Spaces:
Running on Zero
Running on Zero
| """Precompute the demo's example reservoirs on the Space's GPU, through its /generate endpoint (same model and | |
| sampler as the live demo). Needs a Hugging Face token (huggingface-cli login). | |
| python make_examples.py NAME -> examples/NAME.npz""" | |
| import io, json, sys, time | |
| import urllib.request | |
| import numpy as np | |
| from huggingface_hub import get_token | |
| from matplotlib.path import Path | |
| SPACE = 'https://baghishov-resflow-demo.hf.space' | |
| Z = 32 | |
| WELL_LOGS = { # as in backend.py: base (z = 0) to top, 1 sand, 0 mud | |
| 'Two sand bodies': [0] * 6 + [1] * 7 + [0] * 7 + [1] * 8 + [0] * 4, | |
| 'Thick sand at the base': [1] * 14 + [0] * 18, | |
| } | |
| HEADERS = {'Authorization': f'Bearer {get_token()}'} | |
| def fetch(url, data=None): | |
| req = urllib.request.Request(url, data=None if data is None else json.dumps(data).encode(), | |
| headers={**HEADERS, 'Content-Type': 'application/json'}) | |
| return urllib.request.urlopen(req, timeout=900) | |
| def call(api, data): | |
| """Run a Gradio API endpoint and return its output list.""" | |
| eid = json.load(fetch(f'{SPACE}/gradio_api/call/{api}', {'data': data}))['event_id'] | |
| event = None | |
| with fetch(f'{SPACE}/gradio_api/call/{api}/{eid}') as r: | |
| for line in (l.decode().rstrip('\n') for l in r): | |
| if line.startswith('event:'): | |
| event = line[6:].strip() | |
| elif line.startswith('data:') and event in ('complete', 'error'): | |
| if event == 'error': | |
| raise RuntimeError(line) | |
| return json.loads(line[5:]) | |
| raise RuntimeError('stream ended without a result') | |
| def blob(nx, ny, seed=3): | |
| """An irregular reservoir outline: a smooth random closed curve.""" | |
| rng = np.random.default_rng(seed) | |
| t = np.linspace(0, 2 * np.pi, 400) | |
| r = 0.36 + sum(rng.uniform(0.02, 0.06) * np.cos(k * t + rng.uniform(0, 6.3)) for k in range(2, 6)) | |
| x, y = 0.5 + r * np.cos(t), 0.5 + 0.9 * r * np.sin(t) | |
| gx, gy = np.meshgrid((np.arange(nx) + .5) / nx, (np.arange(ny) + .5) / ny, indexing='ij') | |
| return Path(np.c_[x, y]).contains_points(np.c_[gx.ravel(), gy.ravel()]).reshape(nx, ny) | |
| EX = { | |
| 'lobe_outline': dict(title='Deep-water lobes, irregular outline, two wells', label='Lobe (deep-water)', nx=256, ny=256, | |
| azimuth=45.0, outline=True, | |
| wells=[(96, 120, 'Two sand bodies'), (168, 104, 'Thick sand at the base')]), | |
| 'meander_strip': dict(title='Meander belt along flow', label='Meander (oxbow)', nx=384, ny=128, azimuth=0.0, | |
| outline=False, wells=[]), | |
| } | |
| name = sys.argv[1]; e = EX[name] | |
| wells = [(x, y, WELL_LOGS[log]) for x, y, log in e['wells']] | |
| t = time.time() | |
| out = call('generate', [e['label'], e['nx'], e['ny'], json.dumps(wells), 50, 0, json.dumps({'azimuth': e['azimuth']})]) | |
| z = np.load(io.BytesIO(fetch(out[0]['url']).read())) | |
| f = z['facies'] | |
| params = {k: float(z[k]) for k in z.files if k not in ('facies', 'active', 'environment')} | |
| for x, y, log in wells: # wells must be honoured exactly | |
| assert (f[x, y] == np.array(log)).all(), f'well ({x}, {y}) not honoured' | |
| active = blob(e['nx'], e['ny']) if e['outline'] else np.ones((e['nx'], e['ny']), bool) | |
| np.savez_compressed(f'examples/{name}.npz', facies=f, active=active, | |
| wells=np.array([[x, y] + list(log) for x, y, log in wells], np.int16).reshape(-1, 2 + Z), | |
| meta=json.dumps({'title': e['title'], 'label': e['label'], 'nx': e['nx'], 'ny': e['ny'], | |
| 'params': params, 'steps': 50, 'seed': 0})) | |
| print(f'{name}: {f.shape}, sand {f[active].mean():.2f}, wells honoured {len(wells)}, {time.time() - t:.0f}s', flush=True) | |