Working

.gitignore

@@ -1,5 +1,8 @@
 Enrichment/
 __pycache__/
-Logs/
+[Ll]ogs/
-[Dd]ata/
+[Dd]ata
+[Cc]ache
 *.egg-info/
+credentials*
+

logging.yaml

@@ -15,7 +15,7 @@ handlers:
         class: logging.handlers.RotatingFileHandler
         level: INFO
         formatter: simple
-        filename: Logs/info.log
+        filename: logs/info.log
         maxBytes: 10485760 # 10MB
         backupCount: 20
         encoding: utf8
@@ -24,7 +24,7 @@ handlers:
         class: logging.handlers.RotatingFileHandler
         level: ERROR
         formatter: simple
-        filename: Logs/errors.log
+        filename: logs/errors.log
         maxBytes: 10485760 # 10MB
         backupCount: 20
         encoding: utf8

minigrida/database/helpers.py

@@ -12,8 +12,11 @@ from pony import orm
 from datetime import datetime, date
 import json
 import hashlib
+import logging
 
-from .design import *
+from .design import Session, Experiment, Project, db
+
+log = logging.getLogger()
 
 def compute_expe_hash(experiment):
     return hashlib.md5(json.dumps(experiment, sort_keys=True).encode('utf-8')).hexdigest()
@@ -31,7 +34,7 @@ def create_experiment(session_name, protocol, expe, urgency=1):
         e = q.first()
         e.sessions.add(session)
     else:
-        Experiment(sessions=session, protocol=protocol, expe=experiment, expe_hash=expe_hash)
+        Experiment(sessions=session, protocol=protocol, expe=expe, expe_hash=expe_hash)
 
 @orm.db_session
 def create_project(name):
@@ -50,13 +53,46 @@ def create_session(name, desc, project_name, urgency=1):
     else:
         print('Session "{}" already exists.'.format(name))
 
+@orm.db_session
+def pending_experiments():
+    return Experiment.select(lambda x: x.status == 'pending').exists()
+
+@orm.db_session
+def next_experiment():
+    # TODO: take session urgency into account
+    expe = orm.select(e for e in Experiment
+                      if e.status == 'pending'
+                      and e.urgency == orm.max(e.urgency for e in Experiment
+                                               if e.status == 'pending')
+                      ).random(1)
+    if expe:
+        expe = expe[0]
+        expe.status = 'staging'
+        return expe
+
+
+def update_experiment(expe, **params):
+    try:
+        _update_experiment(expe, **params)
+    except orm.DatabaseError as e:
+        log.error(e)
+        log.info('Retry update')
+        _update_experiment(expe, **params)
+
+@orm.db_session
+def _update_experiment(expe, **params):
+    e = Experiment.select(lambda x: x.id == expe.id).first()
+    for k, v in params.items():
+        setattr(e, k, v)
+
+
 def connect_testing():
     db.bind('sqlite', ':memory:')
     db.generate_mapping(create_tables=True)
 
+
 def connect(credentials_file):
     with open(credentials_file) as f:
         credentials = json.load(f)
         db.bind(**credentials)
     db.generate_mapping(create_tables=True)
-

minigrida/descriptors/dfc_base.py

@@ -1,4 +1,4 @@
-#!/usr/bin/python
+j#!/usr/bin/python
 # -*- coding: utf-8 -*-
 # \file dfc_base.py
 # \brief TODO

minigrida/descriptors/pixel.py

@@ -0,0 +1,37 @@
+#!/usr/bin/env python
+# file pixel.py
+# author Florent Guiotte <florent.guiotte@irisa.fr>
+# version 0.0
+# date 26 mai 2020
+"""Abstract
+
+doc.
+"""
+
+import numpy as np
+
+
+def run(gt, rasters, remove=None):
+    X = []
+    y = []
+    groups = []
+
+    for i, (gti, rastersi) in enumerate(zip(gt, rasters)):
+        # Create vectors
+        X_raw = np.moveaxis(np.array(list(rastersi.values())), 0, -1)
+        y_raw = gti
+
+        # Remove unwanted label X, y
+        lbl = np.ones_like(y_raw, dtype=np.bool)
+        for l in remove if remove else []:
+            lbl &= y_raw != l
+
+        X += [X_raw[lbl]]
+        y += [y_raw[lbl]]
+        groups += [np.repeat(i, lbl.sum())]
+
+    X = np.concatenate(X)
+    y = np.concatenate(y)
+    groups = np.concatenate(groups)
+
+    return X, y, groups

