Lint (#1)

* lint 1

* lint 2

* lint 3

* Create LICENSE

* Add License to README.md

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 Morten Kretschmer
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -42,3 +42,7 @@ python3 main.py Sounding
 ## Datasource
 - ICON Nest: https://opendata.dwd.de/weather/nwp/icon-eu/
 - IFS: https://www.ecmwf.int/en/forecasts/datasets/open-data
+
+## License
+
+This project is licensed under the terms of the MIT license. See the [LICENSE](LICENSE) file for details.

src/creategridinfo.py

@@ -3,23 +3,29 @@
 
 import numpy as np
 
-path_icon='./'
+path_icon = './'
 
 if (os.getcwd() != path_icon):
     os.chdir(path_icon)
 
+
 def creategridinfo(d_grad=0.0625, filename="gitter_icon"):
     lonmin = -23.5
-    lonmax =  45.0
-    latmin =  29.5
-    latmax =  70.5
-    xsize=np.size(np.arange(lonmin, lonmax+d_grad, d_grad))
-    ysize=np.size(np.arange(latmin, latmax+d_grad, d_grad))
-    test_string='#\n# gridID 1\n#\ngridtype  = lonlat\ngridsize  = %d\nxname     = lon\nxlongname = longitude\nxunits    = degrees_east\nyname     = lat\nylongname = latitude\nyunits    = degrees_north\nxsize     = %d\nysize     = %d\nxfirst    = -23.5\nxinc      = %.1f\nyfirst    = 29.5\nyinc      = %.1f' %(xsize*ysize, xsize, ysize, d_grad, d_grad)
-    fd = open(filename, "x") 
+    lonmax = 45.0
+    latmin = 29.5
+    latmax = 70.5
+    xsize = np.size(np.arange(lonmin, lonmax+d_grad, d_grad))
+    ysize = np.size(np.arange(latmin, latmax+d_grad, d_grad))
+    test_string = (f"#\n# gridID 1\n#\ngridtype  = lonlat\ngridsize  = {xsize*ysize}\nxname     = lon\nxlongname = longitude"
+                   f"\nxunits    = degrees_east\nyname     = lat\nylongname = latitude\nyunits    = degrees_north"
+                   f"\nxsize     = {xsize}\nysize     = {ysize}\nxfirst    = -23.5\nxinc      = {d_grad}\n"
+                   f"yfirst    = 29.5\nyinc      = {d_grad}"
+                   )
+    fd = open(filename, "x")
     fd.write(test_string)
     fd.close()
 
+
 creategridinfo()
 creategridinfo(d_grad=0.12, filename="gitter_icon1.2")
 creategridinfo(d_grad=0.2, filename="gitter_icon2")

src/main.py

@@ -12,73 +12,22 @@
 import plotlib
 import modelinfolib as model
 model = model.icon_nest
-# ---------------------------------------------------------------------------------------------------------------------
-
-def main():
-    config = ut.load_yaml('config.yml')
-
-    # command line arguments
-    parser = argparse.ArgumentParser(description="Hodograph Maps")
-    # Add positional argument
-    parser.add_argument('mode', type=str, 
-                        help='Mode: Test, Basic, Sounding, or Nixon')
-
-    # Add optional argument
-    parser.add_argument('-f', '--field', type=str, 
-                        help='Which background field: CAPE ML, CAPE CON or LPI ')
-
-    parser.add_argument('-d', '--date', type=str, 
-                        help='Date Format YYYY-MM-DD')
-
-    parser.add_argument('-fp', '--fp', type=str, 
-                        help='Leadtime or forecast periode')
-
-    parser.add_argument('-r', '--run', type=str, 
-                        help='Run (0,6,12,18,.. .etc)')
-
-    # Parse the command line arguments
-    args = parser.parse_args()
-
-    if args.field == None:
-        args.field = "CAPE ML"
-
-    if (args.field != "CAPE ML") and (args.field != "CAPE CON") and (args.field != "LPI") and (args.field != "WMAXSHEAR"):
-        print("Unknown field")
-        exit(-1)
-
-    if args.date == None:
-        rundate = datetime.strptime(config["default_date"], "%Y-%m-%d")
-    else:
-        rundate = datetime.strptime(args.date, "%Y-%m-%d")
-
-    if args.fp == None:
-        fp = config["fp"]
-    else:
-        fp = args.fp
-
-    if args.run == None:
-        run = config["run"]
-    else:
-        run = args.run
-
-    # replace space with underscores
-    fieldname = args.field.replace(" ", "_")
 
