improved documentation

d3af461f · Stefano Serafin · 9720101a · d3af461f
Commit d3af461f authored 1 month ago by Stefano Serafin
--- a/Overview.ipynb
+++ b/Overview.ipynb
@@ -27,14 +27,13 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
-      "loading .//experiment.pickle failed, running it\n",
      "Spinup        : # ...done\n",
      "Nature run    : # ...done\n",
      "Cycle 0000    : ########## ...done\n"
@@ -43,45 +42,26 @@
   ],
   "source": [
    "from ENDA import experiment\n",
-    "import pickle\n",
    "import json\n",
    "from PE_CBL_graphics import *\n",
    "\n",
-    "def get_experiment(settings_file):\n",
-    "\n",
-    "    with open(settings_file, 'r') as fp:\n",
-    "        settings = json.load(fp)\n",
-    "    exp = load_or_run(settings)\n",
-    "\n",
-    "    return exp\n",
-    "\n",
-    "def load_or_run(settings):\n",
-    "\n",
-    "    try:\n",
-    "        exp = pickle.load(open(settings['path']+'/'+settings['filename'], \"rb\"))\n",
-    "        print('loaded experiment %s'%(settings['path']+'/'+settings['filename']))\n",
-    "    except:\n",
-    "        print('loading %s failed, running it'%(settings['path']+'/'+settings['filename']))\n",
-    "        exp = experiment(settings)\n",
-    "        pickle.dump(exp, open(settings['path']+'/'+settings['filename'], 'wb')) \n",
-    "\n",
-    "    return exp\n",
-    "\n",
-    "exp = get_experiment('./default_da.json')"
+    "with open('./default_da.json', 'r') as fp:\n",
+    "    settings = json.load(fp)\n",
+    "exp = experiment(settings)"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
-       "<matplotlib.legend.Legend at 0x1542d54f7850>"
+       "<matplotlib.legend.Legend at 0x1542d5630430>"
      ]
     },
-     "execution_count": 13,
+     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
@@ -98,6 +78,7 @@
   ],
   "source": [
    "from matplotlib import pyplot as p\n",
+    "\n",
    "fig = p.figure(151)\n",
    "fig.set_size_inches(6,4)\n",
    "ax1 = fig.add_subplot(1,1,1)\n",

 %% Cell type:markdown id: tags:

 # References

 For the data assimilation algorithms:
 * Anderson, J. L., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Weather Rev., 129, 2884–2903. [https://doi.org/10.1175/1520-0493(2001)129%3C2884:AEAKFF%3E2.0.CO;2]
 * Anderson, J. L., 2003: A local least squares framework for ensemble filtering. Mon. Weather Rev., 131, 634–642. [https://doi.org/10.1175/1520-0493(2003)131%3C0634:ALLSFF%3E2.0.CO;2]
 * Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D, 230, 112–126.
 [http://dx.doi.org/10.1016/j.physd.2006.11.008]

 For the single-column model of the convective boundary layer (CBL):
 * Troen, I. B., and L. Mahrt, 1986: A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Bound.-Layer Meteorol., 37, 129–148. [https://doi.org/10.1007/BF00122760]

 %% Cell type:markdown id: tags:

 # How to run a simple OSSE experiment

 The default configuration files (in `json` format) are set to compute a single analysis that assimilates a single observation. For configuration details, see below. Simply run:

 %% Cell type:code id: tags:

 ``` python
 from ENDA import experiment
-import pickle
 import json
 from PE_CBL_graphics import *

-def get_experiment(settings_file):
-
-    with open(settings_file, 'r') as fp:
-        settings = json.load(fp)
-    exp = load_or_run(settings)
-
-    return exp
-
-def load_or_run(settings):
-
-    try:
-        exp = pickle.load(open(settings['path']+'/'+settings['filename'], "rb"))
-        print('loaded experiment %s'%(settings['path']+'/'+settings['filename']))
-    except:
-        print('loading %s failed, running it'%(settings['path']+'/'+settings['filename']))
-        exp = experiment(settings)
-        pickle.dump(exp, open(settings['path']+'/'+settings['filename'], 'wb'))
-
-    return exp
-
-exp = get_experiment('./default_da.json')
+with open('./default_da.json', 'r') as fp:
+    settings = json.load(fp)
+exp = experiment(settings)
 ```

 %% Output

-    loading .//experiment.pickle failed, running it
    Spinup        : # ...done
    Nature run    : # ...done
    Cycle 0000    : ########## ...done

 %% Cell type:code id: tags:

 ``` python
 from matplotlib import pyplot as p
+
 fig = p.figure(151)
 fig.set_size_inches(6,4)
 ax1 = fig.add_subplot(1,1,1)
 ax1 = plot_CBL_assimilation(exp,_,ax = ax1)
 ax1.set_xlabel(r'$\theta$ (K)')
 ax1.set_ylabel(r'$z$ (m)')
 ax1.set_title(r'Ensemble state at $t=3600$ s')
 ax1.legend(frameon=False)
 ```

 %% Output

-    <matplotlib.legend.Legend at 0x1542d54f7850>
+    <matplotlib.legend.Legend at 0x1542d5630430>



 %% Cell type:markdown id: tags:

 # Configuration of the CBL model

 See the file `default_cbl.json`
 ```
 {
 "g": 9.806,
 "f": 0.0001,
 "kvonk": 0.4,
 "z0": 0.1,
 "ug": 0,
 "vg": 10,
 "theta_0": 290,
 "gamma": 0.003,
 "Hmax": 0.1,
 "H0_perturbation_ampl_init": 0.0,
 "H0_perturbation_ampl_time": 0.0,
 "exct": 0.3,
 "pfac": 1.5,
 "Kmin": 0.1,
 "Kmax": 200,
 "is_bwind": false,
 "is_cgrad": true,
 "is_cycle": false,
 "dz": 50,
 "ztop": 4000,
 "rnseed": 181612,
 "perturb_ensemble_state": true,
 "perturbations_type": "smooth",
 "perturbations_theta_amplitude": 0.1,
 "perturbations_uv_amplitude": 0.1,
 "perturbations_smooth_number": 11,
 "perturbations_symmetric": true,
 "error_growth_perturbations_amplitude": 0.1,
 "perturb_ensemble_parameters": true,
 "parameter_number": 1,
 "parameter_transform": "pit",
 "parameter_ensemble_min": 0.5,
 "parameter_ensemble_max": 4.5,
 "parameter_true": 1.5,
 "do_parameter_estimation": true,
 "parameter_inflation_rtps_alpha": 0.4,
 "return_covariances_increments_and_innovations": true
 }
 ```

 %% Cell type:markdown id: tags:

 # Configuration of the data assimilation cycle

 See the file `default_da.json`
 ```
 {
    "cbl_settings_file": "./default_cbl.json",
    "type": "OSSE",
    "tspinup": 10800,
    "trun": 3600,
    "tspinup_assim": 0,
    "assimilation_interval": 3600,
    "randomize_obs": true,
    "nobs": 1,
    "obs_coordinates_min": 433,
    "obs_coordinates_max": 433,
    "obs_kinds": "theta",
    "obs_error_sdev_generate": 0.2,
    "obs_error_sdev_assimilate": 0.1,
    "localization_cutoff": 400,
    "nens": 50,
    "FILTER": "EAKF",
    "inflation_rtps_alpha": 0.1,
    "simulate_underdispersiveness": false,
    "rnseed": 181612,
    "path": "./",
    "filename": "experiment.pickle",
    "label": "X",
    "nature_run_from_file": false,
    "do_parameter_estimation": true
   }
 ```