Only propagates carriers that belong to Amp bandwidth

The commit introduces mux/demux functions in amps and ensures that the
propagation is only done on carriers that are in the Amp bandwitdh, ie
with all their spectrum including slot width is in bandwidth.

For consistency, default amp f_min is changed:
Objective is to use amplifiers' band to bound the possible frequencies
to be propagated. Since the current default f_min of Amp in json_io.py is
higher than the SI one, this would result in a different nb of channels
than currently used in tests, and a change in all tests. In order to
avoid this, I preferred to change this value and have consistency
between SI f_min and Amp f_min.

The commits adds a set of functions to make amps band the useable
spectrum on each OMS. Thee OMS generation is changed to use the amp band.

The commit adds filtering functions (demux and mux) to filter out spectrum
which is not in the amplifier band.

Spectrum assignment is also corrected to correctly match the amp bandwidth
constraint with guardband: center frequency index must be within the
usable part of the amp band. This changes a bit the notion of freq_index
and guardband in the functions, but this is transparent to user:
f_min, f_max represent the amp band, while self.freq_index_min/max
represent the center frequency boundary for a reference 50GHz channel.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I225b2b2dc0e1f1992c0460f6e08fa9c9bc641edf

gnpy/core/info.py

@@ -11,7 +11,7 @@ This module contains classes for modelling :class:`SpectralInformation`.
 from __future__ import annotations
 from collections import namedtuple
 from collections.abc import Iterable
-from typing import Union
+from typing import Union, List
 from dataclasses import dataclass
 from numpy import argsort, mean, array, append, ones, ceil, any, zeros, outer, full, ndarray, asarray
 
@@ -317,6 +317,56 @@ def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, spacing
                                                  tx_osnr=tx_osnr, tx_power=tx_power, label=label)
 
 
+def is_in_band(frequency: float, band: dict) -> bool:
+    """band has {"f_min": value, "f_max": value} format
+    """
+    if frequency >= band['f_min'] and frequency <= band['f_max']:
+        return True
+    return False
+
+
+def demuxed_spectral_information(input_si: SpectralInformation, band: dict) -> SpectralInformation:
+    """extract a si based on band
+    """
+    filtered_indices = [i for i, f in enumerate(input_si.frequency)
+                        if is_in_band(f - input_si.slot_width[i] / 2, band)
+                        and is_in_band(f + input_si.slot_width[i] / 2, band)]
+    if filtered_indices:
+        frequency = input_si.frequency[filtered_indices]
+        baud_rate = input_si.baud_rate[filtered_indices]
+        slot_width = input_si.slot_width[filtered_indices]
+        signal = input_si.signal[filtered_indices]
+        nli = input_si.nli[filtered_indices]
+        ase = input_si.ase[filtered_indices]
+        roll_off = input_si.roll_off[filtered_indices]
+        chromatic_dispersion = input_si.chromatic_dispersion[filtered_indices]
+        pmd = input_si.pmd[filtered_indices]
+        pdl = input_si.pdl[filtered_indices]
+        latency = input_si.latency[filtered_indices]
+        delta_pdb_per_channel = input_si.delta_pdb_per_channel[filtered_indices]
+        tx_osnr = input_si.tx_osnr[filtered_indices]
+        tx_power = input_si.tx_power[filtered_indices]
+        label = input_si.label[filtered_indices]
+
+        return SpectralInformation(frequency=frequency, baud_rate=baud_rate, slot_width=slot_width, signal=signal,
+                                   nli=nli, ase=ase, roll_off=roll_off, chromatic_dispersion=chromatic_dispersion,
+                                   pmd=pmd, pdl=pdl, latency=latency, delta_pdb_per_channel=delta_pdb_per_channel,
+                                   tx_osnr=tx_osnr, tx_power=tx_power, label=label)
+    return None
+
+
+def muxed_spectral_information(input_si_list: List[SpectralInformation]) -> SpectralInformation:
+    """return the assembled spectrum
+    """
+    if input_si_list and len(input_si_list) > 1:
+        si = input_si_list[0] + muxed_spectral_information(input_si_list[1:])
+        return si
+    elif input_si_list and len(input_si_list) == 1:
+        return input_si_list[0]
+    else:
+        raise ValueError('liste vide')
+
+
 def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier],
                                      power: float) -> SpectralInformation:
     """Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.