Merge pull request #76 from nsidc/nsidc-iceflow

Consistently use `nsidc-iceflow` instead of `iceflow`

Author: trey-stafford

CHANGELOG.md

@@ -19,15 +19,15 @@
 - Update `transform_itrf` function to be more flexible. Both forward and reverse
   transformations between proj-supported ITRFs are now supported, which means
   that more ITRF-to-ITRF transformations are handled.
-- Update `icepyx` dependency to >=2.0.0 for the "Using iceflow with icepyx to
-  Generate an Elevation Timeseries" notebook.
+- Update `icepyx` dependency to >=2.0.0 for the "Using nsidc-iceflow with icepyx
+  to Generate an Elevation Timeseries" notebook.
 - Filter for cloud-hosted data, avoiding duplicate granule results from
   `fetch.find_iceflow_data`
 - Pass through search kwargs to `earthaccess` without any type validation. This
   allows earthaccess to do watever validation it needs to, and then it passes
   those on to CMR. This provides much greater flexibility over data search and
   makes the interface more consistent with `icepyx` and `earthaccess`.
-  https://github.com/nsidc/iceflow/issues/51.
+  https://github.com/nsidc/nsidc-iceflow/issues/51.
 - Remove restrictive `fetch_iceflow_df` function from public API. Users should
   utilize the search, download, and read functions described in
   `doc/getting-started.md` instead.
@@ -42,7 +42,7 @@
 - Add support for ILVIS2 v1 and v2.
 - Improve API, providing ability to search across datasets and save to
   intermediate parquet file.
-- Add jupyter notebook showing use of `iceflow` alongside `icepyx`
+- Add jupyter notebook showing use of `nsidc-iceflow` alongside `icepyx`
 
 # v0.2.0
 

README.md

@@ -2,13 +2,13 @@
   <img alt="NSIDC logo" src="https://nsidc.org/themes/custom/nsidc/logo.svg" width="150" />
 </p>
 
-# Iceflow Python Library
+# `nsidc-iceflow` Python Library
 
-`iceflow` is a Python library that provides the ability to search, download, and
-access laser altimetry data from (pre-)Operation IceBridge and ICESat/GLAS
-datasets. The library also supports International Terrestrial Reference Frame
-(ITRF) transformations to facilitate comparisons across datasets. `iceflow`
-supports the following datasets:
+`nsidc-iceflow` is a Python library that provides the ability to search,
+download, and access laser altimetry data from (pre-)Operation IceBridge and
+ICESat/GLAS datasets. The library also supports International Terrestrial
+Reference Frame (ITRF) transformations to facilitate comparisons across
+datasets. `nsidc-iceflow` supports the following datasets:
 
 | Dataset                                                  | Temporal Coverage             |
 | -------------------------------------------------------- | ----------------------------- |
@@ -26,12 +26,12 @@ submissions and pull requests in order to foster community contribution. We will
 strive to respond to contributions in a timely manner, but make no guarantees.
 
 If you discover any problems or bugs, please submit an
-[Issue](https://github.com/nsidc/iceflow/issues/new).
+[Issue](https://github.com/nsidc/nsidc-iceflow/issues/new).
 
 If you would like to contribute to this repository, you may fork the repository
 and submit a pull request. See our
 [contributing documentation](https://iceflow.readthedocs.io/en/latest/contributing.html)
-for more information about how to contribute to `iceflow`.
+for more information about how to contribute to `nsidc-iceflow`.
 
 See the [LICENSE](./LICENSE) for details on permissions and warranties. Please
 contact [email protected] for more information.
@@ -49,11 +49,11 @@ contact [email protected] for more information.
 pip install nsidc-iceflow
 ```
 
-### Using `iceflow`
+### Using `nsidc-iceflow`
 
 See
-[Getting started with iceflow](https://iceflow.readthedocs.io/en/latest/getting-started.html)
-for information and examples about how to use `iceflow`.
+[Getting started with `nsidc-iceflow`](https://iceflow.readthedocs.io/en/latest/getting-started.html)
+for information and examples about how to use `nsidc-iceflow`.
 
 ## Credit
 

docs/altimetry-data-overview.md

@@ -91,7 +91,7 @@ pulses are used to determine elevation data.
 ```{note}
 