minigrida/loader/__init__.py

@@ -0,0 +1,9 @@
+#!/usr/bin/env python
+# file __init__.py
+# author Florent Guiotte <florent.guiotte@irisa.fr>
+# version 0.0
+# date 26 mai 2020
+"""Abstract
+
+doc.
+"""

minigrida/loader/tiles.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python
+# file tiles.py
+# author Florent Guiotte <florent.guiotte@irisa.fr>
+# version 0.0
+# date 26 mai 2020
+"""Abstract
+
+doc.
+"""
+
+from pathlib import Path
+import rasterio as rio
+
+
+def run(tiles_count, gt_path, gt_name, rasters_path, rasters_name):
+    gt = []
+    rasters = []
+
+    for i in range(tiles_count):
+        gt += [load_tif(raster_path(gt_path, gt_name, i))]
+        rasters += [{Path(n).stem: load_tif(raster_path(rasters_path, n, i))
+                     for n in rasters_name}]
+
+    return gt, rasters
+
+
+def load_tif(path):
+    return rio.open(str(path)).read()[0]
+
+
+def raster_path(path, name, i):
+    return Path(path) / '{}_{}_{}.tif'.format(Path(name).stem, 0, i)

minigrida/protocols/__init__.py

@@ -7,3 +7,6 @@
 # \date 09 sept. 2018
 #
 # TODO details
+
+#from .jurse import Jurse
+from .jurse2 import Jurse2

minigrida/protocols/jurse2.py

@@ -11,7 +11,6 @@ doc.
 import importlib
 import numpy as np
 from sklearn import metrics
-import rasterio
 from .protocol import Protocol, TestError
 
 
@@ -23,58 +22,50 @@ class Jurse2(Protocol):
     def __init__(self, expe):
         super().__init__(expe, self.__class__.__name__)
 
-    def _get_hashes(self):
-        hashes = OrderedDict()
-        glob = hashlib.sha1()
-
-        for k in ['ground_truth', 'descriptors_script',
-                  'cross_validation', 'classifier']:
-            val = str(self._expe[k]).encode('utf-8')
-            hashes[k] = hashlib.sha1(val).hexdigest()
-            glob.update(val)
-        hashes['global'] = glob.hexdigest()
-
-        return hashes
-
     def _run(self):
+        self._log.info('Load data')
+        try:
+            data = self._load_data()
+        except Exception:
+            raise TestError('Error occured during data loading')
+
         self._log.info('Compute descriptors')
         try:
-            descriptors = self._compute_descriptors()
+            descriptors = self._compute_descriptors(data)
         except Exception:
             raise TestError('Error occured during description')
-        self._time('description')
 
-        self._log.info('Classify data')
+        self._log.info('Classify descriptors')
         try:
             classification = self._compute_classification(descriptors)
         except Exception:
             raise TestError('Error occured during classification')
-        self._time('classification')
 
         self._log.info('Run metrics')
         metrics = self._run_metrics(classification, descriptors)
-        self._time('metrics')
 
-        cmap = str(self._results_base_name) + '.tif'
+        results = {}
-        self._log.info('Saving classification map {}'.format(cmap))
-        triskele.write(cmap, classification)
-
-        results = OrderedDict()
-        results['classification'] = cmap
         results['metrics'] = metrics
         self._results = results
 
-    def _compute_descriptors(self):
+    def _load_data(self):
+        data_loader = self._expe['data_loader']
+
+        loader = importlib.import_module(data_loader['name'])
+        data = loader.run(**data_loader['parameters'])
+
+        return data
+
+    def _compute_descriptors(self, data):
         script = self._expe['descriptors_script']
 
         desc = importlib.import_module(script['name'])
-        att = desc.run(**script['parameters'])
+        att = desc.run(*data, **script['parameters'])
 
         return att
 
     def _compute_classification(self, descriptors):
-        # Ground truth
+        X, y, groups = descriptors
-        gt = self._get_ground_truth()
 
