diff --git a/shotmap_cleaner/.gitignore b/shotmap_cleaner/.gitignore
new file mode 100644
index 00000000..505a3b1c
--- /dev/null
+++ b/shotmap_cleaner/.gitignore
@@ -0,0 +1,10 @@
+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
diff --git a/shotmap_cleaner/.python-version b/shotmap_cleaner/.python-version
new file mode 100644
index 00000000..24ee5b1b
--- /dev/null
+++ b/shotmap_cleaner/.python-version
@@ -0,0 +1 @@
+3.13
diff --git a/shotmap_cleaner/README.md b/shotmap_cleaner/README.md
new file mode 100644
index 00000000..61910a50
--- /dev/null
+++ b/shotmap_cleaner/README.md
@@ -0,0 +1,39 @@
+# Shot Map Cleaner
+
+## Installation
+
+Use `uv` or `pip` to install:
+
+```sh
+uv sync
+```
+
+or
+
+```sh
+pip install -r requirements.txt
+```
+
+If you want to use a virtual environment with pip:
+
+```sh
+py -m venv venv
+
+.\venv\Scripts\activate
+
+pip install -r requirements.txt
+```
+
+## Usage:
+
+Simply run main.py  (`uv run main.py` or `py main.py`).
+
+Select either manual or automatic mode.
+
+Automatic mode will prompt you for error bounds. These should likely be considerably smaller than the acceptable error margin for our fire control; this error will be added to that error in terms of the final amount of error allowed while shooting, as this error controls the *setpoint* rather than the actual position. You can use h/j/k/l to move your cursor left and right and to increment/decrement the hovered digit of the number you're entering.
+
+Manual mode will allow you to manually pick points to keep/drop:
+
+Select data points to keep (k/j for up and down and space to toggle selection). Press enter and the program will compare the map you've cherrypicked to the original map. It will print out a summary of the differences between the maps (itemwise subtraction for each datapoint from min to max distance at 1cm increments). If you're satisfied, answer `y` to the done prompt. Otherwise, answer `n` to select new points.
+
+Once you've indicated that you're done, the program will serialize the new map to `ShotMapsCleaned.json` in the `deploy/constants/comp/` directory.
diff --git a/shotmap_cleaner/main.py b/shotmap_cleaner/main.py
new file mode 100644
index 00000000..abe844e5
--- /dev/null
+++ b/shotmap_cleaner/main.py
@@ -0,0 +1,275 @@
+import json
+import pandas as pd
+import numpy as np
+from InquirerPy import inquirer
+from InquirerPy.base.control import Choice
+from typing import TypedDict, Literal
+import matplotlib.pyplot as plt
+
+
+class UnitedValue(TypedDict):
+    value: float
+    unit: Literal["Degree"] | Literal["Second"] | Literal["Meter"]
+
+
+class MapDataPoint(TypedDict):
+    distance: UnitedValue
+    shooterRPM: float
+    hoodAngle: UnitedValue
+    flightTime: UnitedValue
+
+
+class ShotMaps(TypedDict):
+    hubDataPoints: list[MapDataPoint]
+    passDataPoints: list[MapDataPoint]
+    mechanismCompensationDelay: UnitedValue
+    rpmCompensation: UnitedValue
+
+
+class ShotMapDFDict(TypedDict):
+    distance: list[float]
+    rpm: list[float]
+    pitchDegrees: list[float]
+    flightTimeSeconds: list[float]
+
+
+def number(n: str) -> int | float:
+    try:
+        if float(int(n)) != float(n):
+            raise Exception()
+        return int(n)
+    except:
+        return float(n)
+
+
+def convert_shotmaps_to_frame(shot_map_data: ShotMaps) -> ShotMapDFDict:
+    output: ShotMapDFDict = {
+        "distance": [],
+        "rpm": [],
+        "pitchDegrees": [],
+        "flightTimeSeconds": [],
+    }
+
+    for data_point in shot_map_data["hubDataPoints"]:
+        output["distance"].append(data_point["distance"]["value"])
+        output["rpm"].append(data_point["shooterRPM"])
+        output["pitchDegrees"].append(data_point["hoodAngle"]["value"])
+        output["flightTimeSeconds"].append(data_point["flightTime"]["value"])
+
+    return output
+
+
+def convert_frame_to_shotmaps(frame: pd.DataFrame) -> ShotMaps:
+    with open(
+        "../2026-Robot-Code/src/main/deploy/constants/comp/ShotMaps.json", "r"
+    ) as f:
+        shot_map_data = json.load(f)
+
+    shot_map_data["hubDataPoints"] = []
+
+    for distance in frame.index:
+        shot_map_data["hubDataPoints"].append(
+            {
+                "distance": {
+                    "value": number(distance),
+                    "unit": "Meter",
+                },
+                "shooterRPM": number(frame["rpm"][distance]),
+                "hoodAngle": {
+                    "value": number(frame["pitchDegrees"][distance]),
+                    "unit": "Degree",
+                },
+                "flightTime": {
+                    "value": number(frame["flightTimeSeconds"][distance]),
+                    "unit": "Second",
+                },
+            }
+        )
+
+    return shot_map_data
+
+
+def filter_and_reindex(df, selected_distances):
+    filtered_df = df[df["distance"].isin(selected_distances)]
+
+    filtered_df = filtered_df.set_index("distance", drop=True)
+    df = df.set_index("distance", drop=True)
