index int64 | repo_name string | branch_name string | path string | content string | import_graph string |
|---|---|---|---|---|---|
46,517 | AnthonyMrt/Poyosei | refs/heads/master | /models/modelsHistorique.py | from django.db import models
# from decimal import Decimal
# from django.utils import timezone
# from django.forms import DateTimeField
# from project import settings
# from django.db.models import Q
# from django.db.models.signals import post_save
# from poyosei.models import *
# from django.shortcuts import get_object_or_404
# from datetime import datetime
from simple_history.models import HistoricalRecords
class planteurHistorique(models.model):
pacage = models.ForeignKey(Planteur, on_delete=models.CASCADE)
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,518 | AnthonyMrt/Poyosei | refs/heads/master | /models/modelsProductionCommerciale.py | from django.db import models
from decimal import Decimal
# from django.utils import timezone
# from django.forms import DateTimeField
# from datetime import datetime
# from project import settings
from poyosei.models import *
class ProductionCommerciale(models.Model):
pacage = models.CharField(max_length=9)
année = models.CharField(max_length=4)
production_commerciale = models.DecimalField(
max_digits=9, decimal_places=0, default=Decimal('0'))
class Meta:
app_label = 'poyosei'
unique_together = ('pacage', 'année',)
def __str_(self):
return self.pacage
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,519 | AnthonyMrt/Poyosei | refs/heads/master | /forms/formsTypeMouvement.py | from django import forms
from django.contrib.admin import widgets
from django.forms import ModelChoiceField
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Div, Submit, HTML, Button, Row, Field
from crispy_forms.bootstrap import AppendedText, PrependedText, FormActions
from poyosei.models import *
from datetime import datetime
class TypeMouvementForm(forms.ModelForm):
class Meta:
model = typeMouvement
fields = '__all__'
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,520 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0026_auto_20180814_1107.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-14 15:07
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0025_auto_20180814_1051'),
]
operations = [
migrations.RemoveField(
model_name='exportcampagne',
name='planteur',
),
migrations.RemoveField(
model_name='exportcampagne',
name='statistique',
),
migrations.AlterField(
model_name='statistique',
name='pacage',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='poyosei.Planteur'),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,521 | AnthonyMrt/Poyosei | refs/heads/master | /views/viewsRelation.py | from django.shortcuts import render, redirect
# from django.views import View
# from django.views.generic.edit import UpdateView
from poyosei.forms import *
# from django.views.decorators.csrf import csrf_exempt
from poyosei.models import *
# from poyosei.ressources import PlanteurResource, mouvementResource
# from tablib import Dataset
# import json
# @csrf_exempt
def planteurAjoutRelation(request, pacage):
form = RelationForm(initial={'pacageA':pacage})
relations = Relation.objects.filter(pacageA=pacage)
if request.method == 'POST':
form = RelationForm(request.POST, initial={'pacageA':pacage})
if form.is_valid():
form.save()
return redirect('poyosei:planteurEditer', pacage=pacage)
return render(request, 'relation/ajout.html', {"active_tab": "operation", 'form':form, 'relations':relations})
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,522 | AnthonyMrt/Poyosei | refs/heads/master | /views/viewsStatic.py | from django.db.models import Avg, Sum
from django.shortcuts import render
from poyosei.models import *
def home(request):
return render(request, 'pages/home.html')
def index(request):
planteurs = Planteur.objects.all()
mouvements = Mouvement.objects.all()
campagne = Campagne.objects.all()
c = Campagne.objects.order_by('annee').last()
moyenne = Mouvement.objects.all().aggregate(Avg('quantite_reference_individuelle_accorde'))['quantite_reference_individuelle_accorde__avg'] or 0.00
total = Mouvement.objects.all().aggregate(Sum('quantite_reference_individuelle_accorde'))['quantite_reference_individuelle_accorde__sum'] or 0.00
Cannee = int(c.annee)
return render(request, 'index.html', {'planteurs': planteurs, 'mouvements': mouvements, 'campagne': campagne, 'moyenne':moyenne, 'total':total, 'Cannee':Cannee })
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,523 | AnthonyMrt/Poyosei | refs/heads/master | /models/modelsPlanteur.py | from django.db import models
from decimal import Decimal
from django.utils import timezone
from django.forms import DateTimeField
from project import settings
from django.db.models import Q
from django.db.models.signals import post_save
from poyosei.models import *
from django.shortcuts import get_object_or_404
from datetime import datetime
from simple_history.models import HistoricalRecords
from django.db.models import ForeignKey
from statistics import *
CIVILITE_CHOICE = (
('Mr', 'Monsieur'),
('gérant', 'Mr le gérant'),
('gérante', 'Mme la gérante'),
('Mme', 'Madame'),
('Societe', 'Societe'),
('Autre', 'Autre'),
('', '')
)
class Planteur(models.Model):
pacage = models.CharField("Numéro pacage", max_length=9,
primary_key=True, help_text="Un nombre de 9 chiffres")
civilite = models.CharField(
"Civilité", max_length=20, choices=CIVILITE_CHOICE, default='', blank=True)
nom = models.CharField("Nom", max_length=200,
help_text="200 caractères maximum.")
prenom = models.CharField("Prénom", max_length=100,
help_text="200 caractères maximum.")
siret = models.CharField("SIRET", max_length=14, blank=True,
help_text="code Insee permettant l'identification d'un établissement ou d'une entreprise française.", null=True)
LPG = models.CharField("Numéro LPG", max_length=100, blank=True,
help_text="Identifiant LPG du planteur.", null=True)
contre_marque = models.CharField(
"Contremarque", max_length=100, blank=True, null=True)
denomination = models.TextField(
"Dénomination", help_text="Texte d'aide", null=True, max_length=100, blank=True)
gerant = models.TextField(
"Gérant", help_text="Texte d'aide", null=True, blank=True)
adresse = models.CharField(
"Adresse", help_text="Adresse du planteur", max_length=255, null=True, blank=True)
adresse_complementaire = models.CharField(
max_length=255, null=True, blank=True)
code_postal = models.CharField(
"Code postal", help_text="Code postal planteur", null=True, max_length=10, blank=True)
commune = models.CharField(
"Commune", max_length=100, help_text="Commune du planteur", blank=True, null=True)
telephone_principale = models.CharField(
"Numéro de téléphone", null=True, help_text='Téléphone de contact', max_length=50, blank=True)
telephone_secondaire = models.CharField(
"Autre téléphone", help_text='téléphone de contact', max_length=50, null=True, blank=True)
courriel = models.EmailField(
"Courriel", help_text="Adresse de courriel de contact.", null=True, blank=True)
dateNaissance = models.DateField(
"Date de naissance", help_text="Date de naissance du planteur", null=True, blank=True)
date_adhesion = models.DateField(
"Date d'adhésion à l'organisme de production", help_text="Date adhésion", null=True, blank=True)
numero_exemption_Diecte = models.CharField(
"Numéro d'exemption DIECTE", help_text="Numéro d'exemption DIECTE", max_length=50, null=True, blank=True)
date_fin_Diecte = models.DateField(
"Date de fin d'exemption DIECTE", help_text="Date de fin d'exemption DIECTE", null=True, blank=True)
entreprise_associé = models.TextField(
"Entreprise associé par Actionnaire", help_text="Autre entreprise associé", null=True, blank=True)
controle = models.BooleanField(
"Exemption de contrôle", help_text='Le planteur est-il exempte de contrôle ?', default=False, blank=True)
date_cessation_Activite = models.DateField(
"Date de cessation d'activité", help_text="Date de cessation d'activité", null=True, blank=True)
commentaire = models.TextField(
"Commentaire", help_text="Toute information utile à l'instruction", null=True, blank=True)
date_creation = models.DateField(auto_now_add=True, null=True, blank=True)
history = HistoricalRecords()
class Meta:
ordering = ['pacage']
def __str__(self):
"""Pour chaque methode ajouter sa fonction."""
return self.pacage
def save(self, *args, **kwargs):
"""fonction qui crée et sauvegarde un planteur tout en lui créeant des campagnes et des statistiques vide de données pour les années antérieurs."""
listeAnnee = Campagne.objects.values_list(
'annee', flat=True).distinct()
for annee in listeAnnee:
from poyosei.models import Statistique
if Campagne.objects.filter(pacage=self.pacage, annee=annee).exists() and Statistique.objects.filter(pacage=self, annee=annee).exists():
super(Planteur, self).save(*args, **kwargs)
else:
Campagne.objects.create(pacage=self.pacage, annee=annee, rid=0.0, rit=0.0, commentaire='Pas de données disponible pour cette campagne') and Statistique.objects.create(
pacage=self, annee=annee, commentaire='Pas de données statistiques disponibles pour cette année')
super(Planteur, self).save(*args, **kwargs)
def get_fk_model(model, fieldname):
field_object = model._meta.get_field(fieldname)
if field_object.is_relation:
return True
return False
def planteurExport(self):
"""Fonction qui récupère les noms des champs de la table planteur pour les transmettre dans les rapports de type CSV"""
Model = Planteur
line = Model.objects.get(pacage=self.pacage)
headers = []
for field in Model._meta.get_fields():
headers.append(field.name)
row = []
for field in headers:
if field in headers:
if not Model._meta.get_field(field).is_relation:
val = getattr(line, field)
row.append(str(val))
return row
def annee():
return int(Campagne.CampagneEnCours())
@property
def ridAnneeP(self):
"""Fonction qui recupère la référence individuelle définitive du planteur pour l'année précédent l'année de la campagne en cours."""
rid = float(self.ridDerniereCampagne)
mvtCedant = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='définitive', année_concerne=Campagne.CampagneEnCours() - 1)
for mvt in mvtCedant:
rid += float(mvt.ridCedant)
mvtRepreneur = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='définitive', année_concerne=Campagne.CampagneEnCours() - 1)
for mvt in mvtRepreneur:
rid += float(mvt.ridRepreneur)
return rid
@property
def ritAnneeP(self):
"""Fonction qui recupère la référence individuelle temporaire du planteur pour l'année précédent l'année de la campagne en cours."""
rit = 0
mvtCedant = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='temporaire', année_concerne=Campagne.CampagneEnCours() - 1)
for mvt in mvtCedant:
rit += float(mvt.ridCedant)
mvtRepreneur = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='temporaire', année_concerne=Campagne.CampagneEnCours() - 1)
for mvt in mvtRepreneur:
rit += float(mvt.ridRepreneur)
return rit
@property
def ridDerniereCampagne(self):
"""Fonction qui renvoie la rid de la dernière campagne"""
query = Campagne.objects.filter(pacage=self.pacage)
p = query.order_by('annee').last()
ri = p.rid
return ri
@property
def ridCampagneP(self):
"""Fonction qui renvoie la rid a campagne précédent la dernière campagne"""
query = Campagne.objects.filter(pacage=self.pacage)
p = query.order_by('annee').last() - 1
ri = p.rid
return ri
@property
def ritDerniereCampagne(self):
"""Fonction qui recupère la rid de la campagne précédent la campagne en cours"""
query = Campagne.objects.filter(pacage=self.pacage)
p = query.order_by('annee').last()
ri = p.rit
return ri
@property
def ridAnneeEnCours(self):
"""Fonction qui récupère la référence individuelle du planteur pour la campagne en cours"""
rid = float(self.ridDerniereCampagne)
mvtCedant = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='définitive', année_concerne=Campagne.CampagneEnCours())
for mvt in mvtCedant:
rid += float(mvt.ridCedant)
mvtRepreneur = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='définitive', année_concerne=Campagne.CampagneEnCours())
for mvt in mvtRepreneur:
rid += float(mvt.ridRepreneur)
return rid
@property
def ritAnneeEnCours(self):
"""Fonction qui recupère la référence individuelle temporaire du planteur pour la campagne en cours"""
rit = 0
mvtCedant = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='temporaire', année_concerne=Campagne.CampagneEnCours())
for mvt in mvtCedant:
rit += float(mvt.ridCedant)
mvtRepreneur = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='temporaire', année_concerne=Campagne.CampagneEnCours())
for mvt in mvtRepreneur:
rit += float(mvt.ridRepreneur)
return rit
@property
def riTotale(self):
"""Fonction qui calcule la référence individuelle totale pour l'année en cours"""
if self.pacage == '000000000':
total = self.ridAnneeEnCours + self.ritAnneeEnCours + self.taxeReserve
else:
total = self.ridAnneeEnCours + self.ritAnneeEnCours
return total
@property
def ridAnneeEnCoursMvtenAttente(self):
"""Fonction qui renvoie la rid en cours en comptabilisant les mouvements non valide"""
rid = float(self.ridDerniereCampagne)
ridFalse = float(0)
mvtCedantTrue = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='définitive', mouvement_valide=True)
mvtCedantFalse = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='définitive', mouvement_valide=False)
for mvt in mvtCedantTrue:
rid += float(mvt.ridCedant)
for mvt in mvtCedantFalse:
ridFalse += float(mvt.ridCedant)
mvtRepreneur = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='définitive', mouvement_valide=True)
mvtRepreneurFalse = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='définitive', mouvement_valide=False)
for mvt in mvtRepreneur:
rid += float(mvt.ridRepreneur)
for mvt in mvtRepreneurFalse:
ridFalse += float(mvt.ridRepreneur)
return ridFalse
@property
def ritAnneeEnCoursMvtTemporaire(self):
"""Fonction qui renvoie la rit"""
rit = float(self.ritDerniereCampagne)
ritFalse = float(0)
mvtCedantTrue = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='temporaire', mouvement_valide=True)
mvtCedantFalse = Mouvement.objects.filter(
pacage_cedant=self.pacage, type_reference_individuelle_modifie='temporaire', mouvement_valide=False)
for mvt in mvtCedantTrue:
rit += float(mvt.ritCedant)
for mvt in mvtCedantFalse:
ritFalse += float(mvt.ritCedant)
mvtRepreneur = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='temporaire', mouvement_valide=True)
mvtRepreneurFalse = Mouvement.objects.filter(
pacage_repreneur=self.pacage, type_reference_individuelle_modifie='temporaire', mouvement_valide=False)
for mvt in mvtRepreneur:
rit += float(mvt.ritRepreneur)
for mvt in mvtRepreneurFalse:
ritFalse += float(mvt.ritRepreneur)
return ritFalse
@property
def taxeReserve(self):
"""Fonction qui récupère la taxe percu sur la réserve sur les mouvements de la campagne en cours."""
reserve = Planteur.objects.get(pacage='000000000')
ri = 0
p = Campagne.objects.order_by('annee').last()
annee = p.annee
mvt = Mouvement.objects.all()
for m in mvt:
if m.type_mouvement == 'Transfert de Référence Individuelle sans foncier' and m.année_concerne == annee:
ri += float(m.ridReserve)
return ri
@property
def ridAnneePrecedente(self, annee):
cPre = Campagne.objects.get(pacage=self.pacage, annee=annee)
ridPre = cPre.rid
return ridPre
@property
def totalRI(self):
planteurs = Planteur.objects.all()
reserve = Planteur.objects.get(pacage='000000000')
ri = float(reserve.ridDerniereCampagne)
C = Campagne.objects.order_by('annee').last()
annee = C.annee
mvt = Mouvement.objects.all()
for m in mvt:
if m.type_mouvement == 'Transfert de Référence Individuelle sans foncier' and m.année_concerne == annee:
ri += float(m.ridReserve)
for p in planteurs:
if p.pacage != reserve.pacage:
total = float(p.ridAnneeEnCours)+float(p.ritAnneeEnCours)
elif p.pacage == reserve.pacage:
total = float(ri)+float(p.ritAnneeEnCours)
return total
@property
def prodCommercialeTotale(self, annee):
"""Fonction qui calcule la production commerciale totale"""
tonnageReconstitué = reconstitutionTonnage.objects.get(
pacage=self.pacage, annee=annee)
stats = Statistique.objects.get(pacage=self.pacage, annee=annee)
total = tonnageReconstitué.reconstitution_tonnage + \
stats.production_exporte + stats.production_locale
return total
@property
def moyenneOlympique(self):
"""Fonction qui calcule la moyenne olympique"""
year = Campagne.objects.values_list('annee', flat=True).last()
i = int(year)
y = i
rang = []
while i > y - 5:
rang.append(i)
i -= 1
tabRI = []
for y in year:
p = Campagne.objects.get(pacage=self.pacage, annee=y)
ri = p.riTotale
tabRI.append(ri)
maxi = max(tabRI)
mini = min(tabRI)
tabRI.remove(Maxi)
tabRI.remove(Mini)
moy = mean(tabRI)
return moy
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,524 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0005_reconstitutiontonnage.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-05-31 14:48
from __future__ import unicode_literals
from decimal import Decimal
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0004_statistique'),
]
operations = [
migrations.CreateModel(
name='reconstitutionTonnage',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('pacage', models.DecimalField(decimal_places=0, default=Decimal('0'), max_digits=9)),
('annee', models.CharField(max_length=4)),
('reconstitution_tonnage', models.DecimalField(decimal_places=0, default=Decimal('0'), max_digits=9)),
('justification', models.TextField()),
],
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,525 | AnthonyMrt/Poyosei | refs/heads/master | /views/viewsExport.py | from django.shortcuts import get_object_or_404, render, redirect, HttpResponseRedirect, HttpResponse
from django.views import View
from poyosei.forms import *
# from django.views.decorators.csrf import csrf_exempt
from poyosei.models import *
from poyosei.ressources import PlanteurResource, mouvementResource
from tablib import Dataset
from datetime import datetime
from django.template import loader, Context
from django.db.models import Q
import json
# @csrf_exempt
def planteurExport(request):
#planteur_resource = PlanteurResource()
planteurs = Planteur.objects.all()
listeLigne = []
#liste_export = []
toto = "toto"
CampagneAnnee = Campagne.objects.values_list('annee', flat=True).distinct()
#listeCampagne = []
#listeCampagne.append(CampagneAnnee)
for planteur in planteurs:
for annee in CampagneAnnee:
ligne = []
#try:
campagnes = get_object_or_404(Campagne, pacage=planteur.pacage, annee=annee)
statistiques = get_object_or_404(Statistique, pacage=planteur.pacage, annee=annee)
ligne.append(planteur.planteurExport())
ligne.append(campagnes.campagneExport(annee))
ligne.append(statistiques.statistiqueExport(annee))
#except:
#ligne.append(planteur.planteurExport())
listeLigne.append(ligne)
#toto = list(campagnes)
#for campagne in campagnes:
#listeLigne.append(campagne.export)
# for stats in statistiques:
date = datetime.now().strftime('%Y%m%d-%H%M')
fields = Planteur._meta.get_fields() + Campagne._meta.get_fields() + Statistique._meta.get_fields()
csv = render(request, 'rapport/historiqueDesCampagnes.txt', {'ligne':listeLigne, 'fields':fields, 'annee':CampagneAnnee, 'toto':toto})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-campagne.csv"'
#return render(request, 'my_template_name.txt', {'data': dataset, 'listes':listeP, 'fields':fields})
return response
#return response
def mouvementExport(request):
mouvements = Mouvement.objects.all()
listeLigne = []
for mouvement in mouvements:
ligne = []
planteurC = get_object_or_404(Planteur, pacage=mouvement.pacage_cedant)
planteurR = get_object_or_404(Planteur, pacage=mouvement.pacage_repreneur)
ligne.append(mouvement.mouvementExport())
ligne.append(planteurC.planteurExport())
ligne.append(planteurR.planteurExport())
listeLigne.append(ligne)
date = datetime.now().strftime('%Y%m%d-%H%M')
fields = Mouvement._meta.get_fields() + Planteur._meta.get_fields() + Planteur._meta.get_fields()
csv = render(request, 'rapport/rapportMouvement.txt', {'ligne':listeLigne, 'fields':fields})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-mouvements.csv"'
return response
def planteurExport2(request, pacage):
listeLigne = []
planteur = get_object_or_404(Planteur, pacage=pacage)
CampagneAnnee = Campagne.objects.values_list('annee', flat=True).distinct()
for annee in CampagneAnnee:
ligne = []
campagnes = get_object_or_404(Campagne, pacage=planteur.pacage, annee=annee)
statistiques = get_object_or_404(Statistique, pacage=planteur.pacage, annee=annee)
ligne.append(planteur.planteurExport())
ligne.append(campagnes.campagneExport(annee))
ligne.append(statistiques.statistiqueExport(annee))
#except:
#ligne.append(planteur.planteurExport())
listeLigne.append(ligne)
#toto = list(campagnes)
#for campagne in campagnes:
#listeLigne.append(campagne.export)
# for stats in statistiques:
date = datetime.now().strftime('%Y%m%d-%H%M')
fields = Planteur._meta.get_fields() + Campagne._meta.get_fields() + Statistique._meta.get_fields()
csv = render(request, 'rapport/rapportPlanteur.txt', {'ligne':listeLigne, 'fields':fields})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-campagneplanteurs.csv"'
#return render(request, 'my_template_name.txt', {'data': dataset, 'listes':listeP, 'fields':fields})
return response
def mouvementExport2(request, pacage):
listeLigne = []
mouvements = Mouvement.objects.filter(Q(pacage_cedant=pacage) | Q(pacage_repreneur=pacage))
for mouvement in mouvements:
ligne = []
planteurC = get_object_or_404(Planteur, pacage=mouvement.pacage_cedant)
planteurR = get_object_or_404(Planteur, pacage=mouvement.pacage_repreneur)
ligne.append(mouvement.mouvementExport())
ligne.append(planteurC.planteurExport())
ligne.append(planteurR.planteurExport())
listeLigne.append(ligne)
date = datetime.now().strftime('%Y%m%d-%H%M')
fields = Mouvement._meta.get_fields() + Planteur._meta.get_fields() + Planteur._meta.get_fields()
csv = render(request, 'rapport/rapportMouvementDuPlanteur.txt', {'ligne':listeLigne, 'fields':fields})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-mouvements.csv"'
return response
def campagneEnCoursExport(request, pacage):
listeLigne = []
planteur = get_object_or_404(Planteur, pacage=pacage)
CampagneAnnee = Campagne.objects.values_list('annee', flat=True).last()
ligne = []
ligne.append(planteur.planteurExport())
RID = planteur.ridAnneeEnCours
RIT = planteur.ritAnneeEnCours
RI = planteur.riTotale
listeLigne.append(ligne)
date = datetime.now().strftime('%Y%m%d-%H%M')
header = ['RI définitive', 'RI temporaire', 'RI Totale']
fields = Planteur._meta.get_fields()
csv = render(request, 'rapport/rapportCampagneEnCours.txt', {'ligne':listeLigne, 'test':header, 'RID':RID, 'RIT':RIT, 'RI':RI, 'fields':fields})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-campagneEnCours.csv"'
return response
def rapportODEADOM(request):
planteurs = Planteur.objects.all()
listeLigne = []
toto = "toto"
CampagneAnnee = Campagne.objects.values_list('annee', flat=True).distinct()
for planteur in planteurs:
for annee in CampagneAnnee:
ligne = []
#try:
campagnes = get_object_or_404(Campagne, pacage=planteur.pacage, annee=annee)
statistiques = get_object_or_404(Statistique, pacage=planteur.pacage, annee=annee)
tonnage = get_object_or_404(reconstitutionTonnage, pacage=planteur.pacage, annee=annee)
ligne.append(planteur.planteurExport())
ligne.append(campagnes.campagneExport(annee))
ligne.append(statistiques.statistiqueExport(annee))
ligne.append(tonnage.tonnageExport(annee))
prodComTotale = planteur.prodCommercialeTotale(annee)
#except:
#ligne.append(planteur.planteurExport())
listeLigne.append(ligne)
date = datetime.now().strftime('%Y%m%d-%H%M')
fields = Planteur._meta.get_fields() + Campagne._meta.get_fields() + Statistique._meta.get_fields() + reconstitutionTonnage._meta.get_fields()
header = ['ProdCommercialeTotale']
csv = render(request, 'my_template_name.txt', {'ligne':listeLigne, 'fields':fields, 'annee':CampagneAnnee, 'total':prodComTotale, 'header':header, 'toto':toto})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-poyosei.csv"'
#return render(request, 'my_template_name.txt', {'data': dataset, 'listes':listeP, 'fields':fields})
return response
def rapportODEADOMAnneeEnCours(request):
planteurs = Planteur.objects.all()
listeLigne = []
CampagneAnnee = Campagne.objects.values_list('annee', flat=True).last()
annee = int(CampagneAnnee)
for planteur in planteurs:
ligne = []
#try:
campagnes = get_object_or_404(Campagne, pacage=planteur.pacage, annee=annee)
statistiques = get_object_or_404(Statistique, pacage=planteur.pacage, annee=annee)
tonnage = get_object_or_404(reconstitutionTonnage, pacage=planteur.pacage, annee=annee)
ligne.append(planteur.planteurExport())
ligne.append(campagnes.campagneExport(annee))
ligne.append(statistiques.statistiqueExport(annee))
ligne.append(tonnage.tonnageExport(annee))
prodComTotale = planteur.prodCommercialeTotale(annee)
#except:
#ligne.append(planteur.planteurExport())
listeLigne.append(ligne)
date = datetime.now().strftime('%Y%m%d-%H%M')
fields = Planteur._meta.get_fields() + Campagne._meta.get_fields() + Statistique._meta.get_fields() + reconstitutionTonnage._meta.get_fields()
header = ['ProdCommercialeTotale']
csv = render(request, 'my_template_name.txt', {'ligne':listeLigne, 'fields':fields, 'annee':CampagneAnnee, 'total':prodComTotale, 'header':header})
response = HttpResponse(csv, content_type='text/csv')
response['Content-Disposition'] = 'attachement; filename="' + str(date) +'-poyosei.csv"'
#return render(request, 'my_template_name.txt', {'data': dataset, 'listes':listeP, 'fields':fields})
return response
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,526 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0014_historicalmouvement_historicalplanteur.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-06-07 18:33
from __future__ import unicode_literals
from decimal import Decimal
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('poyosei', '0013_remove_mouvement_quantite_reference_individuelle_accorde2'),
]
operations = [
migrations.CreateModel(
name='HistoricalMouvement',
fields=[
('id', models.IntegerField(auto_created=True, blank=True, db_index=True, verbose_name='ID')),
('type_mouvement', models.CharField(choices=[("transfert total d'une exploitation", "transfert total d'une exploitation"), ('Transfert de Référence Individuelle avec cession partielle de foncier', 'Transfert de Référence Individuelle avec cession partielle de foncier'), ('Transfert de Référence Individuelle sans foncier', 'Transfert de Référence Individuelle sans foncier'), ('Reprise administrative', 'Reprise administrative'), ('Cession volontaire définitive', 'Cession volontaire définitive'), ('Cession volontaire temporaire', 'Cession volontaire temporaire'), ('Cessation d’activite sans repreneur', 'Cessation d’activite sans repreneur'), ('Attribution de Reference Individuelle par la reserve', 'Attribution de Reference Individuelle par la réserve'), ('Autre', 'Autre'), ('', '')], default='', max_length=100)),
('informations', models.TextField(blank=True)),
('pacage_cedant', models.CharField(max_length=10)),
('pacage_repreneur', models.CharField(max_length=10)),
('année_concerne', models.CharField(blank=True, max_length=4)),
('date_demande', models.DateField(blank=True, null=True)),
('mouvement_valide', models.BooleanField(default=False)),
('date_COSDA_Valide', models.DateField(blank=True, null=True)),
('type_reference_individuelle_modifie', models.CharField(blank=True, choices=[('définitive', 'définitive'), ('temporaire', 'temporaire'), ('autre', 'autre'), ('', '')], default='', max_length=100)),
('quantite_reference_individuelle_demande', models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10)),
('quantite_reference_individuelle_accorde', models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10)),
('date_creation', models.DateTimeField(blank=True, editable=False, null=True)),
('taxe', models.FloatField(blank=True, default=0.0)),
('history_id', models.AutoField(primary_key=True, serialize=False)),
('history_change_reason', models.CharField(max_length=100, null=True)),
('history_date', models.DateTimeField()),
('history_type', models.CharField(choices=[('+', 'Created'), ('~', 'Changed'), ('-', 'Deleted')], max_length=1)),
('history_user', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to=settings.AUTH_USER_MODEL)),
('typemouvementmodel_ptr', models.ForeignKey(blank=True, db_constraint=False, null=True, on_delete=django.db.models.deletion.DO_NOTHING, related_name='+', to='poyosei.typeMouvementModel')),
],
options={
'ordering': ('-history_date', '-history_id'),
'get_latest_by': 'history_date',
