diff --git a/README.rst b/README.rst index 290c3b5d..37e5ddde 100644 --- a/README.rst +++ b/README.rst @@ -9,7 +9,7 @@ planning and optimization tools in real-world mesh optical networks.** `gnpy `__ is: -- a sponsored project of the `OOPT/PSE `_ working group of the `Telecom Infra Project `_. +- a sponsored project of the `OOPT/PSE `_ working group of the `Telecom Infra Project `_ - fully community-driven, fully open source library - driven by a consortium of operators, vendors, and academic researchers - intended for rapid development of production-grade route planning tools @@ -135,8 +135,8 @@ By default, this script operates on a single span network defined in `examples/edfa_example_network.json `_ You can specify a different network at the command line as follows. For -example, to use the CORONET Continental US (CONUS) network defined in -`examples/coronet_conus_example.json `_: +example, to use the CORONET Global network defined in +`examples/CORONET_Global_Topology.json `_: .. code-block:: shell @@ -150,10 +150,9 @@ further instructions on how to prepare the Excel input file, see `Excel_userguide.rst `_. The main transmission example will calculate the average signal OSNR and SNR -across 93 network elements (transceiver, ROADMs, fibers, and amplifiers) -between two transceivers selected by the user. (By default, for the CORONET US -network, it will show the transmission of spectral information between Abilene, -Texas and Albany, New York.) +across network elements (transceiver, ROADMs, fibers, and amplifiers) +between two transceivers selected by the user. (By default, for the CORONET Global +network, it will show the transmission of spectral information between Abilene, Texas and Albany, New York.) This script calculates the average signal OSNR = |OSNR| and SNR = |SNR|. @@ -182,7 +181,7 @@ can be added and existing ones removed. Three different noise models are availab 1. `'type_def': 'variable_gain'` is a simplified model simulating a 2-coil EDFA with internal, input and output VOAs. The NF vs gain response is calculated accordingly based on the input parameters: `nf_min`, `nf_max`, and `gain_flatmax`. It is not a simple interpolation but a 2-stage NF calculation. 2. `'type_def': 'fixed_gain'` is a fixed gain model. `NF == Cte == nf0` if `gain_min < gain < gain_flatmax` -3. `'type_def': None` is an advanced model. A detailed json configuration file is required (by default `examples/advanced_config_from.json `_.) It uses a 3rd order polynomial where NF = f(gain), NF_ripple = f(frequency), gain_ripple = f(frequency), N-array dgt = f(frequency). Compared to the previous models, NF ripple and gain ripple are modelled. +3. `'type_def': None` is an advanced model. A detailed json configuration file is required (by default `examples/std_medium_gain_advanced_config.json `_.) It uses a 3rd order polynomial where NF = f(gain), NF_ripple = f(frequency), gain_ripple = f(frequency), N-array dgt = f(frequency). Compared to the previous models, NF ripple and gain ripple are modelled. For all amplifier models: @@ -204,12 +203,12 @@ For all amplifier models: | | | Excel template topology files.) | +----------------------+-----------+-----------------------------------------+ -The fiber library currently describes SSMF but additional fiber types can be entered by the user following the same model: +The fiber library currently describes SSMF and NZDF but additional fiber types can be entered by the user following the same model: +----------------------+-----------+-----------------------------------------+ | field | type | description | +======================+===========+=========================================+ -| `type_variety` | (string) | a unique name to ID the amplifier in the| +| `type_variety` | (string) | a unique name to ID the fiber in the | | | | JSON or Excel template topology input | | | | file | +----------------------+-----------+-----------------------------------------+ @@ -226,7 +225,7 @@ path_request_run.py routine. +----------------------+-----------+-----------------------------------------+ | field | type | description | +======================+===========+=========================================+ -| `type_variety` | (string) | a unique name to ID the amplifier in | +| `type_variety` | (string) | a unique name to ID the transceiver in | | | | the JSON or Excel template topology | | | | input file | +----------------------+-----------+-----------------------------------------+ @@ -252,7 +251,7 @@ The modes are defined as follows: +----------------------+-----------+-----------------------------------------+ | `bit_rate` | (number) | in bit/s | +----------------------+-----------+-----------------------------------------+ -| `roll_off` | (number) | | +| `roll_off` | (number) | Not used. | +----------------------+-----------+-----------------------------------------+ Simulation parameters are defined as follows. @@ -269,8 +268,8 @@ For amplifiers defined in the topology JSON input but whose gain = 0 (placeholder), auto-design will set its gain automatically: see `power_mode` in the `Spans` library to find out how the gain is calculated. -Span configuration is performed as followws. It is not a list (which may change -in later releases,) and the user can only modify the value of existing +Span configuration is performed as follows. It is not a list (which may change +in later releases) and the user can only modify the value of existing parameters: +------------------------+-----------+---------------------------------------------+ @@ -470,11 +469,6 @@ dBm/channel. These are not yet parametrized but can be modified directly in the script (via the SpectralInformation structure) to accomodate any baud rate, spacing, power or channel count demand. -The amplifier's gain is set to exactly compensate for the loss in each network -element. The amplifier is currently defined with gain range of 15 dB to 25 dB -and 21 dBm max output power. Ripple and NF models are defined in -`examples/std_medium_gain_advanced_config.json `_ - Use `examples/path_requests_run.py `_ to run multiple optimizations as follows: .. code-block:: shell @@ -496,8 +490,8 @@ library. The program computes performances for the list of services (accepts json or excel format) using the same spectrum propagation modules as transmission_main_example.py. Explanation on the Excel template is provided in the `Excel_userguide.rst `_. Template for -the json format can be found here: `service_template.json -`_. +the json format can be found here: `service-template.json +`_. Contributing ------------ @@ -588,4 +582,4 @@ License ``gnpy`` is distributed under a standard BSD 3-Clause License. -See `LICENSE `__ for more details. +See `LICENSE `__ for more details. \ No newline at end of file