         # CrossVal and ML
         cv = self._expe['cross_validation']
@@ -83,46 +74,40 @@ class Jurse2(Protocol):
         cross_val = getattr(importlib.import_module(cv['package']), cv['name'])
         classifier = getattr(importlib.import_module(cl['package']), cl['name'])
 
-        prediction = np.zeros_like(gt, dtype=np.uint8)
+        y_pred = np.zeros_like(y)
 
-        for xt, xv, yt, yv, ti in cross_val(gt, descriptors, **cv['parameters']):
+        cvi = cross_val(**cv['parameters'])
-            rfc = classifier(**cl['parameters'])
+        for train_index, test_index in cvi.split(X, y, groups):
-            rfc.fit(xt, yt)
+            cli = classifier(**cl['parameters'])
 
-            ypred = rfc.predict(xv)
+            self._log.info('  - fit')
+            cli.fit(X[train_index], y[train_index])
 
-            prediction[ti] = ypred
+            self._log.info('  - predict')
+            y_pred[test_index] = cli.predict(X[test_index])
 
-        return prediction
+        return y_pred
-
-    def _get_ground_truth(self):
-        gt_expe = self._expe['ground_truth']
-        gt = triskele.read(gt_expe['raster'])
-
-        # Meta labeling
-        idx_map = np.arange(gt.max() + 1)
-
-        if 'meta_labels' in gt_expe:
-            meta_idx = pd.read_csv(gt_expe['meta_labels'])
-            idx = np.array(meta_idx['index'])
-            midx = np.array(meta_idx['metaclass_index'])
-            idx_map[idx] = midx
-
-        return idx_map[gt]
 
     def _get_results(self):
         return self._results
 
     def _run_metrics(self, classification, descriptors):
-        gt = self._get_ground_truth()
+        X, y_true, groups = descriptors
+        y_pred = classification
 
-        f = np.nonzero(classification)
+        self._log.info('  - Scores')
-        pred = classification[f].ravel()
+        self.oa = metrics.accuracy_score(y_true, y_pred)
-        gt = gt[f].ravel()
+        self.aa = metrics.balanced_accuracy_score(y_true, y_pred)
+        self.k = metrics.cohen_kappa_score(y_true, y_pred)
 
-        results = OrderedDict()
+        self._log.info('  - Additional results')
-        results['dimensions'] = descriptors.shape[-1]
+        p, r, f, s = metrics.precision_recall_fscore_support(y_true, y_pred)
-        results['overall_accuracy'] = float(metrics.accuracy_score(gt, pred))
+        cm = metrics.confusion_matrix(y_true, y_pred)
-        results['cohen_kappa'] = float(metrics.cohen_kappa_score(gt, pred))
+        results = {'dimensions': X.shape[-1],
+                   'precision': p.tolist(),
+                   'recall': r.tolist(),
+                   'f1score': f.tolist(),
+                   'support': s.tolist(),
+                   'confusion': cm.tolist()}
 
         return results

minigrida/protocols/protocol.py

@@ -11,52 +11,41 @@
 import logging
 import time
 
+
 class Protocol:
     def __init__(self, expe, name=None):
         self._log = logging.getLogger(name)
         self._expe = expe
         self._name = name
         self._log.debug('expe loaded: {}'.format(self._expe))
-
+        self.k = None
-    def get_hashes(self):
+        self.oa = None
-        self._log.info('Computing hashes')
+        self.aa = None
-        return(self._get_hashes())
-
-    def set_results_base_name(self, base_name):
-        self._results_base_name = base_name
 
     def run(self):
-        self._pt = time.process_time()
+        spt = time.process_time()
         self._run()
+        self._pt = time.process_time() - spt
 
     def get_results(self):
         return self._get_results()
 
