Merge pull request #79 from stellema/master

Add eva main function, update fit_gev and add fitstart options
AusClimateService · Oct 23, 2024 · 1afb9d8 · 1afb9d8
2 parents 5727504 + 27f7e09
commit 1afb9d8
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Showing 10 changed files with 1,111 additions and 632 deletions.
diff --git a/ci/environment.yml b/ci/environment.yml
@@ -9,6 +9,7 @@ dependencies:
   - dask-jobqueue
   - geopandas
   - gitpython
+  - lmoments3
   - netcdf4
   - numpy
   - pip

diff --git a/docs/user_guide/worked_example-HadGEM3-GC31-MM.ipynb b/docs/user_guide/worked_example-HadGEM3-GC31-MM.ipynb
@@ -1220,9 +1220,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/599/dbi599/unseen/unseen/eva.py:253: UserWarning: Data fit failed. Retrying with 'generate_estimates=True'.\n",
+      "/home/599/dbi599/unseen/unseen/eva.py:253: UserWarning: Data fit failed. Retrying with 'fitstart='scipy_subet''.\n",
       "  warnings.warn(\n",
-      "/home/599/dbi599/unseen/unseen/eva.py:253: UserWarning: Data fit failed. Retrying with 'generate_estimates=True'.\n",
+      "/home/599/dbi599/unseen/unseen/eva.py:253: UserWarning: Data fit failed. Retrying with 'fitstart='scipy_subet''.\n",
       "  warnings.warn(\n"
      ]
     },
@@ -2609,12 +2609,12 @@
    ],
    "source": [
     "model_da_indep.plot.hist(bins=50, density=True, alpha=0.7, facecolor='tab:blue')\n",
-    "model_raw_shape, model_raw_loc, model_raw_scale = eva.fit_gev(model_da_indep_stacked.values, generate_estimates=True)\n",
+    "model_raw_shape, model_raw_loc, model_raw_scale = eva.fit_gev(model_da_indep_stacked.values, fitstart='scipy_subet')\n",
     "model_raw_pdf = gev.pdf(xvals, model_raw_shape, model_raw_loc, model_raw_scale)\n",
     "plt.plot(xvals, model_raw_pdf, color='tab:blue', linewidth=4.0, label='model')\n",
     "\n",
     "model_da_bc.plot.hist(bins=50, density=True, alpha=0.7, facecolor='tab:orange')\n",
-    "model_bc_shape, model_bc_loc, model_bc_scale = eva.fit_gev(model_da_bc_stacked.values, generate_estimates=True)\n",
+    "model_bc_shape, model_bc_loc, model_bc_scale = eva.fit_gev(model_da_bc_stacked.values, fitstart='scipy_subet')\n",
     "model_bc_pdf = gev.pdf(xvals, model_bc_shape, model_bc_loc, model_bc_scale)\n",
     "plt.plot(xvals, model_bc_pdf, color='tab:orange', linewidth=4.0, label='model (corrected)')\n",
     "\n",

diff --git a/docs/user_guide/worked_example_stationary.rst b/docs/user_guide/worked_example_stationary.rst
@@ -438,12 +438,12 @@ to see the effect of the bias correction.
     model_da_bc_stacked = model_da_bc.dropna('lead_time').stack({'sample': ['ensemble', 'init_date', 'lead_time']})
 
     model_da_indep.plot.hist(bins=50, density=True, alpha=0.7, facecolor='tab:blue')
-    model_raw_shape, model_raw_loc, model_raw_scale = eva.fit_gev(model_da_indep_stacked.values, generate_estimates=True)
+    model_raw_shape, model_raw_loc, model_raw_scale = eva.fit_gev(model_da_indep_stacked.values, fitstart='scipy_subet')
     model_raw_pdf = gev.pdf(xvals, model_raw_shape, model_raw_loc, model_raw_scale)
     plt.plot(xvals, model_raw_pdf, color='tab:blue', linewidth=4.0, label='model')
 
     model_da_bc.plot.hist(bins=50, density=True, alpha=0.7, facecolor='tab:orange')
-    model_bc_shape, model_bc_loc, model_bc_scale = eva.fit_gev(model_da_bc_stacked.values, generate_estimates=True)
+    model_bc_shape, model_bc_loc, model_bc_scale = eva.fit_gev(model_da_bc_stacked.values, fitstart='scipy_subet')
     model_bc_pdf = gev.pdf(xvals, model_bc_shape, model_bc_loc, model_bc_scale)
     plt.plot(xvals, model_bc_pdf, color='tab:orange', linewidth=4.0, label='model (corrected)')
 

diff --git a/setup.py b/setup.py
@@ -29,6 +29,7 @@
             "bias_correction = unseen.bias_correction:_main",
             "stability = unseen.stability:_main",
             "moments = unseen.moments:_main",
+            "eva = unseen.eva:_main",
         ]
     },
 )