Fiber latency calculation

Fiber latency evaluated during propagation. The speed of ligth in fiber is evaluated as the vacuum speed of ligth  divided by the core reflective index n1.
The latency in the transceiver is evaluated in ms.

Change-Id: I7a3638c49f346aecaf1d4897cecf96d345fdb26c

gnpy/core/parameters.py

@@ -158,6 +158,7 @@ class FiberParams(Parameters):
             self._beta3 = ((self.dispersion_slope - (4*pi*c/self.ref_wavelength**3) * self.beta2) /
                            (2*pi*c/self.ref_wavelength**2)**2)
             self._effective_area = kwargs.get('effective_area')  # m^2
+            self._n1 = 1.468
             n2 = 2.6e-20  # m^2/W
             if self._effective_area:
                 self._gamma = kwargs.get('gamma', 2 * pi * n2 / (self.ref_wavelength * self._effective_area))  # 1/W/m
@@ -177,6 +178,7 @@ class FiberParams(Parameters):
                 self._loss_coef = asarray(kwargs['loss_coef']) * 1e-3  # lineic loss dB/m
                 self._f_loss_ref = asarray(self._ref_frequency)  # Hz
             self._lumped_losses = kwargs['lumped_losses'] if 'lumped_losses' in kwargs else []
+            self._latency = self._length / (c / self._n1)  # s
         except KeyError as e:
             raise ParametersError(f'Fiber configurations json must include {e}. Configuration: {kwargs}')
 
@@ -261,6 +263,10 @@ class FiberParams(Parameters):
     def raman_efficiency(self):
         return self._raman_efficiency
 
+    @property
+    def latency(self):
+        return self._latency
+
     def asdict(self):
         dictionary = super().asdict()
         dictionary['loss_coef'] = self.loss_coef * 1e3