+# ---------------------------------------------------------------------------------------------------------------------
 
-    print(f"\nDate: {rundate}\n Arguments: {args} \nConfig-File: {config}\n\n")
 
-    #ut.download_nwp(fieldname, datum="20240227", run="00", fp=0, store_path="./")
+def run(program_mode, fieldname, rundate, model_run, fp):
+    config = ut.load_yaml('config.yml')
 
-
-    if args.mode == "Test":
-        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, run, fp, path="./iconnest/")
+    if program_mode == "Test":
+        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, model_run, fp, path="./iconnest/")
         assert cape_fld.shape == (model.getnlat, model.getnlon), "Shape inconsistency"
-        plotlib.test_plot (cape_fld, lats, lons, fp, run, titel='CAPE')
+        plotlib.test_plot(cape_fld, lats, lons, fp, model_run, titel='CAPE')
 
-    elif args.mode == "Sounding":
-        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, run, fp, path="./iconnest/")
+    elif program_mode == "Sounding":
+        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, model_run, fp, path="./iconnest/")
 
-        steps=config["steps"]
+        steps = config["steps"]
         nlvl = int(model.getnlev()/steps)
         t_fld = np.empty(nlvl*model.getpoints()).reshape((nlvl, model.getnlat(), model.getnlon()))
         t_fld.fill(np.nan)
@@ -95,20 +44,20 @@ def main():
 
         lvl_idx = 0
         for level in range(config["levels"][0], config["levels"][1], steps):
-            t_fld[lvl_idx,:,:] = ut.open_gribfile_multi("T", level, rundate, run, fp, path="./iconnest/")
-            q_fld[lvl_idx,:,:] = ut.open_gribfile_multi("QV", level, rundate, run, fp, path="./iconnest/")
-            p_fld[lvl_idx,:,:] = ut.open_gribfile_multi("P", level, rundate, run, fp, path="./iconnest/")
+            t_fld[lvl_idx, :, :] = ut.open_gribfile_multi("T", level, rundate, model_run, fp, path="./iconnest/")
+            q_fld[lvl_idx, :, :] = ut.open_gribfile_multi("QV", level, rundate, model_run, fp, path="./iconnest/")
+            p_fld[lvl_idx, :, :] = ut.open_gribfile_multi("P", level, rundate, model_run, fp, path="./iconnest/")
 
             lvl_idx += 1
             if lvl_idx >= nlvl:
                 break
 
-        print(np.nanmean(t_fld, axis=(1,2))-273.15)
-        plotlib.sounding_plot (cape_fld, t_fld, q_fld, p_fld, lats, lons, fp, run, titel='CAPE')
-    elif args.mode == "Basic":
-        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, run, fp, path="./iconnest/")
+        print(np.nanmean(t_fld, axis=(1, 2))-273.15)
+        plotlib.sounding_plot(cape_fld, t_fld, q_fld, p_fld, lats, lons, fp, model_run, titel='CAPE')
+    elif program_mode == "Basic":
+        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, model_run, fp, path="./iconnest/")
 
-        steps=config["steps"]
+        steps = config["steps"]
         nlvl = int(model.getnlev()/steps)
         u_fld = np.empty(nlvl*model.getpoints()).reshape((nlvl, model.getnlat(), model.getnlon()))
         u_fld.fill(np.nan)
@@ -123,20 +72,22 @@ def main():
 
         lvl_idx = 0
         for level in range(config["levels"][0], config["levels"][1], steps):
-            u_fld[lvl_idx,:,:] = ut.open_gribfile_multi("U", level, rundate, run, fp, path="./iconnest/")
-            v_fld[lvl_idx,:,:] = ut.open_gribfile_multi("V", level, rundate, run, fp, path="./iconnest/")
+            u_fld[lvl_idx, :, :] = ut.open_gribfile_multi("U", level, rundate, model_run, fp, path="./iconnest/")
+            v_fld[lvl_idx, :, :] = ut.open_gribfile_multi("V", level, rundate, model_run, fp, path="./iconnest/")
 
