wavefrontshaping/pymmf – Run with an API on Replicate

wavefrontshaping / pymmf

Test mode computation in multimode fibers

Cold

Public
188 runs
CPU
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=wavefrontshaping/pymmf

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run wavefrontshaping/pymmf using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "wavefrontshaping/pymmf:9fb41924130419c54811387e9a5de83581201a0f8fcde3d235487d4f13b1dba6",
  {
    input: {
      NA: 0.2,
      wl: 1550,
      core_diam: 50,
      mode_repr: "cos",
      n_cladding: 1.45,
      curvature_x: 10,
      is_curvature: "No",
      profile_type: "GRIN"
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run wavefrontshaping/pymmf using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "wavefrontshaping/pymmf:9fb41924130419c54811387e9a5de83581201a0f8fcde3d235487d4f13b1dba6",
    input={
        "NA": 0.2,
        "wl": 1550,
        "core_diam": 50,
        "mode_repr": "cos",
        "n_cladding": 1.45,
        "curvature_x": 10,
        "is_curvature": "No",
        "profile_type": "GRIN"
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run wavefrontshaping/pymmf using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "9fb41924130419c54811387e9a5de83581201a0f8fcde3d235487d4f13b1dba6",
    "input": {
      "NA": 0.2,
      "wl": 1550,
      "core_diam": 50,
      "mode_repr": "cos",
      "n_cladding": 1.45,
      "curvature_x": 10,
      "is_curvature": "No",
      "profile_type": "GRIN"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on CPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

Download the modes

Click on modes.npz to download the results as a numpy file or click modes.mat to download as a Matlab file.

To retrieve the data in Python:

import numpy as np

data = np.load('modes.npz')
n_modes = data['n_modes']
n_points = data ['n_points']
# matrix of mode profiles
mode_profiles = data['profiles'] 
# propagation constants
betas = data['betas']

# Profile of the i-th mode
i = 5
field = mode_profiles[...,i].reshape([n_points]*2)

How is it computed?

Check our tutorials to know more: - Simulation of multimode fiber modes: Straight fibers - Simulation of multimode fiber modes: Bent fibers - pyMMF: Step index benchmark - Compare bending methods for MMF simulations using pyMMF - Fast numerical estimations of axisymmetric multimode fibers modes