Code formatting

README.rst

@@ -2,11 +2,10 @@
 ecmwf_models
 ============
 
-
 |ci| |cov| |pip| |doc|
 
 .. |ci| image:: https://github.com/TUW-GEO/ecmwf_models/actions/workflows/ci.yml/badge.svg?branch=master
-   :target: https://github.com/ecmwf_models/c3s_sm/actions
+   :target: https://github.com/TUW-GEO/ecmwf_models/actions
 
 .. |cov| image:: https://coveralls.io/repos/TUW-GEO/ecmwf_models/badge.png?branch=master
   :target: https://coveralls.io/r/TUW-GEO/ecmwf_models?branch=master
@@ -18,7 +17,7 @@ ecmwf_models
    :target: https://ecmwf-models.readthedocs.io/en/latest/
 
 
-Readers and converters for data from the `ECMWF reanalysis models
+Readers and converters for `ECMWF reanalysis (ERA) data
 <http://apps.ecmwf.int/datasets/>`_. Written in Python.
 
 Works great in combination with `pytesmo <https://github.com/TUW-GEO/pytesmo>`_.

src/ecmwf_models/era5/download.py

@@ -18,7 +18,9 @@
 from ecmwf_models.utils import (
     lookup,
     update_image_summary_file,
-    default_variables, split_array, check_api_ready,
+    default_variables,
+    split_array,
+    check_api_ready,
 )
 from ecmwf_models.extract import save_ncs_from_nc, save_gribs_from_grib
 
@@ -329,8 +331,7 @@ def download_and_move(
         n_hsteps=len(h_steps),
         max_req_size=n_max_request,
         reduce=True,
-        daily_request=True if stepsize == "day" else False
-    )
+        daily_request=True if stepsize == "day" else False)
 
     logger.info(f"Request is split into {len(req_periods)} chunks")
     logger.info(f"Target directory {target_path}")
@@ -348,8 +349,7 @@ def _download(curr_start, curr_end):
         fname = "{start}_{end}.{ext}".format(
             start=curr_start.strftime("%Y%m%d"),
             end=curr_end.strftime("%Y%m%d"),
-            ext="grb" if grb else "nc"
-        )
+            ext="grb" if grb else "nc")
 
         dl_file = os.path.join(downloaded_data_path, fname)
 
@@ -394,8 +394,7 @@ def _download(curr_start, curr_end):
                     target_path,
                     product_name=product.upper(),
                     keep_original=keep_original,
-                    keep_prelim=keep_prelim
-                )
+                    keep_prelim=keep_prelim)
             else:
                 save_ncs_from_nc(
                     dl_file,
@@ -404,13 +403,10 @@ def _download(curr_start, curr_end):
                     grid=grid,
                     remap_method=remap_method,
                     keep_original=keep_original,
-                    keep_prelim=keep_prelim
-                )
+                    keep_prelim=keep_prelim)
 
         return status_code
 
-
-
     # Since we download month/month or day/day we need to
     # collect all the status codes to return a valid
     # status code for the whole time period
@@ -420,8 +416,8 @@ def _download(curr_start, curr_end):
             'curr_start': [p[0] for p in req_periods],
             'curr_end': [p[1] for p in req_periods]
         },
-        logger_name='cdsapi', loglevel='DEBUG'
-    )
+        logger_name='cdsapi',
+        loglevel='DEBUG')
 
     # remove temporary files
     if not keep_original:
@@ -501,6 +497,9 @@ def download_record_extension(path, dry_run=False, cds_token=None):
               - timedelta(days=1)  # yesterday
 
     return download_and_move(
-        path, startdate=startdate, enddate=enddate,
-        cds_token=cds_token, dry_run=dry_run,
+        path,
+        startdate=startdate,
+        enddate=enddate,
+        cds_token=cds_token,
+        dry_run=dry_run,
         **props['download_settings'])

src/ecmwf_models/era5/reader.py

@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-
 """
 This module contains ERA5/ERA5-Land specific child classes of the netcdf
 and grib base classes, that are used for reading all ecmwf products.

src/ecmwf_models/era5/reshuffle.py

@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-
 """
 Image to time series conversion tools.
 """
@@ -17,6 +16,7 @@
 from ecmwf_models.grid import ERA_RegularImgGrid, ERA5_RegularImgLandGrid
 from ecmwf_models.utils import parse_filetype, parse_product, get_first_last_image_date
 