+
+    return df, filtered_df
+
+
+def get_residuals(df, filtered_df, resolution=0.01):
+    min_dist = df.index.min()
+    max_dist = df.index.max()
+
+    # Dense grid using linspace avoids np.arange floating-point drift
+    dense_index = pd.Index(
+        np.linspace(min_dist, max_dist, int((max_dist - min_dist) / resolution) + 1)
+    )
+
+    # Union of filtered points + dense grid, then interpolate
+    combined_index = filtered_df.index.union(dense_index)
+    interpolated = (
+        filtered_df.reindex(combined_index)
+        .sort_index()
+        .interpolate(method="linear")
+        .reindex(dense_index)
+    )
+
+    # Do the same for df to get the "ground truth" at high resolution
+    full_combined_index = df.index.union(dense_index)
+    full_interpolated = (
+        df.reindex(full_combined_index)
+        .sort_index()
+        .interpolate(method="linear")
+        .reindex(dense_index)
+    )
+
+    return interpolated - full_interpolated
+
+
+def evaluate(df, filtered_df):
+    residuals = get_residuals(df, filtered_df)
+
+    # print("residuals:\n", residuals)
+    # print(residuals.describe())
+    residuals_abs = residuals.abs()
+    print("residuals abs:")
+    print(residuals_abs.describe())
+
+    print("Points with large error:")
+    print(residuals_abs[residuals_abs["rpm"] > 25.0])
+
+
+def main():
+    with open("../src/main/deploy/constants/comp/ShotMaps.json", "r") as f:
+        shot_map_data = json.load(f)
+
+    shot_map_df_dict = convert_shotmaps_to_frame(shot_map_data)
+
+    selected_distances = []
+    while True:
+        df = pd.DataFrame(shot_map_df_dict).sort_values(by="distance")
+
+        action_choices = [
+            Choice(value="manual", name="Select points manually"),
+            Choice(value="auto", name="Automatically filter points"),
+        ]
+        mode = inquirer.select(
+            message="Select filtering method",
+            choices=action_choices,
+            vi_mode=True,
+            long_instruction="(j/k to move down/up, enter to select)",
+        ).execute()
+
+        if mode == "manual":
+            distance_choices = [
+                Choice(value=d, name=f"{d} meters", enabled=d in selected_distances)
+                for d in df["distance"]
+            ]
+            selected_distances = inquirer.checkbox(
+                message="Select points to use",
+                long_instruction="(j/k to move down/up, space to toggle 1, C-r to toggle all, enter to try this set)",
+                choices=distance_choices,
+                vi_mode=True,
+                default=selected_distances,
+            ).execute()
+            df, filtered_df_to_write = filter_and_reindex(df, selected_distances)
+        else:
+            max_rpm_error = float(
+                inquirer.number(
+                    message="Max RPM error",
+                    instruction="(RPM)",
+                    vi_mode=True,
+                    float_allowed=True,
+                    min_allowed=0,
+                    transformer=lambda x: x + " RPM",
+                ).execute()
+            )
+            max_angle_error = float(
+                inquirer.number(
+                    message="Max hood angle error",
+                    instruction="(degrees)",
+                    vi_mode=True,
+                    float_allowed=True,
+                    min_allowed=0,
+                    transformer=lambda x: x + " degrees",
+                ).execute()
+            )
+            max_tof_error = float(
+                inquirer.number(
+                    message="Max time of flight error",
+                    instruction="(seconds)",
+                    vi_mode=True,
+                    float_allowed=True,
+                    min_allowed=0,
+                    transformer=lambda x: x + " seconds",
+                ).execute()
+            )
+
+            df = df.set_index("distance", drop=True)
+            filtered_df = df.copy()
+
+            while True:
+                best_distance = None
+                best_max_rpm_err = float("inf")
+                best_max_angle_err = float("inf")
+                best_max_tof_err = float("inf")
+
+                for distance in filtered_df.index:
+                    # Never remove endpoints — interpolation can't extrapolate
+                    if (
+                        distance == filtered_df.index.min()
+                        or distance == filtered_df.index.max()
+                    ):
+                        continue
+
+                    trial_filtered_df = filtered_df[filtered_df.index != distance]
+                    residuals = get_residuals(df, trial_filtered_df).abs()
+
+                    # If NaNs exist, the trial doesn't cover the full range — skip
+                    if residuals.isna().any().any():
+                        continue
+
+                    rpm_err = residuals["rpm"].max()
+                    angle_err = residuals["pitchDegrees"].max()
