Adds `nist_lpbf_scan_tracks.py` file.

README.md

@@ -5,11 +5,9 @@ language:
 tags:
 - NIST
 ---
-# Dataset Card for Dataset Name
+#  NIST LPBF Scan Tracks
 
-<!-- Provide a quick summary of the dataset. -->
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+2 single and 2 multiple lpbf scan tracks on nickel alloy 625.
 
 ## Dataset Details
 
@@ -17,8 +15,6 @@ This dataset card aims to be a base template for new datasets. It has been gener
 
 <!-- Provide a longer summary of what this dataset is. -->
 
-
-
 - **Curated by:** [More Information Needed]
 - **Funded by [optional]:** [More Information Needed]
 - **Shared by [optional]:** [More Information Needed]
@@ -30,7 +26,7 @@ This dataset card aims to be a base template for new datasets. It has been gener
 <!-- Provide the basic links for the dataset. -->
 
 - **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
+- **Paper [optional]:** [Thermographic measurements of single and multiple scan tracks on nickel alloy 625 substrates with and without a powder layer in a commercial laser powder bed fusion process (an additive manufacturing technology)](https://data.nist.gov/od/id/5887178FE62C46F8E0531A57068103631858)
 - **Demo [optional]:** [More Information Needed]
 
 ## Uses

nist_lpbf_scan_tracks.py

@@ -0,0 +1,195 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# TODO: Address all TODOs and remove all explanatory comments
+"""NIST LPBF Scan Tracks"""
+
+import os
+
+import datasets
+
+
+# # TODO: Add BibTeX citation
+# # Find for instance the citation on arxiv or on the dataset repo/website
+# _CITATION = """\
+# @InProceedings{huggingface:dataset,
+# title = {A great new dataset},
+# author={huggingface, Inc.
+# },
+# year={2020}
+# }
+# """
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+Dataset from https://doi.org/10.18434/M3C37Q
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = ""
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = "MIT"
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URLS = {
+    "powder_single_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_1_single_line/radiant_temperature.pkl",
+    "powder_single_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_1_single_line/camera_signal.pkl",
+    "powder_multiple_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_2_pad/radiant_temperature.pkl",
+    "powder_multiple_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_2_pad/camera_signal.pkl",
+    "bare_single_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_6_bare_single_line_195_w_800_mm_s/radiant_temperature.pkl",
+    "bare_single_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_6_bare_single_line_195_w_800_mm_s/camera_signal.pkl",
+    "bare_multiple_track_radiant_temperature": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_7_bare_pad_195_w_800_mm_s/radiant_temperature.pkl",
+    "bare_multiple_track_camera_signal": "https://huggingface.co/datasets/ppak10/NIST-LPBF-Scan-Tracks/resolve/main/data/powder_plate_7_bare_pad_195_w_800_mm_s/camera_signal.pkl",
+}
+
+
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class AMDataset(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version("0.0.1")
+
+    # This is an example of a dataset with multiple configurations.
+    # If you don't want/need to define several sub-sets in your dataset,
+    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+    # If you need to make complex sub-parts in the datasets with configurable options
+    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+    # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="powder_single_track_radiant_temperature",
+            version=VERSION,
+            description="Radiant temperature from single track raster with powder"
+        ),
+        datasets.BuilderConfig(
+            name="powder_single_track_camera_signal",
+            version=VERSION,
+            description="Camera signal from single track raster with powder"
+        ),
+        datasets.BuilderConfig(
+            name="powder_multiple_track_radiant_temperature",
+            version=VERSION,
+            description="Radiant temperature from multiple track raster with powder"
+        ),
+        datasets.BuilderConfig(
+            name="powder_multiple_track_camera_signal",
+            version=VERSION,
+            description="Camera signal from multiple track raster with powder"
+        ),
+        datasets.BuilderConfig(
+            name="bare_single_track_radiant_temperature",
+            version=VERSION,
+            description="Radiant temperature from single track raster without powder"
+        ),
+        datasets.BuilderConfig(
+            name="bare_single_track_camera_signal",
+            version=VERSION,
+            description="Camera signal from single track raster without powder"
+        ),
+        datasets.BuilderConfig(
+            name="bare_multiple_track_radiant_temperature",
+            version=VERSION,
+            description="Radiant temperature from multiple track raster without powder"
+        ),
+        datasets.BuilderConfig(
+            name="bare_multiple_track_camera_signal",
+            version=VERSION,
+            description="Camera signal from multiple track raster without powder"
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "train"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features = datasets.Features({ "i": datasets.Image() }),
+            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
+            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
+            # supervised_keys=("sentence", "label"),
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            # citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        # urls = _URLS[self.config.name]
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    # "filepath": os.path.join(data_dir, "train.jsonl"),
+                    # "split": "train",
+                    "files": downloaded_files
+                },
+            ),
+            # datasets.SplitGenerator(
+            #     name=datasets.Split.VALIDATION,
+            #     # These kwargs will be passed to _generate_examples
+            #     # gen_kwargs={
+            #         # "filepath": os.path.join(data_dir, "dev.jsonl"),
+            #         # "split": "dev",
+            #     # },
+            # ),
+            # datasets.SplitGenerator(
+            #     name=datasets.Split.TEST,
+            #     # These kwargs will be passed to _generate_examples
+            #     # gen_kwargs={
+            #         # "filepath": os.path.join(data_dir, "test.jsonl"),
+            #         # "split": "test"
+            #     # },
+            # ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    # def _generate_examples(self, filepath, split):
+    #     # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+    #     # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+    #     with open(filepath, encoding="utf-8") as f:
+    #         for key, row in enumerate(f):
+    #             data = json.loads(row)
+    #             if self.config.name == "raw":
+    #                 # Yields examples as (key, example) tuples
+    #                 yield key, {
+    #                     "sentence": data["sentence"],
+    #                     "option1": data["option1"],
+    #                     "answer": "" if split == "test" else data["answer"],
+    #                 }
+    #             else:
+    #                 yield key, {
+    #                     "sentence": data["sentence"],
+    #                     "option2": data["option2"],
+    #                     "second_domain_answer": "" if split == "test" else data["second_domain_answer"],
+    #                 }