xdat - pypi Package Compare versions

Comparing version 0.1.294 to 0.1.295

PKG-INFO

 Metadata-Version: 2.4
 Name: xdat
-Version: 0.1.294
+Version: 0.1.295
 Summary: eXtended Data Analysis Toolkit
@@ -5,0 +5,0 @@ Home-page: https://bitbucket.org/hermetric/xdat/

xdat.egg-info/PKG-INFO

 Metadata-Version: 2.4
 Name: xdat
-Version: 0.1.294
+Version: 0.1.295
 Summary: eXtended Data Analysis Toolkit
@@ -5,0 +5,0 @@ Home-page: https://bitbucket.org/hermetric/xdat/

xdat/VERSION

@@ -1,1 +0,1 @@
-0.1.294
+0.1.295

xdat/x1d.py

@@ -145,3 +145,3 @@ import inspect
 
-def x_best_curve_fit(y, funcs=None, x=None, maxfev=500000):
+def x_best_curve_fit(y, funcs=None, x=None, maxfev=500000, on_fail='ignore'):
     if funcs is None:
@@ -153,3 +153,11 @@ funcs = DEFAULT_CURVE_FIT_FUNCS[:]
         cf = CurveFit(func, maxfev=maxfev)
-        cf.fit(y, x=x)
+
+        try:
+            cf.fit(y, x=x)
+        except ValueError:
+            if on_fail == 'ignore':
+                print("- WARN: can't fit model")
+                continue
+            raise
+
         if best_cf is None or cf.stats.p_value < best_cf.stats.p_value:
@@ -156,0 +164,0 @@ best_cf = cf

xdat/xkeras.py

@@ -290,2 +290,12 @@ import hashlib
 
+    def merge_gens(self, *gens):
+        dfs = [g.data_orig for g in [self] + list(gens)]
+        assert len(dfs) > 1, "Need at least 2 generators to merge"
+        assert isinstance(dfs[0], pd.DataFrame), 'Required df generators'
+
+        data_merged = pd.concat(dfs, ignore_index=True)
+        g = self
+        m = self.__class__(data_merged, batch_size=g.batch_size, mode=g.mode, n_jobs=g.n_jobs, n_jobs_batch_size=g.n_jobs_batch_size, dtype=g.dtype, cache_folder=g._cache_folder, verbose=g.verbose)
+        return m
+
     def log(self, text):
@@ -292,0 +302,0 @@ if self.verbose:

xdat/xpd.py

@@ -56,3 +56,3 @@ from collections import Counter, defaultdict
 
-def x_iter_groups(df, on, dropna=True, df_only=False, with_tqdm=False, yield_total=False, sort_on=None):
+def x_iter_groups(df, on, dropna=True, df_only=False, with_tqdm=False, yield_total=False, sort_on=None, title_mode='k=v'):
     if not on:
@@ -99,3 +99,8 @@ yield df, dict(), ""
 
-        group_title = ", ".join([f"{k}={v}" for k,v in zip(on, group_keys)])
+        if title_mode == 'k=v':
+            group_title = ", ".join([f"{k}={v}" for k,v in zip(on, group_keys)])
+        elif title_mode == 'v':
+            group_title = ", ".join([f"{v}" for k, v in zip(on, group_keys)])
+        else:
+            raise ValueError(title_mode)
         series_group_keys = pd.Series(data=group_keys, index=on)
@@ -102,0 +107,0 @@

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Improved metrics

Total package byte prevSize

927806

0.1%

Lines of code

8958

0.21%