     def get_process_time(self):
-        return self._times
+        return self._pt
-
-    def _time(self, process):
-        self._times[process] = time.process_time() - self._pt
-        self._pt = time.process_time()
-
-    def _get_hashes(self):
-        self._log.warning('Protocol did not override _get_hashes()')
-        hashes = OrderedDict()
-        hashes['global'] = 'Protocol did not override _get_hashes()'
-        return hashes
 
     def _run(self):
         self._log.error('Protocol did not override _run()')
-        raise NotImplementedError('Protocol {} did not override _run()'.format(self))
+        raise NotImplementedError('Protocol {} did not override _run()'
+                                  .format(self))
 
     def _get_results(self):
         self._log.warning('Protocol did not override _get_results()')
-        results = OrderedDict()
+        results = {}
         results['global'] = 'Protocol did not override _get_results()'
         return results
 
     def __str__(self):
-        return('{}'.format(self._name))
+        return '{}'.format(self._name)
 
 
 class TestError(Exception):

minigrida/supervisor.py

@@ -9,189 +9,75 @@
 # TODO details
 
 import importlib
-import json
 import time
 import os
-import datetime
+from datetime import datetime
-from pathlib import Path
-from operator import itemgetter
 import traceback
 import logging
 import logger
 from protocols.protocol import TestError
 import database
 
-log = logging.getLogger('Supervisor [{}]'.format(os.uname()[1]))
+host = os.uname()[1]
-
+log = logging.getLogger('Supervisor [{}]'.format(host))
-def update_queue():
-    tmp_queue = list()
-    for child in TEST_DIR.iterdir():
-        if child.is_file() and child.suffix == '.yml':
-            tmp_queue.append({'expe_file': ExpePath(child),
-                              'priority': get_priority(child)})
-
-    queue = sorted(tmp_queue, key=itemgetter('priority'))
-    return queue
 
 
-def get_priority(yml_file):
+def run(expe):
-    with open(yml_file) as f:
+    database.update_experiment(expe, worker=host, start_date=datetime.now())
-        expe = OrderedDict(yaml.safe_load(f))
-    return expe['priority']
 
+    # Load protocol
+    log.info('Load protocol {}'.format(expe.protocol))
+    protocol_module = importlib.import_module('protocols')
+    importlib.reload(protocol_module)
+    protocol = getattr(protocol_module, expe.protocol)
+    test = protocol(expe.expe)
 
-def run(expe_file):
+    # Run test
-    start_time = time.time()
-    log.info('Run test {}'.format(expe_file))
-    test = expe_file.read()
-
-    ### Stage experience
-    expe_file.stage(test)
-
-    ### Load protocol
     try:
-        #protocol = getattr(importlib.import_module(test['protocol']['package']), test['protocol']['name'])
+        test.run()
-        protocol_module = importlib.import_module(test['protocol']['package'])
-        importlib.reload(protocol_module)
-        protocol = getattr(protocol_module, test['protocol']['name'])
-        experience = protocol(test['expe'])
-    except Exception as e:
-        err = 'Could not load protocol from test {}'.format(expe_file)
-        log.warning(err)
-        expe_file.error(test, 'loading protocol', e)
-        raise TestError(err)
-    log.info('{} test protocol loaded'.format(experience))
-
-    ### Get hashes
-    test['hashes'] = experience.get_hashes()
-    test['report'] = create_report(experience, start_time)
-
-    ### Stage experience
-    expe_file.stage(test)
-
-    experience.set_results_base_name(expe_file.get_result_path())
-
-    ### Run test
-    try:
-        experience.run()
     except Exception as e:
         err = 'Experience error'
         log.warning(err)
-        expe_file.error(test, 'testing', e)
+        report = {'error': {'name': str(err),
+                            'trace': traceback.format_exc()}}
+        database.update_experiment(expe, report=report, status='error')
         raise TestError(err)
 
-    end_time = time.time()
+    # Write report
+    log.info('Write report')
+    database.update_experiment(expe,
+                               end_date=datetime.now(),
+                               oa=test.oa,
+                               aa=test.aa,
+                               k=test.k,
+                               report=test.get_results(),
+                               status='complete')
 
