pvsystem.singlediode with method='newton' can be passed pd.Series of length one.

docs/sphinx/source/whatsnew/v0.10.2.rst

@@ -21,6 +21,9 @@ Bug fixes
 ~~~~~~~~~
 * :py:func:`~pvlib.iotools.get_psm3` no longer incorrectly returns clear-sky
   DHI instead of clear-sky GHI when requesting ``ghi_clear``. (:pull:`1819`)
+* :py:func:`pvlib.singlediode.bishop88` with `method='newton'` no longer
+  crashes when passed `pandas.Series` of length one.
+  (:issue:`1787`, :pull:`1822`)
 
 Testing
 ~~~~~~~

pvlib/pvsystem.py

@@ -2651,28 +2651,19 @@ def v_from_i(current, photocurrent, saturation_current, resistance_series,
        parameters of real solar cells using Lambert W-function", Solar
        Energy Materials and Solar Cells, 81 (2004) 269-277.
     '''
+    args = (current, photocurrent, saturation_current,
+            resistance_series, resistance_shunt, nNsVth)
     if method.lower() == 'lambertw':
-        return _singlediode._lambertw_v_from_i(
-            current, photocurrent, saturation_current, resistance_series,
-            resistance_shunt, nNsVth
-        )
+        return _singlediode._lambertw_v_from_i(*args)
     else:
         # Calculate points on the IV curve using either 'newton' or 'brentq'
         # methods. Voltages are determined by first solving the single diode
         # equation for the diode voltage V_d then backing out voltage
-        args = (current, photocurrent, saturation_current,
-                resistance_series, resistance_shunt, nNsVth)
         V = _singlediode.bishop88_v_from_i(*args, method=method.lower())
-        # find the right size and shape for returns
-        size, shape = _singlediode._get_size_and_shape(args)
-        if size <= 1:
-            if shape is not None:
-                V = np.tile(V, shape)
-        if np.isnan(V).any() and size <= 1:
-            V = np.repeat(V, size)
-            if shape is not None:
-                V = V.reshape(shape)
-        return V
+        if all(map(np.isscalar, args)):
+            return V
+        shape = _singlediode._shape_of_max_size(*args)
+        return np.broadcast_to(V, shape)
 
 
 def i_from_v(voltage, photocurrent, saturation_current, resistance_series,
@@ -2742,28 +2733,19 @@ def i_from_v(voltage, photocurrent, saturation_current, resistance_series,
        parameters of real solar cells using Lambert W-function", Solar
        Energy Materials and Solar Cells, 81 (2004) 269-277.
     '''
+    args = (voltage, photocurrent, saturation_current,
+            resistance_series, resistance_shunt, nNsVth)
     if method.lower() == 'lambertw':
-        return _singlediode._lambertw_i_from_v(
-            voltage, photocurrent, saturation_current, resistance_series,
-            resistance_shunt, nNsVth
-        )
+        return _singlediode._lambertw_i_from_v(*args)
     else:
         # Calculate points on the IV curve using either 'newton' or 'brentq'
         # methods. Voltages are determined by first solving the single diode
         # equation for the diode voltage V_d then backing out voltage
-        args = (voltage, photocurrent, saturation_current, resistance_series,
-                resistance_shunt, nNsVth)
         current = _singlediode.bishop88_i_from_v(*args, method=method.lower())
-        # find the right size and shape for returns
-        size, shape = _singlediode._get_size_and_shape(args)
-        if size <= 1:
-            if shape is not None:
-                current = np.tile(current, shape)
-        if np.isnan(current).any() and size <= 1:
-            current = np.repeat(current, size)
-            if shape is not None:
-                current = current.reshape(shape)
-        return current
+        if all(map(np.isscalar, args)):
+            return current
+        shape = _singlediode._shape_of_max_size(*args)
+        return np.broadcast_to(current, shape)
 
 
 def scale_voltage_current_power(data, voltage=1, current=1):

pvlib/singlediode.py

@@ -287,8 +287,8 @@ def bishop88_i_from_v(voltage, photocurrent, saturation_current,
     ...     method_kwargs={'full_output': True})
     """
     # collect args
-    args = (photocurrent, saturation_current, resistance_series,
-            resistance_shunt, nNsVth, d2mutau, NsVbi,
+    args = (photocurrent, saturation_current,
+            resistance_series, resistance_shunt, nNsVth, d2mutau, NsVbi,
             breakdown_factor, breakdown_voltage, breakdown_exp)
     method = method.lower()
 