'verbose_name': 'historical mouvement',
},
),
migrations.CreateModel(
name='HistoricalPlanteur',
fields=[
('pacage', models.CharField(db_index=True, help_text='Un nombre de 9 chiffres', max_length=9, verbose_name='Numéro pacage')),
('civilite', models.CharField(blank=True, choices=[('Mr', 'Monsieur'), ('gérant', 'Mr le gérant'), ('gérante', 'Mme la gérante'), ('Mme', 'Madame'), ('Societe', 'Societe'), ('Autre', 'Autre'), ('', '')], default='', max_length=20, verbose_name='Civilité')),
('nom', models.CharField(help_text='200 caractères maximum.', max_length=200, verbose_name='Nom')),
('prenom', models.CharField(help_text='200 caractères maximum.', max_length=100, verbose_name='Prénom')),
('siret', models.CharField(blank=True, help_text="code Insee permettant l'identification d'un établissement ou d'une entreprise française.", max_length=14, null=True, verbose_name='SIRET')),
('LPG', models.CharField(blank=True, help_text='Identifiant LPG du planteur.', max_length=100, null=True, verbose_name='Numéro LPG')),
('contremarque', models.CharField(blank=True, max_length=100, null=True, verbose_name='Contremarque')),
('denomination', models.TextField(blank=True, help_text="Texte d'aide", max_length=100, null=True, verbose_name='Dénomination')),
('gerant', models.TextField(blank=True, help_text="Texte d'aide", null=True, verbose_name='Gérant')),
('adresse', models.CharField(blank=True, help_text='Adresse du planteur', max_length=255, null=True, verbose_name='Adresse')),
('adresse_complementaire', models.CharField(blank=True, max_length=255, null=True)),
('code_postal', models.CharField(blank=True, help_text='Code postal planteur', max_length=10, null=True, verbose_name='Code postal')),
('commune', models.CharField(blank=True, help_text='Commune du planteur', max_length=100, null=True, verbose_name='Commune')),
('telephone_principale', models.CharField(blank=True, help_text='Téléphone de contact', max_length=50, null=True, verbose_name='Numéro de téléphone')),
('telephone_secondaire', models.CharField(blank=True, help_text='téléphone de contact', max_length=50, null=True, verbose_name='Autre téléphone')),
('courriel', models.EmailField(blank=True, help_text='Adresse de courriel de contact.', max_length=254, null=True, verbose_name='Courriel')),
('dateNaissance', models.DateField(blank=True, help_text='Date de naissance du planteur', null=True, verbose_name='Date de naissance')),
('date_adhesion', models.DateField(blank=True, help_text='Date adhésion', null=True, verbose_name="Date d'adhésion à l'organisme de production")),
('numero_exemption_Diecte', models.CharField(blank=True, help_text="Numéro d'exemption DIECTE", max_length=50, null=True, verbose_name="Numéro d'exemption DIECTE")),
('date_fin_Diecte', models.DateField(blank=True, help_text="Date de fin d'exemption DIECTE", null=True, verbose_name="Date de fin d'exemption DIECTE")),
('entreprise_associé', models.TextField(blank=True, help_text='Autre entreprise associé', null=True, verbose_name='Entreprise associé par Actionnaire')),
('controle', models.BooleanField(default=False, help_text='Le planteur est-il exempte de contrôle ?', verbose_name='Exemption de contrôle')),
('date_cessation_Activite', models.DateField(blank=True, help_text="Date de cessation d'activité", null=True, verbose_name="Date de cessation d'activité")),
('commentaire', models.TextField(blank=True, help_text="Toute information utile à l'instruction", null=True, verbose_name='Commentaire')),
('date_creation', models.DateField(blank=True, editable=False, null=True)),
('history_id', models.AutoField(primary_key=True, serialize=False)),
('history_change_reason', models.CharField(max_length=100, null=True)),
('history_date', models.DateTimeField()),
('history_type', models.CharField(choices=[('+', 'Created'), ('~', 'Changed'), ('-', 'Deleted')], max_length=1)),
('history_user', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to=settings.AUTH_USER_MODEL)),
],
options={
'ordering': ('-history_date', '-history_id'),
'get_latest_by': 'history_date',
'verbose_name': 'historical planteur',
},
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,527 | AnthonyMrt/Poyosei | refs/heads/master | /forms/formsProdCommerciale.py | from django import forms
from django.contrib.admin import widgets
from django.forms import ModelChoiceField
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Div, Submit, HTML, Button, Row, Field
from crispy_forms.bootstrap import AppendedText, PrependedText, FormActions
from poyosei.models import *
from datetime import datetime
def year_choices():
return [(r,r) for r in range(datetime.now().year-4, datetime.now().year+5)]
class ProdCommercialeForm(forms.ModelForm):
class Meta:
model = ProductionCommerciale
fields = '__all__'
def __init__(self, *args, **kwargs):
super(ProdCommercialeForm, self).__init__(*args, **kwargs)
self.fields['pacage'] = forms.ModelChoiceField(queryset=Planteur.objects.all())
self.fields['année'] = forms.TypedChoiceField(coerce=int, choices=year_choices, initial=datetime.now().year)
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,528 | AnthonyMrt/Poyosei | refs/heads/master | /models/modelsStatistique.py | from django.db import models
from decimal import Decimal
# from project import settings
# import datetime
class Statistique(models.Model):
pacage = models.CharField(max_length=9, default='')
annee = models.CharField(max_length=4)
surface_banane = models.DecimalField(max_digits=10, decimal_places=2, default=Decimal('0.00'))
surface_jachere = models.DecimalField(max_digits=10, decimal_places=2, default=Decimal('0.00'))
surface_autre = models.DecimalField(max_digits=9, decimal_places=2, default=Decimal('0.00'))
surface_totale_utile = models.DecimalField(max_digits=9, decimal_places=2, default=Decimal('0.00'))
surface_totale_exploitation = models.DecimalField(max_digits=9, decimal_places=2, default=Decimal('0.00'))
rendement = models.DecimalField(max_digits=9, decimal_places=0, default=Decimal('0'))
production_exporte = models.DecimalField(max_digits=9, decimal_places=0, default=Decimal('0'))
production_locale = models.DecimalField(max_digits=9, decimal_places=0, default=Decimal('0'))
information_diverse = models.TextField(blank=True)
surface_propriete = models.DecimalField(max_digits=10, decimal_places=2, default=Decimal('0.00'))
surface_location = models.DecimalField(max_digits=10, decimal_places=2, default=Decimal('0.00'))
commentaire = models.TextField(blank=True)
class Meta:
ordering = ['pacage']
unique_together = ('pacage', 'annee',)
def __str__(self):
return self.pacage
def prodCommercialeTotale(self):
"""Fonction qui calcule la production production totale d'un planteur pour la campagne en cours"""
CampagneAnnee = Campagne.objects.values_list('annee', flat=True).last()
for annee in CampagneAnnee:
tonnageReconstitué = reconstitutionTonnage.objects.get(pacage=self.pacage, annee=annee)
total = self.production_exporte + self.production_locale + tonnageReconstitué.reconstitution_tonnage
return total
def statistiqueExport(self, annee):
"""Fonction qui recupère les noms de champs de la table statistique pour les transmettres aux rapport de type CSV"""
Model = Statistique
line = Model.objects.get(pacage=self.pacage, annee=annee)
headers = []
for field in Model._meta.get_fields():
headers.append(field.name)
row = []
for field in headers:
if field in headers:
val = getattr(line, field)
row.append(str(val))
return row | {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,529 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0039_auto_20180818_0144.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-18 05:44
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0038_auto_20180818_0134'),
]
operations = [
migrations.RemoveField(
model_name='historicalmouvement',
name='numéro',
),
migrations.RemoveField(
model_name='typemouvementmodel',
name='numéro',
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,530 | AnthonyMrt/Poyosei | refs/heads/master | /views/viewsCampagne.py | from django.shortcuts import get_object_or_404, render, redirect, HttpResponseRedirect, HttpResponse
from django.views import View
from poyosei.forms import *
# from django.views.decorators.csrf import csrf_exempt
from poyosei.models import *
#from poyosei.ressources import campagneResource, mouvementResource
from tablib import Dataset
import json
# @csrf_exempt
def campagne(request):
return render(request, 'campagne/index.html', {"active_tab": "campagne"})
def campagneListe(request):
campagne = Campagne.objects.all()
return render(request, 'campagne/liste.html', {'active_tab': 'campagne', 'campagne': campagne})
def campagneAjouter(request):
campagnes = Campagne.objects.all()
if request.method == 'POST':
form = CampagneForm(request.POST)
if form.is_valid():
form.save()
return redirect('poyosei:campagneListe')
else:
form = CampagneForm()
return render(request, 'campagne/ajouter.html', {'active_tab': 'campagne', 'active_tabP': 'ajout', 'form': form, 'campagnes': campagnes})
def campagneEditer(request, pacage, annee):
campagnes = Campagne.objects.all()
instance = get_object_or_404(Campagne, pacage=pacage, annee=annee)
form = CampagneForm(request.POST or None, instance=instance)
if form.is_valid():
form.save(commit=False)
form.save()
return render(request, 'campagne/editer.html', {'form': form, 'active_tab': 'campagne', 'campagnes': campagnes, 'instance': instance})
def campagneSupprimer(request, pacage, annee, id):
campagnes = Campagne.objects.all()
query = get_object_or_404(Campagne, pacage=pacage)
query.delete()
return redirect('poyosei:campagneListe')
def campagneFiche(request, pacage, annee):
campagnes = Campagne.objects.all()
instance = get_object_or_404(Campagne, pacage=pacage, annee=annee)
form = CampagneForm(request.POST or None, instance=instance)
if form.is_valid():
campagne = form.save(commit=False)
campagne.save()
return render(request, 'campagne/fiche.html', {'form': form, 'active_tab': 'campagne', 'campagnes': campagnes, 'instance': instance}) | {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,531 | AnthonyMrt/Poyosei | refs/heads/master | /views/viewsPlanteur.py | from django.db.models import Q
from django.shortcuts import get_object_or_404, render, redirect
from poyosei.forms import *
from poyosei.models import *
def planteurListe(request):
planteurs = Planteur.objects.all()
#active_tab = 'planteur'
return render(request, 'planteur/liste.html', {'active_tab': 'planteur', 'planteurs': planteurs})
def planteurAjouter(request):
#Controlleur pour ajouter un planteur
planteurs = Planteur.objects.all()
if request.method == 'POST':
form = PlanteurForm(request.POST)
if form.is_valid():
form.save()
return redirect('poyosei:planteurListe')
else:
form = PlanteurForm()
return render(request, 'planteur/ajouter.html', {'active_tab': 'planteur', 'active_tabP': 'ajout', 'form': form, 'planteurs': planteurs})
def planteurEditer(request, pacage):
#Controlleur pour editer un planteur
planteurs = Planteur.objects.all()
instance = get_object_or_404(Planteur, pacage=pacage)
form = PlanteurForm(request.POST or None, instance=instance)
mouvements = Mouvement.objects.filter(Q(pacage_cedant=pacage) | Q(pacage_repreneur=pacage))
relations = Relation.objects.filter(pacageA=pacage)
reverse = instance.relation_set.all()
qry = Planteur.objects.filter(pacage__in=[r for r in reverse])
statistique = Statistique.objects.filter(pacage=pacage)
prodCommerciale = ProductionCommerciale.objects.all()
if form.is_valid():
planteur = form.save(commit=False)
planteur.save()
return render(request, 'planteur/editer.html', {'qry':qry, 'form': form, 'reverse': reverse, 'relations': relations, 'active_tab': 'planteur', 'mouvements':mouvements, 'planteurs': planteurs, 'instance': instance, 'statistique':statistique, 'prodCommerciale':prodCommerciale})
def planteurSupprimer(request, pacage):
#Controlleur pour supprimer un planteur
planteurs = Planteur.objects.all()
query = get_object_or_404(Planteur, pacage=pacage)
query.delete()
return redirect('poyosei:planteurListe')
def planteurFiche(request, pacage):
#Controlleur pour visualiser un planteur
planteurs = Planteur.objects.all()
instance = get_object_or_404(Planteur, pacage=pacage)
form = PlanteurForm(request.POST or None, instance=instance)
mouvements = Mouvement.objects.filter(Q(pacage_cedant=pacage) | Q(pacage_repreneur=pacage))
relations = Relation.objects.filter(pacageA=pacage)
statistiques = Statistique.objects.all()
prodCommerciale = ProductionCommerciale.objects.all()
if form.is_valid():
planteur = form.save(commit=False)
planteur.save()
return render(request, 'planteur/fiche.html', {'form': form, 'active_tab': 'planteur', 'planteurs': planteurs, 'mouvements':mouvements, 'relations':relations, 'instance': instance, 'statistique':statistiques, 'prodCommerciale':prodCommerciale })
def searchPlanteur(request):
if request.method == 'POST':
form = PacageForm(request.POST)
planteurs = ""
if form.is_valid():
pacPlan = form.cleaned_data
planteurSearch = pacPlan['planteurSearch']
value = request.POST['planteurSearch']
planteurs = Planteur.objects.filter(pacage__contains=value)
return render(request, 'poyosei/ajax/ajax.html', {'planteurs' : planteurs})
# def ajax_query(request):
# form = PacageForm()
# if request.method == 'POST':
# form = PacageForm(request.POST)
# if form.is_valid():
# pacPlan = form.cleaned_data
# planteurSearch = pacPlan['planteurSearch']
# value = request.POST['planteurSearch']
# planteurs = Planteur.objects.objects.filter(pacage__contains=value)
# return HttpResponseRedirect('ajax_query.html', {'planteurs': planteurs})
# else:
# form = PacageForm()
# args = {'form': form}
# return render(request, 'ajax_query.html', { 'form': form})
def planteurRID(request, pacage):
instance = Planteur.objects.get(pacage=pacage)
test = instance.ridAnneeEnCours
return render(request, 'planteur/rid.html', {'test': test})
def planteurHistorique(request):
"""Controlleur pour l'historique"""
historique = Planteur.history.all()
return render (request, 'planteur/historique.html', {'historique':historique} ) | {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,532 | AnthonyMrt/Poyosei | refs/heads/master | /test.old/testPlanteur.py | import sys, os
from django.test import TestCase
from django.core.urlresolvers import reverse
from poyosei.models import *
from poyosei.views import *
from django.db.models.query import QuerySet
from datetime import datetime
from django.shortcuts import get_object_or_404
class CampagneTest(TestCase):
def setUp(self):
Planteur.objects.create(pacage='831279456', nom='planteurA', prenom='TestA')
Planteur.objects.create(pacage='246831759', nom='planteurB', prenom='TestB')
Planteur.objects.create(pacage='000000000', nom='planteurR', prenom='TestR')
Campagne.objects.create(pacage='831279456', rid=100, annee=2013)
Campagne.objects.create(pacage='246831759', rid=50 , annee=2013)
Campagne.objects.create(pacage='000000000', rid=45 , annee=2013)
Campagne.objects.create(pacage='831279456', rid=100, annee=2014)
Campagne.objects.create(pacage='246831759', rid=50 , annee=2014)
Campagne.objects.create(pacage='000000000', rid=45 , annee=2014)
Campagne.objects.create(pacage='831279456', rid=100, annee=2019)
Campagne.objects.create(pacage='246831759', rid=50 , rit=50, annee=2019)
Campagne.objects.create(pacage='000000000', rid=45, annee=2015)
Campagne.objects.create(pacage='000000000', rid=45, annee=2019)
Campagne.objects.create(pacage='831279456', rid=100, annee=2012)
Campagne.objects.create(pacage='246831759', rid=50 , annee=2012)
Campagne.objects.create(pacage='000000000', rid=45 , annee=2012)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='831279456', pacage_repreneur='246831759', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='temporaire', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='000000000', pacage_repreneur='831279456', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='831279456', pacage_repreneur='000000000', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='246831759', pacage_repreneur='831279456', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='831279456', pacage_repreneur='246831759', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='246831759', pacage_repreneur='831279456', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=False, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='831279456', pacage_repreneur='246831759', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='246831759', pacage_repreneur='831279456', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='831279456', pacage_repreneur='246831759', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=False, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant='246831759', pacage_repreneur='831279456', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True,type_reference_individuelle_modifie='temporaire', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
Mouvement.objects.create( type_mouvement='Attribution de Reference Individuelle par la reserve', pacage_cedant='000000000', pacage_repreneur='246831759', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='définitive', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=100, taxe=15)
Mouvement.objects.create( type_mouvement='Attribution de Reference Individuelle par la reserve', pacage_cedant='000000000', pacage_repreneur='246831759', année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, type_reference_individuelle_modifie='temporaire', date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=50, taxe=15)
def test_annee_derniere_campagne(self):
PlanteurB = Planteur.objects.get(pacage='831279456')
annee = PlanteurB.annee
self.assertEqual(annee, 2019)
def test_rid_derniere_campagne(self):
PlanteurA = Planteur.objects.get(pacage='000000000')
rid = PlanteurA.ridDerniereCampagne
self.assertEqual(rid, 45)
def test_rid_annee_en_cours(self):
PlanteurB = Planteur.objects.get(pacage='246831759')
rid = PlanteurB.ridAnneeEnCours
self.assertEqual(rid, 121.5)
def test_rit_annee_en_cours(self):
PlanteurB = Planteur.objects.get(pacage='246831759')
rit = PlanteurB.ritAnneeEnCours
self.assertEqual(rit, -4.5)
def test_rit_annee_en_cours(self):
PlanteurB = Planteur.objects.get(pacage='246831759')
rid = PlanteurB.ridAnneeEnCoursMvtValide
self.assertEqual(rid, -4.5)
def test_taxeReserve(self):
PlanteurB = Planteur.objects.get(pacage='000000000')
ri = PlanteurB.taxeReserve
self.assertEqual(ri, 90)
#def test_ridAnnePrecedente(self):
# PlanteurB = Planteur.objects.get('246831759')
# test = PlanteurB.ridAnneePrecedente
# self.assertListEqual(test, [100])
def test_createCampagneAuto(self):
PlanteurE = Planteur.objects.create(pacage='777444111', nom="PlanteurE", prenom='TestE')
campagneE = Campagne.objects.get(pacage='777444111')
self.assertTrue(isinstance(campagneE, Campagne))
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,533 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0002_mouvement_rule_typemouvementmodel.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-05-31 14:43
from __future__ import unicode_literals
from decimal import Decimal
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Rule',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('start_date', models.DateField()),
('end_date', models.DateField()),
('deposit_percent', models.FloatField()),
('credit_percent', models.FloatField()),
],
),
migrations.CreateModel(
name='typeMouvementModel',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('type_mouvement', models.CharField(choices=[("transfert total d'une exploitation", "transfert total d'une exploitation"), ('Transfert de Référence Individuelle avec cession partielle de foncier', 'Transfert de Référence Individuelle avec cession partielle de foncier'), ('Transfert de Référence Individuelle sans foncier', 'Transfert de Référence Individuelle sans foncier'), ('Reprise administrative', 'Reprise administrative'), ('Cession volontaire définitive', 'Cession volontaire définitive'), ('Cession volontaire temporaire', 'Cession volontaire temporaire'), ('Cessation d’activite sans repreneur', 'Cessation d’activite sans repreneur'), ('Attribution de Reference Individuelle par la reserve', 'Attribution de Reference Individuelle par la réserve'), ('Prélèvement sur cessions sans foncier', 'Prélèvement sur cessions sans foncier')], default='', max_length=100)),
('informations', models.TextField(blank=True)),
],
),
migrations.CreateModel(
name='Mouvement',
fields=[
('typemouvementmodel_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='poyosei.typeMouvementModel')),
('pacage_cedant', models.CharField(blank=True, max_length=100)),
('pacage_repreneur', models.CharField(blank=True, max_length=100)),
('année_concerne', models.CharField(blank=True, max_length=4)),
('date_demande', models.DateField(blank=True, null=True)),
('mouvement_valide', models.BooleanField(default=False)),
('date_COSDA_Valide', models.DateField(blank=True, null=True)),
('type_reference_individuelle_modifie', models.CharField(blank=True, max_length=100)),
('quantite_reference_individuelle_demande', models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10)),
('quantite_reference_individuelle_accorde', models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10)),
('date_creation', models.DateTimeField(auto_now_add=True, null=True)),
('taxe', models.FloatField(blank=True, default=0.0)),
],
bases=('poyosei.typemouvementmodel',),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,534 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0048_auto_20180820_0646.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-20 10:46
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0047_auto_20180820_0516'),
]
operations = [
migrations.AlterField(
model_name='typemouvement',
name='Nom_mouvement',
field=models.TextField(max_length=100),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,535 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0027_delete_exportcampagne.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-14 15:07
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0026_auto_20180814_1107'),
]
operations = [
migrations.DeleteModel(
name='ExportCampagne',
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,536 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0008_campagne_cloturer.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-06-01 13:41
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0007_auto_20180531_1344'),
]
operations = [
migrations.AddField(
model_name='campagne',
name='cloturer',
field=models.BooleanField(default=False),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,537 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0019_auto_20180802_1341.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-02 17:41
from __future__ import unicode_literals
from decimal import Decimal
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0018_auto_20180802_0936'),
]
operations = [
migrations.AlterField(
model_name='historicalmouvement',
name='quantite_reference_individuelle_demande',
field=models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10, null=True),
),
migrations.AlterField(
model_name='mouvement',
name='quantite_reference_individuelle_demande',
field=models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10, null=True),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,538 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0024_auto_20180814_1049.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-14 14:49
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0023_auto_20180807_1412'),
]
operations = [
migrations.CreateModel(
name='ExportCampagne',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
],
),
migrations.CreateModel(
name='newTypeMouvement',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('Nom_mouvement', models.CharField(max_length=100)),
('informations', models.TextField()),
],
),
migrations.RemoveField(
model_name='planteurback',
name='planteur_ptr',
),
migrations.RemoveField(
model_name='historicalplanteur',
name='référence_individuelle_définitive',
),
migrations.RemoveField(
model_name='planteur',
name='référence_individuelle_définitive',
),
migrations.AlterUniqueTogether(
name='statistique',
unique_together=set([('pacage', 'annee')]),
),
migrations.DeleteModel(
name='PlanteurBack',
),
migrations.AddField(
model_name='exportcampagne',
name='planteur',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='poyosei.Planteur'),
),
migrations.AddField(
model_name='exportcampagne',
name='statistique',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='poyosei.statistique'),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,539 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0012_auto_20180606_0922.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-06-06 13:22
from __future__ import unicode_literals
from decimal import Decimal
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0011_auto_20180606_0912'),
]
operations = [
migrations.AddField(
model_name='mouvement',
name='quantite_reference_individuelle_accorde2',
field=models.DecimalField(blank=True, decimal_places=0, default=Decimal('0'), max_digits=10),
),
migrations.AlterField(
model_name='mouvement',
name='pacage_cedant',
field=models.CharField(max_length=10),
),
migrations.AlterField(
model_name='mouvement',
name='pacage_repreneur',
field=models.CharField(max_length=10),
),
migrations.AlterField(
model_name='mouvement',
name='type_reference_individuelle_modifie',
field=models.CharField(blank=True, choices=[('définitive', 'définitive'), ('temporaire', 'temporaire'), ('autre', 'autre'), ('', '')], default='', max_length=100),
),
migrations.AlterField(
model_name='typemouvementmodel',
name='type_mouvement',
field=models.CharField(choices=[("transfert total d'une exploitation", "transfert total d'une exploitation"), ('Transfert de Référence Individuelle avec cession partielle de foncier', 'Transfert de Référence Individuelle avec cession partielle de foncier'), ('Transfert de Référence Individuelle sans foncier', 'Transfert de Référence Individuelle sans foncier'), ('Reprise administrative', 'Reprise administrative'), ('Cession volontaire définitive', 'Cession volontaire définitive'), ('Cession volontaire temporaire', 'Cession volontaire temporaire'), ('Cessation d’activite sans repreneur', 'Cessation d’activite sans repreneur'), ('Attribution de Reference Individuelle par la reserve', 'Attribution de Reference Individuelle par la réserve'), ('Autre', 'Autre'), ('', '')], default='', max_length=100),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,540 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0030_auto_20180814_1344.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-14 17:44
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0029_auto_20180814_1146'),
]
operations = [
migrations.RemoveField(
model_name='historicalplanteur',
name='campagne',
),
migrations.RemoveField(
model_name='planteur',
name='campagne',
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,541 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0041_delete_ajoutmouvement.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-19 06:12
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0040_auto_20180819_0205'),
]
operations = [
migrations.DeleteModel(
name='ajoutMouvement',
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,542 | AnthonyMrt/Poyosei | refs/heads/master | /test.old/testMouvement.py | import sys, os
from django.test import TestCase
from django.core.urlresolvers import reverse
from poyosei.models import *
from poyosei.views import *
from django.db.models.query import QuerySet
from datetime import datetime
from django.shortcuts import get_object_or_404
class mouvementTest(TestCase):
def setUp(self):
Planteur.objects.create(pacage='831279456', nom='planteurA', prenom='TestA')
Planteur.objects.create(pacage='246831759', nom='planteurB', prenom='TestB')
Planteur.objects.create(pacage='000000000', nom='planteurC', prenom='TestC')
Campagne.objects.create(pacage='831279456', rid=100, annee=2013)
Campagne.objects.create(pacage='246831759', rid=50 , annee=2013)
Campagne.objects.create(pacage='000000000', rid=45 , annee=2013)
Campagne.objects.create(pacage='831279456', rid=100, annee=2014)
Campagne.objects.create(pacage='246831759', rid=50 , annee=2014)
Campagne.objects.create(pacage='000000000', rid=45 , annee=2014)
Campagne.objects.create(pacage='831279456', rid=1000, annee=2019)
Campagne.objects.create(pacage='246831759', rid=50 , rit=50, annee=2019, production_commerciale_totale=30)
Campagne.objects.create(pacage='000000000', rid=1000 , annee=2019)