 We recommend using the [_icepyx_](https://github.com/icesat2py/icepyx)
-library to access and interact with ICESat-2 data. Learn more about using `icepyx` with `iceflow` in the [Using iceflow with icepyx to Generate an Elevation Timeseries](notebooks/iceflow-with-icepyx) Jupyter notebook.
+library to access and interact with ICESat-2 data. Learn more about using `icepyx` with `nsidc-iceflow` in the [Using nsidc-iceflow with icepyx to Generate an Elevation Timeseries](notebooks/iceflow-with-icepyx) Jupyter notebook.
 
 ```
 
@@ -148,7 +148,7 @@ ILVIS V2 data:
 
 - `TLAT`/`TLON`/`ZT`, which represent the highest detected signal.
 
-By default, `iceflow` will use `GLAT`/`GLON`/`GZ` as the primary
+By default, `nsidc-iceflow` will use `GLAT`/`GLON`/`GZ` as the primary
 latitude/longitude/elevation fields in `IceflowDataFrame`s. Use the
 `ilvis2_coordinate_set` kwarg on `read_iceflow_datafile(s)` or
 `make_iceflow_parquet` to select an different primary set of
@@ -182,14 +182,14 @@ these missions presents several challenges:
   and longitude is the same. These changes in geolocation need to be reconciled
   to allow meaningful comparisons within the long-term data record.
 
-The `iceflow` Python library addresses these concerns by providing the ability
-to search, download, and access laser altimetry data from (pre-)Operation
-IceBridge and ICESat/GLAS datasets. The library also supports International
-Terrestrial Reference Frame (ITRF) transformations to facilitate comparisons
-across datasets.
+The `nsidc-iceflow` Python library addresses these concerns by providing the
+ability to search, download, and access laser altimetry data from
+(pre-)Operation IceBridge and ICESat/GLAS datasets. The library also supports
+International Terrestrial Reference Frame (ITRF) transformations to facilitate
+comparisons across datasets.
 
 Companion Jupyter notebooks give additional information and contain example code
-about `iceflow`.
+about `nsidc-iceflow`.
 
 [NSIDC Iceflow example](./notebooks/iceflow-example) provides an example of how
 to search for, download, and interact with `ILATM1B v1` data for a small area of
@@ -199,13 +199,13 @@ datasets. To learn more about ITRF transformations, see the
 [Applying Coordinate Transformations to Facilitate Data Comparison](./notebooks/corrections)
 notebook.
 
-[Using iceflow with icepyx to Generate an Elevation Timeseries](./notebooks/iceflow-with-icepyx)
+[Using nsidc-iceflow with icepyx to Generate an Elevation Timeseries](./notebooks/iceflow-with-icepyx)
 shows how to search for, download, and interact with a large amount of data
-across many datasets supported by `iceflow`. It also illustrates how to utilize
-[icepyx](https://icepyx.readthedocs.io/en/latest/) to find and access ICESat-2
-data. Finally, the notebook provides a simple time-series analysis for elevation
-change over an area of interest across `iceflow` supported datasets and
-ICESat-2.
+across many datasets supported by `nsidc-iceflow`. It also illustrates how to
+utilize [icepyx](https://icepyx.readthedocs.io/en/latest/) to find and access
+ICESat-2 data. Finally, the notebook provides a simple time-series analysis for
+elevation change over an area of interest across `nsidc-iceflow` supported
+datasets and ICESat-2.
 
 ## References
 
@@ -227,4 +227,4 @@ ICESat-2.
 With the knowledge gained from reading this page, users should be prepared for
 the [NSIDC Iceflow example](./notebooks/iceflow-example) notebook, which
 provides an example of how to search for, download, and interact with
-`ILATM1B v1` data for a small area of interest with the `iceflow` library.
+`ILATM1B v1` data for a small area of interest with the `nsidc-iceflow` library.

docs/conf.py

@@ -35,7 +35,7 @@
     "footer_icons": [
         {
             "name": "GitHub",
-            "url": "https://github.com/NSIDC/iceflow",
+            "url": "https://github.com/NSIDC/nsidc-iceflow",
             "html": """
                 <svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 16 16">
                     <path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.013 8.013 0 0 0 16 8c0-4.42-3.58-8-8-8z"></path>
@@ -44,7 +44,7 @@
             "class": "",
         },
     ],
-    "source_repository": "https://github.com/NSIDC/iceflow",
+    "source_repository": "https://github.com/NSIDC/nsidc-iceflow",
     "source_branch": "main",
     "source_directory": "docs/",
 }

docs/contributing.md

@@ -44,7 +44,7 @@ Available tasks:
 
 ## Jupyter Notebooks
 
-There are Jupyter Notebooks showing `iceflow` functionality under
+There are Jupyter Notebooks showing `nsidc-iceflow` functionality under
 `docs/notebooks/`.
 
 To get started with developing existing or new notebooks, first install the

docs/getting-started.md

@@ -1,26 +1,27 @@
-# Getting started with iceflow
+# Getting started with `nsidc-iceflow`
 
 ## Altimetry Overview
 
-Before working with `iceflow` directly, it may be helpful to understand the
-basics about pre-IceBridge, IceBridge, ICESat/GLAS and ICESat-2 datasets. Learn
-about these `iceflow` supported datasets in
+Before working with `nsidc-iceflow` directly, it may be helpful to understand
+the basics about pre-IceBridge, IceBridge, ICESat/GLAS and ICESat-2 datasets.
+Learn about these `nsidc-iceflow` supported datasets in
 [Altimetry Data at the NSIDC DAAC: Point Cloud Data Overview](./altimetry-data-overview)
 
 ## Jupyter Notebooks
 
-Executable Jupyter Notebooks provide a great starting point for using `iceflow`.
-See [Jupyter Notebooks](./notebooks/index.md) for more information.
+Executable Jupyter Notebooks provide a great starting point for using
+`nsidc-iceflow`. See [Jupyter Notebooks](./notebooks/index.md) for more
+information.
 
 ## API overview
 
-`iceflow` provides a simple API for finding, downloading, and accessing
+`nsidc-iceflow` provides a simple API for finding, downloading, and accessing
 iceflow-supported datasets.
 
 ### Finding data
 
-To find `iceflow`-supported data for an area of interest and timeframe, use
-[`find_iceflow_data`](nsidc.iceflow.find_iceflow_data):
+To find `nsidc-iceflow`-supported data for an area of interest and timeframe,
+use [`find_iceflow_data`](nsidc.iceflow.find_iceflow_data):
 
