fix: multi dim fits fixed in least squares. Test added. (#160)

Co-authored-by: Simon Kuberski <simon.kuberski@uni-muenster.de>

pyerrors/fits.py

@@ -554,7 +554,7 @@ def _combined_fit(x, y, func, silent=False, **kwargs):
     for key in key_ls:
         if not callable(funcd[key]):
             raise TypeError('func (key=' + key + ') is not a function.')
-        if len(xd[key]) != len(yd[key]):
+        if np.asarray(xd[key]).shape[-1] != len(yd[key]):
             raise Exception('x and y input (key=' + key + ') do not have the same length')
         for i in range(100):
             try:

tests/fits_test.py

@@ -913,6 +913,17 @@ def test_combined_resplot_qqplot():
     plt.close('all')
 
 
+def test_x_multidim_fit():
+    x1 = np.arange(1, 10)
+    x = np.array([[xi, xi] for xi in x1]).T
+    y = [pe.pseudo_Obs(i + 2 / i, .1 * i, 't') for i in x[0]]
+    [o.gm() for o in y]
+    def fitf(a, x):
+        return a[0] * x[0] + a[1] / x[1]
+
+    pe.fits.least_squares(x, y, fitf)
+
+
 def fit_general(x, y, func, silent=False, **kwargs):
     """Performs a non-linear fit to y = func(x) and returns a list of Obs corresponding to the fit parameters.