+                    flight_time_err = residuals["flightTimeSeconds"].max()
+
+                    if (
+                        rpm_err <= max_rpm_error
+                        and angle_err <= max_angle_error
+                        and flight_time_err <= max_tof_error
+                        and rpm_err < best_max_rpm_err
+                    ):
+                        best_max_rpm_err = rpm_err
+                        best_max_angle_err = angle_err
+                        best_max_tof_err = flight_time_err
+                        best_distance = distance
+
+                if best_distance is None:
+                    break
+
+                print(
+                    f"Dropped point at {best_distance} meters. (rpm_err={
+                        best_max_rpm_err:.2f} angle_err={
+                        best_max_angle_err:.2f} tof_err={best_max_tof_err:.2f})"
+                )
+                filtered_df = filtered_df[filtered_df.index != best_distance]
+
+            filtered_df_to_write = filtered_df
+
+        evaluate(df, filtered_df_to_write)
+
+        done = inquirer.confirm(message="Done?").execute()
+        if done:
+            break
+
+    with open("../src/main/deploy/constants/comp/ShotMapsCleaned.json", "w+") as f:
+        f.truncate()
+        json.dump(convert_frame_to_shotmaps(filtered_df_to_write), f, indent=2)
+
+    print("Wrote file to ShotMapsCleaned.json.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/shotmap_cleaner/pyproject.toml b/shotmap_cleaner/pyproject.toml
new file mode 100644
index 00000000..962741af
--- /dev/null
+++ b/shotmap_cleaner/pyproject.toml
@@ -0,0 +1,11 @@
+[project]
+name = "shotmap-cleaner"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "inquirerpy>=0.3.4",
+    "matplotlib>=3.10.8",
+    "pandas>=3.0.1",
+]
diff --git a/shotmap_cleaner/requirements.txt b/shotmap_cleaner/requirements.txt
new file mode 100644
index 00000000..393f726a
--- /dev/null
+++ b/shotmap_cleaner/requirements.txt
@@ -0,0 +1,347 @@
+# This file was autogenerated by uv via the following command:
+#    uv export --format requirements.txt
+contourpy==1.3.3 \
+    --hash=sha256:083e12155b210502d0bca491432bb04d56dc3432f95a979b429f2848c3dbe880 \
+    --hash=sha256:13b68d6a62db8eafaebb8039218921399baf6e47bf85006fd8529f2a08ef33fc \
+    --hash=sha256:177fb367556747a686509d6fef71d221a4b198a3905fe824430e5ea0fda54eb5 \
+    --hash=sha256:1cadd8b8969f060ba45ed7c1b714fe69185812ab43bd6b86a9123fe8f99c3263 \
+    --hash=sha256:1fd43c3be4c8e5fd6e4f2baeae35ae18176cf2e5cced681cca908addf1cdd53b \
+    --hash=sha256:22e9b1bd7a9b1d652cd77388465dc358dafcd2e217d35552424aa4f996f524f5 \
+    --hash=sha256:283edd842a01e3dcd435b1c5116798d661378d83d36d337b8dde1d16a5fc9ba3 \
+    --hash=sha256:2a2a8b627d5cc6b7c41a4beff6c5ad5eb848c88255fda4a8745f7e901b32d8e4 \
+    --hash=sha256:2b7e9480ffe2b0cd2e787e4df64270e3a0440d9db8dc823312e2c940c167df7e \
+    --hash=sha256:33c82d0138c0a062380332c861387650c82e4cf1747aaa6938b9b6516762e772 \
+    --hash=sha256:348ac1f5d4f1d66d3322420f01d42e43122f43616e0f194fc1c9f5d830c5b286 \
+    --hash=sha256:3c30273eb2a55024ff31ba7d052dde990d7d8e5450f4bbb6e913558b3d6c2301 \
+    --hash=sha256:4debd64f124ca62069f313a9cb86656ff087786016d76927ae2cf37846b006c9 \
+    --hash=sha256:4feffb6537d64b84877da813a5c30f1422ea5739566abf0bd18065ac040e120a \
+    --hash=sha256:50ed930df7289ff2a8d7afeb9603f8289e5704755c7e5c3bbd929c90c817164b \
+    --hash=sha256:644a6853d15b2512d67881586bd03f462c7ab755db95f16f14d7e238f2852c67 \
+    --hash=sha256:655456777ff65c2c548b7c454af9c6f33f16c8884f11083244b5819cc214f1b5 \
+    --hash=sha256:66c8a43a4f7b8df8b71ee1840e4211a3c8d93b214b213f590e18a1beca458f7d \
+    --hash=sha256:6afc576f7b33cf00996e5c1102dc2a8f7cc89e39c0b55df93a0b78c1bd992b36 \
+    --hash=sha256:6c3d53c796f8647d6deb1abe867daeb66dcc8a97e8455efa729516b997b8ed99 \
+    --hash=sha256:87acf5963fc2b34825e5b6b048f40e3635dd547f590b04d2ab317c2619ef7ae8 \
+    --hash=sha256:88df9880d507169449d434c293467418b9f6cbe82edd19284aa0409e7fdb933d \
+    --hash=sha256:95b181891b4c71de4bb404c6621e7e2390745f887f2a026b2d99e92c17892339 \
+    --hash=sha256:a15459b0f4615b00bbd1e91f1b9e19b7e63aea7483d03d804186f278c0af2659 \
+    --hash=sha256:a22738912262aa3e254e4f3cb079a95a67132fc5a063890e224393596902f5a4 \
+    --hash=sha256:ab2fd90904c503739a75b7c8c5c01160130ba67944a7b77bbf36ef8054576e7f \
+    --hash=sha256:ab3074b48c4e2cf1a960e6bbeb7f04566bf36b1861d5c9d4d8ac04b82e38ba20 \
+    --hash=sha256:afe5a512f31ee6bd7d0dda52ec9864c984ca3d66664444f2d72e0dc4eb832e36 \
+    --hash=sha256:b20c7c9a3bf701366556e1b1984ed2d0cedf999903c51311417cf5f591d8c78d \
+    --hash=sha256:b7301b89040075c30e5768810bc96a8e8d78085b47d8be6e4c3f5a0b4ed478a0 \
+    --hash=sha256:b7448cb5a725bb1e35ce88771b86fba35ef418952474492cf7c764059933ff8b \
+    --hash=sha256:ca0fdcd73925568ca027e0b17ab07aad764be4706d0a925b89227e447d9737b7 \
+    --hash=sha256:ca658cd1a680a5c9ea96dc61cdbae1e85c8f25849843aa799dfd3cb370ad4fbe \
+    --hash=sha256:cbedb772ed74ff5be440fa8eee9bd49f64f6e3fc09436d9c7d8f1c287b121d77 \