             lvl_idx += 1
             if lvl_idx >= nlvl:
                 break
-
-        print(np.nanmean(u_fld, axis=(1,2)))
-        plotlib.basic_plot (cape_fld, u_fld, v_fld, lats, lons, fp, run, titel='CAPE', threshold=config["threshold"])
-        plotlib.basic_plot_custarea (cape_fld, u_fld, v_fld, lats, lons, fp, run, titel='CAPE', threshold=config["threshold"])
-    elif args.mode == "Nixon":
-        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, run, fp, path="./iconnest/")
-
-        steps=config["steps"]
+
+        print(np.nanmean(u_fld, axis=(1, 2)))
+        plotlib.basic_plot(cape_fld, u_fld, v_fld, lats, lons, fp, model_run,
+                           titel='CAPE', threshold=config["threshold"])
+        plotlib.basic_plot_custarea(cape_fld, u_fld, v_fld, lats, lons, fp, model_run,
+                                    titel='CAPE', threshold=config["threshold"])
+    elif program_mode == "Nixon":
+        cape_fld, lats, lons = ut.open_gribfile_single(fieldname, rundate, model_run, fp, path="./iconnest/")
+
+        steps = config["steps"]
         nlvl = int(model.getnlev()/steps)
         u_fld = np.empty(nlvl*model.getpoints()).reshape((nlvl, model.getnlat(), model.getnlon()))
         u_fld.fill(np.nan)
@@ -155,26 +106,90 @@ def main():
 
         lvl_idx = 0
         for level in range(config["levels"][0], config["levels"][1], steps):
-            u_fld[lvl_idx,:,:] = ut.open_gribfile_multi("U", level, rundate, run, fp, path="./iconnest/")
-            v_fld[lvl_idx,:,:] = ut.open_gribfile_multi("V", level, rundate, run, fp, path="./iconnest/")
-            h_fld[lvl_idx,:,:] = ut.open_gribfile_multi("H", level, rundate, run, fp, path="./iconnest/")
-            p_fld[lvl_idx,:,:] = ut.open_gribfile_multi("P", level, rundate, run, fp, path="./iconnest/")
+            u_fld[lvl_idx, :, :] = ut.open_gribfile_multi("U", level, rundate, model_run, fp, path="./iconnest/")
+            v_fld[lvl_idx, :, :] = ut.open_gribfile_multi("V", level, rundate, model_run, fp, path="./iconnest/")
+            h_fld[lvl_idx, :, :] = ut.open_gribfile_multi("H", level, rundate, model_run, fp, path="./iconnest/")
+            p_fld[lvl_idx, :, :] = ut.open_gribfile_multi("P", level, rundate, model_run, fp, path="./iconnest/")
 
             lvl_idx += 1
             if lvl_idx >= nlvl:
                 break
 
-        print(np.nanmean(p_fld, axis=(1,2)))
+        print(np.nanmean(p_fld, axis=(1, 2)))
 
-        du = np.subtract(u_fld[30,:,:], u_fld[0,:,:])
-        dv = np.subtract(v_fld[30,:,:], v_fld[0,:,:])
+        du = np.subtract(u_fld[30, :, :], u_fld[0, :, :])
+        dv = np.subtract(v_fld[30, :, :], v_fld[0, :, :])
         dls_fld = np.sqrt(np.add(np.square(du), np.square(dv)))
-        plotlib.nixon_proj(cape_fld, dls_fld, u_fld, v_fld, p_fld, h_fld, lats, lons, fp, run, imfmt="png")
+        plotlib.nixon_proj(cape_fld, dls_fld, u_fld, v_fld, p_fld, h_fld, lats, lons, fp, model_run, imfmt="png")
     else:
         print("Wrong command line argument")
         exit(-1)
 
+# ---------------------------------------------------------------------------------------------------------------------
+
+
+def main():
+    config = ut.load_yaml('config.yml')
+
+    # command line arguments
+    parser = argparse.ArgumentParser(description="Hodograph Maps")
+    # Add positional argument
+    parser.add_argument('mode', type=str,
+                        help='Mode: Test, Basic, Sounding, or Nixon')
+
+    # Add optional argument
+    parser.add_argument('-f', '--field', type=str,
+                        help='Which background field: CAPE ML, CAPE CON or LPI ')
+
+    parser.add_argument('-d', '--date', type=str,
+                        help='Date Format YYYY-MM-DD')
+
+    parser.add_argument('-fp', '--fp', type=str,
+                        help='Leadtime or forecast periode')
+
+    parser.add_argument('-r', '--run', type=str,
+                        help='Run (0,6,12,18,.. .etc)')
+
+    # Parse the command line arguments
+    args = parser.parse_args()
+
+    if args.field is None:
+        args.field = "CAPE ML"
+
+    if (args.field != "CAPE ML") and (args.field != "CAPE CON") and (args.field != "LPI") and (args.field != "WMAXSHEAR"):
+        print("Unknown field")
+        exit(-1)
+
+    if args.date is None:
+        rundate = datetime.strptime(config["default_date"], "%Y-%m-%d")
+    else:
+        rundate = datetime.strptime(args.date, "%Y-%m-%d")
+
+    if args.fp is None:
+        fp = config["fp"]
+    else:
+        fp = args.fp
+
+    if args.run is None:
+        model_run = config["run"]
+    else:
+        model_run = args.run
+
+    if args.mode != "Test" or args.mode != "Sounding" or args.mode != "Basic" or args.mode != "Nixon":
+        print("Unknown Mode. Exit program.")
+        exit(0)
+    else:
+        program_mode = args.mode
+
+    # replace space with underscores
+    fieldname = args.field.replace(" ", "_")
+
+    print(f"\nDate: {rundate}\n Arguments: {args} \nConfig-File: {config}\n\n")
+
+    run(program_mode, fieldname, rundate, model_run, fp)
+
+# ---------------------------------------------------------------------------------------------------------------------
+
 