Campagne.objects.create(pacage='831279456', rid=100, annee=2012)
Campagne.objects.create(pacage='246831759', rid=50 , annee=2012)
Campagne.objects.create(pacage='000000000', rid=45 , annee=2012)
def test_transfert_sans_foncier(self):
mvt1 = Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle sans foncier', pacage_cedant=831279456, pacage_repreneur=246831759, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30, taxe=15)
mvt = Mouvement.objects.get(pk=mvt1.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -30)
self.assertEqual(obtenue, 25.5)
self.assertEqual(taxe, 4.5)
def test_cession_volontaire_définitive(self):
mvt2 = Mouvement.objects.create( type_mouvement='Cession volontaire définitive', pacage_cedant=831279456, pacage_repreneur=246831759, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -30)
self.assertEqual(obtenue, 30)
self.assertEqual(taxe, 0.0)
def test_cession_volontaire_temporaire(self):
mvt2 = Mouvement.objects.create( type_mouvement='Cession volontaire temporaire', pacage_cedant=831279456, pacage_repreneur=246831759, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -30)
self.assertEqual(obtenue, 30)
self.assertEqual(taxe, 0.0)
def test_Cession_activité_sans_repreneur(self):
mvt2 = Mouvement.objects.create( type_mouvement='Cessation d’activite sans repreneur', pacage_cedant=246831759, pacage_repreneur=000000000, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -30)
self.assertEqual(obtenue, 30)
self.assertEqual(taxe, 0.0)
def test_Transfert_de_Référence_individuelle_avec_foncier(self):
mvt2 = Mouvement.objects.create( type_mouvement='Transfert de Référence Individuelle avec cession partielle de foncier', pacage_cedant=246831759, pacage_repreneur=831279456, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=30)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -30)
self.assertEqual(obtenue, 30)
self.assertEqual(taxe, 0.0)
def test_Transfert_total_exploitation(self):
mvt2 = Mouvement.objects.create( type_mouvement='transfert total d\'une exploitation', pacage_cedant=246831759, pacage_repreneur=831279456, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=1000)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -1000)
self.assertEqual(obtenue, 1000)
self.assertEqual(taxe, 0.0)
def test_Attribution_de_reférence_individuelle_par_la_reserve(self):
mvt2 = Mouvement.objects.create( type_mouvement='Attribution de Reference Individuelle par la reserve', pacage_cedant=000000000, pacage_repreneur=831279456, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=50)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -50)
self.assertEqual(obtenue, 50)
self.assertEqual(taxe, 0.0)
def test_Reprise_administrative(self):
mvt2 = Mouvement.objects.create( type_mouvement='Reprise administrative', pacage_cedant=246831759, pacage_repreneur=000000000, année_concerne=datetime.now().year, date_demande=datetime.now(), mouvement_valide=True, date_COSDA_Valide=datetime.now(), quantite_reference_individuelle_accorde=50)
mvt = Mouvement.objects.get(pk=mvt2.pk)
ceder = mvt.ridCedant
obtenue = mvt.ridRepreneur
taxe = mvt.ridReserve
self.assertEqual(ceder, -10)
self.assertEqual(obtenue, 10)
self.assertEqual(taxe, 0.0)
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,543 | AnthonyMrt/Poyosei | refs/heads/master | /migrations/0052_auto_20180828_1023.py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-08-28 14:23
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('poyosei', '0051_auto_20180822_0349'),
]
operations = [
migrations.AddField(
model_name='statistique',
name='commentaire',
field=models.TextField(blank=True),
),
migrations.AlterField(
model_name='historicalmouvement',
name='type_reference_individuelle_modifie',
field=models.CharField(choices=[('définitive', 'définitive'), ('temporaire', 'temporaire'), ('autre', 'autre'), ('', '')], default='', max_length=100),
),
migrations.AlterField(
model_name='mouvement',
name='type_reference_individuelle_modifie',
field=models.CharField(choices=[('définitive', 'définitive'), ('temporaire', 'temporaire'), ('autre', 'autre'), ('', '')], default='', max_length=100),
),
]
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,544 | AnthonyMrt/Poyosei | refs/heads/master | /ressources.py | from import_export import resources, fields
from .models import *
from import_export.widgets import ForeignKeyWidget, ManyToManyWidget
class PlanteurResource(resources.ModelResource):
#nom_planteur = fields.Field(attribute='planteur_nom')
#rid = fields.Field(column_name='Référence individuelle définitive', attribute='campagne', widget=ForeignKeyWidget('poyosei:Campagne', field='rid'))
class Meta:
model = Planteur
#fields = ('planteur_nom')
class mouvementResource(resources.ModelResource):
class Meta:
model = Mouvement
| {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,545 | AnthonyMrt/Poyosei | refs/heads/master | /test.old/__init__.py | from .testMouvement import *
from .testPlanteur import * | {"/admin.py": ["/models/__init__.py"], "/forms/__init__.py": ["/forms/formsPlanteur.py", "/forms/formsMouvement.py", "/forms/formsRelation.py", "/forms/formsCampagne.py", "/forms/formsProdCommerciale.py", "/forms/formsTypeMouvement.py"], "/views/__init__.py": ["/views/viewsCampagne.py", "/views/viewsExport.py", "/views/viewsMouvement.py", "/views/viewsOperation.py", "/views/viewsPlanteur.py", "/views/viewsRapport.py", "/views/viewsRelation.py", "/views/viewsStatic.py", "/views/viewsHistorique.py", "/views/viewsProdCommerciale.py", "/views/viewsStatistique.py", "/views/viewsTypeMouvement.py", "/views/viewsTonnage.py"], "/models/modelsRelation.py": ["/models/modelsPlanteur.py"], "/models/__init__.py": ["/models/modelsCampagne.py", "/models/modelsMouvement.py", "/models/modelsPlanteur.py", "/models/modelsRelation.py", "/models/modelsStatistique.py", "/models/modelsTonnage.py", "/models/modelsProductionCommerciale.py", "/models/modelsTypeMouvement.py"], "/ressources.py": ["/models/__init__.py"], "/test.old/__init__.py": ["/test.old/testMouvement.py", "/test.old/testPlanteur.py"]} |
46,552 | fen0s/LootboxSim-Rewritten | refs/heads/master | /systems/application.py | import tkinter as tk
from PIL import ImageTk, Image
import random
from systems.engine import Engine
from systems.inventory import Inventory
from data.prefstuff import quality_colors
from winsound import PlaySound, SND_FILENAME
class Application():
def __init__(self, engine, inventory):
self.root = tk.Tk()
self.engine = engine
self.inventory = inventory
imgbg_path = './imgs/bg.png'
imglootbox_path = './imgs/lbox.png'
bg = ImageTk.PhotoImage(Image.open(imgbg_path))
lbimage = ImageTk.PhotoImage(Image.open(imglootbox_path).resize(size=(170, 150)))
#background and lootbox image placing
panel = tk.Label(self.root, image=bg)
panel.place(relx=0.89, rely=0.07, anchor=tk.CENTER)
img = tk.Label(self.root, image = lbimage)
img.place(relx=0.5, rely=0.5,anchor=tk.CENTER)
self.root.geometry('600x400')
#statistics text
self.stats = tk.Label(self.root,
text = self.engine.statistics,
width=17, height=3,
bg='#e07ef9',
font='arial 10')
self.stats.place(relx=0.89, rely=0.07, anchor=tk.CENTER)
#lootbox opening button
self.open_button = tk.Button(self.root,
text = f'Buy lootbox for ${self.engine.price}',
width=16, height=2,
bg = "#bd7ad8", fg='#6900b6', font='arial 13')
self.open_button.place(relx=0.5, rely=0.9, anchor=tk.S)
self.open_button.bind('<Button-1>', self.open_lootbox)
#inventory window button
invbutton = tk.Button(self.root,
text='Open inventory',
width=20, height = 1,
bg="#e07ef9", fg='purple', font='arial 10')
invbutton.bind('<Button-1>', self.openinv)
invbutton.place(relx=0.1, rely=0.02, anchor=tk.CENTER)
#balance label
self.balancelabel = tk.Label(self.root,
text=engine.balancestr,
width=20, height=1,
bg='#bd7ad8', fg='#59d327', font='arial 10')
self.balancelabel.place(relx=0.1, rely=0.97, anchor=tk.CENTER)
self.root.mainloop()
def update_statistics(self):
self.stats.configure(text=self.engine.statistics)
def update_balance(self):
self.balancelabel.configure(text=str(self.engine.balancestr))
def open_lootbox(self, event):
if self.open_button['state'] == tk.NORMAL:
self.open_button['state'] = tk.DISABLED
self.engine.opened += 1
self.engine.spent += self.engine.price
self.engine.balance -= self.engine.price
self.update_statistics()
self.update_balance()
self.root.update()
#lootbox opening window
lbwindow = tk.Toplevel()
lbwindow.geometry('200x100')
lbwindtext = tk.Label(lbwindow,
text='Opening lootbox... \nPlease wait...',
width=17, height=2,
font='arial 10')
lbwindtext.place(relx=0.5, rely=0.5, anchor=tk.CENTER)
lbwindow.after(1300, lambda: self.get_loot(lbwindow))
def get_loot(self, opening_window):
self.open_button['state'] = tk.NORMAL
opening_window.destroy() #destroy the "please wait" window
lootwindow = tk.Toplevel()
lootwindow.geometry('600x400')
lootlb = tk.Label(lootwindow,
text='Congratulations! You got...',
width=20, height=3,
font='arial 14')
lootlb.pack(side='top')
loot = self.inventory.generate_loot()
tier, item, price = loot[0], loot[1], loot[2]
self.inventory.add_to_inventory(item, price)
#loot text
loot = tk.Label(lootwindow,
text=item,
width=35, height=2,
fg = quality_colors.get(tier),
font='arial 19')
#quality text
qual = tk.Label(lootwindow,
text=tier.upper() + ' Quality!',
fg=quality_colors.get(tier),
width=20, height=2,
font='arial 22')
loot.place(rely=0.9, relx=0.5, anchor=tk.CENTER)
qual.place(rely=0.5, relx=0.5, anchor=tk.CENTER)
PlaySound('l.wav', SND_FILENAME)
def sell(self, event):
self.inventory.sell_inventory()
self.update_balance()
self.update_statistics()
self.root.update()
#just opens "items sold" window to notify user that the thing gone successfuly
sold = tk.Toplevel()
sold.geometry('50x50')
soldlabel = tk.Label(sold,
text='Items sold!',
width=10, height=1,
font='arial 10')
soldlabel.place(relx=0.5, rely=0.5, anchor=tk.CENTER)
def openinv(self, event):
inv_window = tk.Toplevel()
inv_window.geometry('1000x500')
inv_title = tk.Label(inv_window,
text='YOUR ITEMS:',
width=30, height=2,
font='arial 22')
inv_title.pack(side='top')
itemlist_label = tk.Label(inv_window,
text=self.inventory.all_items,
width=100, height=40,
font='arial 14')
itemlist_label.pack(side='top')
sellbutton = tk.Button(inv_window,
text=f'Sell items for price of {self.inventory.inventory_price}$?',
width=40, height=1,
font='arial 15')
sellbutton.place(relx=0.5, rely=0.95, anchor=tk.CENTER)
sellbutton.bind('<Button-1>', self.sell)
| {"/systems/application.py": ["/systems/engine.py", "/systems/inventory.py", "/data/prefstuff.py"], "/systems/inventory.py": ["/data/prefstuff.py"], "/main.py": ["/systems/application.py", "/systems/engine.py", "/systems/inventory.py"]} |
46,553 | fen0s/LootboxSim-Rewritten | refs/heads/master | /systems/engine.py | class Engine():
def __init__(self, balance=100, price=10):
self.balance = balance
self.price = price
self.spent, self.earned, self.opened, = 0, 0, 0
@property
def statistics(self):
return f"Lootboxes opened: {self.opened}\n Money spent: ${self.spent}\nMoney earned: ${self.earned}"
@property
def balancestr(self):
return f'Balance: ${self.balance}' | {"/systems/application.py": ["/systems/engine.py", "/systems/inventory.py", "/data/prefstuff.py"], "/systems/inventory.py": ["/data/prefstuff.py"], "/main.py": ["/systems/application.py", "/systems/engine.py", "/systems/inventory.py"]} |
46,554 | fen0s/LootboxSim-Rewritten | refs/heads/master | /systems/inventory.py | from data.prefstuff import prices, prefdict, qualities, prefix_number
import random
from data.nouns import nouns
class Inventory():
def __init__(self, engine):
self.items = {}
self.engine = engine
@property
def inventory_price(self):
return sum([price for price in list(self.items.values())])
def generate_loot(self):
lootstr = ''
tier = random.choice(qualities)
for _ in range(prefix_number.get(tier)):
prefix = random.choice(prefdict.get(tier))
if prefix in lootstr:
continue
lootstr += prefix + ' '
lootstr += random.choice(nouns).title()
tier_maxprice = prices.get(tier)
loot = [tier, tier.title() + ' ' + lootstr, random.randint(1, tier_maxprice)]
return loot
def add_to_inventory(self, loot, price):
self.items.update({loot: price})
def sell_inventory(self):
self.engine.balance += self.inventory_price
self.engine.earned += self.inventory_price
self.items.clear()
@property
def all_items(self):
item_list = ''
for itemprice_pair in self.items.items():
item_list += f'Item: {itemprice_pair[0]}, price: {itemprice_pair[1]}$\n'
return item_list | {"/systems/application.py": ["/systems/engine.py", "/systems/inventory.py", "/data/prefstuff.py"], "/systems/inventory.py": ["/data/prefstuff.py"], "/main.py": ["/systems/application.py", "/systems/engine.py", "/systems/inventory.py"]} |
46,555 | fen0s/LootboxSim-Rewritten | refs/heads/master | /main.py | from systems.application import Application
from systems.engine import Engine
from systems.inventory import Inventory
if __name__ == '__main__':
engine = Engine()
inventory = Inventory(engine)
main_application = Application(engine, inventory)
| {"/systems/application.py": ["/systems/engine.py", "/systems/inventory.py", "/data/prefstuff.py"], "/systems/inventory.py": ["/data/prefstuff.py"], "/main.py": ["/systems/application.py", "/systems/engine.py", "/systems/inventory.py"]} |
46,556 | fen0s/LootboxSim-Rewritten | refs/heads/master | /data/prefstuff.py | prices = {'legendary' : 100,
'epic' : 20,
'appealing' : 15,
'bad' : 2,
'awful' : 1 }
prefdict = {'legendary' : ['Stunning', 'Powerful', 'Nightmare', 'Godlike', 'Enchanted', 'Magical', 'Superb', 'Scary', 'Sinister', 'Astonishing', 'Hyper'],
'epic': ['Amazing', 'Great', 'Crushing', 'Rageful', "Hell's", 'Angelic', 'Ranger', 'Rogue', 'Explosive', 'Legend', 'Efficient', 'Suitable', 'Decent'],
'appealing' : ['Nice', 'Pleasant', 'Cool', 'Not Bad', 'Useful', 'Favorable', 'Satisfying', 'Valuable', 'Neat'],
'bad' : ['Rusty', 'Corrosed', 'Worn', 'Meh', 'Cracked', 'Damaged', 'Mangled', 'Torn'],
'awful' : ['Worst', 'Shameful', 'Useless', 'Broken', 'Utter']}
qualities = ['legendary', 'epic', 'appealing', 'bad', 'awful']
prefix_number = {'legendary' : 3,
'epic' : 2,
'appealing' : 1,
'bad' : 1,
'awful' : 2}
quality_colors = {'legendary' : 'orange',
'epic' : 'purple',
'appealing' : 'green',
'bad' : '#a6acaf',
'awful' : 'gray'} | {"/systems/application.py": ["/systems/engine.py", "/systems/inventory.py", "/data/prefstuff.py"], "/systems/inventory.py": ["/data/prefstuff.py"], "/main.py": ["/systems/application.py", "/systems/engine.py", "/systems/inventory.py"]} |
46,558 | produktz/django-alexa | refs/heads/master | /django_alexa/serializers.py | from __future__ import absolute_import
import logging
from rest_framework import serializers
from .api import validation, IntentsSchema
log = logging.getLogger(__name__)
class Obj(object):
def __init__(self, data):
self.__dict__.update(data)
class BaseASKSerializer(serializers.Serializer):
def create(self, validated_data):
return Obj(data=validated_data)
class ASKApplicationSerializer(BaseASKSerializer):
applicationId = serializers.CharField(validators=[validation.validate_app_ids])
class ASKUserSerializer(BaseASKSerializer):
userId = serializers.CharField()
class ASKSessionSerializer(BaseASKSerializer):
sessionId = serializers.CharField()
application = ASKApplicationSerializer()
attributes = serializers.DictField(required=False, allow_null=True)
user = ASKUserSerializer()
new = serializers.BooleanField()
class ASKIntentSerializer(BaseASKSerializer):
name = serializers.CharField()
slots = serializers.DictField(required=False, allow_null=True)
class ASKRequestSerializer(BaseASKSerializer):
type = serializers.CharField()
requestId = serializers.CharField()
timestamp = serializers.DateTimeField(format="%Y-%m-%dT%H:%M:%SZ")
intent = ASKIntentSerializer(required=False)
reason = serializers.CharField(required=False)
class ASKOutputSpeechSerializer(BaseASKSerializer):
# TODO: Choice validation to check if text or ssml is filed
type = serializers.ChoiceField(choices=("PlainText", "SSML"))
text = serializers.CharField(required=False)
ssml = serializers.CharField(required=False)
class ASKCardSerializer(BaseASKSerializer):
type = serializers.ChoiceField(choices=("Simple", "LinkAccount"))
title = serializers.CharField(required=False)
content = serializers.CharField(required=False)
class ASKRempromptSerializer(BaseASKSerializer):
outputSpeech = ASKOutputSpeechSerializer(required=False)
class ASKResponseSerializer(BaseASKSerializer):
outputSpeech = ASKOutputSpeechSerializer(required=False, validators=[validation.validate_char_limit])
card = ASKCardSerializer(required=False, validators=[validation.validate_char_limit])
reprompt = ASKRempromptSerializer(required=False)
shouldEndSession = serializers.BooleanField()
class ASKSerializer(BaseASKSerializer):
version = serializers.FloatField(required=True)
session = ASKSessionSerializer(write_only=True)
request = ASKRequestSerializer(write_only=True)
sessionAttributes = serializers.DictField(required=False, read_only=True)
response = ASKResponseSerializer(read_only=True)
def create(self, validated_data):
# TODO: handle session attributes somehow
intent_kwargs = {}
if validated_data["request"]["type"] == "IntentRequest":
intent_name = validated_data["request"]["intent"]["name"]
for slot, slot_data in validated_data["request"]["intent"].get("slots", {}).items():
intent_kwargs[slot_data["name"]] = slot_data['value']
else:
intent_name = validated_data["request"]["type"]
response = IntentsSchema.route(intent_name, intent_kwargs)
if isinstance(response, ASKResponseSerializer) is not True:
msg = "Intent '{0}' does not return an ASKResponseSerializer"
raise serializers.ValidationError(detail=msg.format(intent_name))
validated_data['response'] = response.validated_data
return Obj(data=validated_data)
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,559 | produktz/django-alexa | refs/heads/master | /django_alexa/api/response_builder.py | from __future__ import absolute_import
import logging
from rest_framework.exceptions import ValidationError
from ..serializers import ASKResponseSerializer, ASKOutputSpeechSerializer, ASKRempromptSerializer, ASKCardSerializer
log = logging.getLogger(__name__)
class ResponseBuilder(object):
"""
Simple class to help users to build alexa responses
"""
@classmethod
def create_response(cls,
message=None, message_is_ssml=False,
reprompt=None, reprompt_is_ssml=False,
title=None, content=None, card_type=None,
end_session=True):
"""
Shortcut to create a fully baked ASKResponseSerializer
Output Speech:
message - text message to be spoken out by the Echo
message_is_ssml - If true the "message" is ssml formated and should be treated as such
Reprompt Speech:
reprompt - text message to be spoken out by the Echo
reprompt_is_ssml - If true the "repropt" is ssml formated and should be treated as such
Card:
card_type - A string describing the type of card to render.
title - A string containing the title of the card. (not applicable for cards of type LinkAccount).
content - A string containing the contents of the card (not applicable for cards of type LinkAccount).
Note that you can include line breaks in the content for a card of type Simple.
end_session - flag to determine whether this interaction should end the session
For more comprehensive documentation see:
https://developer.amazon.com/public/solutions/alexa/alexa-skills-kit/docs/alexa-skills-kit-interface-reference
"""
data = {}
data['shouldEndSession'] = end_session
if message:
data['outputSpeech'] = cls.create_speech(message=message,
is_ssml=message_is_ssml)
if title or content:
data['card'] = cls.create_card(title=title,
content=content,
card_type=card_type)
if reprompt:
data['reprompt'] = cls.create_reprompt(message=reprompt,
is_ssml=reprompt_is_ssml)
log.debug("ASK RESPONSE : {0}".format(data))
response = ASKResponseSerializer(data=data)
try:
response.is_valid(raise_exception=True)
except ValidationError as e:
log.exception("Error occured during response serialization!")
raise e
return response
@classmethod
def create_speech(cls, message=None, is_ssml=False):
data = {}
if is_ssml:
data['type'] = "SSML"
data['ssml'] = message
else:
data['type'] = "PlainText"
data['text'] = message
speech = ASKOutputSpeechSerializer(data=data)
speech.is_valid(raise_exception=True)
return speech.validated_data
@classmethod
def create_reprompt(cls, message=None, is_ssml=False):
data = {}
data['outputSpeech'] = cls.create_speech(message=message,
is_ssml=is_ssml)
reprompt = ASKRempromptSerializer(data=data)
reprompt.is_valid(raise_exception=True)
return reprompt.validated_data
@classmethod
def create_card(cls, title=None, content=None, card_type=None):
data = {"type": card_type or "Simple"}
if title: data["title"] = title
if content: data["content"] = content
card = ASKCardSerializer(data=data)
card.is_valid(raise_exception=True)
return card.validated_data
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,560 | produktz/django-alexa | refs/heads/master | /django_alexa/api/__init__.py | from __future__ import absolute_import
from rest_framework.serializers import Serializer as Slots # flake8: noqa
from . import validation, fields # flake8: noqa
from .intents_schema import intent, IntentsSchema # flake8: noqa
from .response_builder import ResponseBuilder # flake8: noqa
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,561 | produktz/django-alexa | refs/heads/master | /django_alexa/views.py | from __future__ import absolute_import
import logging
from rest_framework.status import HTTP_200_OK
from rest_framework.viewsets import GenericViewSet
from rest_framework.response import Response
from rest_framework.exceptions import ValidationError
from . import serializers
from .api import validation
log = logging.getLogger(__name__)
class ASKViewSet(GenericViewSet):
serializer_class = serializers.ASKSerializer
def create(self, request, *args, **kwargs):
serializer = self.get_serializer(data=request.data)
try:
serializer.is_valid(raise_exception=True)
except ValidationError as e:
log.exception("Error occured during request serialization!")
raise e
serializer.save()
response = Response(serializer.data, status=HTTP_200_OK)
return response
def dispatch(self, request, *args, **kwargs):
validation.validate_alexa_request(request.META, request.body)
response = super(ASKViewSet, self).dispatch(request, *args, **kwargs)
validation.validate_reponse_limit(response.render().content)
return response
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,562 | produktz/django-alexa | refs/heads/master | /django_alexa/management/commands/alexa_utterances.py | from __future__ import absolute_import
from django.core.management.base import BaseCommand
from ...api import IntentsSchema
class Command(BaseCommand):
help = 'Prints the Alexa Skills Kit utterances schema'
def handle(self, *args, **options):
data = IntentsSchema.generate_utterances()
self.stdout.write('\n'.join(data))
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,563 | produktz/django-alexa | refs/heads/master | /django_alexa/api/intents_schema.py | from __future__ import absolute_import
import logging
from string import Formatter
from rest_framework.serializers import ValidationError
from .fields import INTENT_SLOT_TYPES, VALID_SLOT_TYPES
log = logging.getLogger(__name__)
class IntentsSchema():
intents = {}
@classmethod
def route(cls, name, data=None):
"""Routes an intent to the proper method"""
if name not in cls.intents.keys():
msg = "Unable to find an intent defined for '{0}'"
raise ValidationError(detail=msg.format(name))
kwargs = {}
func, slot = cls.intents[name]
if slot:
if data is None:
msg = "Intent '{0}' requires slots data and none was provided"
raise ValidationError(detail=msg.format(name))
else:
slots = slot(data=data)
slots.is_valid(raise_exception=True)
kwargs.update(slots.data)
log.info("Routing: '{0}' with args {1} to '{2}.{3}'".format(name, kwargs, func.__module__, func.__name__))
return func(**kwargs)
@classmethod
def register(cls, func, name, slot=None):
if slot:
s = slot()
for field_name, field in s.get_fields().items():
if field.__class__.__name__ not in VALID_SLOT_TYPES:
msg = "'{0}' on slot '{1}' is not a valid alexa slot type"
raise ValueError(msg.format(field_name,
s.__class__.__name__))
cls.intents[name] = (func, slot)
@classmethod
def generate_schema(cls):
"""Generates the alexa intents schema json"""
intents = []
for intent_name in cls.intents.keys():
intent_data = {"intent": intent_name,
"slots": []}
_, slot = cls.intents[intent_name]
if slot:
s = slot()
for field_name, field in s.get_fields().items():
slot_type = INTENT_SLOT_TYPES.get(field.__class__.__name__,
field.label)
if slot_type is None:
msg = "Intent '{0}' slot '{1}' does not have a valid slot_type"
raise ValueError(msg.format(intent_name, field_name))
if slot_type == "AMAZON.LITERAL":
msg = "Please upgrade intent '{0}' slot '{1}' to a ChoiceField with choices!"
log.warning(msg.format(intent_name, field_name))
slot_data = {
"name": field_name,
"type": slot_type
}
intent_data['slots'].append(slot_data)
intents.append(intent_data)
return {"intents": intents}
@classmethod
def generate_utterances(cls):
"""Generates the alexa utterances schema for all intents"""
utterance_format = "{0} {1}"
utterances = []
for intent_name in cls.intents.keys():
func, slot = cls.intents[intent_name]
fields = []
if slot:
s = slot()
fields = s.get_fields().keys()
docstring = """"""
if func.__doc__:
if "---\n" in func.__doc__:
docstring = func.__doc__.split("---")[-1].strip()
for line in docstring.splitlines():
line = line.strip()
for key in [i[1] for i in Formatter().parse(line) if i[1]]:
if "|" in key:
key = key.split("|")[-1]
if key not in fields:
msg = "Intent '{0}' utterance '{1}' has a missing the key in the slot '{2}'"
raise ValueError(msg.format(intent_name,
line,
s.__class__.__name__))
utterances.append(utterance_format.format(intent_name, line))
return utterances
def intent(*args, **kwargs):
"""
Decorator that registers a function to the IntentsSchema
"""
invoked = bool(not args or kwargs)
if not invoked:
func, args = args[0], ()
def register(func):
name = kwargs.get('name', func.__name__)
slot = kwargs.get('slot', None)
IntentsSchema.register(func, name, slot)
return func
return register if invoked else register(func)
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,564 | produktz/django-alexa | refs/heads/master | /django_alexa/api/validation.py | from __future__ import absolute_import
import os
import logging
import json
import requests
import base64
import pytz
from datetime import datetime, timedelta
from urlparse import urlparse
from OpenSSL import crypto
from rest_framework.exceptions import ValidationError
from django.conf import settings
log = logging.getLogger(__name__)
def validate_reponse_limit(value):
"""
value - response content
"""
log.debug("RESPONSE LIMIT VALIDATE: {0}".format(value))
if len(value.encode('utf-8')) > 1000 * 1000 * 24:
msg = "Alexa response content is bigger then 24 kilobytes"
raise ValidationError(detail=msg)
def validate_app_ids(value):
"""
value - an alexa app id
"""
if value not in settings.ALEXA_APP_IDS:
msg = "{0} is not a valid alexa skills application id"
raise ValidationError(detail=msg.format(value))
def validate_current_timestamp(value):
"""
value - a timestamp formatted in ISO 8601 (for example, 2015-05-13T12:34:56Z).
"""
# TODO: flesh out current timestamp validation
timestamp = datetime.strptime(value, "%Y-%m-%dT%H:%M:%SZ")
utc_timestamp = pytz.utc.localize(timestamp)
utc_timestamp_now = pytz.utc.localize(datetime.utcnow())
delta = utc_timestamp - utc_timestamp_now
log.debug("DATE TIME CHECK!")
log.debug("Alexa: {0}".format(utc_timestamp))
log.debug("Server: {0}".format(utc_timestamp_now))
log.debug("Delta: {0}".format(delta))
return False if delta > timedelta(minutes=2, seconds=30) else True
def validate_char_limit(value):
"""
value - a serializer to check to make sure the character limit is not excceed
"""
data = json.dumps(value)
log.debug("CHAR LIMIT VALIDATING: {0}".format(data))
if len(data) > 8000:
msg = "{0} has exceeded the total character limit of 8000"
raise ValidationError(detail=msg.format(value.__class__.__name__))
def verify_cert_url(cert_url):
"""
Verify the URL location of the certificate
"""
if cert_url is None:
return False
parsed_url = urlparse(cert_url)
if parsed_url.scheme == 'https':
if parsed_url.hostname == "s3.amazonaws.com":
if os.path.normpath(parsed_url.path).startswith("/echo.api/"):
return True
return False
def verify_signature(request_body, signature, cert_url):
"""
Verify the request signature is valid.
