improve handling of mdot=0, use correct hofer_numba

src/pandapipes/pf/derivative_calculation.py

@@ -157,7 +157,7 @@ def calc_lambda_transition_area(lambda_laminar, lambda_turb, re, begin_transitio
 def calc_lambda(m, eta, d, k, gas_mode, friction_model, lengths, options, area):
     """
     Function calculates the friction factor of a pipe. Turbulence is calculated based on
-    Nikuradse. If v equals 0, a value of 0.001 is used in order to avoid division by zero.
+    Nikuradse. If m equals 0, a value of 0.001 is used in order to avoid division by zero.
     This should not be a problem as the pressure loss term will equal zero (lambda * u^2).
 
     :param m:
@@ -184,9 +184,8 @@ def calc_lambda(m, eta, d, k, gas_mode, friction_model, lengths, options, area):
     if options["use_numba"]:
         from pandapipes.pf.derivative_toolbox_numba import calc_lambda_nikuradse_incomp_numba as \
             calc_lambda_nikuradse_incomp, colebrook_numba as colebrook, \
-            calc_lambda_nikuradse_comp_numba as calc_lambda_nikuradse_comp
-        from pandapipes.pf.derivative_toolbox import calc_lambda_hofer_comp_np as calc_lambda_hofer_comp # numba version
-        # not yet implemented
+            calc_lambda_nikuradse_comp_numba as calc_lambda_nikuradse_comp, \
+            calc_lambda_hofer_comp_numba as calc_lambda_hofer_comp
     else:
         from pandapipes.pf.derivative_toolbox import calc_lambda_nikuradse_incomp_np as \
             calc_lambda_nikuradse_incomp, colebrook_np as colebrook, \
@@ -213,7 +212,7 @@ def calc_lambda(m, eta, d, k, gas_mode, friction_model, lengths, options, area):
         lambda_swamee_jain = 0.25 / ((np.log10(k / (3.7 * d) + 5.74 / (re ** 0.9))) ** 2)
         return lambda_swamee_jain, re
     elif friction_model.lower() == "hofer":
-        re, lambda_hofer = calc_lambda_hofer_comp(m, d, k, eta, area)
+        re, lambda_laminar, lambda_hofer = calc_lambda_hofer_comp(m, d, k, eta, area)
         lambda_tot = calc_lambda_transition_area(lambda_laminar, lambda_hofer, re,
                                                  begin_transition_re=2000, end_transition_re=4000)
         return lambda_tot, re
@@ -251,7 +250,7 @@ def calc_der_lambda(m, eta, d, k, friction_model, lambda_pipe, area):
     df_dm = np.zeros_like(m)
     df_dlambda = np.zeros_like(m)
     lambda_der = np.zeros_like(m)
-    pos = m != 0
+    pos = ~np.isclose(abs(m), 0)
 
     if friction_model.lower() in ["colebrook", "hofer"]: # hofer is explicit approximation of
         # colebrook

src/pandapipes/pf/derivative_toolbox.py

@@ -110,7 +110,7 @@ def calc_lambda_hofer_comp_np(m, d, k, eta, area, hofer_re_threshold=2000):
     lambda_hofer = \
         np.divide(1, (-2 * np.log10((4.518/re_lower_lim) * np.log10(re_lower_lim/7) + (k / (3.71 * d)))) ** 2)
     lambda_hofer[re < hofer_re_threshold] = 0
-    return re, lambda_hofer
+    return re, lambda_laminar, lambda_hofer
 
 
 def calc_medium_pressure_with_derivative_np(p_init_i_abs, p_init_i1_abs):

src/pandapipes/pf/derivative_toolbox_numba.py

@@ -120,8 +120,8 @@ def calc_lambda_nikuradse_comp_numba(m, d, k, eta, area):
     return re, lambda_laminar, lambda_nikuradse
 
 
-@jit((float64[:], float64[:], float64[:], float64[:], float64[:], int64), nopython=True)
-def calc_lambda_hofer_comp_numba(m, d, k, eta, area, hofer_re_threshold=2000):
+@jit((float64[:], float64[:], float64[:], float64[:], float64[:]), nopython=True)
+def calc_lambda_hofer_comp_numba(m, d, k, eta, area):
     """Calculate Lambda acc. to Hofer-Equation (explicit version of Colebrook) [1].
        Due to nested log10 operations, small Reynolds numbers must be avoided.
        It is justified because the laminar Lambda (instead of Hofer) will be applied for small
@@ -130,6 +130,7 @@ def calc_lambda_hofer_comp_numba(m, d, k, eta, area, hofer_re_threshold=2000):
        [1]: P. Hofer. Beurteilung von Fehlern in Rohrnetzberechnungen (Error evaluation in calculation
            of pipelines). GWF–Gas/Erdgas, 114(3):113–119, 1973
        """
+    hofer_re_threshold = 2000
     lambda_hofer = np.zeros_like(m)
     lambda_laminar = np.zeros_like(m)
     re = np.empty_like(m)