 if __name__ == "__main__":
     main()
-

src/meteolib.py

@@ -1,7 +1,7 @@
 #!/usr/bin/python3
 ################################
 #
-# Meteorology library 
+# Meteorology library
 #
 ################################
 
@@ -15,11 +15,12 @@
 GRAV = 9.80665          # Gravity
 TOL = 1e-10             # Floating Point Tolerance
 
-def uv2spddir(u,v):
 
-    direction = np.rad2deg(np.arctan2(-u,v))
+def uv2spddir(u, v):
 
-    if type(direction) == np.ndarray:
+    direction = np.rad2deg(np.arctan2(-u, v))
+
+    if isinstance(direction, np.ndarray):
         direction[np.where(direction < 0)] += 360
     else:
         if direction < 0:
@@ -39,6 +40,7 @@ def q_to_mixrat(q):
     """
     return q/(1.0-q)
 
+
 def temp_at_mixrat(w, p):
     """
     Returns the temperature in K of air at the given mixing ratio in g/kg and pressure in hPa
@@ -55,11 +57,15 @@ def temp_at_mixrat(w, p):
     """
 
     # Constants Used
-    c1 = 0.0498646455 ; c2 = 2.4082965 ; c3 = 7.07475
-    c4 = 38.9114 ; c5 = 0.0915 ; c6 = 1.2035
+    c1 = 0.0498646455
+    c2 = 2.4082965
+    c3 = 7.07475
+    c4 = 38.9114
+    c5 = 0.0915
+    c6 = 1.2035
 
     x = np.log10(w * p / (622. + w))
-    x = (np.power(10.,((c1 * x) + c2)) - c3 + (c4 * np.power((np.power(10,(c5 * x)) - c6),2)))
+    x = (np.power(10., ((c1 * x) + c2)) - c3 + (c4 * np.power((np.power(10, (c5 * x)) - c6), 2)))
     return x
 
 
@@ -92,20 +98,20 @@ def non_parcel_bunkers_motion_experimental(u, v, ps, i_500m, i_5km, i_6km):
 
 
     """
-    d=7.5
+    d = 7.5
 
     # sfc-500m Mean Wind
     mnu500m, mnv500m = mean_wind(u[:i_500m], v[:i_500m], ps[:i_500m])
 
-    ## 5.5km-6.0km Mean Wind
+    # 5.5km-6.0km Mean Wind
     mnu5500m_6000m, mnv5500m_6000m = mean_wind(u[i_5km:i_6km], v[i_5km:i_6km], ps[i_5km:i_6km])
 
     # shear vector of the two mean winds
     shru = mnu5500m_6000m - mnu500m
     shrv = mnv5500m_6000m - mnv500m
 
     # SFC-6km Mean Wind
-    mnu6, mnv6 =  mean_wind(u[:i_6km], v[:i_6km], ps[:i_6km])
+    mnu6, mnv6 = mean_wind(u[:i_6km], v[:i_6km], ps[:i_6km])
 
     # Bunkers Right Motion
     tmp = d / np.sqrt(shru*shru + shrv*shrv)
@@ -114,4 +120,4 @@ def non_parcel_bunkers_motion_experimental(u, v, ps, i_500m, i_5km, i_6km):
     lstu = mnu6 - (tmp * shrv)
     lstv = mnv6 + (tmp * shru)
 
-    return rstu, rstv, lstu, lstv, mnu6, mnv6
+    return rstu, rstv, lstu, lstv, mnu6, mnv6