+    --hash=sha256:cf9022ef053f2694e31d630feaacb21ea24224be1c3ad0520b13d844274614fd \
+    --hash=sha256:d002b6f00d73d69333dac9d0b8d5e84d9724ff9ef044fd63c5986e62b7c9e1b1 \
+    --hash=sha256:d06bb1f751ba5d417047db62bca3c8fde202b8c11fb50742ab3ab962c81e8216 \
+    --hash=sha256:d304906ecc71672e9c89e87c4675dc5c2645e1f4269a5063b99b0bb29f232d13 \
+    --hash=sha256:e4e6b05a45525357e382909a4c1600444e2a45b4795163d3b22669285591c1ae \
+    --hash=sha256:e74a9a0f5e3fff48fb5a7f2fd2b9b70a3fe014a67522f79b7cca4c0c7e43c9ae \
+    --hash=sha256:ea37e7b45949df430fe649e5de8351c423430046a2af20b1c1961cae3afcda77 \
+    --hash=sha256:f64836de09927cba6f79dcd00fdd7d5329f3fccc633468507079c829ca4db4e3 \
+    --hash=sha256:fd6ec6be509c787f1caf6b247f0b1ca598bef13f4ddeaa126b7658215529ba0f \
+    --hash=sha256:fd914713266421b7536de2bfa8181aa8c699432b6763a0ea64195ebe28bff6a9 \
+    --hash=sha256:fde6c716d51c04b1c25d0b90364d0be954624a0ee9d60e23e850e8d48353d07a
+    # via matplotlib
+cycler==0.12.1 \
+    --hash=sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30 \
+    --hash=sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c
+    # via matplotlib
+fonttools==4.62.0 \
+    --hash=sha256:0361a7d41d86937f1f752717c19f719d0fde064d3011038f9f19bdf5fc2f5c95 \
+    --hash=sha256:03c6068adfdc67c565d217e92386b1cdd951abd4240d65180cec62fa74ba31b2 \
+    --hash=sha256:0dc477c12b8076b4eb9af2e440421b0433ffa9e1dcb39e0640a6c94665ed1098 \
+    --hash=sha256:106aec9226f9498fc5345125ff7200842c01eda273ae038f5049b0916907acee \
+    --hash=sha256:15d86b96c79013320f13bc1b15f94789edb376c0a2d22fb6088f33637e8dfcbc \
+    --hash=sha256:273acb61f316d07570a80ed5ff0a14a23700eedbec0ad968b949abaa4d3f6bb5 \
+    --hash=sha256:274c8b8a87e439faf565d3bcd3f9f9e31bca7740755776a4a90a4bfeaa722efa \
+    --hash=sha256:28a9ea2a7467a816d1bec22658b0cce4443ac60abac3e293bdee78beb74588f3 \
+    --hash=sha256:3f9e20c4618f1e04190c802acae6dc337cb6db9fa61e492fd97cd5c5a9ff6d07 \
+    --hash=sha256:4f16c07e5250d5d71d0f990a59460bc5620c3cc456121f2cfb5b60475699905f \
+    --hash=sha256:4fa5a9c716e2f75ef34b5a5c2ca0ee4848d795daa7e6792bf30fd4abf8993449 \
+    --hash=sha256:5ae611294f768d413949fd12693a8cba0e6332fbc1e07aba60121be35eac68d0 \
+    --hash=sha256:6247e58b96b982709cd569a91a2ba935d406dccf17b6aa615afaed37ac3856aa \
+    --hash=sha256:625f5cbeb0b8f4e42343eaeb4bc2786718ddd84760a2f5e55fdd3db049047c00 \
+    --hash=sha256:6826a5aa53fb6def8a66bf423939745f415546c4e92478a7c531b8b6282b6c3b \
+    --hash=sha256:75064f19a10c50c74b336aa5ebe7b1f89fd0fb5255807bfd4b0c6317098f4af3 \
+    --hash=sha256:83c6524c5b93bad9c2939d88e619fedc62e913c19e673f25d5ab74e7a5d074e5 \
+    --hash=sha256:840632ea9c1eab7b7f01c369e408c0721c287dfd7500ab937398430689852fd1 \
+    --hash=sha256:93e27131a5a0ae82aaadcffe309b1bae195f6711689722af026862bede05c07c \
+    --hash=sha256:a5f974006d14f735c6c878fc4b117ad031dc93638ddcc450ca69f8fd64d5e104 \
+    --hash=sha256:b448075f32708e8fb377fe7687f769a5f51a027172c591ba9a58693631b077a8 \
+    --hash=sha256:d28d5baacb0017d384df14722a63abe6e0230d8ce642b1615a27d78ffe3bc983 \
+    --hash=sha256:d31558890f3fa00d4f937d12708f90c7c142c803c23eaeb395a71f987a77ebe3 \
+    --hash=sha256:d4108c12773b3c97aa592311557c405d5b4fc03db2b969ed928fcf68e7b3c887 \
+    --hash=sha256:e5f1fa8cc9f1a56a3e33ee6b954d6d9235e6b9d11eb7a6c9dfe2c2f829dc24db \
+    --hash=sha256:f8c8ea812f82db1e884b9cdb663080453e28f0f9a1f5027a5adb59c4cc8d38d1
+    # via matplotlib
+inquirerpy==0.3.4 \
+    --hash=sha256:89d2ada0111f337483cb41ae31073108b2ec1e618a49d7110b0d7ade89fc197e \
+    --hash=sha256:c65fdfbac1fa00e3ee4fb10679f4d3ed7a012abf4833910e63c295827fe2a7d4
+    # via shotmap-cleaner
+kiwisolver==1.5.0 \
+    --hash=sha256:012b1eb16e28718fa782b5e61dc6f2da1f0792ca73bd05d54de6cb9561665fc9 \
+    --hash=sha256:0255a027391d52944eae1dbb5d4cc5903f57092f3674e8e544cdd2622826b3f0 \
+    --hash=sha256:0b85aad90cea8ac6797a53b5d5f2e967334fa4d1149f031c4537569972596cb8 \
+    --hash=sha256:0bf3acf1419fa93064a4c2189ac0b58e3be7872bf6ee6177b0d4c63dc4cea276 \
+    --hash=sha256:0c50b89ffd3e1a911c69a1dd3de7173c0cd10b130f56222e57898683841e4f96 \
+    --hash=sha256:0cbe94b69b819209a62cb27bdfa5dc2a8977d8de2f89dfd97ba4f53ed3af754e \
+    --hash=sha256:0e3aafb33aed7479377e5e9a82e9d4bf87063741fc99fc7ae48b0f16e32bdd6f \
+    --hash=sha256:16b85d37c2cbb3253226d26e64663f755d88a03439a9c47df6246b35defbdfb7 \
+    --hash=sha256:1b0feb50971481a2cc44d94e88bdb02cdd497618252ae226b8eb1201b957e368 \
+    --hash=sha256:1d49a49ac4cbfb7c1375301cd1ec90169dfeae55ff84710d782260ce77a75a02 \
+    --hash=sha256:1dd9b0b119a350976a6d781e7278ec7aca0b201e1a9e2d23d9804afecb6ca681 \
+    --hash=sha256:2a075bd7bd19c70cf67c8badfa36cf7c5d8de3c9ddb8420c51e10d9c50e94920 \
+    --hash=sha256:332b4f0145c30b5f5ad9374881133e5aa64320428a57c2c2b61e9d891a51c2f3 \
+    --hash=sha256:377815a8616074cabbf3f53354e1d040c35815a134e01d7614b7692e4bf8acfa \
+    --hash=sha256:38f4a703656f493b0ad185211ccfca7f0386120f022066b018eb5296d8613e23 \