"""
if signature is None or cert_url is None:
return False
cert_str = requests.get(cert_url)
certificate = crypto.load_certificate(crypto.FILETYPE_PEM, str(cert_str.text))
if certificate.has_expired() is True:
return False
if certificate.get_subject().CN != "echo-api.amazon.com":
return False
decoded_signature = base64.b64decode(signature)
try:
if crypto.verify(certificate, decoded_signature, request_body, 'sha1') is None:
return True
except:
log.exception("Error occured during signature validation")
return False
def validate_alexa_request(request_headers, request_body):
"""
Validates this is a valid alexa request
value - a django request object
"""
# see https://github.com/anjishnu/ask-alexa-pykit/blob/388fb947009bc28671a09d258061529b494d09ad/lib/validation_utils.py
log.debug(request_headers)
log.debug(request_body)
if settings.ALEXA_ENABLE_REQUEST_VERIFICATON is True:
if verify_cert_url(request_headers.get('HTTP_SIGNATURECERTCHAINURL')) is False:
raise ValidationError("Invalid Certificate Chain URL")
if verify_signature(request_body, request_headers.get('HTTP_SIGNATURE'), request_headers.get('HTTP_SIGNATURECERTCHAINURL')) is False:
raise ValidationError("Invalid Request Signature")
timestamp = json.loads(request_body)['request']['timestamp']
if validate_current_timestamp(timestamp) is False:
raise ValidationError("Invalid Request Timestamp")
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,565 | produktz/django-alexa | refs/heads/master | /django_alexa/urls.py | from __future__ import absolute_import
from django.conf.urls import url, include
from rest_framework import routers
from .views import ASKViewSet
router = routers.DefaultRouter()
router.register(r"ask", ASKViewSet, base_name="ask")
router.include_root_view = False
urlpatterns = [
url(r'^alexa/', include(router.urls), name="alexa"),
]
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,566 | produktz/django-alexa | refs/heads/master | /django_alexa/api/fields.py | '''These are the only serializer fields support by the Alexa skills kit'''
from rest_framework.serializers import CharField, IntegerField, DateField, TimeField, DurationField, ChoiceField # flake8: noqa
# This maps serializer fields to the amazon intent slot types
INTENT_SLOT_TYPES = {
"CharField": "AMAZON.LITERAL",
"IntegerField": "AMAZON.NUMBER",
"DateField": "AMAZON.DATE",
"TimeField": "AMAZON.TIME",
"DurationField": "AMAZON.DURATION",
"USCityField": "AMAZON.US_CITY",
"FirstNameField": "AMAZON.US_FIRST_NAME",
"USStateField": "AMAZON.US_STATE",
"FourDigitField": "AMAZON.FOUR_DIGIT_NUMBER",
}
# Choicefield does not have a amazon mapping because it represents
# a custom slot type which has but has to have a defined choice set in the
# alexa skills kit interaction model
VALID_SLOT_TYPES = INTENT_SLOT_TYPES.keys() + [
"ChoiceField"
]
class USCityField(CharField):
def __init__(self, **kwargs):
super(USCityField, self).__init__(**kwargs)
class FirstNameField(CharField):
def __init__(self, **kwargs):
super(FirstNameField, self).__init__(**kwargs)
class USStateField(CharField):
def __init__(self, **kwargs):
super(USStateField, self).__init__(**kwargs)
class FourDigitField(IntegerField):
def __init__(self, **kwargs):
super(FourDigitField, self).__init__(**kwargs)
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,567 | produktz/django-alexa | refs/heads/master | /django_alexa/management/commands/alexa_intents.py | from __future__ import absolute_import
import json
from django.core.management.base import BaseCommand
from ...api import IntentsSchema
class Command(BaseCommand):
help = 'Prints the Alexa Skills Kit intents schema'
def handle(self, *args, **options):
data = IntentsSchema.generate_schema()
self.stdout.write(json.dumps(data, indent=4, sort_keys=True))
| {"/django_alexa/serializers.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/response_builder.py": ["/django_alexa/serializers.py"], "/django_alexa/api/__init__.py": ["/django_alexa/api/intents_schema.py", "/django_alexa/api/response_builder.py"], "/django_alexa/views.py": ["/django_alexa/api/__init__.py"], "/django_alexa/management/commands/alexa_utterances.py": ["/django_alexa/api/__init__.py"], "/django_alexa/api/intents_schema.py": ["/django_alexa/api/fields.py"], "/django_alexa/urls.py": ["/django_alexa/views.py"], "/django_alexa/management/commands/alexa_intents.py": ["/django_alexa/api/__init__.py"]} |
46,580 | kelliebanzon/csc202-proj3 | refs/heads/master | /linked_list_tests.py | import unittest
from linked_list import *
def less_than(a, b):
if a < b:
return True
else:
return False
class TestList(unittest.TestCase):
# Note that this test doesn't assert anything! It just verifies your
# class and function definitions.
def test_interface(self):
temp_list = empty_list()
temp_list = add(temp_list, 0, "Hello!")
length(temp_list)
get(temp_list, 0)
temp_list = set(temp_list, 0, "Bye!")
remove(temp_list, 0)
list_1 = Pair(0, None)
list_2 = Pair(0, Pair(1, Pair(2, None)))
list_none = Pair(0, Pair(None, Pair(2, None)))
def test_repr(self):
self.assertEqual(self.list_1.__repr__(), "0, None")
def test_empty_list(self):
self.assertEqual(empty_list(), None)
def test_add(self):
self.assertEqual(add(self.list_1, 0, 4), Pair(4, Pair(0, None)))
self.assertEqual(add(self.list_1, 1, 4), Pair(0, Pair(4, None)))
self.assertRaises(IndexError, add, self.list_1, 4, 6)
self.assertRaises(IndexError, add, empty_list(), 1, 12)
def test_length(self):
self.assertEqual(length(Pair(0, Pair(1, Pair(2, Pair(3, None))))), 4)
self.assertEqual(length(None), 0)
def test_get(self):
self.assertEqual(get(self.list_1, 0), 0)
self.assertEqual(get(self.list_none, 1), None)
self.assertEqual(get(Pair(None, Pair(1, Pair(2, None))), 0), None)
self.assertRaises(IndexError, get, self.list_1, 4)
self.assertRaises(IndexError, get, empty_list(), 0)
self.assertRaises(IndexError, get, add(add(add(add(empty_list(), 0, 87), 0, 2), 0, 4), 0, 3), 4)
self.assertRaises(IndexError, get, add(add(add(add(empty_list(), 0, 87), 0, 2), 0, 4), 0, 3), -2)
def test_set(self):
self.assertEqual(set(self.list_1, 0, 12), Pair(12, None))
self.assertRaises(IndexError, set, empty_list(), 0, 23)
self.assertRaises(IndexError, set, self.list_1, 4, 12)
self.assertRaises(IndexError, set, add(add(add(empty_list(), 0, 42), 0, "z"), 0, 2), 3, "abc")
def test_remove(self):
self.assertEqual(remove(self.list_2, 1), (1, Pair(0, Pair(2, None))))
self.assertRaises(IndexError, remove, self.list_2, 8)
self.assertRaises(IndexError, remove, add(add(add(empty_list(), 0, 5), 0, 4), 0, 3), 3)
def test_insert_sorted(self):
self.assertEqual(insert_sorted(Pair(0, None), 12, less_than), Pair(0, Pair(12)))
self.assertEqual(insert_sorted(Pair(12, None), 0, less_than), Pair(0, Pair(12)))
self.assertEqual(insert_sorted(empty_list(), 9, less_than), Pair(9))
self.assertEqual(insert_sorted(Pair(1, Pair(2, Pair(3, Pair(4, None)))), 5, less_than),
Pair(1, Pair(2, Pair(3, Pair(4, Pair(5, None))))))
if __name__ == '__main__':
unittest.main() | {"/linked_list_tests.py": ["/linked_list.py"], "/array_list_tests.py": ["/array_list.py"], "/huffman.py": ["/array_list.py", "/linked_list.py"]} |
46,581 | kelliebanzon/csc202-proj3 | refs/heads/master | /array_list_tests.py | import unittest
from array_list import *
class TestList(unittest.TestCase):
# Note that this test doesn't assert anything! It just verifies your
# class and function definitions.
def test_interface(self):
temp_list = empty_list()
temp_list = add(temp_list, 0, "Hello!")
length(temp_list)
get(temp_list, 0)
temp_list = set(temp_list, 0, "Bye!")
remove(temp_list, 0)
list_1 = ArrayList([0, 1, 2, 3])
list_2 = ArrayList([0, 1, 2, 3])
list_nones = ArrayList([0, 1, None, 3])
list_all_nones = ArrayList([None, None, None])
def test_repr(self):
self.assertEqual(ArrayList([0, 1, 2, 3]).__repr__(), "0, 1, 2, 3")
def test_eq(self):
self.assertEqual(self.list_1.__eq__("string"), False)
self.assertEqual(self.list_1.__eq__(ArrayList([0, 13])), False)
def test_empty_list(self):
self.assertEqual(empty_list(), ArrayList([]))
def test_add(self):
self.assertEqual(add(ArrayList([0, 1, 2, 3]), 1, 1), ArrayList([0, 1, 1, 2, 3]))
self.assertEqual(add(ArrayList([0, 1, 2, 3]), 0, "a"), ArrayList(["a", 0, 1, 2, 3]))
self.assertEqual(add(ArrayList([0, 1, 2, 3]), 4, 4), ArrayList([0, 1, 2, 3, 4]))
self.assertEqual(add(add(ArrayList([0, 1, 2, 3]), 4, 4), 2, "a"), ArrayList([0, 1, "a", 2, 3, 4]))
self.assertRaises(IndexError, add, self.list_1, 7, 2)
self.assertRaises(IndexError, add, self.list_1, -7, 2)
self.assertEqual((add(add(add(add(empty_list(), 0, "bc"), 0, 87), 0, 2), 0, 3) == add(
add(add(add(empty_list(), 0, "bc"), 0, 87), 0, 2), 0, 3)), True)
self.assertEqual((add(add(add(add(empty_list(), 0, "bc"), 0, 87), 0, 2), 0, 3) == add(
add(add(add(empty_list(), 0, "bc"), 0, 87), 0, 3), 0, 3)), False)
self.assertEqual(add(add(add(add(empty_list(), 0, "bc"), 0, 87), 0, 2), 0, 3), ArrayList([3, 2, 87, "bc"]))
def test_length(self):
self.assertEqual(length(ArrayList([0, 1, 2, 3])), 4)
self.assertEqual(length(add(ArrayList([0, 1, 2, 3]), 4, 4)), 5)
self.assertEqual(length(empty_list()), 0)
self.assertEqual(length(remove_index(ArrayList([0, 1, 2, 3]), 0)), 3)
def test_get(self):
self.assertEqual(get(self.list_1, 0), 0)
self.assertEqual(get(ArrayList([None, 1, 2]), 0), None)
self.assertEqual(get(self.list_all_nones, 1), None)
self.assertEqual(get(self.list_all_nones, 2), None)
self.assertEqual(get(add(self.list_1, 0, 0), 0), 0)
self.assertEqual(get(add(ArrayList([0, 1, 2, 3]), 0, 0), 4), 3)
temp = add(ArrayList([0, 1, 2, 3]), 0, 0)
self.assertRaises(IndexError, get, temp, 5)
self.assertRaises(IndexError, get, self.list_1, 12)
self.assertRaises(IndexError, get, self.list_1, -1)
self.assertRaises(IndexError, get, empty_list(), 12)
self.assertRaises(IndexError, get, empty_list(), 0)
def test_set(self):
self.assertEqual(set(ArrayList([0, 1, 2, 3]), 0, 16), ArrayList([16, 1, 2, 3]))
self.assertRaises(IndexError, set, self.list_1, 27, 0)
def test_increment(self):
self.assertEqual(increment(ArrayList([0,1,2,3]), 2), ArrayList([0,1,3,3]))
self.assertRaises(IndexError, increment, empty_list(), 2)
self.assertRaises(IndexError, increment, ArrayList([0,1,2,3]), 16)
self.assertEqual(increment(increment(ArrayList([0,1,2,3]), 2), 0), ArrayList([1,1,3,3]))
self.assertEqual(increment(ArrayList([0, None, 2]), 1), ArrayList([0, 1, 2]))
def test_remove(self):
self.assertEqual(remove(ArrayList([0, 1, 2, 3]), 0), (0, ArrayList([1, 2, 3])))
self.assertEqual(remove(ArrayList([0, 1, 2, 3]), 2), (2, ArrayList([0, 1, 3])))
self.assertRaises(IndexError, remove, self.list_1, 12)
self.assertRaises(IndexError, remove, add(add(add(empty_list(), 0, 5), 0, 4), 0, 3), 3)
def test_remove_index(self):
self.assertEqual(remove_index(ArrayList([0, 1, 2, 3]), 0), ArrayList([1, 2, 3]))
self.assertEqual(remove_index(ArrayList([0, 1, 2, 3]), 2), ArrayList([0, 1, 3]))
self.assertRaises(IndexError, remove_index, self.list_1, 12)
def test_foreach(self):
self.assertEqual(foreach(self.list_1, print), None)
def test_less_than(self):
self.assertEqual(less_than(1, 2), True)
self.assertEqual(less_than(2, 1), False)
def test_sort(self):
self.assertEqual(sort(ArrayList([20, 11, 82, 3]), less_than, empty_list()), ArrayList([3, 11, 20, 82]))
self.assertEqual(sort(add(sort(ArrayList([20, 11, 82, 3]), less_than, empty_list()), 2, -6), less_than, empty_list()),
ArrayList([-6, 3, 11, 20, 82]))
if __name__ == '__main__':
unittest.main() | {"/linked_list_tests.py": ["/linked_list.py"], "/array_list_tests.py": ["/array_list.py"], "/huffman.py": ["/array_list.py", "/linked_list.py"]} |
46,582 | kelliebanzon/csc202-proj3 | refs/heads/master | /huffman.py | import array_list as al
import linked_list as ll
# a Huffman Tree is either:
# - a Huffman node (one or more children)
# - a Huffman leaf (no children)
# a Leaf has:
# - char: the ASCII value of the character
# - freq: the number of times that character occurs
class Leaf:
def __init__(self, char, freq):
self.char = char # an int
self.freq = freq # an int
def __eq__(self, other):
return type(other) == Leaf and self.char == other.char and self.freq == other.freq
def __repr__(self):
return "[ {}, freq = {} ]".format(self.char, self.freq)
# a Node has:
# - char: the ASCII value of the character
# - freq: the number of times that character occurs
# - left: a Huffman Tree #TODO: fix this data defn
# - right: a Huffman Tree #TODO: fix this data defn
class Node:
def __init__(self, char, freq, left, right):
self.char = char # an int
self.freq = freq # an int
self.left = left # a Huffman Tree
self.right = right # a Huffman Tree
def __eq__(self, other):
return type(other) == Node and self.char == other.char and self.freq == other.freq and self.left == other.left and self.right == other.right
def __repr__(self):
return "{}, freq = {}\n\tleft = {}\n\tright = {}".format(self.char, self.freq, self.left.__repr__(), self.right.__repr__())
# given a text file, returns a list with the number of times each character within that file appears
# file -> ArrayList
def freq_counter(input):
ls = al.ArrayList([None]*250)
file = open(input, "r")
for line in file:
for char in line:
al.increment(ls, ord(char))
file.close()
return ls
# creates a string of the characters in a Huffman tree in a pre-order traversal
# tree -> string
def tree_traversal(tree):
fin = ""
if type(tree) == Leaf:
fin += chr(tree.char)
return fin
elif type(tree) == Node:
fin += tree_traversal(tree.left)
fin += tree_traversal(tree.right)
return fin
# compares two Huffman trees first by frequency, then by ASCII values
# tree tree -> boolean
def comes_before(a, b):
if a.freq < b.freq:
return True
elif a.freq > b.freq:
return False
else:
if a.char < b.char:
return True
else:
return False
# given a list of frequencies, builds sorted linked_list of leaves
# list -> list
def build_sorted_leaves(list):
sorted = ll.empty_list()
for i in range(0, 250):
if list.values[i] != None:
sorted = ll.insert_sorted(sorted, Leaf(i, list.values[i]), comes_before)
return sorted
# given a list of character occurrences, builds a Huffman tree
# list -> tree
def build_tree(list):
sorted = build_sorted_leaves(list) # TODO: re-nest build_sorted_leaves?
while ll.length(sorted) > 1: # TODO: inefficient
tup = ll.remove(sorted, 0)
first = tup[0]
sorted = tup[1]
tup = ll.remove(sorted, 0)
second = tup[0]
sorted = tup[1]
if first.char < second.char:
char = first.char
else:
char = second.char
node = Node(char, first.freq+second.freq, first, second)
sorted = ll.insert_sorted(sorted, node, comes_before)
return node
# given a Huffman tree, returns a list of the keys for each Leaf
# tree -> list
def build_codes(tree, ls = al.ArrayList([None]*250), acc = ""):
if type(tree) == Leaf:
al.set(ls, tree.char, acc)
else:
build_codes(tree.left, ls, acc+"0")
build_codes(tree.right, ls, acc+"1")
return ls
# ----------------------------------------------------------------------------------------------------------------------
import unittest
class TestList(unittest.TestCase):
huff_list = al.set(al.set(al.set(al.set(al.set(al.ArrayList([None]*250), 97, 4), 98, 3), 99, 2), 100, 1), 32, 3)
huff_tree = Node(32, 13,
Node(32, 6, Leaf(32, 3), Leaf(98, 3)),
Node(97, 7, Node(99, 3, Leaf(100, 1), Leaf(99, 2)), Leaf(97, 4)))
tree0 = Node(32, 6, Leaf(32, 3), Leaf(98, 3))
tree1 = Node(97, 7, Node(99, 3, Leaf(100, 1), Leaf(99, 2)), Leaf(97, 4))
print(tree0)
def test_freq_counter(self):
self.assertRaises(FileNotFoundError, freq_counter, "fake_file.txt")
al_first = al.ArrayList([None]*250)
al.set(al_first, 97, 3)
al.set(al_first, 98, 2)
al.set(al_first, 99, 1)
self.assertEqual(freq_counter("first.txt"), al_first)
def test_tree_traversal(self):
self.assertEqual(tree_traversal(self.tree0), " b")
self.assertEqual(tree_traversal(self.tree1), "dca")
self.assertEqual(tree_traversal(self.huff_tree), " bdca")
def test_comes_before(self):
self.assertEqual(comes_before(self.tree0, self.tree1), True)
self.assertEqual(comes_before(self.huff_tree, self.tree0), False)
self.assertEqual(comes_before(Leaf(32, 3), Leaf(98, 3)), True)
def test_build_sorted_leaves(self):
self.assertEqual(build_sorted_leaves(self.huff_list),
ll.Pair(Leaf(100, 1), ll.Pair(Leaf(99, 2), ll.Pair(Leaf(32, 3), ll.Pair(Leaf(98, 3), ll.Pair(Leaf(97, 4)))))))
def test_build_tree(self):
self.assertEqual(build_tree(self.huff_list), self.huff_tree)
self.assertEqual(build_tree(al.set(al.set(al.ArrayList([None]*250), 32, 3), 98, 3)), self.tree0)
self.assertEqual(build_tree(freq_counter("first.txt")),
Node(97, 6, Leaf(97, 3), Node(98, 3, Leaf(99, 1), Leaf(98, 2))))
def test_build_codes(self):
self.assertEqual(build_codes(self.huff_tree),
al.set(al.set(al.set(al.set(al.set(al.ArrayList([None]*250), 32, "00"), 98, "01"), 100, "100"), 99, "101"), 97, "11"))
self.assertEqual(build_codes(build_tree(self.huff_list)),
al.set(al.set(al.set(al.set(al.set(al.ArrayList([None] * 250), 32, "00"), 98, "01"), 100, "100"), 99, "101"), 97, "11"))
self.assertEqual(build_codes(build_tree(freq_counter("huff_ex.txt"))),
al.set(al.set(al.set(al.set(al.set(al.ArrayList([None] * 250), 32, "00"), 98, "01"), 100, "100"), 99, "101"), 97, "11"))
if __name__ == '__main__':
unittest.main() | {"/linked_list_tests.py": ["/linked_list.py"], "/array_list_tests.py": ["/array_list.py"], "/huffman.py": ["/array_list.py", "/linked_list.py"]} |
46,583 | kelliebanzon/csc202-proj3 | refs/heads/master | /array_list.py | # an ArrayList has:
# - values: a list of values
# - length: a length (an int representing the number of values in the list)
# - fixed: the capacity of the list
class ArrayList:
def __init__(self, ls = []):
count = 0
for value in ls:
count = count + 1
self.length = count # the length of the list (the number of values)
self.fixed = count # the fixed length of the list (the number of spaces)
self.values = [None] * count # the list of values
for i in range(0, count):
self.values[i] = ls[i]
def __eq__(self, other):
if type(other) != ArrayList:
return False
for i in range(0, self.length):
if self.values[i] != other.values[i]:
return False
return True
def __repr__(self):
fin = ""
for i in range(0, self.length):
if i != self.length - 1:
fin += str(self.values[i]) + ", "
else:
fin += str(self.values[i])
return fin
# returns an empty list
# -> ArrayList
def empty_list():
return ArrayList([])
"""def insert(list, func, val):
if list.length == 0:
raise IndexError
else:
new = [None] * (list.length+1)
for i in range(list.length):
if func(val, list.values[i]):
list = add_double(list, i, val)
return list
list = add_double(list, i+1, val)
return list"""
# adds a given value to a given index in the list
# ArrayList int value -> ArrayList
def add(curr, index, val):
if index > curr.length or index < 0:
raise IndexError
else:
new = [None] * (curr.length+1)
for i in range(0, index):
new[i] = curr.values[i]
new[index] = val
for i in range(index, curr.length):
new[i+1] = curr.values[i]
curr.values = new
curr.length = curr.length + 1
curr.fixed = curr.length
return curr
"""def add_grow20(curr, index, val):
if index > curr.length or index < 0:
raise IndexError
elif curr.length == curr.fixed:
curr.fixed = curr.fixed + 20
new = [None] * curr.fixed
for i in range(0, index):
new[i] = curr.values[i]
new[index] = val
for i in range(index, curr.length):
new[i + 1] = curr.values[i]
curr.values = new
curr.length = curr.length + 1
elif curr.values[index] == None:
curr.values[index] = val
curr.length = curr.length + 1
else:
new = [None]*(curr.fixed)
for i in range(0, index):
new[i] = curr.values[i]
new[index] = val
for i in range(index+1, curr.length+1):
new[i] = curr.values[i-1]
curr.values = new
curr.length = curr.length + 1
return curr
def add_double(curr, index, val):
if index > curr.length or index < 0:
raise IndexError
elif curr.length == curr.fixed:
if curr.fixed == 0:
curr.fixed = 1
else:
curr.fixed = (curr.fixed * 2)
test = [None] * curr.fixed
for i in range(0, index):
test[i] = curr.values[i]
test[index] = val
for i in range(index, curr.length):
test[i + 1] = curr.values[i]
curr.values = test
curr.length = curr.length + 1
elif curr.length != 0 and curr.values[index] == None:
curr.values[index] = val
curr.length = curr.length + 1
else:
new = [None]*(curr.fixed)
for i in range(0, index):
new[i] = curr.values[i]
new[index] = val
for i in range(index+1, curr.length+1):
new[i] = curr.values[i-1]
curr.values = new
curr.length = curr.length + 1
return curr"""
# returns the length of a given list
# ArrayList -> int
def length(list):
return list.length
# returns the value of the list at a given index
# ArrayList int -> value
def get(list, index):
if index >= list.length or index < 0:
raise IndexError
else:
return list.values[index]
# replaces the value at a given index
# ArrayList int value -> ArrayList
def set(list, index, value):
if index >= list.length or index < 0:
raise IndexError
else:
list.values[index] = value
return list
# increments the value at a given index by 1
# note: only works for an ArrayList of numbers
# note: uses mutation
# ArrayList -> ArrayList
def increment(list, index):
if index < 0 or index > list.length-1:
raise IndexError
elif list.values[index] == None:
list.values[index] = 1
else:
list.values[index] += 1
return list
# removes the value at a given index
# return the old value and the updated list
# ArrayList int -> value ArrayList
def remove(list, index):
if index >= list.length or index < 0:
raise IndexError
else:
temp = list.values[index]
return (temp, remove_index(list, index))
# removes the value at a given index
# returns the updated list
# ArrayList int -> ArrayList
def remove_index(list, index):
if index >= list.length or index < 0:
raise IndexError
else:
ls = [None] * list.fixed
for i in range(0, index):
ls[i] = list.values[i]
for i in range(index+1, list.length):
ls[i-1] = list.values[i]
"""for i in range(list.length, list.fixed):
ls[i] = None"""
list.values = ls
list.length -= 1
return list
# execute a given function on every object of a given list
# ArrayList function -> None
def foreach(list, func):
for val in list.values:
func(val)
return None
# returns True if the first value is less than the second, returns False otherwise
# value value -> boolean
def less_than(a, b):
if a <= b:
return True
else:
return False
# sort a list by a given function
# ex. [20, 11, 82, 3] -> [3, 11, 20, 82]
# [20]
# [11, 20]
# [11, 20, 82]
# [3, 11, 20, 82]
# ArrayList -> ArrayList
def sort(list, func, new = empty_list()):
for i in range(0, list.length):
j = 0
while j <= new.length-1 and func(list.values[i], new.values[j]) == False:
j += 1
new = add(new, j, list.values[i])
list = ArrayList(new.values)
return list
"""def sort_no_mute(list, func, new = empty_list()):
for i in range(0, list.length):
j = 0
while j <= new.length-1 and func(list.values[i], new.values[j]) == False:
j += 1
new = add(new, j, list.values[i])
new_list = ArrayList(new.values)
return new_list""" | {"/linked_list_tests.py": ["/linked_list.py"], "/array_list_tests.py": ["/array_list.py"], "/huffman.py": ["/array_list.py", "/linked_list.py"]} |
46,584 | kelliebanzon/csc202-proj3 | refs/heads/master | /linked_list.py | # AnyList is either:
# - None
# - Pair(value, AnyList)
class Pair:
def __init__(self, first, rest = None):
self.first = first
self.rest = rest
def __eq__(self, other):
return type(other) == Pair and self.first == other.first and self.rest == other.rest
def __repr__(self):
return ("%r, %r" % (self.first, self.rest))
# returns an empty list
# -> AnyList
def empty_list():
return None
# inserts a given value at a given position in a given list
# AnyList integer value -> AnyList
def add(list, index, value):
if (list == None and index >= 1) or index < 0:
raise IndexError
elif index == 0:
return Pair(value, list)
else:
return Pair(list.first, add(list.rest, index-1, value))
# returns the length of a given list
# AnyList -> int
def length(list):
if list == None:
return 0
else:
return 1 + length(list.rest)
# returns the value of the list at a given index
# AnyList int -> value
def get(list, index):
if (list == None and index >= 0) or index < 0:
raise IndexError
elif index == 0:
return list.first
else:
return get(list.rest, index-1)
# replaces the value at a given index with the given value
# AnyList int value -> AnyList
def set(list, index, value):
if (list == None and index >= 0) or index < 0:
raise IndexError
elif index == 0:
return Pair(value, list.rest)
else:
return Pair(list.first, set(list.rest, index-1, value))
# removes the value at a given index
# returns a tuple with the old value and the updated list
# AnyList int -> value AnyList
def remove(list, index):
if list == None:
raise IndexError()
elif index == 0:
return list.first, list.rest
else:
fin = remove(list.rest, index - 1)
return fin[0], Pair(list.first, fin[1])
# inserts a value into a sorted list in ascending order according to a given comparison function
# AnyList value function -> AnyList
def insert_sorted(list, val, func):
if list == None or func(val, list.first):
return Pair(val, list)
else:
return Pair(list.first, insert_sorted(list.rest, val, func)) | {"/linked_list_tests.py": ["/linked_list.py"], "/array_list_tests.py": ["/array_list.py"], "/huffman.py": ["/array_list.py", "/linked_list.py"]} |
46,615 | zfang92/pahmc-ode-gpu | refs/heads/master | /main.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This is the main executable of pahmc_ode_cpu and should be the point of entry
at which all the necessary information is provided. In particular, the user
is assumed to have the following:
1) The dynamical system. If calling one of the built-in examples, the name
of the dynamics must have a match in 'lib_dynamics.py'; if builing from
scratch, 'def_dynamics.py' must be ready at this point.
2) The data. If performing twin-experiments, the specs should be given but
a data file is not required; if working with real data, the data should be
prepared according to the user manual.
3) If external stimuli are needed, a .npy file containing the time series;
4) Configuration of the code, including the hyper-parameters for PAHMC.
Refer to the manual for the shape and type requirements. Also note that a
lot of them can take either a single or an array/list of values. See user
manual for details.
It is suggested that the user keep a lookup table for the model paramters to
make it easier to preserve order when working on the above steps.