 ```
 import datetime as dt
@@ -54,7 +55,7 @@ search_results = find_iceflow_data(
 
 ```
 
-`iceflow` currently supports the following datasets:
+`nsidc-iceflow` currently supports the following datasets:
 
 | Dataset                                                  | Temporal Coverage             |
 | -------------------------------------------------------- | ----------------------------- |
@@ -139,7 +140,7 @@ crash if physical memory limits are exceeded.
 
 Users of ILVIS2 data should be aware that ILVIS2 data contains multiple sets of
 lat/lon/elev that may be of interest. By default, the `low_mode` set is used as
-the primary set of latitude/longitude/elevation used by `iceflow`.
+the primary set of latitude/longitude/elevation used by `nsidc-iceflow`.
 
 See [ILVIS2 data](./altimetry-data-overview.md#ilvis2-data) for more
 information.

docs/index.md

@@ -1,4 +1,4 @@
-# iceflow
+# `nsidc-iceflow`
 
 ```{toctree}
 :maxdepth: 2

docs/notebooks/iceflow-example.ipynb

@@ -5,7 +5,7 @@
    "id": "7174387c-05aa-4f8f-b3bd-902d4f635d9b",
    "metadata": {},
    "source": [
-    "# NSIDC Iceflow example\n",
+    "# `nsidc-iceflow` example\n",
     "\n",
     "This notebook shows an example of how to use the `nsidc-iceflow` Python library to do ITRF transformations with real data. We recommend starting with the [Applying Coordinate Transformations to Facilitate Data Comparison](./corrections) notebook to learn more about ITRF transformations and why they matter.\n",
     "\n",
@@ -15,7 +15,7 @@
     "\n",
     "Finding, downloading, and reading ILATM1B v1 data with `nsidc-iceflow` is straightforward. ILATM1B data can be very large, so for the purposes of this example we will focus on just a small area near Pine Island Glacier along with a short date range in order to fetch a manageable amount of data.\n",
     "\n",
-    "To learn about how to download and manage larger amounts of data across many datasets with `nsidc-iceflow`, see the [Using iceflow with icepyx to Generate an Elevation Timeseries](./iceflow-with-icepyx) notebook."
+    "To learn about how to download and manage larger amounts of data across many datasets with `nsidc-iceflow`, see the [Using nsidc-iceflow with icepyx to Generate an Elevation Timeseries](./iceflow-with-icepyx) notebook."
    ]
   },
   {