Merge pull request #2578 from SasView/moving_to_sas

Webfit in parallel to qtGUI

.gitignore

@@ -39,6 +39,7 @@ default_categories.json
 **/UI/*.py
 !**/UI/__init__.py
 config.json
+**/db.sqlite3
 
 # doc build
 /docs/sphinx-docs/build

src/sas/webfit/analyze/admin.py

@@ -0,0 +1,3 @@
+from django.contrib import admin
+
+# Register your models here.

src/sas/webfit/analyze/apps.py

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+from django.apps import AppConfig
+
+
+class DataConfig(AppConfig):
+    default_auto_field = "django.db.models.BigAutoField"
+    name = "analyze"

src/sas/webfit/analyze/fitting/admin.py

@@ -0,0 +1,4 @@
+from django.contrib import admin
+from .models import Fit, FitParameter
+
+# Register your models here.

src/sas/webfit/analyze/fitting/apps.py

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+from django.apps import AppConfig
+
+
+class FittingConfig(AppConfig):
+    default_auto_field = "django.db.models.BigAutoField"
+    name = "analyze.fitting"

src/sas/webfit/analyze/fitting/migrations/0001_initial.py

@@ -0,0 +1,40 @@
+# Generated by Django 4.2.2 on 2023-08-10 22:02
+
+from django.db import migrations, models
+import django.db.models.deletion
+
+
+class Migration(migrations.Migration):
+
+    initial = True
+
+    dependencies = [
+        ('analyze', '0001_initial'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='Fit',
+            fields=[
+                ('analysisbase_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='analyze.analysisbase')),
+                ('results', models.CharField(blank=True, help_text='the string result', max_length=1000000, null=True)),
+                ('status', models.IntegerField(choices=[(1, 'Queued'), (2, 'Running'), (3, 'Complete')], default=1)),
+                ('q_minimum', models.FloatField(blank=True, default=0.0005, help_text='Minimum Q value for the fit', null=True)),
+                ('q_maximum', models.FloatField(blank=True, default=0.5, help_text='Maximum Q value for the fit', null=True)),
+                ('polydispersity', models.BooleanField(default=False, help_text='Is polydispersity being checked in this model')),
+                ('magnetism', models.BooleanField(default=False, help_text='Is magnetism being checked in this model?')),
+                ('model', models.CharField(help_text='model string', max_length=256)),
+                ('optimizer', models.CharField(blank=True, help_text='optimizer string', max_length=50)),
+            ],
+            bases=('analyze.analysisbase',),
+        ),
+        migrations.CreateModel(
+            name='FitParameter',
+            fields=[
+                ('analysisparameterbase_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='analyze.analysisparameterbase')),
+                ('polydisperse', models.BooleanField(default=False, help_text='Is this a polydisperse parameter?')),
+                ('magnetic', models.BooleanField(default=False, help_text='is this a magnetic parameter?')),
+            ],
+            bases=('analyze.analysisparameterbase',),
+        ),
+    ]

src/sas/webfit/analyze/fitting/models.py

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+from logging import getLogger
+
+from django.db import models
+
+from ..models import AnalysisBase, AnalysisParameterBase
+
+models_logger = getLogger(__name__)
+
+class Fit(AnalysisBase):
+    results = models.CharField(max_length=1000000, blank=True, 
+                               null=True, help_text="the string result")
+    results_trace = [
+    ]
+
+    class StatusChoices(models.IntegerChoices):
+        QUEUED = 1, "Queued"
+        RUNNING = 2, "Running"
+        COMPLETE = 3, "Complete"
+
+    status = models.IntegerField(default=StatusChoices.QUEUED, choices=StatusChoices.choices)
+
+    q_minimum = models.FloatField(default=0.0005, null=True, 
+                                 blank=True, help_text="Minimum Q value for the fit")
+    q_maximum = models.FloatField(default=0.5, null=True, 
+                                 blank=True, help_text="Maximum Q value for the fit")
+
+    polydispersity = models.BooleanField(default=False, 
+                                         help_text="Is polydispersity being checked in this model")
+
+    magnetism = models.BooleanField(default=False, 
+                                    help_text="Is magnetism being checked in this model?")
+
+    model = models.CharField(blank=False, max_length=256, 
+                             help_text="model string")
+
+    optimizer = models.CharField(blank=True, max_length=50, 
+                                 help_text="optimizer string")
+
+
+class FitParameter(AnalysisParameterBase):
+    polydisperse = models.BooleanField(default=False, 
+                                       help_text="Is this a polydisperse parameter?")
+
+    magnetic = models.BooleanField(default=False, 
+                                   help_text="is this a magnetic parameter?")