+
 def extend_ts(ts_path, **img2ts_kwargs):
     """
     Append any new data from the image path to the time series data.
@@ -41,8 +41,7 @@ def extend_ts(ts_path, **img2ts_kwargs):
             "No overview.yml file found in the passed directory. "
             "This file is required to use the same settings to extend an "
             "existing record. NOTE: Use the `era5 download` or "
-            "`era5land download` programs first."
-        )
+            "`era5land download` programs first.")
 
     ts_props = read_summary_yml(ts_path)
 
@@ -59,7 +58,7 @@ def extend_ts(ts_path, **img2ts_kwargs):
                 img2ts_kwargs[k] = v
 
     if 'enddate' not in img2ts_kwargs:
-        img2ts_kwargs['enddate'] = None   # All available images
+        img2ts_kwargs['enddate'] = None  # All available images
 
     img2ts(outputpath=ts_path, **img2ts_kwargs)
 
@@ -136,8 +135,7 @@ def img2ts(
 
     if land_points:
         if product == "era5":
-            grid = ERA5_RegularImgLandGrid(
-                resolution=0.25, bbox=bbox)
+            grid = ERA5_RegularImgLandGrid(resolution=0.25, bbox=bbox)
         elif product == "era5-land":
             grid = ERA5_RegularImgLandGrid(resolution=0.1, bbox=bbox)
         else:
@@ -187,8 +185,11 @@ def img2ts(
     data = input_dataset.read(first_date_time)
     ts_attributes = data.metadata
 
-    props = {'product': product, 'filetype': filetype,
-             'last_update': datetime.now()}
+    props = {
+        'product': product,
+        'filetype': filetype,
+        'last_update': datetime.now()
+    }
 
     kwargs = {
         'input_root': input_root,
@@ -225,4 +226,3 @@ def img2ts(
     reshuffler.calc()
 
     update_ts_summary_file(outputpath, props)
-

src/ecmwf_models/extract.py

@@ -5,25 +5,26 @@
 import xarray as xr
 from datedown.fname_creator import create_dt_fpath
 
+from ecmwf_models.globals import (IMG_FNAME_TEMPLATE,
+                                  IMG_FNAME_DATETIME_FORMAT, EXPVER, SUBDIRS)
 from ecmwf_models.globals import (
-    IMG_FNAME_TEMPLATE,
-    IMG_FNAME_DATETIME_FORMAT,
-    EXPVER, SUBDIRS
-)
-from ecmwf_models.globals import (
-    Cdo, cdo_available, CdoNotFoundError,
-    pygrib, pygrib_available, PygribNotFoundError,
+    Cdo,
+    cdo_available,
+    CdoNotFoundError,
+    pygrib,
+    pygrib_available,
+    PygribNotFoundError,
 )
 
 
 def save_ncs_from_nc(
-        input_nc,
-        output_path,
-        product_name,
-        grid=None,
-        keep_original=True,
-        remap_method="bil",
-        keep_prelim=True,
+    input_nc,
+    output_path,
+    product_name,
+    grid=None,
+    keep_original=True,
+    remap_method="bil",
+    keep_prelim=True,
 ):
     """
     Split the downloaded netcdf file into daily files and add to folder
@@ -48,8 +49,7 @@ def save_ncs_from_nc(
         product="{product}",
         type='AN',
         datetime=IMG_FNAME_DATETIME_FORMAT,
-        ext='nc'
-    )
+        ext='nc')
 
     nc_in = xr.open_dataset(input_nc, mask_and_scale=True)
     if 'valid_time' in nc_in.variables:
@@ -86,8 +86,8 @@ def save_ncs_from_nc(
             continue
 
         if len(ext) > 0:
-            filename_templ = _filename_templ.format(
-                product=product_name + '-' + ext)
+            filename_templ = _filename_templ.format(product=product_name +
+                                                    '-' + ext)
         else:
             filename_templ = _filename_templ.format(product=product_name)
 
