Change any CRLF to LF

equinor · Mar 1, 2021 · 74573c4 · 74573c4
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commit 74573c4
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diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -41,21 +41,21 @@ commands:
       - run:
           name: Install Python dependencies
           command: |
-            if [ `uname -s` == "Darwin" ]; then 
+            if [ `uname -s` == "Darwin" ]; then
               . py_venv/bin/activate
             fi
             python3 --version
             python3 -m pip install -r requirements.txt
             python3 -m pip install -r requirements-dev.txt
-            python3 -m pip install cmake flake8 bandit setuptools-scm 
+            python3 -m pip install cmake flake8 bandit setuptools-scm
             python3 -m pip install coverage codacy-coverage
 
   python-build-test:
     steps:
       - run:
           name: Build & test python
           command: |
-            if [ `uname -s` == "Darwin" ]; then 
+            if [ `uname -s` == "Darwin" ]; then
               . py_venv/bin/activate
             fi
             python3 setup.py build_ext --inplace
@@ -87,7 +87,7 @@ commands:
       - run:
           name: Codacy code coverage check
           command: |
-            if [ ! -z "${CODACY_PROJECT_TOKEN}" ]; then 
+            if [ ! -z "${CODACY_PROJECT_TOKEN}" ]; then
               coverage run setup.py test;
               coverage xml;
               python-codacy-coverage -r coverage.xml;
@@ -153,7 +153,7 @@ jobs:
           python-version: << parameters.python-version >>
       - install-python-deps
       - python-build-test
-  
+
   sdist-deploy:
     docker:
       - image: "circleci/python:3.6"
@@ -239,7 +239,7 @@ workflows:
               only: /[0-9]+(\.[0-9]+)*/
             branches:
               ignore: /.*/
-  
+
   macos-deploy:
     jobs:
       - wheels-macos-deploy:

diff --git a/camille/output/__init__.py b/camille/output/__init__.py
@@ -1,20 +1,20 @@
-"""\
-Outputs
-==========
-This module is a collection of functions producing outputs.
-
-Notes
------
-Used data formats might be too specific, so currently module is mainly
-intended for internal use
-
-Available functions
---------------------
-* :func:`~camille.output.bazefetcher`
-"""
-
-from .bazefetcher import Bazefetcher
-
-__all__ = [
-    'bazefetcher'
-]
+"""\
+Outputs
+==========
+This module is a collection of functions producing outputs.
+
+Notes
+-----
+Used data formats might be too specific, so currently module is mainly
+intended for internal use
+
+Available functions
+--------------------
+* :func:`~camille.output.bazefetcher`
+"""
+
+from .bazefetcher import Bazefetcher
+
+__all__ = [
+    'bazefetcher'
+]
diff --git a/camille/source/__init__.py b/camille/source/__init__.py
@@ -1,27 +1,27 @@
-"""\
-Sources
-==========
-This module is a collection of functions reading inputs.
-
-Notes
------
-Used data formats might be too specific, so currently module is mainly
-intended for internal use
-
-Available functions
--------------------
-* :func:`~camille.source.bazefetcher`
-* :func:`~camille.source.windiris`
-"""
-
-
-from .bazefetcher import Bazefetcher, TagNotFoundError
-from .windiris import windiris
-from .zephyre import Zephyre
-
-
-__all__ = [
-    'Bazefetcher',
-    'windiris',
-    'Zephyre',
-]
+"""\
+Sources
+==========
+This module is a collection of functions reading inputs.
+
+Notes
+-----
+Used data formats might be too specific, so currently module is mainly
+intended for internal use
+
+Available functions
+-------------------
+* :func:`~camille.source.bazefetcher`
+* :func:`~camille.source.windiris`
+"""
+
+
+from .bazefetcher import Bazefetcher, TagNotFoundError
+from .windiris import windiris
+from .zephyre import Zephyre
+
+
+__all__ = [
+    'Bazefetcher',
+    'windiris',
+    'Zephyre',
+]
diff --git a/tests/test_data/synthetic_windiris_generator.py b/tests/test_data/synthetic_windiris_generator.py
@@ -1,62 +1,62 @@
-#!/usr/bin/env python
-"""
-Simple program to create synthetic windiris data
-"""
-
-from datetime import datetime
-from itertools import cycle
-from pytz import utc
-from noise import pnoise2
-import os
-import pandas as pd
-
-
-def perlin(x, y, yoffset, xscale=0.01, yscale=0.133):
-    return pnoise2(x * xscale, y * yscale + yoffset)
-
-
-def main():
-    root = 'windiris'
-    start_date = datetime(2030, 1, 1, tzinfo=utc)
-    end_date = datetime(2030, 1, 4, tzinfo=utc)
-
-    times = pd.date_range(start_date, end_date, freq='S', tz=utc).repeat(10)
-    distances = cycle(
-        [50.0, 80.0, 120.0, 160.0, 200.0, 240.0, 280.0, 320.0, 360.0, 400.0])
-    los_ids = cycle(pd.Series([0, 1, 2, 3]).repeat(10))
-    rowc = len(times)
-
-    tilt = pd.Series([perlin(x, 10, 0) for x in range(rowc // 10)]).repeat(10)
-    roll = pd.Series([perlin(x, 11, 0) for x in range(rowc // 10)]).repeat(10)
-    tilt = tilt + 1
-    roll = roll + 1
-
-    rws = pd.Series([perlin(x, y, 0) for x in range(rowc // 10) for y in range(10)])
-    rws = (rws + 1) * 5
-
-
-    df = pd.DataFrame({
-        'LOS index': [next(los_ids) for _ in range(rowc)],
-        'Distance': [next(distances) for _ in range(rowc)],
-        'RWS': rws.values,
-        'DRWS': 0,
-        'CNR': 0,
-        'Tilt': tilt.values,
-        'Roll': roll.values,
-        'RWS Status': 1,
-        'Overrun Status': 1,
-    }, index=times)
-
-    for d in df.groupby(df.index.date):
-        date = d[0]
-        dfd = d[1].copy()
-        dfd.insert(0, 'Timestamp',
-            dfd.index.map(lambda a: a.strftime('%Y-%m-%d %H:%M:%S.%f')))
-
-        fname = os.path.join(root, date.strftime('WI_%Y-%m-%d.csv'))
-        os.makedirs(root, exist_ok=True)
-        dfd.to_csv(fname, index=False, sep=';')
-
-
-if __name__ == '__main__':
-    main()
+#!/usr/bin/env python
+"""
+Simple program to create synthetic windiris data
+"""
+
+from datetime import datetime
+from itertools import cycle
+from pytz import utc
+from noise import pnoise2
+import os
+import pandas as pd
+
+
+def perlin(x, y, yoffset, xscale=0.01, yscale=0.133):
+    return pnoise2(x * xscale, y * yscale + yoffset)
+
+
+def main():
+    root = 'windiris'
+    start_date = datetime(2030, 1, 1, tzinfo=utc)
+    end_date = datetime(2030, 1, 4, tzinfo=utc)
+
+    times = pd.date_range(start_date, end_date, freq='S', tz=utc).repeat(10)
+    distances = cycle(
+        [50.0, 80.0, 120.0, 160.0, 200.0, 240.0, 280.0, 320.0, 360.0, 400.0])
+    los_ids = cycle(pd.Series([0, 1, 2, 3]).repeat(10))
+    rowc = len(times)
+
+    tilt = pd.Series([perlin(x, 10, 0) for x in range(rowc // 10)]).repeat(10)
+    roll = pd.Series([perlin(x, 11, 0) for x in range(rowc // 10)]).repeat(10)
+    tilt = tilt + 1
+    roll = roll + 1
+
+    rws = pd.Series([perlin(x, y, 0) for x in range(rowc // 10) for y in range(10)])
+    rws = (rws + 1) * 5
+
+
+    df = pd.DataFrame({
+        'LOS index': [next(los_ids) for _ in range(rowc)],
+        'Distance': [next(distances) for _ in range(rowc)],
+        'RWS': rws.values,
+        'DRWS': 0,
+        'CNR': 0,
+        'Tilt': tilt.values,
+        'Roll': roll.values,
+        'RWS Status': 1,
+        'Overrun Status': 1,
+    }, index=times)
+
+    for d in df.groupby(df.index.date):
+        date = d[0]
+        dfd = d[1].copy()
+        dfd.insert(0, 'Timestamp',
+            dfd.index.map(lambda a: a.strftime('%Y-%m-%d %H:%M:%S.%f')))
+
+        fname = os.path.join(root, date.strftime('WI_%Y-%m-%d.csv'))
+        os.makedirs(root, exist_ok=True)
+        dfd.to_csv(fname, index=False, sep=';')
+
+
+if __name__ == '__main__':
+    main()