"""
from datetime import date
from pathlib import Path
import time
from numba import cuda
import numpy as np
from pahmc_ode_gpu.pahmc import anneal
from pahmc_ode_gpu.configure import Configure
from pahmc_ode_gpu import cuda_lib_dynamics
from pahmc_ode_gpu.data_preparation import generate_twin_data
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__zeros1d
#=========================type your code below=========================
"""A name for your dynamics."""
# it will be used to try to find a match in the built-ins
name = 'lorenz96'
"""Specs for the dynamics."""
# set the dimension of your dynamics
D = 20
# set the length of the observation window
M = 200
# set the observed dimensions (list with smallest possible value 1)
obsdim = [1, 2, 4, 6, 8, 10, 12, 14, 15, 17, 19, 20]
# set the discretization interval
dt = 0.025
"""Specs for precision annealing and HMC."""
# set the starting Rf value
Rf0 = 1e6
# set alpha
alpha = 1.0
# set the total number of beta values
betamax = 1
# set the number of HMC samples for each beta
n_iter = 1000
# set the HMC simulation stepsize for each beta
epsilon = 1e-3
# set the number of leapfrog steps for an HMC sample for each beta
S = 100
# set the HMC masses for each beta
mass = (1e0, 1e0, 1e0)
# set the HMC scaling parameter for each beta
scaling = 1.0
# set the "soft" dynamical range for initialization purpose
soft_dynrange = (-10, 10)
# set an initial guess for the parameters
par_start = 8.0
"""Specs for the twin-experiment data"""
# set the length of the data (must be greater than M defined above)
length = 1000
# set the noise levels (standard deviations) in the data for each dimension
noise = 0.4 * np.ones(D)
# set the true parameters (caution: order must be consistent)
par_true = 8.17
# set the initial condition for the data generation process
x0 = np.ones(D)
x0[0] = 0.01
# set the switch for discarding the first half of the generated data
burndata = True
#===============================end here===============================
"""Configure the inputs and the stimuli."""
config = Configure(name,
D, M, obsdim, dt,
Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start,
length, noise, par_true, x0, burndata)
config.check_all()
name, \
D, M, obsdim, dt, \
Rf0, alpha, betamax, \
n_iter, epsilon, S, mass, scaling, \
soft_dynrange, par_start, \
length, noise, par_true, x0, burndata = config.regulate()
stimuli = config.get_stimuli()
"""Fetch dynamics kernels."""
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
k__dfield_dpar = getattr(cuda_lib_dynamics, f'k__{name}_dfield_dpar')
"""Generate twin-experiment data, also trim stimuli as needed."""
data_noisy, stimuli \
= generate_twin_data(name, k__field, k__jacobian,
D, length, dt, noise, par_true, x0, burndata, stimuli)
"""Fetch data and stimuli for the training window."""
Y = data_noisy[obsdim, :M]
stimuli_training = np.ascontiguousarray(stimuli[:, :M])
"""Do precision annealing Hamiltonian Monte Carlo."""
t0 = time.perf_counter()
burn, Rm, Rf, eta_avg, acceptance, \
action, action_meanpath, ME_meanpath, FE_meanpath, \
X_init, X_gd, X_mean, par_history, par_mean, Xfinal_history \
= anneal(k__field, k__jacobian, k__dfield_dpar, stimuli_training, Y,
D, M, obsdim, dt, Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start)
print(f'\nTotal time = {time.perf_counter()-t0:.2f} seconds.')
"""Save the results."""
day = date.today().strftime('%Y-%m-%d')
i = 1
while (Path.cwd() / 'user_results' / f'{name}_{day}_{i}.npz').exists():
i = i + 1
np.savez(Path.cwd()/'user_results'/f'{name}_{day}_{i}',
name=name,
D=D, M=M, obsdim=obsdim, dt=dt,
Rf0=Rf0, alpha=alpha, betamax=betamax,
n_iter=n_iter, epsilon=epsilon, S=S, mass=mass, scaling=scaling,
soft_dynrange=soft_dynrange, par_start=par_start,
length=length, data_noisy=data_noisy, stimuli=stimuli,
noise=noise, par_true=par_true, x0=x0, burndata=burndata,
burn=burn,
Rm=Rm,
Rf=Rf,
eta_avg=eta_avg,
acceptance=acceptance,
action=action,
action_meanpath=action_meanpath,
ME_meanpath=ME_meanpath,
FE_meanpath=FE_meanpath,
X_init=X_init,
X_gd=X_gd,
X_mean=X_mean,
par_history=par_history,
par_mean=par_mean,
Xfinal_history=Xfinal_history)
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,616 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-pahmc.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This module runs Lorenz96 within a fixed Rf. See user manual for what to expect.
"""
import os
from pathlib import Path
import time
from numba import cuda
import numpy as np
from matplotlib import pyplot as plt
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu.pahmc import anneal
from pahmc_ode_gpu.configure import Configure
from pahmc_ode_gpu import cuda_lib_dynamics
from pahmc_ode_gpu.data_preparation import generate_twin_data
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__zeros1d
#=========================type your code below=========================
"""A name for your dynamics."""
# it will be used to try to find a match in the built-ins
name = 'lorenz96'
"""Specs for the dynamics."""
# set the dimension of your dynamics
D = 20
# set the length of the observation window
M = 200
# set the observed dimensions (list with smallest possible value 1)
obsdim = [1, 2, 4, 6, 8, 10, 12, 14, 15, 17, 19, 20]
# set the discretization interval
dt = 0.025
"""Specs for precision annealing and HMC."""
# set the starting Rf value
Rf0 = 1e6
# set alpha
alpha = 1.0
# set the total number of beta values
betamax = 1
# set the number of HMC samples for each beta
n_iter = 1000
# set the HMC simulation stepsize for each beta
epsilon = 1e-3
# set the number of leapfrog steps for an HMC sample for each beta
S = 100
# set the HMC masses for each beta
mass = (1e0, 1e0, 1e0)
# set the HMC scaling parameter for each beta
scaling = 1.0
# set the "soft" dynamical range for initialization purpose
soft_dynrange = (-10, 10)
# set an initial guess for the parameters
par_start = 8.0
"""Specs for the twin-experiment data"""
# set the length of the data (must be greater than M defined above)
length = 1000
# set the noise levels (standard deviations) in the data for each dimension
noise = 0.4 * np.ones(D)
# set the true parameters (caution: order must be consistent)
par_true = 8.17
# set the initial condition for the data generation process
x0 = np.ones(D)
x0[0] = 0.01
# set the switch for discarding the first half of the generated data
burndata = True
#===============================end here===============================
"""Configure the inputs and the stimuli."""
config = Configure(name,
D, M, obsdim, dt,
Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start,
length, noise, par_true, x0, burndata)
config.check_all()
name, \
D, M, obsdim, dt, \
Rf0, alpha, betamax, \
n_iter, epsilon, S, mass, scaling, \
soft_dynrange, par_start, \
length, noise, par_true, x0, burndata = config.regulate()
stimuli = config.get_stimuli()
"""Fetch dynamics kernels."""
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
k__dfield_dpar = getattr(cuda_lib_dynamics, f'k__{name}_dfield_dpar')
"""Generate twin-experiment data, also trim stimuli as needed."""
data_noisy, stimuli \
= generate_twin_data(name, k__field, k__jacobian,
D, length, dt, noise, par_true, x0, burndata, stimuli)
"""Fetch data and stimuli for the training window."""
Y = data_noisy[obsdim, :M]
stimuli_training = np.ascontiguousarray(stimuli[:, :M])
"""Do precision annealing Hamiltonian Monte Carlo."""
t0 = time.perf_counter()
burn, Rm, Rf, eta_avg, acceptance, \
action, action_meanpath, ME_meanpath, FE_meanpath, \
X_init, X_gd, X_mean, par_history, par_mean, Xfinal_history \
= anneal(k__field, k__jacobian, k__dfield_dpar, stimuli_training, Y,
D, M, obsdim, dt, Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start)
print(f'\nTotal time = {time.perf_counter()-t0:.2f} seconds.')
os.chdir(Path.cwd()/'unit_tests')
"""Plot action vs. iteration."""
fig, ax = plt.subplots(figsize=(6,5))
textblue = (49/255, 99/255, 206/255)
ax.loglog(np.arange(1, n_iter+2), action[0, 1:], color=textblue, lw=1.5)
ax.set_xlim(1, n_iter+1)
ax.set_xlabel('iteration')
ax.set_ylabel('action')
"""Get an overview of performance."""
d_stimuli = cuda.to_device(stimuli_training)
d_Y = cuda.to_device(Y)
d_obsdim = cuda.to_device(obsdim)
obs_ind = -np.ones(D, dtype='int64')
for l in range(len(obsdim)):
obs_ind[obsdim[l]] = l
d_obs_ind = cuda.to_device(obs_ind)
def overview(X, par, Rf):
# define device arrays
d_X = cuda.to_device(X)
d_par = cuda.to_device(par)
d_Rf = cuda.to_device(Rf)
d_field = cuda.device_array_like(X)
d_jacobian = cuda.device_array((D,D,M))
d_dfield_dpar = cuda.device_array((D,len(par),M))
d_action = cuda.device_array((1,))
d_diff = cuda.device_array((D,M-1))
d_dAdX = cuda.device_array_like(X)
d_dAdpar = cuda.device_array_like(par)
# get the action
k__field[(16,32), (2,128)](d_X, d_par, d_stimuli, d_field)
k__zeros1d[40, 256](d_action)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X, d_field, d_Rf, d_Y, dt, d_obsdim, Rm,
d_action)
action = d_action.copy_to_host()[0]
# get model error
field = d_field.copy_to_host()
fX = X[:, :M-1] + dt / 2 * (field[:, 1:] + field[:, :M-1])
FE = np.sum(Rf/2/M*np.sum((X[:, 1:]-fX)**2, axis=1))
# get the gradients
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
cuda.synchronize()
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf, 1.0, d_Y, dt,
d_obsdim, d_obs_ind, Rm, d_dAdX)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
k__zeros1d[40, 256](d_dAdpar)
cuda.synchronize()
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar, d_Rf, 1.0, dt,
d_dAdpar)
dAdX = d_dAdX.copy_to_host()
dAdpar = d_dAdpar.copy_to_host()
# print results
print(f'\n action = {action},')
print(f' modelerr = {FE},\n')
print(f' max |dAdX| = {np.max(np.abs(dAdX))},')
print(f' min |dAdX| = {np.min(np.abs(dAdX))},\n')
print(f'max |dAdpar| = {np.max(np.abs(dAdpar))},')
print(f'min |dAdpar| = {np.min(np.abs(dAdpar))}.\n')
return action, FE, dAdX, dAdpar
print('\n--------------------------------------------------')
print('Initially:')
ov1_action, ov1_FE, ov1_dAdX, ov1_dAdpar \
= overview(X_init[0, :, :], par_history[0, 0, :], Rf[0, :])
print('--------------------------------------------------')
print('After exploration:')
ov2_action, ov2_FE, ov2_dAdX, ov2_dAdpar \
= overview(X_gd[0, :, :], par_history[0, 1, :], Rf[0, :])
print('--------------------------------------------------')
print('After exploitation:')
ov3_action, ov3_FE, ov3_dAdX, ov3_dAdpar \
= overview(X_mean[0, :, :], par_mean[0, :], Rf[0, :])
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,617 | zfang92/pahmc-ode-gpu | refs/heads/master | /tune.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
Alternative to 'main.py', if you would like to tune the hyperparameters for
each beta (generally a good practice), use this file as the main executable.
The user is assumed to have the following:
1) The dynamical system. If calling one of the built-in examples, the name
of the dynamics must have a match in 'lib_dynamics.py'; if builing from
scratch, 'def_dynamics.py' must be ready at this point.
2) The data. If performing twin-experiments, the specs should be given but
a data file is not required; if working with real data, the data should be
prepared according to the user manual.
3) If external stimuli are needed, a .npy file containing the time series;
4) Configuration of the code, including the hyper-parameters for PAHMC.
Refer to the manual for the shape and type requirements. Also note that a
lot of them can take either a single or an array/list of values. See user
manual for details.
It is suggested that the user keep a lookup table for the model paramters to
make it easier to preserve order when working on the above steps.
"""
from datetime import date
from pathlib import Path
import time
from numba import cuda
import numpy as np
import matplotlib.pyplot as plt
from pahmc_ode_gpu.pahmc_tune import anneal
from pahmc_ode_gpu.configure import Configure
from pahmc_ode_gpu import cuda_lib_dynamics
from pahmc_ode_gpu.data_preparation import generate_twin_data
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__zeros1d
#================type your code below (stepwise tuning)================
"""Tunable hyperparameters."""
# set the beta value to be tuned
tune_beta = 0
# set the number of HMC samples for each beta
n_iter = 500
# set the HMC simulation stepsize for each beta
epsilon = 1e-3
# set the number of leapfrog steps for an HMC sample for each beta
S = 50
# set the HMC masses for each beta
mass = (1e0, 1e0, 1e0)
# set the HMC scaling parameter for each beta
scaling = 1e5
#===================type your code below (only once)===================
"""A name for your dynamics."""
# it will be used to try to find a match in the built-ins
name = 'nakl'
"""Specs for the dynamics."""
# set the dimension of your dynamics
D = 4
# set the length of the observation window
M = 5000
# set the observed dimensions (list with smallest possible value 1)
obsdim = [1]
# set the discretization interval
dt = 0.02
"""The remaining hyperparameters."""
# set the starting Rf value
Rf0 = np.array([1.0e-1, 1.2e3, 1.6e3, 2.1e3])
# set alpha
alpha = 2.0
# set the "soft" dynamical range for initialization purpose
soft_dynrange = np.array([[-120, 0], [0, 1], [0, 1], [0, 1]])
# set an initial guess for the parameters
par_start = np.array([115, 50, 25, -70, 0.2, -55,
-45, 16, 0.15, 0.4,
-55, -16, 1.2, 6,
-52, 31, 0.8, 5])
"""Specs for the twin-experiment data"""
# set the length of the data (must be greater than M defined above)
length = int(1000/dt)
# set the noise levels (standard deviations) in the data for each dimension
noise = np.array([1, 0, 0, 0])
# set the true parameters (caution: order must be consistent)
par_true = np.array([120, 50, 20, -77, 0.3, -54.4,
-40, 15, 0.1, 0.4,
-60, -15, 1, 7,
-55, 30, 1, 5])
# set the initial condition for the data generation process
x0 = np.array([-70, 0.1, 0.9, 0.1])
# set the switch for discarding the first half of the generated data
burndata = False
#===============================end here===============================
"""Prepare current Rf and set betamax."""
Rf0 = Rf0 * (alpha ** tune_beta)
betamax = 1
"""Configure the inputs and the stimuli."""
config = Configure(name,
D, M, obsdim, dt,
Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start,
length, noise, par_true, x0, burndata)
config.check_all()
name, \
D, M, obsdim, dt, \
Rf0, alpha, betamax, \
n_iter, epsilon, S, mass, scaling, \
soft_dynrange, par_start, \
length, noise, par_true, x0, burndata = config.regulate()
stimuli = config.get_stimuli()
"""Fetch dynamics kernels."""
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
k__dfield_dpar = getattr(cuda_lib_dynamics, f'k__{name}_dfield_dpar')
"""Generate twin-experiment data, also trim stimuli as needed."""
data_noisy, stimuli \
= generate_twin_data(name, k__field, k__jacobian,
D, length, dt, noise, par_true, x0, burndata, stimuli)
"""Fetch data and stimuli for the training window."""
Y = data_noisy[obsdim, :M]
stimuli_training = np.ascontiguousarray(stimuli[:, :M])
"""Do precision annealing Hamiltonian Monte Carlo."""
t0 = time.perf_counter()
burn, Rm, Rf, eta_avg, acceptance, \
action, action_meanpath, ME_meanpath, FE_meanpath, \
X_init, X_gd, X_mean, par_history, par_mean, Xfinal_history \
= anneal(k__field, k__jacobian, k__dfield_dpar, stimuli_training, Y,
D, M, obsdim, dt, Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start, name, tune_beta)
print(f'\nTotal time = {time.perf_counter()-t0:.2f} seconds.')
"""Save the results."""
np.savez(Path.cwd()/'user_results'/f'tune_{name}_{tune_beta}',
name=name,
D=D, M=M, obsdim=obsdim, dt=dt,
Rf0=Rf0, alpha=alpha, betamax=betamax,
n_iter=n_iter, epsilon=epsilon, S=S, mass=mass, scaling=scaling,
soft_dynrange=soft_dynrange, par_start=par_start,
length=length, data_noisy=data_noisy, stimuli=stimuli,
noise=noise, par_true=par_true, x0=x0, burndata=burndata,
burn=burn,
Rm=Rm,
Rf=Rf,
eta_avg=eta_avg,
acceptance=acceptance,
action=action,
action_meanpath=action_meanpath,
ME_meanpath=ME_meanpath,
FE_meanpath=FE_meanpath,
X_init=X_init,
X_gd=X_gd,
X_mean=X_mean,
par_history=par_history,
par_mean=par_mean,
Xfinal_history=Xfinal_history)
"""Plot action vs. iteration for current beta."""
fig, ax = plt.subplots(figsize=(6,5))
textblue = (49/255, 99/255, 206/255)
ax.loglog(np.arange(1, n_iter+2), action[0, 1:], color=textblue, lw=1.5)
ax.set_xlim(1, n_iter+1)
ax.set_xlabel('iteration')
ax.set_ylabel('action')
"""Get an overview of performance."""
d_stimuli = cuda.to_device(stimuli_training)
d_Y = cuda.to_device(Y)
d_obsdim = cuda.to_device(obsdim)
obs_ind = -np.ones(D, dtype='int64')
for l in range(len(obsdim)):
obs_ind[obsdim[l]] = l
d_obs_ind = cuda.to_device(obs_ind)
# retrive the noiseless data (if doing twin experiment)
noiselessfile_name = Path.cwd() / 'user_data' / f'{name}_noiseless.npz'
if noiselessfile_name.exists():
noiselessfile = np.load(noiselessfile_name)
X_true = noiselessfile['data'][:, 0:M]
noiselessfile.close()
def overview(X, par, Rf):
# define device arrays
d_X = cuda.to_device(X)
d_par = cuda.to_device(par)
d_Rf = cuda.to_device(Rf)
d_field = cuda.device_array_like(X)
d_jacobian = cuda.device_array((D,D,M))
d_dfield_dpar = cuda.device_array((D,len(par),M))
d_action = cuda.device_array((1,))
d_diff = cuda.device_array((D,M-1))
d_dAdX = cuda.device_array_like(X)
d_dAdpar = cuda.device_array_like(par)
# get the action
k__field[(16,32), (2,128)](d_X, d_par, d_stimuli, d_field)
k__zeros1d[40, 256](d_action)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X, d_field, d_Rf, d_Y, dt, d_obsdim, Rm,
d_action)
action = d_action.copy_to_host()[0]
# get model error
field = d_field.copy_to_host()
fX = X[:, :M-1] + dt / 2 * (field[:, 1:] + field[:, :M-1])
FE = np.sum(Rf/2/M*np.sum((X[:, 1:]-fX)**2, axis=1))
# get the gradients
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
cuda.synchronize()
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf, 1.0, d_Y, dt,
d_obsdim, d_obs_ind, Rm, d_dAdX)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
k__zeros1d[40, 256](d_dAdpar)
cuda.synchronize()
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar, d_Rf, 1.0, dt,
d_dAdpar)
dAdX = d_dAdX.copy_to_host()
dAdpar = d_dAdpar.copy_to_host()
# print results
print(f'\n action = {action},')
print(f' modelerr = {FE},\n')
print(f' max |dAdX| = {np.max(np.abs(dAdX))},')
print(f' min |dAdX| = {np.min(np.abs(dAdX))},\n')
print(f'max |dAdpar| = {np.max(np.abs(dAdpar))},')
print(f'min |dAdpar| = {np.min(np.abs(dAdpar))}.\n')
return action, FE, dAdX, dAdpar
print('\n--------------------------------------------------')
print('Initially:')
ov1_action, ov1_FE, ov1_dAdX, ov1_dAdpar \
= overview(X_init[0, :, :], par_history[0, 0, :], Rf[0, :])
print('--------------------------------------------------')
print('After exploration:')
ov2_action, ov2_FE, ov2_dAdX, ov2_dAdpar \
= overview(X_gd[0, :, :], par_history[0, 1, :], Rf[0, :])
print('--------------------------------------------------')
print('After exploitation:')
ov3_action, ov3_FE, ov3_dAdX, ov3_dAdpar \
= overview(X_mean[0, :, :], par_mean[0, :], Rf[0, :])
print('\n--------------------------------------------------')
print('L1 distances (traveled and remaining):')
print('\n from X_init to X_mean: '\
+f'{np.sum(np.abs(X_mean[0, :, :]-X_init[0, :, :]))},')
if noiselessfile_name.exists():
print(' from X_mean to X_true: '\
+f'{np.sum(np.abs(X_true-X_mean[0, :, :]))},')
print('\nfrom par_init to par_mean: '\
+f'{np.sum(np.abs(par_mean[0, :]-par_history[0, 0, :]))},')
if noiselessfile_name.exists():
print('from par_mean to par_true: '\
+f'{np.sum(np.abs(par_true-par_mean[0, :]))}.')
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,618 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-cuda_utilities.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This is a unit test. If you would like to further develop pahmc_ode_gpu, you
should visit here frequently.
"""
import os
from pathlib import Path
from numba import cuda, jit
import numpy as np
import torch as th
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__leapfrog_X, k__leapfrog_par, k__linearop2d, k__linearop1d, \
k__zeros1d
os.chdir(Path.cwd()/'unit_tests')
"""Prepare data."""
D = 20
M = 200
X = np.random.uniform(-8.0, 8.0, (D,M))
par = np.concatenate((np.random.uniform(8.1, 8.2, 1),
np.random.uniform(1e-3, 2e-3, 199)))
# get field, jacobian, and dfield_dpar
@jit(nopython=True)
def get_field(X, par):
(D, M) = np.shape(X)
vecfield = np.zeros((D,M))
for m in range(M):
vecfield[0, m] = (X[1, m] - X[D-2, m]) * X[D-1, m] - X[0, m]
vecfield[1, m] = (X[2, m] - X[D-1, m]) * X[0, m] - X[1, m]
vecfield[D-1, m] = (X[0, m] - X[D-3, m]) * X[D-2, m] - X[D-1, m]
for a in range(2, D-1):
vecfield[a, m] = (X[a+1, m] - X[a-2, m]) * X[a-1, m] - X[a, m]
return vecfield + np.sum(par)
field = get_field(X, par)
@jit(nopython=True)
def get_jacobian(X, par):
(D, M) = np.shape(X)
jacob = np.zeros((D,D,M))
for m in range(M):
for i in range(1, D+1):
for j in range(1, D+1):
jacob[i-1, j-1, m] \
= (1 + (i - 2) % D == j) \
* (X[i%D, m] - X[(i-3)%D, m]) \
+ ((1 + i % D == j) - (1 + (i - 3) % D == j)) \
* X[(i-2)%D, m] - (i == j)
return jacob
jacobian = get_jacobian(X, par)
dfield_dpar = np.ones((D,len(par),M))
# get the necessary constants
obsdim = np.array(list(set(np.random.randint(0, D, int(D/2)))), dtype='int64')
Y = np.random.uniform(-8.0, 8.0, (len(obsdim),M))
dt = 0.025
Rf = np.random.uniform(1e3, 1e5, D)
epsilon = 1e-3
mass_X = np.random.uniform(0.5, 1.5, (D,M))
mass_par = np.random.uniform(0.5, 1.5, len(par))
scaling = 1e5
Rm = 1.1
obs_ind = -np.ones(D, dtype='int64')
for l in range(len(obsdim)):
obs_ind[obsdim[l]] = l
pX = np.random.normal(0, 1e3, (D,M))
leapfrog_X = np.random.uniform(-8.0, 8.0, (D,M))
ppar = np.random.normal(0, 1e3, len(par))
leapfrog_par = np.random.uniform(10.0, 20.0, len(par))
Q2d = np.random.uniform(-8.0, 8.0, (D,M))
r2d = np.random.uniform(10.0, 20.0)
S2d = np.random.uniform(-8.0, 8.0, (D,M))
Q1d = np.random.uniform(10.0, 20.0, len(par))
r1d = np.random.uniform(10.0, 20.0)
S1d = np.random.uniform(10.0, 20.0, len(par))
"""Get the comparison variables except for the ones for 'dAdX' and 'dAdpar'."""
print('\nTesting... ', end='')
# for the action
@jit(nopython=True)
def cpu_fX(X, F, D, M, dt):
fX = np.zeros((D,M-1))
for a in range(D):
for m in range(M-1):
fX[a, m] = X[a, m] + dt / 2 * (F[a, m+1] + F[a, m])
return fX
fX = cpu_fX(X, field, D, M, dt)
@jit(nopython=True)
def cpu_action(X, fX, Rf, D, M, Y, obsdim, Rm):
measerr = 0
for m in range(M):
for l in range(len(obsdim)):
measerr = measerr + (X[obsdim[l], m] - Y[l, m]) ** 2
measerr = Rm / (2 * M) * measerr
modelerr = 0
for a in range(D):
ss_a = 0
for m in range(M-1):
ss_a = ss_a + (X[a, m+1] - fX[a, m]) ** 2
modelerr = modelerr + Rf[a] / (2 * M) * ss_a
return measerr + modelerr
action_compared = np.array([cpu_action(X, fX, Rf, D, M, Y, obsdim, Rm)])
# for 'diff'
diff_compared = X[:, 1:] - fX[:, :M-1]
# for 'leapfrog_X'
leapfrog_X_compared = leapfrog_X + epsilon * pX / mass_X
# for 'leapfrog_par'
leapfrog_par_compared = leapfrog_par + epsilon * ppar / mass_par
# for 'linearop2d'
T2d_compared = Q2d + r2d * S2d
# for 'linearop1d'
T1d_compared = Q1d + r1d * S1d
"""Use PyTorch to get 'dAdX_compared' and 'dAdpar_compared'."""