+    --hash=sha256:3ac2360e93cb41be81121755c6462cff3beaa9967188c866e5fce5cf13170859 \
+    --hash=sha256:3cdcb35dc9d807259c981a85531048ede628eabcffb3239adf3d17463518992d \
+    --hash=sha256:413b820229730d358efd838ecbab79902fe97094565fdc80ddb6b0a18c18a581 \
+    --hash=sha256:4432b835675f0ea7414aab3d37d119f7226d24869b7a829caeab49ebda407b0c \
+    --hash=sha256:4db576bb8c3ef9365f8b40fe0f671644de6736ae2c27a2c62d7d8a1b4329f099 \
+    --hash=sha256:4e7f886f47ab881692f278ae901039a234e4025a68e6dfab514263a0b1c4ae05 \
+    --hash=sha256:5060731cc3ed12ca3a8b57acd4aeca5bbc2f49216dd0bec1650a1acd89486bcd \
+    --hash=sha256:5092eb5b1172947f57d6ea7d89b2f29650414e4293c47707eb499ec07a0ac796 \
+    --hash=sha256:5124d1ea754509b09e53738ec185584cc609aae4a3b510aaf4ed6aa047ef9303 \
+    --hash=sha256:56fa888f10d0f367155e76ce849fa1166fc9730d13bd2d65a2aa13b6f5424489 \
+    --hash=sha256:58f812017cd2985c21fbffb4864d59174d4903dd66fa23815e74bbc7a0e2dd57 \
+    --hash=sha256:5b233ea3e165e43e35dba1d2b8ecc21cf070b45b65ae17dd2747d2713d942021 \
+    --hash=sha256:6783e069732715ad0c3ce96dbf21dbc2235ab0593f2baf6338101f70371f4028 \
+    --hash=sha256:70d593af6a6ca332d1df73d519fddb5148edb15cd90d5f0155e3746a6d4fcc65 \
+    --hash=sha256:7a32f72973f0f950c1920475d5c5ea3d971b81b6f0ec53b8d0a956cc965f22e0 \
+    --hash=sha256:7a4aa69609f40fce3cbc3f87b2061f042eee32f94b8f11db707b66a26461591a \
+    --hash=sha256:80aa065ffd378ff784822a6d7c3212f2d5f5e9c3589614b5c228b311fd3063ac \
+    --hash=sha256:893ff3a711d1b515ba9da14ee090519bad4610ed1962fbe298a434e8c5f8db53 \
+    --hash=sha256:89fc958c702ee9a745e4700378f5d23fddbc46ff89e8fdbf5395c24d5c1452a3 \
+    --hash=sha256:8df31fe574b8b3993cc61764f40941111b25c2d9fea13d3ce24a49907cd2d615 \
+    --hash=sha256:9027d773c4ff81487181a925945743413f6069634d0b122d0b37684ccf4f1e18 \
+    --hash=sha256:940dda65d5e764406b9fb92761cbf462e4e63f712ab60ed98f70552e496f3bf1 \
+    --hash=sha256:bc4d8e252f532ab46a1de9349e2d27b91fce46736a9eedaa37beaca66f574ed4 \
+    --hash=sha256:bdd3e53429ff02aa319ba59dfe4ceeec345bf46cf180ec2cf6fd5b942e7975e9 \
+    --hash=sha256:be12f931839a3bdfe28b584db0e640a65a8bcbc24560ae3fdb025a449b3d754e \
+    --hash=sha256:c0e1403fd7c26d77c1f03e096dc58a5c726503fa0db0456678b8668f76f521e3 \
+    --hash=sha256:c95cab08d1965db3d84a121f1c7ce7479bdd4072c9b3dafd8fecce48a2e6b902 \
+    --hash=sha256:ce9bf03dad3b46408c08649c6fbd6ca28a9fce0eb32fdfffa6775a13103b5310 \
+    --hash=sha256:d168fda2dbff7b9b5f38e693182d792a938c31db4dac3a80a4888de603c99554 \
+    --hash=sha256:d1ffeb80b5676463d7a7d56acbe8e37a20ce725570e09549fe738e02ca6b7e1e \
+    --hash=sha256:d36ca54cb4c6c4686f7cbb7b817f66f5911c12ddb519450bbe86707155028f87 \
+    --hash=sha256:d4193f3d9dc3f6f79aaed0e5637f45d98850ebf01f7ca20e69457f3e8946b66a \
+    --hash=sha256:d618fd27420381a4f6044faa71f46d8bfd911bd077c555f7138ed88729bfbe79 \
+    --hash=sha256:d76e2d8c75051d58177e762164d2e9ab92886534e3a12e795f103524f221dd8e \
+    --hash=sha256:db485b3847d182b908b483b2ed133c66d88d49cacf98fd278fadafe11b4478d1 \
+    --hash=sha256:dda366d548e89a90d88a86c692377d18d8bd64b39c1fb2b92cb31370e2896bbd \
+    --hash=sha256:e4415a8db000bf49a6dd1c478bf70062eaacff0f462b92b0ba68791a905861f9 \
+    --hash=sha256:e7a116ae737f0000343218c4edf5bd45893bfeaff0993c0b215d7124c9f77646 \
+    --hash=sha256:e7c4c09a490dc4d4a7f8cbee56c606a320f9dc28cf92a7157a39d1ce7676a657 \
+    --hash=sha256:f443b4825c50a51ee68585522ab4a1d1257fac65896f282b4c6763337ac9f5d2 \
+    --hash=sha256:fa6248cd194edff41d7ea9425ced8ca3a6f838bfb295f6f1d6e6bb694a8518df \
+    --hash=sha256:fa8eb9ecdb7efb0b226acec134e0d709e87a909fa4971a54c0c4f6e88635484c \
+    --hash=sha256:fc20894c3d21194d8041a28b65622d5b86db786da6e3cfe73f0c762951a61167 \
+    --hash=sha256:fc4d3f1fb9ca0ae9f97b095963bc6326f1dbfd3779d6679a1e016b9baaa153d3 \
+    --hash=sha256:fd40bb9cd0891c4c3cb1ddf83f8bbfa15731a248fdc8162669405451e2724b09
+    # via matplotlib
+matplotlib==3.10.8 \
+    --hash=sha256:0a33deb84c15ede243aead39f77e990469fff93ad1521163305095b77b72ce4a \
+    --hash=sha256:113bb52413ea508ce954a02c10ffd0d565f9c3bc7f2eddc27dfe1731e71c7b5f \
+    --hash=sha256:15d30132718972c2c074cd14638c7f4592bd98719e2308bccea40e0538bc0cb5 \
+    --hash=sha256:2299372c19d56bcd35cf05a2738308758d32b9eaed2371898d8f5bd33f084aa3 \
+    --hash=sha256:25d380fe8b1dc32cf8f0b1b448470a77afb195438bafdf1d858bfb876f3edf7b \
+    --hash=sha256:2c1998e92cd5999e295a731bcb2911c75f597d937341f3030cc24ef2733d78a8 \
+    --hash=sha256:2cf5bd12cecf46908f286d7838b2abc6c91cda506c0445b8223a7c19a00df008 \
+    --hash=sha256:32f8dce744be5569bebe789e46727946041199030db8aeb2954d26013a0eb26b \
+    --hash=sha256:3a48a78d2786784cc2413e57397981fb45c79e968d99656706018d6e62e57958 \
+    --hash=sha256:3f2e409836d7f5ac2f1c013110a4d50b9f7edc26328c108915f9075d7d7a91b6 \
+    --hash=sha256:3f5c3e4da343bba819f0234186b9004faba952cc420fbc522dc4e103c1985908 \
+    --hash=sha256:41703cc95688f2516b480f7f339d8851a6035f18e100ee6a32bc0b8536a12a9c \
+    --hash=sha256:495672de149445ec1b772ff2c9ede9b769e3cb4f0d0aa7fa730d7f59e2d4e1c1 \