src/sas/webfit/analyze/fitting/tests.py

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+# Create your tests here.
+import shutil
+import json
+
+from django.conf import settings
+from django.test import TestCase
+from django.contrib.auth.models import User
+from django.shortcuts import get_object_or_404
+from rest_framework import status
+from rest_framework.test import APIRequestFactory, APIClient, force_authenticate, APITestCase
+
+from sasmodels.data import empty_data1D
+from sasdata.dataloader.loader import Loader
+import numpy as np
+
+from data.models import Data
+from .models import (
+    Fit,
+    FitParameter
+)
+from .views import (
+    start,
+    start_fit,
+)
+
+factory = APIRequestFactory()
+
+# Create your tests here.
+class TestLists(APITestCase):
+    """def setUp(self):
+        self.user = User.objects.create_user(username="testUser", password="secret", id = 2)
+        self.client = APIClient()
+        self.client.force_authenticate(user=self.user)"""
+
+    #working
+    def get_model_list(self):
+        request = self.client.post('/v1/analyze/fit/models/')
+        self.assertEqual(request.data, {"all models":['adsorbed_layer', 'barbell', 'bcc_paracrystal', 'be_polyelectrolyte', 'binary_hard_sphere', 'broad_peak', 'capped_cylinder', 'core_multi_shell', 'core_shell_bicelle', 'core_shell_bicelle_elliptical', 'core_shell_bicelle_elliptical_belt_rough', 'core_shell_cylinder', 'core_shell_ellipsoid', 'core_shell_parallelepiped', 'core_shell_sphere', 'correlation_length', 'cylinder', 'dab', 'ellipsoid', 'elliptical_cylinder', 'fcc_paracrystal', 'flexible_cylinder', 'flexible_cylinder_elliptical', 'fractal', 'fractal_core_shell', 'fuzzy_sphere', 'gauss_lorentz_gel', 'gaussian_peak', 'gel_fit', 'guinier', 'guinier_porod', 'hardsphere', 'hayter_msa', 'hollow_cylinder', 'hollow_rectangular_prism', 'hollow_rectangular_prism_thin_walls', 'lamellar', 'lamellar_hg', 'lamellar_hg_stack_caille', 'lamellar_stack_caille', 'lamellar_stack_paracrystal', 'line', 'linear_pearls', 'lorentz', 'mass_fractal', 'mass_surface_fractal', 'mono_gauss_coil', 'multilayer_vesicle', 'onion', 'parallelepiped', 'peak_lorentz', 'pearl_necklace', 'poly_gauss_coil', 'polymer_excl_volume', 'polymer_micelle', 'porod', 'power_law', 'pringle', 'raspberry', 'rectangular_prism', 'rpa', 'sc_paracrystal', 'sphere', 'spherical_sld', 'spinodal', 'squarewell', 'stacked_disks', 'star_polymer', 'stickyhardsphere', 'superball', 'surface_fractal', 'teubner_strey', 'triaxial_ellipsoid', 'two_lorentzian', 'two_power_law', 'unified_power_Rg', 'vesicle']})
+
+    #working
+    def get_model_list_category(self):
+        data = {
+            "category":"Cylinder"
+        }
+        request = self.client.post('/v1/analyze/fit/models/', data, format='json')
+        self.assertEqual(request.data, {"Cylinder models":[['barbell', True], ['capped_cylinder', True], ['core_shell_bicelle', True], ['core_shell_bicelle_elliptical', True], ['core_shell_bicelle_elliptical_belt_rough', True], ['core_shell_cylinder', True], ['cylinder', True], ['elliptical_cylinder', True], ['flexible_cylinder', True], ['flexible_cylinder_elliptical', True], ['hollow_cylinder', True], ['pearl_necklace', True], ['pringle', True], ['stacked_disks', True]]})
+
+    #working
+    def get_model_list_kind(self):
+        data = {
+            "kind":"py"
+        }
+        request = self.client.post('/v1/analyze/fit/models/', data, format='json')
+        self.assertEqual(request.data, {"py models":['adsorbed_layer', 'be_polyelectrolyte', 'broad_peak', 'correlation_length', 'gauss_lorentz_gel', 'guinier_porod', 'line', 'peak_lorentz', 'poly_gauss_coil', 'polymer_excl_volume', 'porod', 'power_law', 'spinodal', 'teubner_strey', 'two_lorentzian', 'two_power_law', 'unified_power_Rg']})
+
+    def get_optimizer_list(self):
+        request = self.client.get('/v1/analyze/fit/optimizers/')
+        self.assertEqual(request.data, {"optimizers": [['amoeba', 'de', 'dream', 'newton', 'scipy.leastsq', 'lm']]})
+
+
+class TestFitStart(TestCase):
+    def setUp(self):
+        self.user = User.objects.create_user(username="testUser", password="secret", id = 1)
+        self.client = APIClient()
+        self.client.force_authenticate(user=self.user)
+
+        self.public_test_data = Data.objects.create(id = 2, file_name = "cyl_400_20.txt", is_public = True)
+        self.public_test_data.file.save("cyl_400_20.txt", open(r"../src/sas/example_data/1d_data/cyl_400_20.txt"))
+
+        #self.private_test_data = Data.objects.create(id = 3, current_user = self.user, file_name = "another.txt", is_public = False)
