From adabf96a965895a50f1a7650843660350fd2a5de Mon Sep 17 00:00:00 2001
From: Julia Kukulies <julia.kukulies@gu.se>
Date: Fri, 21 Jun 2024 12:22:52 -0600
Subject: [PATCH 1/3] updated docstrings for n_min_threshold
---
tobac/feature_detection.py | 22 ++++++++++++++--------
1 file changed, 14 insertions(+), 8 deletions(-)
diff --git a/tobac/feature_detection.py b/tobac/feature_detection.py
index b937a0c0..f8128f50 100644
--- a/tobac/feature_detection.py
+++ b/tobac/feature_detection.py
@@ -390,7 +390,7 @@ def feature_detection_threshold(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: int = 0,
+ n_min_threshold: Union[int, dict, list] = 0 ,
min_distance: float = 0,
idx_start: int = 0,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -428,8 +428,10 @@ def feature_detection_threshold(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, optional
+ n_min_threshold : int, dict or list, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
+ If given as a list, the number of elements must match number of thresholds.
+ If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
min_distance : float, optional
Minimum distance between detected features (in meters). Default is 0.
@@ -897,7 +899,7 @@ def feature_detection_multithreshold_timestep(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: int = 0,
+ n_min_threshold: Union[int, dict, list] = 0,
min_distance: float = 0,
feature_number_start: int = 1,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -944,8 +946,10 @@ def feature_detection_multithreshold_timestep(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, optional
+ n_min_threshold : int, dict or list, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
+ If given as a list, the number of elements must match number of thresholds.
+ If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
min_distance : float, optional
Minimum distance between detected features (in meters). Default is 0.
@@ -1026,7 +1030,7 @@ def feature_detection_multithreshold_timestep(
):
raise ValueError(
"Ambiguous input for threshold values. If n_min_threshold is given as a dict,"
- " the keys not to correspond to the values in threshold."
+ " the keys must correspond to the values in threshold."
)
# sort dictionary by keys (threshold values) so that they match sorted thresholds and
# get values for n_min_threshold
@@ -1139,7 +1143,7 @@ def feature_detection_multithreshold(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: int = 0,
+ n_min_threshold: Union[int, dict, list] = 0,
min_distance: float = 0,
feature_number_start: int = 1,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -1183,9 +1187,11 @@ def feature_detection_multithreshold(
n_erosion_threshold: int, optional
Number of pixels by which to erode the identified features.
Default is 0.
-
- n_min_threshold : int, optional
+
+ n_min_threshold : int, dict or list, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
+ If given as a list, the number of elements must match number of thresholds.
+ If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
min_distance : float, optional
Minimum distance between detected features (in meters). Default is 0.
From 3a18cfb52adbceca6cb1d410be63377fe2914de5 Mon Sep 17 00:00:00 2001
From: Julia Kukulies <julia.kukulies@gu.se>
Date: Fri, 21 Jun 2024 12:37:53 -0600
Subject: [PATCH 2/3] black formatting
---
tobac/feature_detection.py | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/tobac/feature_detection.py b/tobac/feature_detection.py
index f8128f50..564aa03f 100644
--- a/tobac/feature_detection.py
+++ b/tobac/feature_detection.py
@@ -390,7 +390,7 @@ def feature_detection_threshold(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: Union[int, dict, list] = 0 ,
+ n_min_threshold: Union[int, dict, list] = 0,
min_distance: float = 0,
idx_start: int = 0,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -428,10 +428,10 @@ def feature_detection_threshold(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, dict or list, optional
+ n_min_threshold : int, dict or list, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
If given as a list, the number of elements must match number of thresholds.
- If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
+ If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
min_distance : float, optional
Minimum distance between detected features (in meters). Default is 0.
@@ -946,10 +946,10 @@ def feature_detection_multithreshold_timestep(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, dict or list, optional
+ n_min_threshold : int, dict or list, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
If given as a list, the number of elements must match number of thresholds.
- If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
+ If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
min_distance : float, optional
Minimum distance between detected features (in meters). Default is 0.
@@ -1187,11 +1187,11 @@ def feature_detection_multithreshold(
n_erosion_threshold: int, optional
Number of pixels by which to erode the identified features.
Default is 0.
-
- n_min_threshold : int, dict or list, optional
+
+ n_min_threshold : int, dict or list, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
If given as a list, the number of elements must match number of thresholds.
- If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
+ If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
min_distance : float, optional
Minimum distance between detected features (in meters). Default is 0.
From 5551fb7cc32dcb81ea363aba07b9b33f1fa7c1b7 Mon Sep 17 00:00:00 2001
From: Julia Kukulies <44163060+JuliaKukulies@users.noreply.github.com>
Date: Wed, 14 Aug 2024 12:07:36 -0600
Subject: [PATCH 3/3] fixed docstrings and type hint according to Fabians
comments
---
tobac/feature_detection.py | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/tobac/feature_detection.py b/tobac/feature_detection.py
index 564aa03f..0ac5fa8f 100644
--- a/tobac/feature_detection.py
+++ b/tobac/feature_detection.py
@@ -390,7 +390,7 @@ def feature_detection_threshold(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: Union[int, dict, list] = 0,
+ n_min_threshold: Union[int, dict[float, int], list[int]] = 0,
min_distance: float = 0,
idx_start: int = 0,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -428,7 +428,7 @@ def feature_detection_threshold(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, dict or list, optional
+ n_min_threshold : int, dict of float to int, or list of int, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
If given as a list, the number of elements must match number of thresholds.
If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
@@ -899,7 +899,7 @@ def feature_detection_multithreshold_timestep(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: Union[int, dict, list] = 0,
+ n_min_threshold: Union[int, dict[float, int], list[int]] = 0,
min_distance: float = 0,
feature_number_start: int = 1,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -946,7 +946,7 @@ def feature_detection_multithreshold_timestep(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, dict or list, optional
+ n_min_threshold : int, dict of float to int, or list of int, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
If given as a list, the number of elements must match number of thresholds.
If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.
@@ -1143,7 +1143,7 @@ def feature_detection_multithreshold(
] = "center",
sigma_threshold: float = 0.5,
n_erosion_threshold: int = 0,
- n_min_threshold: Union[int, dict, list] = 0,
+ n_min_threshold: Union[int, dict[float, int], list[int]] = 0,
min_distance: float = 0,
feature_number_start: int = 1,
PBC_flag: Literal["none", "hdim_1", "hdim_2", "both"] = "none",
@@ -1188,7 +1188,7 @@ def feature_detection_multithreshold(
Number of pixels by which to erode the identified features.
Default is 0.
- n_min_threshold : int, dict or list, optional
+ n_min_threshold : int, dict of float to int, or list of int, optional
Minimum number of identified contiguous pixels for a feature to be detected. Default is 0.
If given as a list, the number of elements must match number of thresholds.
If given as a dict, the keys need to match the thresholds and the values are the minimum number of identified contiguous pixels for a feature using that specific threshold.