@@ -319,14 +319,11 @@ def vd_from_brent(voc, v, iph, isat, rs, rsh, gamma, d2mutau, NsVbi,
         vd_from_brent_vectorized = np.vectorize(vd_from_brent)
         vd = vd_from_brent_vectorized(voc_est, voltage, *args)
     elif method == 'newton':
-        # make sure all args are numpy arrays if max size > 1
-        # if voltage is an array, then make a copy to use for initial guess, v0
-        args, v0, method_kwargs = \
-            _prepare_newton_inputs((voltage,), args, voltage, method_kwargs)
-        vd = newton(func=lambda x, *a: fv(x, voltage, *a), x0=v0,
+        x0, (voltage, *args), method_kwargs = \
+            _prepare_newton_inputs(voltage, (voltage, *args), method_kwargs)
+        vd = newton(func=lambda x, *a: fv(x, voltage, *a), x0=x0,
                     fprime=lambda x, *a: bishop88(x, *a, gradients=True)[4],
-                    args=args,
-                    **method_kwargs)
+                    args=args, **method_kwargs)
     else:
         raise NotImplementedError("Method '%s' isn't implemented" % method)
 
@@ -422,9 +419,9 @@ def bishop88_v_from_i(current, photocurrent, saturation_current,
     ...     method_kwargs={'full_output': True})
     """
     # collect args
-    args = (photocurrent, saturation_current, resistance_series,
-            resistance_shunt, nNsVth, d2mutau, NsVbi, breakdown_factor,
-            breakdown_voltage, breakdown_exp)
+    args = (photocurrent, saturation_current,
+            resistance_series, resistance_shunt, nNsVth, d2mutau, NsVbi,
+            breakdown_factor, breakdown_voltage, breakdown_exp)
     method = method.lower()
 
     # method_kwargs create dict if not provided
@@ -454,14 +451,11 @@ def vd_from_brent(voc, i, iph, isat, rs, rsh, gamma, d2mutau, NsVbi,
         vd_from_brent_vectorized = np.vectorize(vd_from_brent)
         vd = vd_from_brent_vectorized(voc_est, current, *args)
     elif method == 'newton':
-        # make sure all args are numpy arrays if max size > 1
-        # if voc_est is an array, then make a copy to use for initial guess, v0
-        args, v0, method_kwargs = \
-            _prepare_newton_inputs((current,), args, voc_est, method_kwargs)
-        vd = newton(func=lambda x, *a: fi(x, current, *a), x0=v0,
+        x0, (current, *args), method_kwargs = \
+            _prepare_newton_inputs(voc_est, (current, *args), method_kwargs)
+        vd = newton(func=lambda x, *a: fi(x, current, *a), x0=x0,
                     fprime=lambda x, *a: bishop88(x, *a, gradients=True)[3],
-                    args=args,
-                    **method_kwargs)
+                    args=args, **method_kwargs)
     else:
         raise NotImplementedError("Method '%s' isn't implemented" % method)
 
@@ -555,9 +549,9 @@ def bishop88_mpp(photocurrent, saturation_current, resistance_series,
     ...     method='newton', method_kwargs={'full_output': True})
     """
     # collect args
-    args = (photocurrent, saturation_current, resistance_series,
-            resistance_shunt, nNsVth, d2mutau, NsVbi, breakdown_factor,
-            breakdown_voltage, breakdown_exp)
+    args = (photocurrent, saturation_current,
+            resistance_series, resistance_shunt, nNsVth, d2mutau, NsVbi,
+            breakdown_factor, breakdown_voltage, breakdown_exp)
     method = method.lower()
 