# first define the scalar field (action) for Torch
X = th.from_numpy(X)
par = th.from_numpy(par)
Rf = th.from_numpy(Rf)
Y = th.from_numpy(Y)
X.requires_grad = True
par.requires_grad = True
vecfield = th.zeros(D, M, dtype=th.float64)
vecfield[0, :] = (X[1, :] - X[D-2, :]) * X[D-1, :] - X[0, :]
vecfield[1, :] = (X[2, :] - X[D-1, :]) * X[0, :] - X[1, :]
vecfield[D-1, :] = (X[0, :] - X[D-3, :]) * X[D-2, :] - X[D-1, :]
for a in range(2, D-1):
vecfield[a, :] = (X[a+1, :] - X[a-2, :]) * X[a-1, :] - X[a, :]
vecfield += th.sum(par)
fX = X[:, :M-1] + dt / 2 * (vecfield[:, 1:] + vecfield[:, :M-1])
scalarfield = scaling * (Rm / 2 / M * th.sum((X[obsdim, :]-Y)**2) \
+ th.sum(Rf/2/M*th.sum((X[:, 1:]-fX)**2, dim=1)))
scalarfield.backward()
# for 'dAdX'
dAdX_compared = X.grad.numpy()
# for 'dAdpar'
dAdpar_compared = par.grad.numpy()
# detach torch variables for later use
X = X.detach().numpy()
par = par.detach().numpy()
Rf = Rf.numpy()
Y = Y.numpy()
"""Transfer data and specify grid dimensions."""
d_X = cuda.to_device(X)
d_par = cuda.to_device(par)
d_field = cuda.to_device(field)
d_jacobian = cuda.to_device(jacobian)
d_dfield_dpar = cuda.to_device(dfield_dpar)
d_obsdim = cuda.to_device(obsdim)
d_Y = cuda.to_device(Y)
d_Rf = cuda.to_device(Rf)
d_mass_X = cuda.to_device(mass_X)
d_mass_par = cuda.to_device(mass_par)
d_obs_ind = cuda.to_device(obs_ind)
d_pX = cuda.to_device(pX)
d_leapfrog_X = cuda.to_device(leapfrog_X)
d_ppar = cuda.to_device(ppar)
d_leapfrog_par = cuda.to_device(leapfrog_par)
d_Q2d = cuda.to_device(Q2d)
d_S2d = cuda.to_device(S2d)
d_Q1d = cuda.to_device(Q1d)
d_S1d = cuda.to_device(S1d)
# transfer the output arrays
d_action = cuda.device_array(1, dtype='float64')
d_diff = cuda.device_array_like(diff_compared)
d_dAdX = cuda.device_array_like(X)
d_dAdpar = cuda.device_array_like(par)
d_T2d = cuda.device_array_like(T2d_compared)
d_T1d = cuda.device_array_like(T1d_compared)
"""Define convenience functions."""
def gtimer_action():
k__action[(16,32), (16,16)](d_X, d_field, d_Rf, d_Y, dt, d_obsdim, Rm,
d_action)
cuda.synchronize()
def gtimer_dAdX():
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf, scaling, d_Y,
dt, d_obsdim, d_obs_ind, Rm, d_dAdX)
cuda.synchronize()
def gtimer_dAdpar():
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar, d_Rf,
scaling, dt, d_dAdpar)
cuda.synchronize()
"""Test for correctness."""
k__zeros1d[40, 256](d_action) # don't forget to initialize
cuda.synchronize() # and don't forget to synchronize after initialization
gtimer_action()
action = d_action.copy_to_host()
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
cuda.synchronize()
diff = d_diff.copy_to_host()
gtimer_dAdX()
dAdX = d_dAdX.copy_to_host()
k__zeros1d[40, 256](d_dAdpar) # don't forget to initialize
cuda.synchronize() # and don't forget to synchronize after initialization
gtimer_dAdpar()
dAdpar = d_dAdpar.copy_to_host()
k__leapfrog_X[(32,16), (2,128)](d_pX, epsilon, d_mass_X, d_leapfrog_X)
cuda.synchronize()
leapfrog_X = d_leapfrog_X.copy_to_host()
k__leapfrog_par[40, 256](d_ppar, epsilon, d_mass_par, d_leapfrog_par)
cuda.synchronize()
leapfrog_par = d_leapfrog_par.copy_to_host()
k__linearop2d[(32,16), (2,128)](d_Q2d, r2d, d_S2d, d_T2d)
cuda.synchronize()
T2d = d_T2d.copy_to_host()
k__linearop1d[40, 256](d_Q1d, r1d, d_S1d, d_T1d)
cuda.synchronize()
T1d = d_T1d.copy_to_host()
np.testing.assert_almost_equal(action, action_compared, decimal=4)
np.testing.assert_almost_equal(diff, diff_compared, decimal=6)
np.testing.assert_almost_equal(dAdX, dAdX_compared, decimal=6)
np.testing.assert_almost_equal(dAdpar, dAdpar_compared, decimal=5)
np.testing.assert_almost_equal(leapfrog_X, leapfrog_X_compared, decimal=6)
np.testing.assert_almost_equal(leapfrog_par, leapfrog_par_compared, decimal=6)
np.testing.assert_almost_equal(T2d, T2d_compared, decimal=6)
np.testing.assert_almost_equal(T1d, T1d_compared, decimal=6)
print('ok.')
#======================================================================
# for profiling only
@jit(nopython=True)
def cpu_dAdX(X, fX, J, Rf, scaling, Y, dt, obsdim, Rm):
D, M = X.shape
diff = np.zeros((D,M-1))
for a in range(D):
for m in range(M-1):
diff[a, m] = X[a, m+1] - fX[a, m]
part_meas = np.zeros((D,M))
for m in range(M):
for l in range(len(obsdim)):
part_meas[obsdim[l], m] = Rm * (X[obsdim[l], m] - Y[l, m])
part_model = np.zeros((D,M))
for a in range(D):
# m == 0 corner case
for i in range(D):
part_model[a, 0] = part_model[a, 0] \
+ Rf[i] * J[i, a, 0] * diff[i, 0]
part_model[a, 0] = - Rf[a] * diff[a, 0] - dt / 2 * part_model[a, 0]
# m == M-1 corner case
for i in range(D):
part_model[a, -1] = part_model[a, -1] \
+ Rf[i] * J[i, a, -1] * diff[i, -1]
part_model[a, -1] = Rf[a] * diff[a, -1] - dt / 2 * part_model[a, -1]
# m == {1, ..., M-2}
for m in range(1, M-1):
for i in range(D):
part_model[a, m] = part_model[a, m] \
+ Rf[i] * J[i, a, m] \
* (diff[i, m-1] + diff[i, m])
part_model[a, m] = Rf[a] * (diff[a, m-1] - diff[a, m]) \
- dt / 2 * part_model[a, m]
gradX_A = np.zeros((D,M))
for a in range(D):
for m in range(M):
gradX_A[a, m] = scaling / M * (part_meas[a, m] + part_model[a, m])
return gradX_A
@jit(nopython=True)
def cpu_dAdpar(X, fX, G, Rf, scaling, dt):
D, M = X.shape
gradpar_A = np.zeros(G.shape[1])
for b in range(G.shape[1]):
for i in range(D):
ss_i = 0
for m in range(M-1):
ss_i = ss_i + (X[i, m+1] - fX[i, m]) \
* (G[i, b, m] + G[i, b, m+1])
gradpar_A[b] = gradpar_A[b] + Rf[i] * ss_i
gradpar_A[b] = - scaling / M * dt / 2 * gradpar_A[b]
return gradpar_A
# define convenience functions
def ctimer_action():
fX = cpu_fX(X, field, D, M, dt)
cpu_action(X, fX, Rf, D, M, Y, obsdim, Rm)
def ctimer_dAdX():
fX = cpu_fX(X, field, D, M, dt)
cpu_dAdX(X, fX, jacobian, Rf, scaling, Y, dt, obsdim, Rm)
def ctimer_dAdpar():
fX = cpu_fX(X, field, D, M, dt)
cpu_dAdpar(X, fX, dfield_dpar, Rf, scaling, dt)
for _ in range(3):
gtimer_action(); gtimer_dAdX(); gtimer_dAdpar()
ctimer_action(); ctimer_dAdX(); ctimer_dAdpar()
"""
%timeit -r 50 -n 10 ctimer_action()
%timeit -r 50 -n 10 gtimer_action()
%timeit -r 50 -n 10 ctimer_dAdX()
%timeit -r 50 -n 10 gtimer_dAdX()
%timeit -r 50 -n 10 ctimer_dAdpar()
%timeit -r 50 -n 10 gtimer_dAdpar()
"""
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,619 | zfang92/pahmc-ode-gpu | refs/heads/master | /pahmc_ode_gpu/cuda_utilities.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This file contains all necessary functions for PAHMC other than the dynamics.
The functions are to be called by 'gd' and 'hmc' in 'pahmc.py'.
"""
from numba import cuda
@cuda.jit
def k__action(X, field, Rf, Y, dt, obsdim, Rm, action):
"""
This kernel calculates the action. The parameter 'action' must be
initialized before launching this kernel.
Inputs
------
X: D-by-M device array.
field: D-by-M device array.
Rf: one-dimensional (shapeless) device array of length D.
Y: len(obsdim)-by-M device array.
dt: scalar.
obsdim: one-dimensional (shapeless) device array.
Rm: scalar.
Modifications
------
action: one-dimenaional (shapeless) device array of length 1.
"""
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = X.shape
if start_a >= D or start_m >= M:
return
for l in range(start_a, len(obsdim), stride_a):
for m in range(start_m, M, stride_m):
cuda.atomic.add(action, 0, Rm/2/M*(X[obsdim[l], m]-Y[l, m])**2)
for a in range(start_a, D, stride_a):
for m in range(start_m, M-1, stride_m):
fX = X[a, m] + dt / 2 * (field[a, m+1] + field[a, m])
cuda.atomic.add(action, 0, Rf[a]/2/M*(X[a, m+1]-fX)**2)
@cuda.jit
def k__diff(X, field, dt, diff):
"""
This kernel calculates a necessary piece in calculating dAdX and dAdpar.
Inputs
------
X: D-by-M device array.
field: D-by-M device array.
dt: scalar.
Modifications
------
diff: D-by-(M-1) device array.
"""
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = X.shape
if start_a >= D or start_m >= M:
return
for a in range(start_a, D, stride_a):
for m in range(start_m, M-1, stride_m):
diff[a, m] \
= X[a, m+1] - (X[a, m] + dt / 2 * (field[a, m+1] + field[a, m]))
@cuda.jit
def k__dAdX(X, diff, jacobian, Rf, scaling, Y, dt, obsdim, obs_ind, Rm, dAdX):
"""
This kernel calculates the derivatives of the action with respect to the
path X.
Inputs
------
X: D-by-M device array.
diff: D-by-(M-1) device array.
jacobian: D-by-D-by-M device array.
Rf: one-dimensional (shapeless) device array of length D.
scaling: scalar.
Y: len(obsdim)-by-M device array.
dt: scalar.
obsdim: one-dimensional (shapeless) device array.
obs_ind: one-dimensional (shapeless) device array of length D.
Rm: scalar.
Modifications
------
dAdX: D-by-M device array.
"""
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = X.shape
if start_a >= D or start_m >= M:
return
# 'measurement' part
for a in range(start_a, D, stride_a):
if a == obsdim[obs_ind[a]]:
for m in range(start_m, M, stride_m):
dAdX[a, m] = Rm * (X[a, m] - Y[obs_ind[a], m])
else:
for m in range(start_m, M, stride_m):
dAdX[a, m] = 0
# 'model' part
for m in range(start_m, M, stride_m):
if m >= 1 and m <= M - 2:
for a in range(start_a, D, stride_a):
for i in range(D):
dAdX[a, m] -= Rf[i] * dt / 2 * jacobian[i, a, m] \
* (diff[i, m-1] + diff[i, m])
dAdX[a, m] += Rf[a] * (diff[a, m-1] - diff[a, m])
elif m == 0:
for a in range(start_a, D, stride_a):
for i in range(D):
dAdX[a, m] \
-= Rf[i] * dt / 2 * jacobian[i, a, 0] * diff[i, 0]
dAdX[a, m] -= Rf[a] * diff[a, 0]
else:
for a in range(start_a, D, stride_a):
for i in range(D):
dAdX[a, m] \
-= Rf[i] * dt / 2 * jacobian[i, a, M-1] * diff[i, M-2]
dAdX[a, m] += Rf[a] * diff[a, M-2]
for a in range(start_a, D, stride_a):
for m in range(start_m, M, stride_m):
dAdX[a, m] *= scaling / M
@cuda.jit
def k__dAdpar(X, diff, dfield_dpar, Rf, scaling, dt, dAdpar):
"""
This kernel calculates the derivatives of the action with respect to the
parameters 'par'. The parameter 'dAdpar' must be initialized before
lauching this kernel.
Inputs
------
X: D-by-M device array.
diff: D-by-(M-1) device array.
dfield_dpar: D-by-len(par)-by-M device array.
Rf: one-dimensional (shapeless) device array of length D.
scaling: scalar.
dt: scalar.
Modifications
------
dAdpar: one-dimensional (shapeless) device array of length len(par).
"""
start_i, start_b, start_m = cuda.grid(3)
stride_i, stride_b, stride_m = cuda.gridsize(3)
D, M = X.shape
if start_i >= D or start_b >= len(dAdpar) or start_m >= M:
return
for i in range(start_i, D, stride_i):
for b in range(start_b, len(dAdpar), stride_b):
for m in range(start_m, M-1, stride_m):
cuda.atomic.add(dAdpar, b, -scaling/M*Rf[i]*dt/2*diff[i, m]\
*(dfield_dpar[i, b, m]\
+dfield_dpar[i, b, m+1]))
@cuda.jit
def k__leapfrog_X(pX, epsilon, mass_X, X):
"""
This kernel updates X as part of the leapfrog simulation procedure.
Inputs
------
pX: D-by-M device array.
epsilon: scalar.
mass_X: D-by-M device array.
Modifications
------
X: D-by-M device array.
"""
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = X.shape
if start_a >= D or start_m >= M:
return
for a in range(start_a, D, stride_a):
for m in range(start_m, M, stride_m):
X[a, m] += epsilon * pX[a, m] / mass_X[a, m]
@cuda.jit
def k__leapfrog_par(ppar, epsilon, mass_par, par):
"""
This kernel updates 'par' as part of the leapfrog simulation procedure.
Inputs
------
ppar: one-dimensional (shapeless) device array of length len(par).
epsilon: scalar.
mass_par: one-dimensional (shapeless) device array of length len(par).
Modifications
------
par: one-dimensional (shapeless) device array.
"""
start_b = cuda.grid(1)
stride_b = cuda.gridsize(1)
if start_b >= len(par):
return
for b in range(start_b, len(par), stride_b):
par[b] += epsilon * ppar[b] / mass_par[b]
@cuda.jit
def k__linearop2d(Q, r, S, T):
"""
This kernel calculates the linear equation T=Q+r*S for 2d arrays.
Inputs
------
Q: 2d device array.
r: scalar.
S: 2d device array.
Modifications
------
T: 2d device array.
"""
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = Q.shape
if start_a >= D or start_m >= M:
return
for a in range(start_a, D, stride_a):
for m in range(start_m, M, stride_m):
T[a, m] = Q[a, m] + r * S[a, m]
@cuda.jit
def k__linearop1d(Q, r, S, T):
"""
This kernel calculates the linear equation T=Q+r*S for 1d arrays.
Inputs
------
Q: one-dimensional (shapeless) device array.
r: scalar.
S: one-dimensional (shapeless) device array.
Modifications
------
T: one-dimensional (shapeless) device array.
"""
start_b = cuda.grid(1)
stride_b = cuda.gridsize(1)
if start_b >= len(T):
return
for b in range(start_b, len(T), stride_b):
T[b] = Q[b] + r * S[b]
@cuda.jit
def k__zeros1d(array):
"""
This kernel sets the input array to zero. Doing it this way is more
efficient than transferring a zeros array to the GPU.
Modifications
------
array: one-dimensional (shapeless) device array.
"""
start = cuda.grid(1)
stride = cuda.gridsize(1)
if start >= len(array):
return
for idx in range(start, len(array), stride):
array[idx] = 0.0
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,620 | zfang92/pahmc-ode-gpu | refs/heads/master | /pahmc_ode_gpu/gd.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This module implements the gradient descent algorithm (with custom
modifications) as the 'exploration' part of the PAHMC method.
"""
import time
from numba import cuda
import numpy as np
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__linearop2d, k__linearop1d, k__zeros1d
def descend(k__field, k__jacobian, k__dfield_dpar, X0, par0, Rf,
d_stimuli, d_Y, dt, d_obsdim, d_obs_ind, Rm, eta0=0.1, tmax=1000):
"""
This method implements batch gradient descent with adaptive learning rates.
It is found that this implementation outperforms some advanced algorithms
including the Nesterov Accelerated Gradient in the present context.
Inputs
------
k__field: CUDA kernel for the vector field.
k__jacobian: CUDA kernel for the jacobian.
k__dfield_dpar: CUDA kernel for the derivatives w.r.t. to the parameters.
X0: initial path, a D-by-M numpy array.
par0: initial parameters, a 1d (shapeless) numpy array.
Rf: current Rf, a 1d (shapeless) numpy array of length D.
d_stimuli: the stimuli (synchronous with Y), a D-by-M device array.
d_Y: the data, a len(obsdim)-by-M device array.
dt: the time interval, a float.
d_obsdim: the observed dimensions, a 1d (shapeless) device array.
d_obs_ind: a 1d (shapeless) device array of length D.
Rm: a float.
eta0: initial learning rate, a float.
tmax: maximum number of gradient descent epochs.
Returns
------
X: path after gradient descent, a D-by-M numpy array.
par: parameters after gradient descent, a 1d (shapeless) numpy array.
action: action value after gradient descent, a float.
eta: learning rates, a 1d (shapeless) numpy array with length tmax+1.
"""
t0 = time.perf_counter()
# initialize learning rates
eta = np.zeros(tmax+1)
eta[0] = eta0
# set initial device arrays
d_X = cuda.to_device(X0)
d_par = cuda.to_device(par0)
d_Rf = cuda.to_device(Rf)
D, M = X0.shape
d_field = cuda.device_array_like(X0)
d_jacobian = cuda.device_array((D,D,M))
d_dfield_dpar = cuda.device_array((D,len(par0),M))
d_action = cuda.device_array((1,))
d_diff = cuda.device_array((D,M-1))
d_dAdX = cuda.device_array_like(X0)
d_dAdpar = cuda.device_array_like(par0)
d_X_try = cuda.device_array_like(X0)
d_par_try = cuda.device_array_like(par0)
d_action_try = cuda.device_array((1,))
d_dummy = cuda.device_array((1,))
# calculate initial action
k__field[(16,32), (2,128)](d_X, d_par, d_stimuli, d_field)
k__zeros1d[40, 256](d_action)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X, d_field, d_Rf, d_Y, dt, d_obsdim, Rm,
d_action)
action = d_action.copy_to_host()[0]
# begin gradient descent
accel_flag = 0
for t in range(1, tmax+1):
print(f'\r Exploring A(X) manifold... (step={t})', end='')
# get the gradients
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
cuda.synchronize()
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf, 1.0, d_Y,
dt, d_obsdim, d_obs_ind, Rm, d_dAdX)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
k__zeros1d[40, 256](d_dAdpar)
cuda.synchronize()
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar, d_Rf,
1.0, dt, d_dAdpar)
cuda.synchronize()
# initialize current step learning rate
if accel_flag == 1:
eta[t] = eta[t-1] * 2
else:
eta[t] = eta[t-1]
accel_flag = 1
# get trial X and par
k__linearop2d[(32,16), (2,128)](d_X, -eta[t], d_dAdX, d_X_try)
k__linearop1d[40, 256](d_par, -eta[t], d_dAdpar, d_par_try)
cuda.synchronize()
# get trial action
k__field[(16,32), (2,128)](d_X_try, d_par_try, d_stimuli, d_field)
k__zeros1d[40, 256](d_action_try)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X_try, d_field, d_Rf, d_Y, dt,
d_obsdim, Rm, d_action_try)
action_try = d_action_try.copy_to_host()[0]
# try to tame the trial results
counter = 0
while action_try >= action:
# halve current learning rate
accel_flag = 0
eta[t] /= 2
# get trial X and par
k__linearop2d[(32,16), (2,128)](d_X, -eta[t], d_dAdX, d_X_try)
k__linearop1d[40, 256](d_par, -eta[t], d_dAdpar, d_par_try)
cuda.synchronize()
# get trial action
k__field[(16,32), (2,128)](d_X_try, d_par_try, d_stimuli, d_field)
k__zeros1d[40, 256](d_action_try)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X_try, d_field, d_Rf, d_Y, dt,
d_obsdim, Rm, d_action_try)
action_try = d_action_try.copy_to_host()[0]
# return if getting stuck
counter += 1
if counter == 100:
return d_X.copy_to_host(), d_par.copy_to_host(), action, eta
# finalize results for the current step
d_dummy = d_X
d_X = d_X_try
d_X_try = d_dummy
d_dummy = d_par
d_par = d_par_try
d_par_try = d_dummy
action = action_try
print(f'\r Exploring A(X) manifold... '
+f'finished in {time.perf_counter()-t0:.2f} seconds.')
return d_X.copy_to_host(), d_par.copy_to_host(), action, eta
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,621 | zfang92/pahmc-ode-gpu | refs/heads/master | /pahmc_ode_gpu/data_preparation.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This module generates twin-experiemnt data for training and validation.
"""
from sys import exit
from pathlib import Path
from numba import cuda
import numpy as np
def generate_twin_data(name, k__field, k__jacobian,
D, length, dt, noise, par_true, x0, burndata, stimuli):
"""
This method first searches for existing data file by looking for a filename
that matches the name of the user-defined dynamics. If found successfully,
it then loads the file and compares the detailed specs of its data with
user specs; if everything matches up, the existing data will be returned.
In all other cases, it integrates the user-defined dynamics using the
trapezoidal rule and then outputs the generated data along with the
stimulus, and saves the data files.
Inputs
------
name: name of the dynamics, a string.
k__field: CUDA kernel for the vector field.
k__jacobian: CUDA kernel for the jacobian of the vector field.
D: model degrees of freedom, an integer.
length: total number of time steps for the generated data, an integer.
dt: discretization interval, a float.
noise: standard deviation of the added noise, an 1d (shapeless) numpy
array of length D.
par_true: true parameters used to generate the data, an 1d (shapeless)
numpy array.
x0: initial condition, an 1d (shapeless) numpy array of length D.
burndata: switch for burning the first half of the generated data, a
boolean.
stimuli: the stimuli, a 2d numpy array.
Returns
-------
data_noisy: the generated noisy data, a D-by-length numpy array.
stimuli: the tailored stimuli, a D-by-length numpy array.
"""
print('\nGenerating data... ', end='')
if burndata == True:
start = length
if stimuli.shape[1] < 2 * length:
print('aborted. Please make sure the length of \'stimuli\' is at '
+'least 2*\'length\' since \'burndata\' is set to be True.')
exit()
else:
start = 0
if np.shape(par_true) == ():
par_true = np.array([par_true])
filepath = Path.cwd() / 'user_data'
if (filepath / f'{name}.npz').exists(): # if a match is found
file = np.load(filepath/f'{name}.npz')
try:
file['device']
except:
print(f'aborted. Please remove files \"{name}.npz\" and '
+f'\"{name}_noiseless.npz\" from the user data '
+'directory and run again.\n')
exit()
if file['device'] == 'gpu' \
and np.shape(file['data']) == (D, length) \
and file['dt'] == dt \
and np.array_equal(file['noise'], noise) \
and np.array_equal(file['par_true'], par_true) \
and bool(file['burndata']) == burndata \
and np.array_equal(file['stimuli'], stimuli[:, start:start+length]):
data_noisy = file['data']
file.close()
print('successful (data with the same specs already exist).\n')
return data_noisy, stimuli[:, start:start+length]
# for all other cases
rawdata = np.zeros((D,start+length))
rawdata[:, 0] = x0
d_par = cuda.to_device(par_true)
d_field = cuda.device_array_like(np.zeros((D,1)))
d_jacobian = cuda.device_array_like(np.zeros((D,D,1)))
for k in range(start+length-1):
print(f'\rGenerating data... (t={k})', end='')
d_stimulusk = cuda.to_device(stimuli[:, [k]])
d_stimuluskp1 = cuda.to_device(stimuli[:, [k+1]])
d_rawdatak = cuda.to_device(rawdata[:, [k]])
# Newton-Raphson's initial guess using the Euler method
k__field[(16,32), (2,128)](d_rawdatak, d_par, d_stimulusk, d_field)
x_start = rawdata[:, [k]] + dt * d_field.copy_to_host()
# first iteration of Newton-Raphson for the trapezoidal rule
d_xstart = cuda.to_device(x_start)
k__field[(16,32), (2,128)](d_xstart, d_par, d_stimuluskp1, d_field)
field1 = d_field.copy_to_host()
k__field[(16,32), (2,128)](d_rawdatak, d_par, d_stimulusk, d_field)
field2 = d_field.copy_to_host()
g_x = dt / 2 * (field1[:, 0] + field2[:, 0]) \
+ rawdata[:, k] - x_start[:, 0]
k__jacobian[(4,4,32), (2,2,64)](d_xstart, d_par, d_jacobian)
J = dt / 2 * d_jacobian.copy_to_host()[:, :, 0] - np.identity(D)
x_change = np.linalg.solve(J, g_x)[:, np.newaxis]
x_new = x_start - x_change
x_start = x_new
# iterate until the correction reaches tolerance level
while np.sum(abs(x_change)) > 1e-13:
d_xstart = cuda.to_device(x_start)
k__field[(16,32), (2,128)](d_xstart, d_par, d_stimuluskp1, d_field)
field1 = d_field.copy_to_host()
g_x = dt / 2 * (field1[:, 0] + field2[:, 0]) \
+ rawdata[:, k] - x_start[:, 0]
k__jacobian[(4,4,32), (2,2,64)](d_xstart, d_par, d_jacobian)
J = dt / 2 * d_jacobian.copy_to_host()[:, :, 0] - np.identity(D)
x_change = np.linalg.solve(J, g_x)[:, np.newaxis]
x_new = x_start - x_change
x_start = x_new
rawdata[:, [k+1]] = x_new # final value
data_noiseless = rawdata[:, start:start+length]
np.savez(filepath/f'{name}_noiseless',
device='gpu',
data=data_noiseless,
dt=dt,
noise=np.zeros(D),
par_true=par_true,
burndata=burndata,
stimuli=stimuli[:, start:start+length])
data_noisy = np.zeros((D,length))
for a in range(D):
data_noisy[a, :] \
= data_noiseless[a, :] + np.random.normal(0, noise[a], length)
np.savez(filepath/f'{name}',
device='gpu',
data=data_noisy,
dt=dt,
noise=noise,
par_true=par_true,
burndata=burndata,
stimuli=stimuli[:, start:start+length])
print('\rGenerating data... successful.\n')
return data_noisy, stimuli[:, start:start+length]
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,622 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-cuda_dynamics (lorenz96).py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This is a unit test. If you would like to further develop pahmc_ode_gpu, you
should visit here frequently.
"""
import os
from pathlib import Path
from numba import cuda, jit
import numpy as np
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu import cuda_lib_dynamics
os.chdir(Path.cwd()/'unit_tests')
"""Prepare data, as well as variables to be compared to."""
name = 'lorenz96'
D = 200
M = 2000
X = np.random.uniform(-8.0, 8.0, (D,M))
par = np.array([8.17])
stimulus = np.random.uniform(-1.0, 1.0, (D,M))
# these functions have been tested in pahmc_ode_cpu
@jit(nopython=True)
def cpu_field(X, par, stimulus):
(D, M) = np.shape(X)
vecfield = np.zeros((D,M))
for m in range(M):
vecfield[0, m] = (X[1, m] - X[D-2, m]) * X[D-1, m] - X[0, m]
vecfield[1, m] = (X[2, m] - X[D-1, m]) * X[0, m] - X[1, m]
vecfield[D-1, m] = (X[0, m] - X[D-3, m]) * X[D-2, m] - X[D-1, m]
for a in range(2, D-1):
vecfield[a, m] = (X[a+1, m] - X[a-2, m]) * X[a-1, m] - X[a, m]
return vecfield + par[0]
@jit(nopython=True)
def cpu_jacobian(X, par):
(D, M) = np.shape(X)
jacob = np.zeros((D,D,M))
for m in range(M):
for i in range(1, D+1):
for j in range(1, D+1):
jacob[i-1, j-1, m] \
= (1 + (i - 2) % D == j) \
* (X[i%D, m] - X[(i-3)%D, m]) \
+ ((1 + i % D == j) - (1 + (i - 3) % D == j)) \
* X[(i-2)%D, m] - (i == j)
return jacob
@jit(nopython=True)
def cpu_dfield_dpar(X, par):
(D, M) = np.shape(X)
return np.ones((D,len(par),M))
print('\nTesting... ', end='')
field_compared = cpu_field(X, par, stimulus)
jacobian_compared = cpu_jacobian(X, par)
dfield_dpar_compared = cpu_dfield_dpar(X, par)
"""Fetch the kernels, transfer data, and specify grid dimensions."""
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
k__dfield_dpar = getattr(cuda_lib_dynamics, f'k__{name}_dfield_dpar')
d_X = cuda.to_device(X)
d_par = cuda.to_device(par)
d_stimulus = cuda.to_device(stimulus)
d_field = cuda.to_device(np.zeros((D,M)))
d_jacobian = cuda.to_device(np.zeros((D,D,M)))
d_dfield_dpar = cuda.to_device(np.zeros((D,1,M)))
"""Define convenience functions."""
def gtimer1():
k__field[(16,32), (2,128)](d_X, d_par, d_stimulus, d_field)
cuda.synchronize()
def gtimer2():
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
cuda.synchronize()
def gtimer3():
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
cuda.synchronize()
def gtimer4():
gtimer1(); gtimer2(); gtimer3()
def gtimer5():
k__field[(16,32), (2,128)](d_X, d_par, d_stimulus, d_field)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
cuda.synchronize()
"""Make sure everything is correct."""
gtimer5()
field = d_field.copy_to_host()
jacobian = d_jacobian.copy_to_host()
dfield_dpar = d_dfield_dpar.copy_to_host()
np.testing.assert_almost_equal(field, field_compared, decimal=12)
np.testing.assert_almost_equal(jacobian, jacobian_compared, decimal=12)
np.testing.assert_almost_equal(dfield_dpar, dfield_dpar_compared, decimal=12)
print('ok.')