+    --hash=sha256:4cf267add95b1c88300d96ca837833d4112756045364f5c734a2276038dae27d \
+    --hash=sha256:56271f3dac49a88d7fca5060f004d9d22b865f743a12a23b1e937a0be4818ee1 \
+    --hash=sha256:595ba4d8fe983b88f0eec8c26a241e16d6376fe1979086232f481f8f3f67494c \
+    --hash=sha256:5f62550b9a30afde8c1c3ae450e5eb547d579dd69b25c2fc7a1c67f934c1717a \
+    --hash=sha256:646d95230efb9ca614a7a594d4fcacde0ac61d25e37dd51710b36477594963ce \
+    --hash=sha256:83d282364ea9f3e52363da262ce32a09dfe241e4080dcedda3c0db059d3c1f11 \
+    --hash=sha256:a0a7f52498f72f13d4a25ea70f35f4cb60642b466cbb0a9be951b5bc3f45a486 \
+    --hash=sha256:ad3d9833a64cf48cc4300f2b406c3d0f4f4724a91c0bd5640678a6ba7c102077 \
+    --hash=sha256:b44d07310e404ba95f8c25aa5536f154c0a8ec473303535949e52eb71d0a1565 \
+    --hash=sha256:b53285e65d4fa4c86399979e956235deb900be5baa7fc1218ea67fbfaeaadd6f \
+    --hash=sha256:b5a2b97dbdc7d4f353ebf343744f1d1f1cca8aa8bfddb4262fcf4306c3761d50 \
+    --hash=sha256:c108a1d6fa78a50646029cb6d49808ff0fc1330fda87fa6f6250c6b5369b6645 \
+    --hash=sha256:d9050fee89a89ed57b4fb2c1bfac9a3d0c57a0d55aed95949eedbc42070fea39 \
+    --hash=sha256:e8ea3e2d4066083e264e75c829078f9e149fa119d27e19acd503de65e0b13149 \
+    --hash=sha256:eb3823f11823deade26ce3b9f40dcb4a213da7a670013929f31d5f5ed1055b22 \
+    --hash=sha256:f89c151aab2e2e23cb3fe0acad1e8b82841fd265379c4cecd0f3fcb34c15e0f6
+    # via shotmap-cleaner
+numpy==2.4.3 \
+    --hash=sha256:0200b25c687033316fb39f0ff4e3e690e8957a2c3c8d22499891ec58c37a3eb5 \
+    --hash=sha256:0448e7f9caefb34b4b7dd2b77f21e8906e5d6f0365ad525f9f4f530b13df2afc \
+    --hash=sha256:0a195f4216be9305a73c0e91c9b026a35f2161237cf1c6de9b681637772ea657 \
+    --hash=sha256:0a60e17a14d640f49146cb38e3f105f571318db7826d9b6fef7e4dce758faecd \
+    --hash=sha256:120df8c0a81ebbf5b9020c91439fccd85f5e018a927a39f624845be194a2be02 \
+    --hash=sha256:148d59127ac95979d6f07e4d460f934ebdd6eed641db9c0db6c73026f2b2101a \
+    --hash=sha256:1ec84fd7c8e652b0f4aaaf2e6e9cc8eaa9b1b80a537e06b2e3a2fb176eedcb26 \
+    --hash=sha256:22654fe6be0e5206f553a9250762c653d3698e46686eee53b399ab90da59bd92 \
+    --hash=sha256:22c31dc07025123aedf7f2db9e91783df13f1776dc52c6b22c620870dc0fab22 \
+    --hash=sha256:2629289168f4897a3c4e23dc98d6f1731f0fc0fe52fb9db19f974041e4cc12b9 \
+    --hash=sha256:297837823f5bc572c5f9379b0c9f3a3365f08492cbdc33bcc3af174372ebb168 \
+    --hash=sha256:2e03c05abaee1f672e9d67bc858f300b5ccba1c21397211e8d77d98350972093 \
+    --hash=sha256:45f003dbdffb997a03da2d1d0cb41fbd24a87507fb41605c0420a3db5bd4667b \
+    --hash=sha256:483a201202b73495f00dbc83796c6ae63137a9bdade074f7648b3e32613412dd \
+    --hash=sha256:4bd4741a6a676770e0e97fe9ab2e51de01183df3dcbcec591d26d331a40de950 \
+    --hash=sha256:4d382735cecd7bcf090172489a525cd7d4087bc331f7df9f60ddc9a296cf208e \
+    --hash=sha256:52077feedeff7c76ed7c9f1a0428558e50825347b7545bbb8523da2cd55c547a \
+    --hash=sha256:54f29b877279d51e210e0c80709ee14ccbbad647810e8f3d375561c45ef613dd \
+    --hash=sha256:5884ce5c7acfae1e4e1b6fde43797d10aa506074d25b531b4f54bde33c0c31d4 \
+    --hash=sha256:5e10da9e93247e554bb1d22f8edc51847ddd7dde52d85ce31024c1b4312bfba0 \
+    --hash=sha256:679f2a834bae9020f81534671c56fd0cc76dd7e5182f57131478e23d0dc59e24 \
+    --hash=sha256:6bd06731541f89cdc01b261ba2c9e037f1543df7472517836b78dfb15bd6e476 \
+    --hash=sha256:7aa4e54f6469300ebca1d9eb80acd5253cdfa36f2c03d79a35883687da430875 \
+    --hash=sha256:7d1ce23cce91fcea443320a9d0ece9b9305d4368875bab09538f7a5b4131938a \
+    --hash=sha256:7f3408ff897f8ab07a07fbe2823d7aee6ff644c097cc1f90382511fe982f647f \
+    --hash=sha256:94f3c4a151a2e529adf49c1d54f0f57ff8f9b233ee4d44af623a81553ab86368 \
+    --hash=sha256:9684823a78a6cd6ad7511fc5e25b07947d1d5b5e2812c93fe99d7d4195130720 \
+    --hash=sha256:a111698b4a3f8dcbe54c64a7708f049355abd603e619013c346553c1fd4ca90b \
+    --hash=sha256:a749547700de0a20a6718293396ec237bb38218049cfce788e08fcb716e8cf73 \
+    --hash=sha256:a97cbf7e905c435865c2d939af3d93f99d18eaaa3cabe4256f4304fb51604349 \
+    --hash=sha256:b346845443716c8e542d54112966383b448f4a3ba5c66409771b8c0889485dd3 \
+    --hash=sha256:b44fd60341c4d9783039598efadd03617fa28d041fc37d22b62d08f2027fa0e7 \
+    --hash=sha256:bb2e3cf95854233799013779216c57e153c1ee67a0bf92138acca0e429aefaee \
+    --hash=sha256:be3b8487d725a77acccc9924f65fd8bce9af7fac8c9820df1049424a2115af6c \
+    --hash=sha256:c59020932feb24ed49ffd03704fbab89f22aa9c0d4b180ff45542fe8918f5611 \
+    --hash=sha256:c9619741e9da2059cd9c3f206110b97583c7152c1dc9f8aafd4beb450ac1c89d \
+    --hash=sha256:cd32fbacb9fd1bf041bf8e89e4576b6f00b895f06d00914820ae06a616bdfef7 \
+    --hash=sha256:d1b90d840b25874cf5cd20c219af10bac3667db3876d9a495609273ebe679070 \
+    --hash=sha256:d213c7e6e8d211888cc359bab7199670a00f5b82c0978b9d1c75baf1eddbeac0 \
+    --hash=sha256:d5f51900414fc9204a0e0da158ba2ac52b75656e7dce7e77fb9f84bfa343b4cc \
+    --hash=sha256:d71e379452a2f670ccb689ec801b1218cd3983e253105d6e83780967e899d687 \
+    --hash=sha256:d84f0f881cb2225c2dfd7f78a10a5645d487a496c6668d6cc39f0f114164f3d0 \