-    ### Get complete report
+    # End of test
-    test['report'] = create_report(experience, start_time, end_time)
+    log.info('Expe {} complete'.format(expe.expe_hash))
 
-    ### Get results
-    test['results'] = experience.get_results()
-
-    ### Write experience
-    expe_file.result(test)
-
-    ### End of test
-    log.info('Test complete')
-
-def create_report(experience, stime=None, etime=None):
-    expe_report = OrderedDict()
-    host = os.getenv("HOST")
-    expe_report['supervisor'] = host if host is not None else os.uname()[1]
-
-    # Dates
-    for datek, timev in zip(('start_date', 'end_date'), (stime, etime)):
-        expe_report[datek] = datetime.datetime.fromtimestamp(timev).strftime('Le %d/%m/%Y à %H:%M:%S') if timev is not None else None
-
-    # Ressources
-    ressources = OrderedDict()
-    ressources['ram'] = None
-    ressources['proccess_time'] = experience.get_process_time()
-    expe_report['ressources'] = ressources
-
-    return expe_report
-
-class ExpePath:
-    """Utility wrapper for expe files.
-
-    Extend pathlib Path with staging, result and errors function to move the
-    test report through the Enrichment center.
-
-    """
-    def __init__(self, path, hash_length=6):
-        self._actual = Path(path)
-        self._base_name = self._actual.stem
-        self._hash_length = hash_length
-        self._hash = None
-
-    def __str__(self):
-        return self._get_complete_name()
-
-    def read(self):
-        with open(self._actual) as f:
-            return OrderedDict(yaml.safe_load(f))
-
-    def _get_hash_name(self):
-        return '{}{}'.format(self._base_name,
-                '_' + self._hash[:self._hash_length] if self._hash is not None else '')
-
-    def _get_complete_name(self):
-        return self._get_hash_name() + '.yml'
-
-    def exists(self):
-        return self._actual.exists()
-
-    def stage(self, expe):
-        log.info('Staging {}'.format(self._base_name))
-        self._check_hash(expe)
-        self._write(STAGING_DIR, expe)
-
-    def result(self, expe):
-        log.info('Write results for test {}'.format(self._base_name))
-        self._check_hash(expe)
-        self._write(RESULT_DIR, expe)
-
-    def error(self, expe, when='', e=Exception):
-        error = OrderedDict()
-        error['when'] = when
-        error['what'] = str(e)
-        error['where'] = traceback.format_exc()
-        expe['error'] = error
-        self._write(FAILED_DIR, expe)
-
-    def get_result_path(self):
-        return Path(RESULT_DIR) / self._get_hash_name()
-
-def get_database():
 
 def main():
-    print('Hello again')
+    log.info('Connecting to database')
-    database
+    database.connect('credentials.json')
-    return
+
     while(True):
-        try:
+        if not database.pending_experiments():
-            queue = update_queue()
+            log.info('No pending experiments, waiting...')
-        except Exception:
+            time.sleep(30)
-            log.error('Critical exception while updating work queue')
+
-            log.error(traceback.format_exc())
+        else:
-            log.warning('Resuming')
+            log.info('Loading next experiment')
-            continue
+            expe = database.next_experiment()
-        if not queue:
+            if not expe:
-            watch_folder()
+                continue
-            continue
+            log.info('Expe {} loaded'.format(expe.expe_hash))
-        try:
+            try:
-            expe_file = queue.pop()['expe_file']
+                run(expe)
-            while(not expe_file.exists() and queue):
+            except Exception as e:
-                expe_file = queue.pop()['expe_file']
+                log.error(e)
-            if expe_file.exists():
+                log.error('Error occured on expe {}'.format(expe.id))
-                run(expe_file)
+
-        except TestError:
-            log.warning('Test failed, error logged. Resuming')
-        except Exception:
-            log.error('Critical exception while running test. Resuming')
-            log.error(traceback.format_exc())
-            log.warning('Resuming')
-            continue
 
 if __name__ == '__main__':
     logger.setup_logging()