     # method_kwargs create dict if not provided
@@ -584,12 +578,11 @@ def fmpp(x, *a):
     elif method == 'newton':
         # make sure all args are numpy arrays if max size > 1
         # if voc_est is an array, then make a copy to use for initial guess, v0
-        args, v0, method_kwargs = \
-            _prepare_newton_inputs((), args, voc_est, method_kwargs)
-        vd = newton(
-            func=fmpp, x0=v0,
-            fprime=lambda x, *a: bishop88(x, *a, gradients=True)[7], args=args,
-            **method_kwargs)
+        x0, args, method_kwargs = \
+            _prepare_newton_inputs(voc_est, args, method_kwargs)
+        vd = newton(func=fmpp, x0=x0,
+                    fprime=lambda x, *a: bishop88(x, *a, gradients=True)[7],
+                    args=args, **method_kwargs)
     else:
         raise NotImplementedError("Method '%s' isn't implemented" % method)
 
@@ -603,46 +596,42 @@ def fmpp(x, *a):
         return bishop88(vd, *args)
 
 
-def _get_size_and_shape(args):
-    # find the right size and shape for returns
-    size, shape = 0, None  # 0 or None both mean scalar
-    for arg in args:
-        try:
-            this_shape = arg.shape  # try to get shape
-        except AttributeError:
-            this_shape = None
-            try:
-                this_size = len(arg)  # try to get the size
-            except TypeError:
-                this_size = 0
-        else:
-            this_size = arg.size  # if it has shape then it also has size
-            if shape is None:
-                shape = this_shape  # set the shape if None
-        # update size and shape
-        if this_size > size:
-            size = this_size
-            if this_shape is not None:
-                shape = this_shape
-    return size, shape
-
-
-def _prepare_newton_inputs(i_or_v_tup, args, v0, method_kwargs):
-    # broadcast arguments for newton method
-    # the first argument should be a tuple, eg: (i,), (v,) or ()
-    size, shape = _get_size_and_shape(i_or_v_tup + args)
-    if size > 1:
-        args = [np.asarray(arg) for arg in args]
-    # newton uses initial guess for the output shape
-    # copy v0 to a new array and broadcast it to the shape of max size
-    if shape is not None:
-        v0 = np.broadcast_to(v0, shape).copy()
+def _shape_of_max_size(*args):
+    return max(((np.size(a), np.shape(a)) for a in args),
+               key=lambda t: t[0])[1]
+
+
+def _prepare_newton_inputs(x0, args, method_kwargs):
+    """
+    Make inputs compatible with Scipy's newton by:
+    - converting all arugments (`x0` and `args`) into numpy.ndarrays if any
+      argument is not a scalar.
+    - broadcasting the initial guess `x0` to the shape of the argument with
+      the greatest size.
+
+    Parameters
+    ----------
+    x0: numeric
+        Initial guess for newton.
+    args: Iterable(numeric)
+        Iterable of additional arguments to use in SciPy's newton.
+    method_kwargs: dict
+        Options to pass to newton.
+
+    Returns
+    -------
+    tuple
+        The updated initial guess, arguments, and options for newton.
+    """
+    if not (np.isscalar(x0) and all(map(np.isscalar, args))):
+        args = tuple(map(np.asarray, args))
+        x0 = np.broadcast_to(x0, _shape_of_max_size(x0, *args))
 
     # set abs tolerance and maxiter from method_kwargs if not provided
     # apply defaults, but giving priority to user-specified values
     method_kwargs = {**NEWTON_DEFAULT_PARAMS, **method_kwargs}
 
-    return args, v0, method_kwargs
+    return x0, args, method_kwargs
 
 
 def _lambertw_v_from_i(current, photocurrent, saturation_current,

pvlib/tests/test_singlediode.py

@@ -557,3 +557,14 @@ def test_bishop88_full_output_kwarg(method, bishop88_arguments):
     assert isinstance(ret_val[1], tuple)  # second is output from optimizer
     # any root finder returns at least 2 elements with full_output=True
     assert len(ret_val[1]) >= 2
+
+
+@pytest.mark.parametrize('method', ['newton', 'brentq'])
+def test_bishop88_pdSeries_len_one(method, bishop88_arguments):
+    for k, v in bishop88_arguments.items():
+        bishop88_arguments[k] = pd.Series([v])
+
+    # should not raise error
+    bishop88_i_from_v(pd.Series([0]), **bishop88_arguments, method=method)
+    bishop88_v_from_i(pd.Series([0]), **bishop88_arguments, method=method)
+    bishop88_mpp(**bishop88_arguments, method=method)