+        #self.private_test_data.file.save("another.txt",open(r""))
+
+        """self.fit = Fit.objects.create(id = 4, current_user = self.user, data_id = self.public_test_data, model = "cylinder", optimizer = "amoeba")
+        self.radius = FitParameter.objects.create(id = 5, base_id = self.fit, name = "radius", value = 35, data_type = "int", lower_limit = 1, upper_limit = 50)
+        self.length = FitParameter.objects.create(id = 6, base_id = self.fit, name = "length", value = 350, data_type = "int", lower_limit = 1, upper_limit = 500)
+        self.background = FitParameter.objects.create(id = 7, base_id = self.fit, name = "background", value = 0.0, data_type = "float")
+        self.scale = FitParameter.objects.create(id = 8, base_id = self.fit, name = "scale", value = 1.0, data_type = "float")
+        self.sld = FitParameter.objects.create(id = 9, base_id = self.fit, name = "sld", value = 4.0, data_type = "float")
+        self.sld_solvent = FitParameter.objects.create(id = 10, base_id = self.fit, name = "sld_solvent", value = 1.0, data_type = "float")
+        self.all_params = [self.radius, self.length, self.background, self.scale, self.sld, self.sld_solvent]"""
+
+    def test_can_fit_start_give_correct_answer(self):
+        data = Data.objects.get(is_public = True)
+        chisq = start_fit(fit_db=self.fit, par_dbs=self.all_params)
+        self.assertEqual(chisq,"0.03(13)")
+
+    def test_can_fit_give_right_answer(self):
+        data = {
+            "model":"cylinder",
+            "data_id":2,
+            "optimizer":"amoeba",
+            "parameters" : 
+            [
+                {
+                    "name":"radius",
+                    "value":35,
+                    "data_type":"int",
+                    "lower_limit":1,
+                    "upper_limit":50
+                },
+                {
+                    "name":"length",
+                    "value":350,
+                    "data_type":"int",
+                    "lower_limit":1,
+                    "upper_limit":500
+                },
+                {
+                    "name":"background",
+                    "value":0.0,
+                    "data_type":"float"
+                },
+                {
+                    "name":"scale",
+                    "value":1.0,
+                    "data_type":"float"
+                },
+                {
+                    "name":"sld",
+                    "value":4.0,
+                    "data_type":"float"
+                },
+                {
+                    "name":"sld_solvent",
+                    "value":1.0,
+                    "data_type":"float"
+                }
+            ]
+        }
+        request = self.client.post('/v1/analyze/fit/', data=json.dumps(data), content_type="application/json")
+        self.assertEqual(request.data,{'authenticated': True, 'fit_id': 1, 'results': '0.03(13)'})
+
+    def tearDown(self):
+        shutil.rmtree(settings.MEDIA_ROOT)
+
+class TestLoader(TestCase):
+
+    def testing_loader(self):
+        test_data = get_object_or_404(Data, is_public=True)
+        loader = Loader()
+        loader.load(test_data.file.path)
+
+    def testing_syntax(self):
+        test_data = Data.objects.create(id = 2, is_public = True)
+        self.assertEqual("cyl_400_20.txt",test_data.current_user)
+
+    def tearDown(self):
+        shutil.rmtree(settings.MEDIA_ROOT)

src/sas/webfit/analyze/fitting/urls.py

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+import logging
+from django.urls import path, re_path, include
+from . import views
+
+logger = logging.getLogger(__name__)
+
+#info urls
+info_patterns = [
+    path("", views.fit_info),
+    path("status/", views.status, name = "get status using fit_id"),
+    path("parameters/", views.view_parameters, name = "current parameters"),
+    #TODO impliment parameter trace
+    #path("parameter_history/"),
+    #TODO allow user to find specific parts of results
+    path("results/", views.view_results, name = "current results"),
+    #TODO impliment results trace
+    #path("results_history/")
+]
+
+#urls to fit
+urlpatterns = [
+    path("", views.start, name = "starting a fit"),
+    path("status/", views.status, name = "get status of all user's fits"),  
+    path("<int:fit_id>/", include(info_patterns), name = "get fit info"),
+    path("optimizers/", views.list_optimizers, name = "lists all fit optimizers"),
+    path("models/", views.list_model, name = "lists all fit models"),
+    path("models/<str:category>/", views.list_model, name = "lists all fit models"),
+    path("models/<str:kind>/", views.list_model, name = "lists all fit models"),
+]