From ec898ee54cfb1ad261ec639e3e3054b022643ad6 Mon Sep 17 00:00:00 2001 From: Joseph Crawford Date: Mon, 28 Sep 2020 09:21:06 -0400 Subject: [PATCH 1/2] Fix typos in a few files (cherry picked from commit f7d531151bebdb958c160b143fb7a7e803c8cd07) --- verde/distances.py | 2 +- verde/model_selection.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/verde/distances.py b/verde/distances.py index 7a49ddb76..1ac69e9fe 100644 --- a/verde/distances.py +++ b/verde/distances.py @@ -15,7 +15,7 @@ def median_distance(coordinates, k_nearest=1, projection=None): distance to its *k_nearest* neighbors among the other points in the dataset. Sparse uniformly spaced datasets can use *k_nearest* of 1. Datasets with points clustered into tight groups (e.g., densely sampled - along a flight line or ship treck) will have very small distances to the + along a flight line or ship wreck) will have very small distances to the closest neighbors, which is not representative of the actual median spacing because it doesn't take the spacing between lines into account. In these cases, a median of the 10 or 20 nearest neighbors might be more diff --git a/verde/model_selection.py b/verde/model_selection.py index c230e5991..dfff35532 100644 --- a/verde/model_selection.py +++ b/verde/model_selection.py @@ -86,7 +86,7 @@ class BlockShuffleSplit(BaseBlockCrossValidator): The number of splits generated per iteration to try to balance the amount of data in each set so that *test_size* and *train_size* are respected. If 1, then no extra splits are generated (essentially - disabling the balacing). Must be >= 1. + disabling the balancing). Must be >= 1. See also -------- From c17ab8b1443edc371c8557594cba5d54f4653ece Mon Sep 17 00:00:00 2001 From: dcslagel Date: Fri, 27 Nov 2020 20:54:40 -0700 Subject: [PATCH 2/2] Fix typos on docstrings --- verde/distances.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/verde/distances.py b/verde/distances.py index 1ac69e9fe..dd0e8afdf 100644 --- a/verde/distances.py +++ b/verde/distances.py @@ -15,7 +15,7 @@ def median_distance(coordinates, k_nearest=1, projection=None): distance to its *k_nearest* neighbors among the other points in the dataset. Sparse uniformly spaced datasets can use *k_nearest* of 1. Datasets with points clustered into tight groups (e.g., densely sampled - along a flight line or ship wreck) will have very small distances to the + along a flight line or ship track) will have very small distances to the closest neighbors, which is not representative of the actual median spacing because it doesn't take the spacing between lines into account. In these cases, a median of the 10 or 20 nearest neighbors might be more