#======================================================================
for _ in range(5):
gtimer5()
temp = cpu_field(X, par, stimulus)
temp = cpu_jacobian(X, par)
temp = cpu_dfield_dpar(X, par)
"""
%timeit -r 50 -n 10 temp = cpu_field(X, par, stimulus)
%timeit -r 50 -n 10 gtimer1()
%timeit -r 50 -n 10 temp = cpu_jacobian(X, par)
%timeit -r 50 -n 10 gtimer2()
%timeit -r 50 -n 10 temp = cpu_dfield_dpar(X, par)
%timeit -r 50 -n 10 gtimer3()
%timeit -r 50 -n 10 gtimer4()
%timeit -r 50 -n 10 gtimer5()
"""
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,623 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-data_generation (lorenz96).py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
As advised in the user manual, it is better to generate data using this test
module than directly running PAHMC since here allows you to view the generated
data.
"""
import os
from pathlib import Path
import time
import numpy as np
from matplotlib import pyplot as plt
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu import cuda_lib_dynamics
from pahmc_ode_gpu.data_preparation import generate_twin_data
"""Write down specs for the twin-experiment data."""
name = 'lorenz96'
D = 20
length = 1000
dt = 0.025
noise = 0.4 * np.ones(D)
par_true = 8.17
x0 = np.ones(D); x0[0] = 0.01
burndata = True
stimuli = np.zeros((D,2*length))
"""Generate data."""
# fetch the kernels
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
# run the data generator
t0 = time.perf_counter()
data_noisy, stimuli \
= generate_twin_data(name, k__field, k__jacobian,
D, length, dt, noise, par_true, x0, burndata, stimuli)
print(f'Time elapsed = {time.perf_counter()-t0:.2f} seconds.')
# get the noise level
file = np.load(Path.cwd()/'user_data'/f'{name}_noiseless.npz')
data_noiseless = file['data']
file.close()
print(f'Chi-squared = {np.sum((data_noisy-data_noiseless)**2):.4f} '
+f'({np.sum(noise**2)*length:.4f} expected).')
"""Plot."""
fig, ax = plt.subplots(figsize=(8,4.5))
textblue = (49/255, 99/255, 206/255)
time = np.linspace(0, int(length*dt)-dt, length)
ax.plot(time, data_noisy[1, :], color=textblue, lw=1.5)
ax.legend(['data_noisy'], loc='upper right')
ax.set_xlim(0, 25)
ax.set_xticks(np.linspace(0, 25, 11))
ax.set_xlabel('Time ($\Delta t = 0.025$s)')
ax.set_ylabel('$x_1(t)$', rotation='vertical')
os.chdir(Path.cwd()/'unit_tests')
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,624 | zfang92/pahmc-ode-gpu | refs/heads/master | /pahmc_ode_gpu/cuda_lib_dynamics.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This module contains all the built-in dynamics, each being a bundle of CUDA
kernels, that is ready for deployment. If the user inputs a name (should be all
lowercase) that has a match here, the 'def_dynamics' module will be ignored and
the corresponding kernels will be fetched into __init__.Fetch via main.py.
The name of each kernel below has form 'k__<name>_field/jacobian/dfield_dpar'.
Future added kernels should be named this way.
Only three kernels need to be implemented for each dynamics. See below.
1) k__<name>_field(X, par, stimulus, field):
Inputs
------
X: D-by-M GPU device array for any positive integer M.
par: one-dimensional (shapeless) device array.
stimulus: D-by-M device array for any positive integer M.
Modifications
-------
field: D-by-M device array.
2) k__<name>_jacobian(X, par, jacobian):
Inputs
------
X: D-by-M device array for any positive integer M.
par: one-dimensional (shapeless) device array.
Modifications
-------
jacobian: D-by-D-by-M device array for any positive integer M.
3) k__<name>_dfield_dpar(X, par, dfield_dpar):
Inputs
------
X: D-by-M device array for any positive integer M.
par: one-dimensional (shapeless) device array.
Modifications
-------
dfield_dpar: D-by-len(par)-by-M device array. Each index in the third
axis corresponds to a D-by-M device array that contains
the derivatives with respect to the path X.
"""
import math
from numba import cuda
#===================================Lorenz96====================================
"""
Below implements the standard Lorenz96 model. Fortunately, there is only one
representation of the model.
"""
@cuda.jit
def k__lorenz96_field(X, par, stimulus, field):
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = X.shape
if start_a >= D or start_m >= M:
return
for a in range(start_a, D, stride_a):
if a == 0:
for m in range(start_m, M, stride_m):
field[a, m] \
= (X[1, m] - X[D-2, m]) * X[D-1, m] - X[0, m] + par[0]
elif a == 1:
for m in range(start_m, M, stride_m):
field[a, m] \
= (X[2, m] - X[D-1, m]) * X[0, m] - X[1, m] + par[0]
elif a == D - 1:
for m in range(start_m, M, stride_m):
field[a, m] \
= (X[0, m] - X[D-3, m]) * X[D-2, m] - X[D-1, m] + par[0]
else:
for m in range(start_m, M, stride_m):
field[a, m] \
= (X[a+1, m] - X[a-2, m]) * X[a-1, m] - X[a, m] + par[0]
@cuda.jit
def k__lorenz96_jacobian(X, par, jacobian):
start_i, start_j, start_m = cuda.grid(3)
stride_i, stride_j, stride_m = cuda.gridsize(3)
D, M = X.shape
if start_i >= D or start_j >= D or start_m >= M:
return
for i in range(start_i+1, D+1, stride_i):
for j in range(start_j+1, D+1, stride_j):
for m in range(start_m, M, stride_m):
jacobian[i-1, j-1, m] \
= (1 + (i - 2) % D == j) \
* (X[i%D, m] - X[(i-3)%D, m]) \
+ ((1 + i % D == j) - (1 + (i - 3) % D == j)) \
* X[(i-2)%D, m] - (i == j)
@cuda.jit
def k__lorenz96_dfield_dpar(X, par, dfield_dpar):
start_i, start_b, start_m = cuda.grid(3)
stride_i, stride_b, stride_m = cuda.gridsize(3)
D, M = X.shape
if start_i >= D or start_b >= len(par) or start_m >= M:
return
for i in range(start_i, D, stride_i):
for b in range(start_b, len(par), stride_b):
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = 1
#=====================================NaKL======================================
"""
Below implements the Hodgkin-Huxley model as described in Toth et al.,
Biological Cybernetics (2011). It has 18 parameters as follows:
g_Na, E_Na, g_K, E_K, g_L, E_L;
Vm, dVm, tau_m0, tau_m1;
Vh, dVh, tau_h0, tau_h1;
Vn, dVn, tau_n0, tau_n1.
"""
@cuda.jit
def k__nakl_field(X, par, stimulus, field):
start_a, start_m = cuda.grid(2)
stride_a, stride_m = cuda.gridsize(2)
D, M = X.shape
if start_a >= D or start_m >= M:
return
for a in range(start_a, D, stride_a):
if a == 0:
for m in range(start_m, M, stride_m):
field[a, m] \
= stimulus[0, m] \
+ par[0] * (X[1, m] ** 3) * X[2, m] * (par[1] - X[0, m]) \
+ par[2] * (X[3, m] ** 4) * (par[3] - X[0, m]) \
+ par[4] * (par[5] - X[0, m])
if a == 1:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
field[a, m] = ((1 + tanh_m) / 2 - X[1, m]) \
/ (par[8] + par[9] * (1 - tanh_m * tanh_m))
if a == 2:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
field[a, m] = ((1 + tanh_h) / 2 - X[2, m]) \
/ (par[12] + par[13] * (1 - tanh_h * tanh_h))
if a == 3:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
field[a, m] = ((1 + tanh_n) / 2 - X[3, m]) \
/ (par[16] + par[17] * (1 - tanh_n * tanh_n))
@cuda.jit
def k__nakl_jacobian(X, par, jacobian):
start_i, start_j, start_m = cuda.grid(3)
stride_i, stride_j, stride_m = cuda.gridsize(3)
D, M = X.shape
if start_i >= D or start_j >= D or start_m >= M:
return
for i in range(start_i, D, stride_i):
for j in range(start_j, D, stride_j):
if i == 0 and j == 0:
for m in range(start_m, M, stride_m):
jacobian[i, j, m] = - par[0] * (X[1, m] ** 3) * X[2, m] \
- par[2] * (X[3, m] ** 4) - par[4]
elif i == 0 and j == 1:
for m in range(start_m, M, stride_m):
jacobian[i, j, m] = 3 * par[0] * (X[1, m] ** 2) \
* X[2, m] * (par[1] - X[0, m])
elif i == 0 and j == 2:
for m in range(start_m, M, stride_m):
jacobian[i, j, m] \
= par[0] * (X[1, m] ** 3) * (par[1] - X[0, m])
elif i == 0 and j == 3:
for m in range(start_m, M, stride_m):
jacobian[i, j, m] \
= 4 * par[2] * (X[3, m] ** 3) * (par[3] - X[0, m])
elif i == 1 and j == 0:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
kernel_m = 1 - tanh_m * tanh_m
tau_m = par[8] + par[9] * kernel_m
jacobian[i, j, m] \
= kernel_m / (2 * par[7]) / tau_m \
- 2 * par[9] / par[7] * tanh_m * kernel_m \
* (X[1, m] - (1 + tanh_m) / 2) / (tau_m * tau_m)
elif i == 2 and j == 0:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
kernel_h = 1 - tanh_h * tanh_h
tau_h = par[12] + par[13] * kernel_h
jacobian[i, j, m] \
= kernel_h / (2 * par[11]) / tau_h \
- 2 * par[13] / par[11] * tanh_h * kernel_h \
* (X[2, m] - (1 + tanh_h) / 2) / (tau_h * tau_h)
elif i == 3 and j == 0:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
kernel_n = 1 - tanh_n * tanh_n
tau_n = par[16] + par[17] * kernel_n
jacobian[i, j, m] \
= kernel_n / (2 * par[15]) / tau_n \
- 2 * par[17] / par[15] * tanh_n * kernel_n \
* (X[3, m] - (1 + tanh_n) / 2) / (tau_n * tau_n)
elif i == 1 and j == 1:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
jacobian[i, j, m] \
= - 1 / (par[8] + par[9] * (1 - tanh_m * tanh_m))
elif i == 2 and j == 2:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
jacobian[i, j, m] \
= - 1 / (par[12] + par[13] * (1 - tanh_h * tanh_h))
elif i == 3 and j == 3:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
jacobian[i, j, m] \
= - 1 / (par[16] + par[17] * (1 - tanh_n * tanh_n))
else:
for m in range(start_m, M, stride_m):
jacobian[i, j, m] = 0
@cuda.jit
def k__nakl_dfield_dpar(X, par, dfield_dpar):
start_i, start_b, start_m = cuda.grid(3)
stride_i, stride_b, stride_m = cuda.gridsize(3)
D, M = X.shape
if start_i >= D or start_b >= len(par) or start_m >= M:
return
for i in range(start_i, D, stride_i):
for b in range(start_b, len(par), stride_b):
if i == 0 and b == 0:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] \
= (X[1, m] ** 3) * X[2, m] * (par[1] - X[0, m])
elif i == 0 and b == 1:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = par[0] * (X[1, m] ** 3) * X[2, m]
elif i == 0 and b == 2:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = (X[3, m] ** 4) * (par[3] - X[0, m])
elif i == 0 and b == 3:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = par[2] * (X[3, m] ** 4)
elif i == 0 and b == 4:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = par[5] - X[0, m]
elif i == 0 and b == 5:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = par[4]
elif i == 1 and b == 6:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
kernel_m = 1 - tanh_m * tanh_m
tau_m = par[8] + par[9] * kernel_m
dfield_dpar[i, b, m] \
= 2 * par[9] / par[7] * tanh_m * kernel_m \
* (X[1, m] - (1 + tanh_m) / 2) / (tau_m * tau_m) \
- kernel_m / (2 * par[7]) / tau_m
elif i == 1 and b == 7:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
kernel_m = 1 - tanh_m * tanh_m
tau_m = par[8] + par[9] * kernel_m
dfield_dpar[i, b, m] \
= 2 * par[9] * (X[0, m] - par[6]) / (par[7] ** 2) \
* tanh_m * kernel_m * (X[1, m] - (1 + tanh_m) / 2) \
/ (tau_m * tau_m) \
- (X[0, m] - par[6]) \
/ (2 * (par[7] ** 2)) * kernel_m / tau_m
elif i == 1 and b == 8:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
tau_m = par[8] + par[9] * (1 - tanh_m * tanh_m)
dfield_dpar[i, b, m] \
= (X[1, m] - (1 + tanh_m) / 2) / (tau_m * tau_m)
elif i == 1 and b == 9:
for m in range(start_m, M, stride_m):
tanh_m = math.tanh((X[0, m]-par[6])/par[7])
kernel_m = 1 - tanh_m * tanh_m
tau_m = par[8] + par[9] * kernel_m
dfield_dpar[i, b, m] \
= kernel_m * (X[1, m] - (1 + tanh_m) / 2) \
/ (tau_m * tau_m)
elif i == 2 and b == 10:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
kernel_h = 1 - tanh_h * tanh_h
tau_h = par[12] + par[13] * kernel_h
dfield_dpar[i, b, m] \
= 2 * par[13] / par[11] * tanh_h * kernel_h \
* (X[2, m] - (1 + tanh_h) / 2) / (tau_h * tau_h) \
- kernel_h / (2 * par[11]) / tau_h
elif i == 2 and b == 11:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
kernel_h = 1 - tanh_h * tanh_h
tau_h = par[12] + par[13] * kernel_h
dfield_dpar[i, b, m] \
= 2 * par[13] * (X[0, m] - par[10]) / (par[11] ** 2) \
* tanh_h * kernel_h * (X[2, m] - (1 + tanh_h) / 2) \
/ (tau_h * tau_h) \
- (X[0, m] - par[10]) \
/ (2 * (par[11] ** 2)) * kernel_h / tau_h
elif i == 2 and b == 12:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
tau_h = par[12] + par[13] * (1 - tanh_h * tanh_h)
dfield_dpar[i, b, m] \
= (X[2, m] - (1 + tanh_h) / 2) / (tau_h * tau_h)
elif i == 2 and b == 13:
for m in range(start_m, M, stride_m):
tanh_h = math.tanh((X[0, m]-par[10])/par[11])
kernel_h = 1 - tanh_h * tanh_h
tau_h = par[12] + par[13] * kernel_h
dfield_dpar[i, b, m] \
= kernel_h * (X[2, m] - (1 + tanh_h) / 2) \
/ (tau_h * tau_h)
elif i == 3 and b == 14:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
kernel_n = 1 - tanh_n * tanh_n
tau_n = par[16] + par[17] * kernel_n
dfield_dpar[i, b, m] \
= 2 * par[17] / par[15] * tanh_n * kernel_n \
* (X[3, m] - (1 + tanh_n) / 2) / (tau_n * tau_n) \
- kernel_n / (2 * par[15]) / tau_n
elif i == 3 and b == 15:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
kernel_n = 1 - tanh_n * tanh_n
tau_n = par[16] + par[17] * kernel_n
dfield_dpar[i, b, m] \
= 2 * par[17] * (X[0, m] - par[14]) / (par[15] ** 2) \
* tanh_n * kernel_n * (X[3, m] - (1 + tanh_n) / 2) \
/ (tau_n * tau_n) \
- (X[0, m] - par[14]) \
/ (2 * (par[15] ** 2)) * kernel_n / tau_n
elif i == 3 and b == 16:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
tau_n = par[16] + par[17] * (1 - tanh_n * tanh_n)
dfield_dpar[i, b, m] \
= (X[3, m] - (1 + tanh_n) / 2) / (tau_n * tau_n)
elif i == 3 and b == 17:
for m in range(start_m, M, stride_m):
tanh_n = math.tanh((X[0, m]-par[14])/par[15])
kernel_n = 1 - tanh_n * tanh_n
tau_n = par[16] + par[17] * kernel_n
dfield_dpar[i, b, m] \
= kernel_n * (X[3, m] - (1 + tanh_n) / 2) \
/ (tau_n * tau_n)
else:
for m in range(start_m, M, stride_m):
dfield_dpar[i, b, m] = 0
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,625 | zfang92/pahmc-ode-gpu | refs/heads/master | /pahmc_ode_gpu/pahmc_tune.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This is where everything is put togegher. It receives all the user-provided
specs from 'main.py' as well as the data generated by 'data_preparation.py' (or
by the user if working with real experimental data), and perform the PAHMC
algorithm for state and parameter estimations. The dynamics model is defined in
'cuda_lib_dynamics.py' or in 'def_dynamics.py', other necessary CUDA kernels
are defined in 'cuda_utilities.py', and the gradient descent functionality is
implemented in 'gd.py'.
"""
from pathlib import Path
import time
from numba import cuda, jit
import numpy as np
from pahmc_ode_gpu.gd import descend
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__leapfrog_X, k__leapfrog_par, k__linearop2d, k__linearop1d, \
k__zeros1d
def anneal(k__field, k__jacobian, k__dfield_dpar, stimuli, Y,
D, M, obsdim, dt, Rf0, alpha, betamax,
n_iter, epsilon, S, mass, scaling,
soft_dynrange, par_start, name, tune_beta, Rm=1.0, burn=0.5):
"""
This is the master function that brings the PAHMC algorithm into one piece.
Inputs
------
k__field: CUDA kernel.
k__jacobian: CUDA kernel.
k__dfield_dpar: CUDA kernel.
stimuli: D-by-M numpy array of floats.
Y: len(obsdim)-by-M numpy array of floats.
D: integer.
M: integer.
obsdim: 1d (shapeless) numpy array of integers.
dt: float.
Rf0: 1d (shapeless) numpy array of floats, with length D.
alpha: float.
betamax: integer.
n_iter: 1d (shapeless) numpy array of integers, with length
betamax.
epsilon: 1d (shapeless) numpy array of floats, with length betamax.
S: 1d (shapeless) numpy array of integers, with length
betamax.
mass: betamax-by-3 numpy array of floats.
scaling: 1d (shapeless) numpy array of floats, with length betamax.
soft_dynrange: D-by-2 numpy array of floats.
par_start: 1d (shapeless) numpy array.
name: the name of the dynamical system.
tune_beta: the current beta value that is undergoing stepwise tuning.
Rm: float.
burn: float. Note that this is the proportion of HMC samples that
are thrown away in each beta, which is different from the
'burndata' switch.
Returns
------
Rm: float.
burn: float.
Rf: betamax-by-D numpy array of floats.
eta_avg: 1d (shapeless) numpy array of floats, with length betamax.
acceptance: 1d (shapeless) numpy array of floats, with length betamax.
action: betamax-by-(max(n_iter)+2) numpy array of floats.
action_meanpath: 1d (shapeless) numpy array of floats, with length betamax.
ME_meanpath: 1d (shapeless) numpy array of floats, with length betamax.
FE_meanpath: 1d (shapeless) numpy array of floats, with length betamax.
X_init: betamax-by-D-by-M numpy array of floats.
X_gd: betamax-by-D-by-M numpy array of floats.
X_mean: betamax-by-D-by-M numpy array of floats.
par_history: betamax-by-(max(n_iter)+2)-by-len(par_start) numpy array
of floats.
par_mean: betamax-by-len(par_start) numpy array of floats.
Xfinal_history: betamax-by-(max(n_iter)+2)-by-D numpy array of floats.
"""
# create some utility variables
Rf = Rf0 * (alpha ** np.arange(betamax))[:, np.newaxis]
unobsdim = np.int64(np.setdiff1d(np.arange(D), obsdim))
obs_ind = -np.ones(D, dtype='int64')
for l in range(len(obsdim)):
obs_ind[obsdim[l]] = l
mass_X = np.zeros((betamax,D,M))
mass_par = np.zeros((betamax,len(par_start)))
for beta in range(betamax):
mass_X[beta, obsdim, :] = mass[beta, 0]
mass_X[beta, unobsdim, :] = mass[beta, 1]
mass_par[beta, :] = mass[beta, 2]
# initialize the remaining output variables
eta_avg = np.zeros(betamax)
acceptance = np.zeros(betamax)
action = np.zeros((betamax,np.max(n_iter)+2))
action_meanpath = np.zeros(betamax)
ME_meanpath = np.zeros(betamax)
FE_meanpath = np.zeros(betamax)
X_init = np.zeros((betamax,D,M))
X_gd = np.zeros((betamax,D,M))
X_mean = np.zeros((betamax,D,M))
par_history = np.zeros((betamax,np.max(n_iter)+2,len(par_start)))
par_mean = np.zeros((betamax,len(par_start)))
Xfinal_history = np.zeros((betamax,np.max(n_iter)+2,D))
# bring static variables to GPU
d_stimuli = cuda.to_device(stimuli)
d_Y = cuda.to_device(Y)
d_obsdim = cuda.to_device(obsdim)
d_obs_ind = cuda.to_device(obs_ind)
# initialize device arrays that will be used as outputs for the kernels
d_field = cuda.device_array((D,M))
d_jacobian = cuda.device_array((D,D,M))
d_dfield_dpar = cuda.device_array((D,len(par_start),M))
d_diff = cuda.device_array((D,M-1))
d_dAdX = cuda.device_array((D,M))
d_dAdpar = cuda.device_array((len(par_start),))
d_action = cuda.device_array((1,))
# stepwise tuning===========================================================
if tune_beta == 0:
# perform dynamic initialization, i.e., initialize X and par for beta=0
X_init[0, :, 0] \
= np.random.uniform(soft_dynrange[:, 0], soft_dynrange[:, 1], (D,))
X_init[0, obsdim, 0] = Y[:, 0]
d_par_start = cuda.to_device(par_start)
d_field_m = cuda.device_array((D,1))
for m in range(M-1):
d_X_m = cuda.to_device(X_init[0][:, [m]])
d_stimuli_m = cuda.to_device(stimuli[:, [m]])
k__field[(16,32), (2,128)](d_X_m, d_par_start, d_stimuli_m,
d_field_m)
F = dt / 2 * d_field_m.copy_to_host()
d_X_m = cuda.to_device(X_init[0][:, [m]]+F)
k__field[(16,32), (2,128)](d_X_m, d_par_start, d_stimuli_m,
d_field_m)
X_init[0][:, [m+1]] \
= X_init[0][:, [m]] + dt * d_field_m.copy_to_host()
X_init[0, obsdim, m+1] = Y[:, m+1]
par_history[0, 0, :] = par_start
else:
# extract results from the previous beta
file \
= np.load(Path.cwd()/'user_results'/f'tune_{name}_{tune_beta-1}.npz')
X_init = file['X_mean']
par_history[0, 0, :] = file['par_mean'][0, :]
file.close()
#===========================================================================
# do PAHMC
for beta in range(betamax):
print('-------------------------------------------------------------')
print(f'beta = {beta}:\n')
# initialize device arrays specific to current beta
d_Rf_beta = cuda.to_device(Rf[beta, :])
d_mass_X_beta = cuda.to_device(mass_X[beta, :, :])
d_mass_par_beta = cuda.to_device(mass_par[beta, :])
# initialize action and Xfinal_history (2 out of 4) for current beta
d_X_init_beta = cuda.to_device(X_init[beta, :, :])
d_par_init_beta = cuda.to_device(par_history[beta, 0, :])
k__field[(16,32), (2,128)](d_X_init_beta, d_par_init_beta, d_stimuli,
d_field)
k__zeros1d[40, 256](d_action)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X_init_beta, d_field, d_Rf_beta, d_Y, dt,
d_obsdim, Rm, d_action)
action[beta, 0] = d_action.copy_to_host()[0]
Xfinal_history[beta, 0, :] = X_init[beta, :, -1]
# exploration - gradient descent
X_gd[beta, :, :], par_history[beta, 1, :], action[beta, 1], eta \
= descend(k__field, k__jacobian, k__dfield_dpar,
X_init[beta, :, :], par_history[beta, 0, :], Rf[beta, :],
d_stimuli, d_Y, dt, d_obsdim, d_obs_ind, Rm)
eta_avg[beta] = np.mean(eta)
Xfinal_history[beta, 1, :] = X_gd[beta, :, -1]
# exploitation - Hamiltonian Monte Carlo
t0 = time.perf_counter()
errcount = 0
printflag = 0
X0 = X_gd[beta, :, :]
par0 = par_history[beta, 1, :]
for n in range(2, n_iter[beta]+2):
print(f'\r Performing calculations... (step={n-1})', end='')
# call HMC
X, par, action[beta, n], accept, errflag \
= hmc(X0, par0, action[beta, n-1],
beta, d_Rf_beta, d_mass_X_beta, d_mass_par_beta,
D, M, dt, obsdim, unobsdim, Rm,
epsilon, S, mass, scaling, mass_X, mass_par,
k__field, k__jacobian, k__dfield_dpar,
d_stimuli, d_Y, d_obsdim, d_obs_ind,
d_field, d_jacobian, d_dfield_dpar,
d_diff, d_dAdX, d_dAdpar, d_action)
X0 = X
par0 = par
# sanity check
if errflag == 1:
errcount += 1
if errcount == 5 and printflag == 0:
print('\n WARNING: got bad values when performing '
+'leapfrog simulations!')
printflag = 1
else:
errcount = 0
# keep results
acceptance[beta] += accept
if n - 1 > burn * n_iter[beta]:
X_mean[beta, :, :] += X
par_mean[beta, :] += par
Xfinal_history[beta, n, :] = X[:, -1]
par_history[beta, n, :] = par
print(f'\r Performing calculations... '
+f'finished in {time.perf_counter()-t0:.2f} seconds;\n')
# finalize acceptance rate and mean path for current beta
acceptance[beta] /= n_iter[beta]
X_mean[beta, :, :] /= np.ceil((1-burn)*n_iter[beta])
par_mean[beta, :] /= np.ceil((1-burn)*n_iter[beta])
# calculate action, measurement and model errors from mean path
d_X_mean_beta = cuda.to_device(X_mean[beta, :, :])
d_par_mean_beta = cuda.to_device(par_mean[beta, :])
k__field[(16,32), (2,128)](d_X_mean_beta, d_par_mean_beta, d_stimuli,
d_field)
k__zeros1d[40, 256](d_action)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X_mean_beta, d_field, d_Rf_beta, d_Y, dt,
d_obsdim, Rm, d_action)
action_meanpath[beta] = d_action.copy_to_host()[0]
ME_meanpath[beta] = Rm / 2 / M * np.sum((X_mean[beta, obsdim, :]-Y)**2)
field_mean = d_field.copy_to_host()
fX_mean = X_mean[beta, :, :M-1] \
+ dt / 2 * (field_mean[:, 1:] + field_mean[:, :M-1])
FE_meanpath[beta] \
= np.sum(Rf[beta, :]/2/M\
*np.sum((X_mean[beta, :, 1:]-fX_mean)**2, axis=1))
# print action_meanpath and FE_meanpath for current beta
print(f' action (mean path) = {action_meanpath[beta]};')
print(f' model error (mean path) = {FE_meanpath[beta]}.\n')
# initialize X and par (2 out of 4) for next beta
if beta != betamax - 1:
X_init[beta+1, :, :] = X_mean[beta, :, :]
par_history[beta+1, 0, :] = par_mean[beta, :]
return burn, Rm, Rf, eta_avg, acceptance, \
action, action_meanpath, ME_meanpath, FE_meanpath, \
X_init, X_gd, X_mean, par_history, par_mean, Xfinal_history
def hmc(X0, par0, action0,
beta, d_Rf_beta, d_mass_X_beta, d_mass_par_beta,
D, M, dt, obsdim, unobsdim, Rm,
epsilon, S, mass, scaling, mass_X, mass_par,
k__field, k__jacobian, k__dfield_dpar,
d_stimuli, d_Y, d_obsdim, d_obs_ind,
d_field, d_jacobian, d_dfield_dpar,
d_diff, d_dAdX, d_dAdpar, d_action):
"""
This function generates one HMC proposal per call.
Inputs
------
X0: D-by-M numpy array of floats.
par0: 1d (shapeless) numpy array of floats.
action0: float.
beta: integer.
d_Rf_beta: 1d (shapeless) device array of floats, with length D.
d_mass_X_beta: D-by-M device array of floats.
d_mass_par_beta: 1d (shapeless) device array of floats, with length
len(par0).
