update stepping for numdifftools

rvs_warn if logg is on the edge

py/rvspecfit/desi/desi_fit.py

@@ -365,6 +365,9 @@ def get_rvs_warn(fit_res, outdict, config):
     teff_thresh = 10
     teff_edges = [2300, 15000]
 
+    logg_thresh = 0.01
+    logg_edges = [-.5, 6.5]
+
     # if we are within this threshold of the RV boundary we set another
     # warning
     rvedge_thresh = 5
@@ -393,7 +396,8 @@ def get_rvs_warn(fit_res, outdict, config):
     # Here we check if the parameter is within the threshold of the edge or
     # beyond the edge.
     parameter_limits = [['teff', teff_edges, teff_thresh],
-                        ['feh', feh_edges, feh_thresh]]
+                        ['feh', feh_edges, feh_thresh],
+                        ['logg', logg_edges, logg_thresh]]
     for cur_param, cur_edges, cur_thresh in parameter_limits:
         if _bad_edge_check(fit_res['param'][cur_param], cur_edges, cur_thresh):
             rvs_warn |= bitmasks['PARAM_WARN']

py/rvspecfit/vel_fit.py

@@ -626,14 +626,14 @@ def hess_func_wrap(p):
         return hess_func(p, best_param_TMP, args)
 
     hess_step = [{
-        'vsini': 1,
-        'logg': 0.1,
-        'feh': 0.1,
-        'alpha': .01,
-        'teff': 10,
-        'vrad': 1,
+        'vsini': 1 / 100,
+        'logg': 0.1 / 100,
+        'feh': 0.1 / 100,
+        'alpha': .01 / 100,
+        'teff': 1 / 100,
+        'vrad': 1 / 100,
     }[_] for _ in specParamNames]
-    hess_step = ndf.MaxStepGenerator(base_step=hess_step)
+    hess_step = ndf.MinStepGenerator(base_step=hess_step)
     hessian = ndf.Hessian(hess_func_wrap, step=hess_step)(
         [ret['param'][_] for _ in specParamNames])
     diag_err, covar_mat = _uncertainties_from_hessian(hessian)