+    --hash=sha256:decb0eb8a53c3b009b0962378065589685d66b23467ef5dac16cbe818afde27f
+    # via
+    #   contourpy
+    #   matplotlib
+    #   pandas
+packaging==26.0 \
+    --hash=sha256:00243ae351a257117b6a241061796684b084ed1c516a08c48a3f7e147a9d80b4 \
+    --hash=sha256:b36f1fef9334a5588b4166f8bcd26a14e521f2b55e6b9de3aaa80d3ff7a37529
+    # via matplotlib
+pandas==3.0.1 \
+    --hash=sha256:06aff2ad6f0b94a17822cf8b83bbb563b090ed82ff4fe7712db2ce57cd50d9b8 \
+    --hash=sha256:108dd1790337a494aa80e38def654ca3f0968cf4f362c85f44c15e471667102d \
+    --hash=sha256:15860b1fdb1973fffade772fdb931ccf9b2f400a3f5665aef94a00445d7d8dd5 \
+    --hash=sha256:1849f0bba9c8a2fb0f691d492b834cc8dadf617e29015c66e989448d58d011ee \
+    --hash=sha256:1ff8cf1d2896e34343197685f432450ec99a85ba8d90cce2030c5eee2ef98791 \
+    --hash=sha256:331ca75a2f8672c365ae25c0b29e46f5ac0c6551fdace8eec4cd65e4fac271ff \
+    --hash=sha256:3b66857e983208654294bb6477b8a63dee26b37bdd0eb34d010556e91261784f \
+    --hash=sha256:4186a699674af418f655dbd420ed87f50d56b4cd6603784279d9eef6627823c8 \
+    --hash=sha256:44f1364411d5670efa692b146c748f4ed013df91ee91e9bec5677fb1fd58b937 \
+    --hash=sha256:4e1b677accee34a09e0dc2ce5624e4a58a1870ffe56fc021e9caf7f23cd7668f \
+    --hash=sha256:5272627187b5d9c20e55d27caf5f2cd23e286aba25cadf73c8590e432e2b7262 \
+    --hash=sha256:56cf59638bf24dc9bdf2154c81e248b3289f9a09a6d04e63608c159022352749 \
+    --hash=sha256:58eeb1b2e0fb322befcf2bbc9ba0af41e616abadb3d3414a6bc7167f6cbfce32 \
+    --hash=sha256:5ae2ab1f166668b41e770650101e7090824fd34d17915dd9cd479f5c5e0065e9 \
+    --hash=sha256:661e0f665932af88c7877f31da0dc743fe9c8f2524bdffe23d24fdcb67ef9d56 \
+    --hash=sha256:6bf0603c2e30e2cafac32807b06435f28741135cb8697eae8b28c7d492fc7d76 \
+    --hash=sha256:6c426422973973cae1f4a23e51d4ae85974f44871b24844e4f7de752dd877098 \
+    --hash=sha256:75e6e292ff898679e47a2199172593d9f6107fd2dd3617c22c2946e97d5df46e \
+    --hash=sha256:85fe4c4df62e1e20f9db6ebfb88c844b092c22cd5324bdcf94bfa2fc1b391221 \
+    --hash=sha256:93325b0fe372d192965f4cca88d97667f49557398bbf94abdda3bf1b591dbe66 \
+    --hash=sha256:94f87a04984d6b63788327cd9f79dda62b7f9043909d2440ceccf709249ca988 \
+    --hash=sha256:97ca08674e3287c7148f4858b01136f8bdfe7202ad25ad04fec602dd1d29d132 \
+    --hash=sha256:99d0f92ed92d3083d140bf6b97774f9f13863924cf3f52a70711f4e7588f9d0a \
+    --hash=sha256:9fea306c783e28884c29057a1d9baa11a349bbf99538ec1da44c8476563d1b25 \
+    --hash=sha256:a8d37a43c52917427e897cb2e429f67a449327394396a81034a4449b99afda59 \
+    --hash=sha256:a9cabbdcd03f1b6cd254d6dda8ae09b0252524be1592594c00b7895916cb1324 \
+    --hash=sha256:b03f91ae8c10a85c1613102c7bef5229b5379f343030a3ccefeca8a33414cf35 \
+    --hash=sha256:c1a9f55e0f46951874b863d1f3906dcb57df2d9be5c5847ba4dfb55b2c815249 \
+    --hash=sha256:c3d288439e11b5325b02ae6e9cc83e6805a62c40c5a6220bea9beb899c073b1c \
+    --hash=sha256:cd9af1276b5ca9e298bd79a26bda32fa9cc87ed095b2a9a60978d2ca058eaf87 \
+    --hash=sha256:d54855f04f8246ed7b6fc96b05d4871591143c46c0b6f4af874764ed0d2d6f06 \
+    --hash=sha256:eca8b4510f6763f3d37359c2105df03a7a221a508f30e396a51d0713d462e68a
+    # via shotmap-cleaner
+pfzy==0.3.4 \
+    --hash=sha256:5f50d5b2b3207fa72e7ec0ef08372ef652685470974a107d0d4999fc5a903a96 \
+    --hash=sha256:717ea765dd10b63618e7298b2d98efd819e0b30cd5905c9707223dceeb94b3f1
+    # via inquirerpy
+pillow==12.1.1 \
+    --hash=sha256:02f84dfad02693676692746df05b89cf25597560db2857363a208e393429f5e9 \
+    --hash=sha256:0330d233c1a0ead844fc097a7d16c0abff4c12e856c0b325f231820fee1f39da \
+    --hash=sha256:03edcc34d688572014ff223c125a3f77fb08091e4607e7745002fc214070b35f \
+    --hash=sha256:097690ba1f2efdeb165a20469d59d8bb03c55fb6621eb2041a060ae8ea3e9642 \
+    --hash=sha256:18e5bddd742a44b7e6b1e773ab5db102bd7a94c32555ba656e76d319d19c3850 \
+    --hash=sha256:1f1be78ce9466a7ee64bfda57bdba0f7cc499d9794d518b854816c41bf0aa4e9 \
+    --hash=sha256:1f90cff8aa76835cba5769f0b3121a22bd4eb9e6884cfe338216e557a9a548b8 \
+    --hash=sha256:2815a87ab27848db0321fb78c7f0b2c8649dee134b7f2b80c6a45c6831d75ccd \
+    --hash=sha256:2e0c664be47252947d870ac0d327fea7e63985a08794758aa8af5b6cb6ec0c9c \
+    --hash=sha256:344cf1e3dab3be4b1fa08e449323d98a2a3f819ad20f4b22e77a0ede31f0faa1 \
+    --hash=sha256:417423db963cb4be8bac3fc1204fe61610f6abeed1580a7a2cbb2fbda20f12af \
+    --hash=sha256:42fc1f4677106188ad9a55562bbade416f8b55456f522430fadab3cef7cd4e60 \
+    --hash=sha256:44ce27545b6efcf0fdbdceb31c9a5bdea9333e664cda58a7e674bb74608b3986 \
+    --hash=sha256:472a8d7ded663e6162dafdf20015c486a7009483ca671cece7a9279b512fcb13 \
+    --hash=sha256:47b94983da0c642de92ced1702c5b6c292a84bd3a8e1d1702ff923f183594717 \
+    --hash=sha256:4ceb838d4bd9dab43e06c363cab2eebf63846d6a4aeaea283bbdfd8f1a8ed58b \
+    --hash=sha256:50480dcd74fa63b8e78235957d302d98d98d82ccbfac4c7e12108ba9ecbdba15 \
+    --hash=sha256:518a48c2aab7ce596d3bf79d0e275661b846e86e4d0e7dec34712c30fe07f02a \
+    --hash=sha256:559b38da23606e68681337ad74622c4dbba02254fc9cb4488a305dd5975c7eeb \
