider finite values when calculating index statistics even when values range to positive or negative infinity. Documentation updates Prioritize the conda-forge channel in environment.yml Minor updates/bug fixes Add conda-forge badge to README Set .gitattributes to use Linux line endings on all platforms A handful of minor changes to functions inside the morphology sub-package. Segment insertion angle was failing on skeleton structures that should have been successful, so a tweak to the part of the algorithm that combines the stem segments into a single object helps. Branch and tip points should be integers. Bugfix within pcv.canny_edge_detect function where the debug parameter had no effect when the line thickness is set. Replaced MAINTAINER command in Dockerfile with LABEL because MAINTAINER is deprecated The workflow parallelization was duplicating the name of the image for the metadata "image". Removed the concatenation of the path (including name) and the name. Version 3.11.0 breaking changes A new sample input was added to the Outputs.add_observations class method. Observations stored in Outputs class instances have an extra hierarchical layer to account for sample names. To access an observation, the sample name needs to be included, for example: pcv.outputs.observations["sample_name"]["variable_name"