@@ -130,11 +130,11 @@ def save_ncs_from_nc(
 
 
 def save_gribs_from_grib(
-        input_grib,
-        output_path,
-        product_name,
-        keep_original=True,
-        keep_prelim=True,
+    input_grib,
+    output_path,
+    product_name,
+    keep_original=True,
+    keep_prelim=True,
 ):
     """
     Split the downloaded grib file into daily files and add to folder structure
@@ -163,8 +163,7 @@ def save_gribs_from_grib(
         product="{product}",
         type='AN',
         datetime=IMG_FNAME_DATETIME_FORMAT,
-        ext='grb'
-    )
+        ext='grb')
 
     grib_in.seek(0)
     prev_date = None
@@ -184,14 +183,13 @@ def save_gribs_from_grib(
             continue
 
         if len(ext) > 0:
-            filename_templ = _filename_templ.format(
-                product=product_name + '-' + ext)
+            filename_templ = _filename_templ.format(product=product_name +
+                                                    '-' + ext)
         else:
             filename_templ = _filename_templ.format(product=product_name)
 
         filepath = create_dt_fpath(
-            filedate, root=output_path, fname=filename_templ,
-            subdirs=SUBDIRS)
+            filedate, root=output_path, fname=filename_templ, subdirs=SUBDIRS)
 
         if not os.path.exists(os.path.dirname(filepath)):
             os.makedirs(os.path.dirname(filepath))

src/ecmwf_models/globals.py

@@ -1,7 +1,6 @@
 import os
 from pathlib import Path
 
-
 IMG_FNAME_TEMPLATE = "{product}_{type}_{datetime}.{ext}"
 IMG_FNAME_DATETIME_FORMAT = "%Y%m%d_%H%M"
 
@@ -33,6 +32,7 @@
 
 
 class PygribNotFoundError(ModuleNotFoundError):
+
     def __init__(self, msg=None):
         _default_msg = ("pygrib could not be imported. "
                         "Pleas run `conda install -c conda-forge pygrib` to "
@@ -41,8 +41,10 @@ def __init__(self, msg=None):
 
 
 class CdoNotFoundError(ModuleNotFoundError):
+
     def __init__(self, msg=None):
-        _default_msg = ("cdo and/or python-cdo not installed. "
-                        "Pleas run `conda install -c conda-forge cdo` and also "
-                        "`pip install cdo`.")
-        self.msg = _default_msg if msg is None else msg
+        _default_msg = (
+            "cdo and/or python-cdo not installed. "
+            "Pleas run `conda install -c conda-forge cdo` and also "
+            "`pip install cdo`.")
+        self.msg = _default_msg if msg is None else msg

src/ecmwf_models/grid.py

@@ -9,6 +9,7 @@
 from typing import Tuple
 import xarray as xr
 
+
 def trafo_lon(lon):
     """
     0...360 -> 0...180...-180
@@ -27,6 +28,7 @@ def trafo_lon(lon):
     lon[lons_gt_180] = lon[lons_gt_180] - 360.0
     return lon
 
+
 def safe_arange(start, stop, step):
     """
     Like numpy.arange, but floating point precision is kept.
@@ -47,10 +49,13 @@ def safe_arange(start, stop, step):
         Range of values in interval at the given step size / sampling
     """
     f_step = (1. / float(step))
-    vals = np.arange(float(start) * f_step, float(stop) * f_step,
-                     float(step) * f_step)
+    vals = np.arange(
+        float(start) * f_step,
+        float(stop) * f_step,
+        float(step) * f_step)
     return vals / f_step
 
+
 def get_grid_resolution(lats: np.ndarray, lons: np.ndarray) -> (float, float):
     """
     try to derive the grid resolution from given coords.
@@ -113,10 +118,9 @@ def ERA5_RegularImgLandGrid(
         ds = ds.assign_coords({'longitude': trafo_lon(ds['longitude'].values)})
         if bbox is not None:
             ds = ds.sel(latitude=slice(bbox[3], bbox[1]))
-            ds = ds.isel(longitude=np.where((
-                    (ds['longitude'].values >= bbox[0]) &
-                    (ds['longitude'].values <= bbox[2])
-            ))[0])
+            ds = ds.isel(
+                longitude=np.where(((ds['longitude'].values >= bbox[0])
+                                    & (ds['longitude'].values <= bbox[2])))[0])
 
         land_mask = np.array(ds.values == 1.0)
 
@@ -167,8 +171,8 @@ def ERA_RegularImgGrid(
     grid = grid.to_cell_grid(cellsize=5.0)
 
     if bbox is not None:
-        subgpis = grid.get_bbox_grid_points(latmin=bbox[1], latmax=bbox[3],
-                                            lonmin=bbox[0], lonmax=bbox[2])
+        subgpis = grid.get_bbox_grid_points(
+            latmin=bbox[1], latmax=bbox[3], lonmin=bbox[0], lonmax=bbox[2])
         grid = grid.subgrid_from_gpis(subgpis)
 
     return grid