+    --hash=sha256:5a8eb7ed8d4198bccbd07058416eeec51686b498e784eda166395a23eb99138e \
+    --hash=sha256:5c0dd1636633e7e6a0afe7bf6a51a14992b7f8e60de5789018ebbdfae55b040a \
+    --hash=sha256:5cb1785d97b0c3d1d1a16bc1d710c4a0049daefc4935f3a8f31f827f4d3d2e7f \
+    --hash=sha256:5d8c41325b382c07799a3682c1c258469ea2ff97103c53717b7893862d0c98ce \
+    --hash=sha256:5dae5f21afb91322f2ff791895ddd8889e5e947ff59f71b46041c8ce6db790bc \
+    --hash=sha256:6408a7b064595afcab0a49393a413732a35788f2a5092fdc6266952ed67de586 \
+    --hash=sha256:652a2c9ccfb556235b2b501a3a7cf3742148cd22e04b5625c5fe057ea3e3191f \
+    --hash=sha256:691ab2ac363b8217f7d31b3497108fb1f50faab2f75dfb03284ec2f217e87bf8 \
+    --hash=sha256:6c6db3b84c87d48d0088943bf33440e0c42370b99b1c2a7989216f7b42eede60 \
+    --hash=sha256:7b03048319bfc6170e93bd60728a1af51d3dd7704935feb228c4d4faab35d334 \
+    --hash=sha256:86172b0831b82ce4f7877f280055892b31179e1576aa00d0df3bb1bbf8c3e524 \
+    --hash=sha256:89b54027a766529136a06cfebeecb3a04900397a3590fd252160b888479517bf \
+    --hash=sha256:8b7e5304e34942bf62e15184219a7b5ad4ff7f3bb5cca4d984f37df1a0e1aee2 \
+    --hash=sha256:98edb152429ab62a1818039744d8fbb3ccab98a7c29fc3d5fcef158f3f1f68b7 \
+    --hash=sha256:9ad8fa5937ab05218e2b6a4cff30295ad35afd2f83ac592e68c0d871bb0fdbc4 \
+    --hash=sha256:a003d7422449f6d1e3a34e3dd4110c22148336918ddbfc6a32581cd54b2e0b2b \
+    --hash=sha256:a285e3eb7a5a45a2ff504e31f4a8d1b12ef62e84e5411c6804a42197c1cf586c \
+    --hash=sha256:a37691702ed687799de29a518d63d4682d9016932db66d4e90c345831b02fb4e \
+    --hash=sha256:a550ae29b95c6dc13cf69e2c9dc5747f814c54eeb2e32d683e5e93af56caa029 \
+    --hash=sha256:b574c51cf7d5d62e9be37ba446224b59a2da26dc4c1bb2ecbe936a4fb1a7cb7f \
+    --hash=sha256:b957b71c6b2387610f556a7eb0828afbe40b4a98036fc0d2acfa5a44a0c2036f \
+    --hash=sha256:c7697918b5be27424e9ce568193efd13d925c4481dd364e43f5dff72d33e10f8 \
+    --hash=sha256:cc7d296b5ea4d29e6570dabeaed58d31c3fea35a633a69679fb03d7664f43fb3 \
+    --hash=sha256:d242e8ac078781f1de88bf823d70c1a9b3c7950a44cdf4b7c012e22ccbcd8e4e \
+    --hash=sha256:d2912fd8114fc5545aa3a4b5576512f64c55a03f3ebcca4c10194d593d43ea36 \
+    --hash=sha256:d470ab1178551dd17fdba0fef463359c41aaa613cdcd7ff8373f54be629f9f8f \
+    --hash=sha256:d6e4571eedf43af33d0fc233a382a76e849badbccdf1ac438841308652a08e1f \
+    --hash=sha256:e65498daf4b583091ccbb2556c7000abf0f3349fcd57ef7adc9a84a394ed29f6 \
+    --hash=sha256:e9e8064fb1cc019296958595f6db671fba95209e3ceb0c4734c9baf97de04b20 \
+    --hash=sha256:f7ed2c6543bad5a7d5530eb9e78c53132f93dfa44a28492db88b41cdab885202 \
+    --hash=sha256:f95c00d5d6700b2b890479664a06e754974848afaae5e21beb4d83c106923fd0 \
+    --hash=sha256:fc44ef1f3de4f45b50ccf9136999d71abb99dca7706bc75d222ed350b9fd2289
+    # via matplotlib
+prompt-toolkit==3.0.52 \
+    --hash=sha256:28cde192929c8e7321de85de1ddbe736f1375148b02f2e17edd840042b1be855 \
+    --hash=sha256:9aac639a3bbd33284347de5ad8d68ecc044b91a762dc39b7c21095fcd6a19955
+    # via inquirerpy
+pyparsing==3.3.2 \
+    --hash=sha256:850ba148bd908d7e2411587e247a1e4f0327839c40e2e5e6d05a007ecc69911d \
+    --hash=sha256:c777f4d763f140633dcb6d8a3eda953bf7a214dc4eff598413c070bcdc117cbc
+    # via matplotlib
+python-dateutil==2.9.0.post0 \
+    --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
+    --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
+    # via
+    #   matplotlib
+    #   pandas
+six==1.17.0 \
+    --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
+    --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
+    # via python-dateutil
+tzdata==2025.3 ; sys_platform == 'emscripten' or sys_platform == 'win32' \
+    --hash=sha256:06a47e5700f3081aab02b2e513160914ff0694bce9947d6b76ebd6bf57cfc5d1 \
+    --hash=sha256:de39c2ca5dc7b0344f2eba86f49d614019d29f060fc4ebc8a417896a620b56a7
+    # via pandas
+wcwidth==0.6.0 \
+    --hash=sha256:1a3a1e510b553315f8e146c54764f4fb6264ffad731b3d78088cdb1478ffbdad \
+    --hash=sha256:cdc4e4262d6ef9a1a57e018384cbeb1208d8abbc64176027e2c2455c81313159
+    # via prompt-toolkit
diff --git a/shotmap_cleaner/uv.lock b/shotmap_cleaner/uv.lock
new file mode 100644
index 00000000..aa685a8f
--- /dev/null
+++ b/shotmap_cleaner/uv.lock
@@ -0,0 +1,482 @@
+version = 1
+revision = 2
+requires-python = ">=3.13"
+resolution-markers = [
+    "python_full_version >= '3.14' and sys_platform == 'win32'",
+    "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.14' and sys_platform == 'win32'",
+    "python_full_version < '3.14' and sys_platform == 'emscripten'",
+    "python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+
+[[package]]
+name = "contourpy"
+version = "1.3.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/58/01/1253e6698a07380cd31a736d248a3f2a50a7c88779a1813da27503cadc2a/contourpy-1.3.3.tar.gz", hash = "sha256:083e12155b210502d0bca491432bb04d56dc3432f95a979b429f2848c3dbe880", size = 13466174, upload-time = "2025-07-26T12:03:12.549Z" }
+wheels = [
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