...
unobsdim: 1d (shapeless) numpy array of integers.
...
mass_X: betamax-by-D-by-M numpy array of floats.
mass_par: betamax-by-len(par0) array of floats.
...
d_stimuli: D-by-M device array of floats.
d_Y: len(obsdim)-by-M device array of floats.
d_obsdim: 1d (shapeless) device array of floats.
d_obs_ind: 1d (shapeless) device array of floats, with length D.
d_field: D-by-M device array of floats.
d_jacobian: D-by-D-by-M device array of floats.
d_dfield_dpar: D-by-len(par0)-by-M device array of floats.
d_diff: D-by-(M-1) deivce array of floats.
d_dAdX: D-by-M device array of floats.
d_dAdpar: 1d (shapeless) device array of floats, with length
len(par0).
d_action: 1d (shapeless) device array of float, with length 1.
Returns
------
X: D-by-M numpy array of floats.
par: 1d (shapeless) numpy array of floats.
action: float.
accept: integer.
errflag: integer.
"""
# generate initial momenta
pX0, ppar0 = pre_process(beta, D, M, obsdim, unobsdim, mass, len(par0))
# bring phase space variables to GPU
d_X = cuda.to_device(X0)
d_par = cuda.to_device(par0)
d_pX = cuda.to_device(pX0)
d_ppar = cuda.to_device(ppar0)
# initialze candidate action
k__zeros1d[40, 256](d_action)
# Hamiltonian dynamics - half step for momenta
k__field[(16,32), (2,128)](d_X, d_par, d_stimuli, d_field)
cuda.synchronize()
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
k__zeros1d[40, 256](d_dAdpar)
cuda.synchronize()
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf_beta,
scaling[beta], d_Y, dt, d_obsdim,
d_obs_ind, Rm, d_dAdX)
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar,
d_Rf_beta, scaling[beta], dt, d_dAdpar)
cuda.synchronize()
k__linearop2d[(32,16), (2,128)](d_pX, -epsilon[beta]/2, d_dAdX, d_pX)
k__linearop1d[40, 256](d_ppar, -epsilon[beta]/2, d_dAdpar, d_ppar)
cuda.synchronize()
# Hamiltonian dynamics - full steps for X, par, and momenta
for i in range(S[beta]):
# full step for X, par
k__leapfrog_X[(32,16), (2,128)](d_pX, epsilon[beta], d_mass_X_beta, d_X)
k__leapfrog_par[40, 256](d_ppar, epsilon[beta], d_mass_par_beta, d_par)
cuda.synchronize()
# full step for momenta except at the end of trajectory
k__field[(16,32), (2,128)](d_X, d_par, d_stimuli, d_field)
cuda.synchronize()
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
k__zeros1d[40, 256](d_dAdpar)
cuda.synchronize()
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf_beta,
scaling[beta], d_Y, dt, d_obsdim,
d_obs_ind, Rm, d_dAdX)
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar,
d_Rf_beta, scaling[beta], dt, d_dAdpar)
cuda.synchronize()
if i != S[beta] - 1:
k__linearop2d[(32,16), (2,128)](d_pX, -epsilon[beta], d_dAdX, d_pX)
k__linearop1d[40, 256](d_ppar, -epsilon[beta], d_dAdpar, d_ppar)
cuda.synchronize()
# Hamiltonian dynamics - half step for momenta
k__linearop2d[(32,16), (2,128)](d_pX, -epsilon[beta]/2, d_dAdX, d_pX)
k__linearop1d[40, 256](d_ppar, -epsilon[beta]/2, d_dAdpar, d_ppar)
cuda.synchronize()
# bring momenta back to CPU
pX = d_pX.copy_to_host()
ppar = d_ppar.copy_to_host()
# get candidate action
k__action[(16,32), (16,16)](d_X, d_field, d_Rf_beta, d_Y, dt, d_obsdim, Rm,
d_action)
action_cand = d_action.copy_to_host()[0]
# calculate change in Hamiltonian
dH = post_process(pX0, ppar0, pX, ppar, action0, action_cand, beta,
D, M, mass_X, mass_par, scaling)
# check for numerical issues
if np.isnan(action_cand) == False and np.isinf(action_cand) == False \
and np.isnan(dH) == False:
errflag = 0
else:
errflag = 1
# Metropolis-Hastings acceptance rule
if np.random.rand() < np.exp(dH):
X = d_X.copy_to_host()
par = d_par.copy_to_host()
action = action_cand
accept = 1
else:
X = X0
par = par0
action = action0
accept = 0
return X, par, action, accept, errflag
@jit(nopython=True)
def pre_process(beta, D, M, obsdim, unobsdim, mass, len_par):
"""
Generate initial momenta for HMC.
Inputs
------
...
len_par: integer.
Returns
------
pX0: D-by-M numpy array of floats.
ppar0: 1d (shapeless) numpy array of floats.
"""
pX0 = np.zeros((D,M))
ppar0 = np.zeros(len_par)
std_obs = np.sqrt(mass[beta, 0])
std_unobs = np.sqrt(mass[beta, 1])
std_par = np.sqrt(mass[beta, 2])
for a in range(len(obsdim)):
for m in range(M):
pX0[obsdim[a], m] = np.random.normal(0, std_obs)
for a in range(len(unobsdim)):
for m in range(M):
pX0[unobsdim[a], m] = np.random.normal(0, std_unobs)
for b in range(len_par):
ppar0[b] = np.random.normal(0, std_par)
return pX0, ppar0
@jit(nopython=True)
def post_process(pX0, ppar0, pX, ppar, action0, action_cand, beta,
D, M, mass_X, mass_par, scaling):
"""
Calculate the change in the Hamiltonian.
Inputs
------
pX0: D-by-M numpy array of floats.
ppar0: 1d (shapeless) numpy array of floats, with length len(par).
pX: D-by-M numpy array of floats.
ppar: 1d (shapeless) numpy array of floats, with length len(par).
action0: float.
action_cand: float.
...
Returns
------
dH: float.
"""
dH = 0.0
for a in range(D):
for m in range(M):
dH += (pX0[a, m] ** 2 - pX[a, m] ** 2) / (2 * mass_X[beta, a, m])
for b in range(len(ppar0)):
dH += (ppar0[b] ** 2 - ppar[b] ** 2) / (2 * mass_par[beta, b])
dH = dH / scaling[beta] + (action0 - action_cand)
return dH
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,626 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-data_generation (nakl).py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
As advised in the user manual, it is better to generate data using this test
module than directly running PAHMC since here allows you to view the generated
data.
"""
import os
from pathlib import Path
import time
import numpy as np
from matplotlib import pyplot as plt
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu import cuda_lib_dynamics
from pahmc_ode_gpu.data_preparation import generate_twin_data
"""Write down specs for the twin-experiment data."""
name = 'nakl'
D = 4
dt = 0.02
length = int(1000/dt)
noise = np.array([1.0, 0, 0, 0], dtype='float64')
par_true = np.array([120, 50, 20, -77, 0.3, -54.4,
-40, 15, 0.1, 0.4,
-60, -15, 1, 7,
-55, 30, 1, 5], dtype='float64')
x0 = np.array([-70, 0.1, 0.9, 0.1], dtype='float64')
burndata = False
stimuli = np.load(Path.cwd()/'user_data'/f'{name}_stimuli.npy')[:, 0:2*length]
"""Generate data."""
# fetch the kernels
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
# run the data generator
t0 = time.perf_counter()
data_noisy, stimuli \
= generate_twin_data(name, k__field, k__jacobian,
D, length, dt, noise, par_true, x0, burndata, stimuli)
print(f'Time elapsed = {time.perf_counter()-t0:.2f} seconds.')
# get the noise level
file = np.load(Path.cwd()/'user_data'/f'{name}_noiseless.npz')
data_noiseless = file['data']
file.close()
print(f'Chi-squared = {np.sum((data_noisy-data_noiseless)**2):.4f} '
+f'({np.sum(noise**2)*length:.4f} expected).')
"""Plot."""
fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(12,8))
textred = (202/255, 51/255, 0)
textblue = (49/255, 99/255, 206/255)
time = np.linspace(0, int(length*dt)-dt, length)
ax1.plot(time, data_noisy[0, :], color=textblue)
ax1.legend(['data_noisy'], loc='upper right')
ax1.set_xlim(0, int(length*dt))
ax1.set_xticks(np.linspace(0, 1000, 11))
ax1.set_xlabel('Time (ms)')
ax1.set_ylabel('V(t)', rotation='horizontal')
ax2.plot(time, stimuli[0, :], color=textred)
ax2.legend(['stimulus'], loc='upper right')
ax2.set_xlim(0, int(length*dt))
ax2.set_xticks(np.linspace(0, 1000, 11))
ax2.set_xlabel('Time (ms)')
ax2.set_ylabel('I_inj(t)', rotation='horizontal')
os.chdir(Path.cwd()/'unit_tests')
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,627 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-gd.py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This module tests the 'exploration' part of PAHMC.
"""
import os
from pathlib import Path
from numba import cuda
import numpy as np
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu import cuda_lib_dynamics
from pahmc_ode_gpu.gd import descend
from user_results.read import get_saved
from pahmc_ode_gpu.cuda_utilities import k__action, k__diff, k__dAdX, \
k__dAdpar, k__zeros1d
os.chdir(Path.cwd()/'unit_tests')
"""Retrieve necessary variables to get started."""
name, D, M, obsdim, dt, Rf0, alpha, betamax, \
n_iter, epsilon, S, mass, scaling, soft_dynrange, par_start, \
length, data_noisy, stimuli, noise, par_true, x0, burndata, \
burn, Rm, Rf, eta_avg, acceptance, \
action, action_meanpath, ME_meanpath, FE_meanpath, \
X_init, X_gd, X_mean, par_history, par_mean, Xfinal_history \
= get_saved(Path.cwd(), 'test-gd')
# fetch the dynamics kernels
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
k__dfield_dpar = getattr(cuda_lib_dynamics, f'k__{name}_dfield_dpar')
# define inputs to 'descend'
X0 = X_init[0, :, :]
par0 = par_history[0, 0, :]
Rf = Rf[0, :]
d_stimuli = cuda.to_device(np.ascontiguousarray(stimuli[:, :M]))
d_Y = cuda.to_device(data_noisy[obsdim, :M])
d_obsdim = cuda.to_device(obsdim)
obs_ind = -np.ones(D, dtype='int64')
for l in range(len(obsdim)):
obs_ind[obsdim[l]] = l
d_obs_ind = cuda.to_device(obs_ind)
"""Define a convenience function."""
def overview(X, par, Rf):
# define device arrays
d_X = cuda.to_device(X)
d_par = cuda.to_device(par)
d_Rf = cuda.to_device(Rf)
d_field = cuda.device_array_like(X)
d_jacobian = cuda.device_array((D,D,M))
d_dfield_dpar = cuda.device_array((D,len(par),M))
d_action = cuda.device_array((1,))
d_diff = cuda.device_array((D,M-1))
d_dAdX = cuda.device_array_like(X)
d_dAdpar = cuda.device_array_like(par)
# get the action
k__field[(16,32), (2,128)](d_X, d_par, d_stimuli, d_field)
k__zeros1d[40, 256](d_action)
cuda.synchronize()
k__action[(16,32), (16,16)](d_X, d_field, d_Rf, d_Y, dt, d_obsdim, Rm,
d_action)
action = d_action.copy_to_host()[0]
# get model error
field = d_field.copy_to_host()
fX = X[:, :M-1] + dt / 2 * (field[:, 1:] + field[:, :M-1])
FE = np.sum(Rf/2/M*np.sum((X[:, 1:]-fX)**2, axis=1))
# get the gradients
k__diff[(32,16), (2,128)](d_X, d_field, dt, d_diff)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
cuda.synchronize()
k__dAdX[(32,16), (2,128)](d_X, d_diff, d_jacobian, d_Rf, 1.0, d_Y, dt,
d_obsdim, d_obs_ind, Rm, d_dAdX)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
k__zeros1d[40, 256](d_dAdpar)
cuda.synchronize()
k__dAdpar[(4,4,32), (2,2,64)](d_X, d_diff, d_dfield_dpar, d_Rf, 1.0, dt,
d_dAdpar)
dAdX = d_dAdX.copy_to_host()
dAdpar = d_dAdpar.copy_to_host()
# print results
print(f'\n action = {action},')
print(f' modelerr = {FE},\n')
print(f' max |dAdX| = {np.max(np.abs(dAdX))},')
print(f' min |dAdX| = {np.min(np.abs(dAdX))},\n')
print(f'max |dAdpar| = {np.max(np.abs(dAdpar))},')
print(f'min |dAdpar| = {np.min(np.abs(dAdpar))}.\n')
return action, FE, dAdX, dAdpar
"""Get results."""
# before gradient descent
print('\n--------------------------------------------------')
print('Initial values before gradient descent:')
ov_action, ov_FE, ov_dAdX, ov_dAdpar = overview(X0, par0, Rf)
# perform gradient descent
X_gd, par_gd, action_gd, eta \
= descend(k__field, k__jacobian, k__dfield_dpar, X0, par0, Rf,
d_stimuli, d_Y, dt, d_obsdim, d_obs_ind, Rm)
# after gradient descent
print('\n--------------------------------------------------')
print('After gradient descent:')
ow_action, ow_FE, ow_dAdX, ow_dAdpar = overview(X_gd, par_gd, Rf)
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,628 | zfang92/pahmc-ode-gpu | refs/heads/master | /unit_tests/test-cuda_dynamics (nakl).py | # -*- coding: utf-8 -*-
"""
@author: Zheng Fang
This is a unit test. If you would like to further develop pahmc_ode_gpu, you
should visit here frequently.
"""
import os
from pathlib import Path
from numba import cuda, jit
import numpy as np
import torch as th
os.chdir(Path.cwd().parent)
from pahmc_ode_gpu import cuda_lib_dynamics
os.chdir(Path.cwd()/'unit_tests')
"""Prepare data, as well as variables to be compared to."""
name = 'nakl'
D = 4
M = 100000
X = np.concatenate((np.random.uniform(-100.0, 50.0, (1,M)),
np.random.uniform(0.0, 1.0, (D-1,M))))
par = np.array([120.0, 50.0, 20.0, -77.0, 0.3, -54.4, -40.0, 15,
0.1, 0.4, -60.0, -15, 1.0, 7.0, -55.0, 30, 1.0, 5.0])
stimulus \
= np.concatenate((np.random.uniform(-30, 30, (1,M)), np.zeros((D-1,M))))
# this function has been tested in pahmc_ode_cpu
@jit(nopython=True)
def cpu_field(X, par, stimulus):
(D, M) = np.shape(X)
vecfield = np.zeros((D,M))
vecfield[0, :] \
= stimulus[0, :] \
+ par[0] * (X[1, :] ** 3) * X[2, :] * (par[1] - X[0, :]) \
+ par[2] * (X[3, :] ** 4) * (par[3] - X[0, :]) \
+ par[4] * (par[5] - X[0, :])
tanh_m = np.tanh((X[0, :]-par[6])/par[7])
eta_m = 1 / 2 * (1 + tanh_m)
tau_m = par[8] + par[9] * (1 - tanh_m * tanh_m)
vecfield[1, :] = (eta_m - X[1, :]) / tau_m
tanh_h = np.tanh((X[0, :]-par[10])/par[11])
eta_h = 1 / 2 * (1 + tanh_h)
tau_h = par[12] + par[13] * (1 - tanh_h * tanh_h)
vecfield[2, :] = (eta_h - X[2, :]) / tau_h
tanh_n = np.tanh((X[0, :]-par[14])/par[15])
eta_n = 1 / 2 * (1 + tanh_n)
tau_n = par[16] + par[17] * (1 - tanh_n * tanh_n)
vecfield[3, :] = (eta_n - X[3, :]) / tau_n
return vecfield
print('\nTesting... ', end='')
field_compared = cpu_field(X, par, stimulus)
# let's tell PyTorch about our model in order to test jacobian and dfield_dpar
X = th.from_numpy(X)
par = th.from_numpy(par)
stimulus = th.from_numpy(stimulus)
X.requires_grad = True
par.requires_grad = True
vecfield = th.zeros(D, M)
vecfield[0, :] \
= stimulus[0, :] \
+ par[0] * (X[1, :] ** 3) * X[2, :] * (par[1] - X[0, :]) \
+ par[2] * (X[3, :] ** 4) * (par[3] - X[0, :]) \
+ par[4] * (par[5] - X[0, :])
tanh_m = th.tanh((X[0, :]-par[6])/par[7])
eta_m = 1 / 2 * (1 + tanh_m)
tau_m = par[8] + par[9] * (1 - tanh_m * tanh_m)
vecfield[1, :] = (eta_m - X[1, :]) / tau_m
tanh_h = th.tanh((X[0, :]-par[10])/par[11])
eta_h = 1 / 2 * (1 + tanh_h)
tau_h = par[12] + par[13] * (1 - tanh_h * tanh_h)
vecfield[2, :] = (eta_h - X[2, :]) / tau_h
tanh_n = th.tanh((X[0, :]-par[14])/par[15])
eta_n = 1 / 2 * (1 + tanh_n)
tau_n = par[16] + par[17] * (1 - tanh_n * tanh_n)
vecfield[3, :] = (eta_n - X[3, :]) / tau_n
# fetch the variables to be compared to
scalarfield = th.sum(vecfield)
scalarfield.backward()
jacobian_compared = X.grad.numpy()
dfield_dpar_compared = par.grad.numpy()
X = X.detach().numpy()
par = par.detach().numpy()
stimulus = stimulus.numpy()
"""Fetch the kernels, transfer data, and specify grid dimensions."""
k__field = getattr(cuda_lib_dynamics, f'k__{name}_field')
k__jacobian = getattr(cuda_lib_dynamics, f'k__{name}_jacobian')
k__dfield_dpar = getattr(cuda_lib_dynamics, f'k__{name}_dfield_dpar')
d_X = cuda.to_device(X)
d_par = cuda.to_device(par)
d_stimulus = cuda.to_device(stimulus)
d_field = cuda.to_device(np.zeros((D,M)))
d_jacobian = cuda.to_device(np.zeros((D,D,M)))
d_dfield_dpar = cuda.to_device(np.zeros((D,len(par),M)))
"""Define convenience functions."""
def gtimer1():
k__field[(16,32), (2,128)](d_X, d_par, d_stimulus, d_field)
cuda.synchronize()
def gtimer2():
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
cuda.synchronize()
def gtimer3():
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
cuda.synchronize()
def gtimer4():
gtimer1(); gtimer2(); gtimer3()
def gtimer5():
k__field[(16,32), (2,128)](d_X, d_par, d_stimulus, d_field)
k__jacobian[(4,4,32), (2,2,64)](d_X, d_par, d_jacobian)
k__dfield_dpar[(4,4,32), (2,2,64)](d_X, d_par, d_dfield_dpar)
cuda.synchronize()
"""Make sure everything is correct."""
gtimer5()
field = d_field.copy_to_host()
jacobian = np.sum(d_jacobian.copy_to_host(), axis=0)
dfield_dpar = np.sum(d_dfield_dpar.copy_to_host(), axis=(0,2))
np.testing.assert_almost_equal(field, field_compared, decimal=6)
np.testing.assert_almost_equal(jacobian, jacobian_compared, decimal=6)
np.testing.assert_almost_equal(dfield_dpar, dfield_dpar_compared, decimal=6)
print('ok.')
#======================================================================
# for profiling only
@jit(nopython=True)
def cpu_jacobian(X, par):
(D, M) = np.shape(X)
jacob = np.zeros((D,D,M))
jacob[0, 0, :] = - par[0] * (X[1, :] ** 3) * X[2, :] \
- par[2] * (X[3, :] ** 4) - par[4]
jacob[0, 1, :] \
= 3 * par[0] * (X[1, :] ** 2) * X[2, :] * (par[1] - X[0, :])
jacob[0, 2, :] = par[0] * (X[1, :] ** 3) * (par[1] - X[0, :])
jacob[0, 3, :] = 4 * par[2] * (X[3, :] ** 3) * (par[3] - X[0, :])
tanh_m = np.tanh((X[0, :]-par[6])/par[7])
kernel_m = (1 - tanh_m * tanh_m)
eta_m = 1 / 2 * (1 + tanh_m)
tau_m = par[8] + par[9] * kernel_m
eta_der_m = 1 / (2 * par[7]) * kernel_m
tau_der_m = - 2 * par[9] / par[7] * tanh_m * kernel_m
jacob[1, 0, :] \
= eta_der_m / tau_m + tau_der_m * (X[1, :] - eta_m) / (tau_m * tau_m)
tanh_h = np.tanh((X[0, :]-par[10])/par[11])
kernel_h = (1 - tanh_h * tanh_h)
eta_h = 1 / 2 * (1 + tanh_h)
tau_h = par[12] + par[13] * kernel_h
eta_der_h = 1 / (2 * par[11]) * kernel_h
tau_der_h = - 2 * par[13] / par[11] * tanh_h * kernel_h
jacob[2, 0, :] \
= eta_der_h / tau_h + tau_der_h * (X[2, :] - eta_h) / (tau_h * tau_h)
tanh_n = np.tanh((X[0, :]-par[14])/par[15])
kernel_n = (1 - tanh_n * tanh_n)
eta_n = 1 / 2 * (1 + tanh_n)
tau_n = par[16] + par[17] * kernel_n
eta_der_n = 1 / (2 * par[15]) * kernel_n
tau_der_n = - 2 * par[17] / par[15] * tanh_n * kernel_n
jacob[3, 0, :] \
= eta_der_n / tau_n + tau_der_n * (X[3, :] - eta_n) / (tau_n * tau_n)
jacob[1, 1, :] = - 1 / tau_m
jacob[2, 2, :] = - 1 / tau_h
jacob[3, 3, :] = - 1 / tau_n
return jacob
@jit(nopython=True)
def cpu_dfield_dpar(X, par):
(D, M) = np.shape(X)
deriv_par = np.zeros((D,M,len(par)))
deriv_par[0, :, 0] = (X[1, :] ** 3) * X[2, :] * (par[1] - X[0, :])
deriv_par[0, :, 1] = par[0] * (X[1, :] ** 3) * X[2, :]
deriv_par[0, :, 2] = (X[3, :] ** 4) * (par[3] - X[0, :])
deriv_par[0, :, 3] = par[2] * (X[3, :] ** 4)
deriv_par[0, :, 4] = par[5] - X[0, :]
deriv_par[0, :, 5] = par[4]
tanh_m = np.tanh((X[0, :]-par[6])/par[7])
kernel_m = (1 - tanh_m * tanh_m)
eta_m = 1 / 2 * (1 + tanh_m)
tau_m = par[8] + par[9] * kernel_m
common_m = (X[1, :] - eta_m) / (tau_m * tau_m)
eta_der_m = - 1 / (2 * par[7]) * kernel_m
tau_der_m = 2 * par[9] / par[7] * tanh_m * kernel_m
deriv_par[1, :, 6] = eta_der_m / tau_m + tau_der_m * common_m
eta_der_m = - (X[0, :] - par[6]) / (2 * (par[7] ** 2)) * kernel_m
tau_der_m = 2 * par[9] * (X[0, :] - par[6]) / (par[7] ** 2) \
* tanh_m * kernel_m
deriv_par[1, :, 7] = eta_der_m / tau_m + tau_der_m * common_m
deriv_par[1, :, 8] = common_m
deriv_par[1, :, 9] = kernel_m * common_m
tanh_h = np.tanh((X[0, :]-par[10])/par[11])
kernel_h = (1 - tanh_h * tanh_h)
eta_h = 1 / 2 * (1 + tanh_h)
tau_h = par[12] + par[13] * kernel_h
common_h = (X[2, :] - eta_h) / (tau_h * tau_h)
eta_der_h = - 1 / (2 * par[11]) * kernel_h
tau_der_h = 2 * par[13] / par[11] * tanh_h * kernel_h
deriv_par[2, :, 10] = eta_der_h / tau_h + tau_der_h * common_h
eta_der_h = - (X[0, :] - par[10]) / (2 * (par[11] ** 2)) * kernel_h
tau_der_h = 2 * par[13] * (X[0, :] - par[10]) / (par[11] ** 2) \
* tanh_h * kernel_h
deriv_par[2, :, 11] = eta_der_h / tau_h + tau_der_h * common_h
deriv_par[2, :, 12] = common_h
deriv_par[2, :, 13] = kernel_h * common_h
tanh_n = np.tanh((X[0, :]-par[14])/par[15])
kernel_n = (1 - tanh_n * tanh_n)
eta_n = 1 / 2 * (1 + tanh_n)
tau_n = par[16] + par[17] * kernel_n
common_n = (X[3, :] - eta_n) / (tau_n * tau_n)
eta_der_n = - 1 / (2 * par[15]) * kernel_n
tau_der_n = 2 * par[17] / par[15] * tanh_n * kernel_n
deriv_par[3, :, 14] = eta_der_n / tau_n + tau_der_n * common_n
eta_der_n = - (X[0, :] - par[14]) / (2 * (par[15] ** 2)) * kernel_n
tau_der_n = 2 * par[17] * (X[0, :] - par[14]) / (par[15] ** 2) \
* tanh_n * kernel_n
deriv_par[3, :, 15] = eta_der_n / tau_n + tau_der_n * common_n
deriv_par[3, :, 16] = common_n
deriv_par[3, :, 17] = kernel_n * common_n
return deriv_par
for _ in range(5):
gtimer5()
temp = cpu_field(X, par, stimulus)
temp = cpu_jacobian(X, par)
temp = cpu_dfield_dpar(X, par)
"""
%timeit -r 50 -n 10 temp = cpu_field(X, par, stimulus)
%timeit -r 50 -n 10 gtimer1()
%timeit -r 50 -n 10 temp = cpu_jacobian(X, par)
%timeit -r 50 -n 10 gtimer2()
%timeit -r 50 -n 10 temp = cpu_dfield_dpar(X, par)
%timeit -r 50 -n 10 gtimer3()
%timeit -r 50 -n 10 gtimer4()
%timeit -r 50 -n 10 gtimer5()
"""
| {"/main.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-pahmc.py": ["/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/tune.py": ["/pahmc_ode_gpu/pahmc_tune.py", "/pahmc_ode_gpu/data_preparation.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-cuda_utilities.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/pahmc_ode_gpu/gd.py": ["/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (lorenz96).py": ["/pahmc_ode_gpu/data_preparation.py"], "/pahmc_ode_gpu/pahmc_tune.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"], "/unit_tests/test-data_generation (nakl).py": ["/pahmc_ode_gpu/data_preparation.py"], "/unit_tests/test-gd.py": ["/pahmc_ode_gpu/gd.py", "/pahmc_ode_gpu/cuda_utilities.py"]} |
46,629 | cmoratobsb/conciergeapi | refs/heads/main | /core/models.py | import uuid
from django.db import models
from administrativo.models import Situacao, Contato, Origem_Documento, CustomUsuario
def get_file_path(_instance, filename):
ext = filename.split('.')[-1]
filename = f'{uuid.uuid4()}.{ext}'
return filename
class BaseModel(models.Model):
criados = models.DateField('Criação', auto_now_add=True)
modificado = models.DateField('Atualização', auto_now=True)
ativo = models.BooleanField('Ativo?', default=True)
class Meta:
abstract = True
class Agenda_Auditorias(BaseModel):
id = models.AutoField(primary_key=True)
descricao = models.CharField('Descrição da Agenda', max_length=255, blank=True, null=True)
dat_ini = models.DateField('Data de Início', blank=True, null=True)
dat_fim = models.DateField('Data de Fim', blank=True, null=True)
situacao = models.ForeignKey(Situacao, on_delete=models.Choices)
class Meta:
verbose_name = 'Agenda de Auditoria'
verbose_name_plural = 'Agendas de Auditoria'
def __str__(self):
return str(self.descricao)
class Tipo_Documento(BaseModel):
id = models.AutoField(primary_key=True)
tipo = models.CharField('Tipo de Documento', max_length=255)
usu_petros = models.ForeignKey(CustomUsuario, on_delete=models.CASCADE)
contato = models.ForeignKey(Contato, on_delete=models.CASCADE, verbose_name='Contato')
agenda_auditoria = models.ForeignKey(Agenda_Auditorias, on_delete=models.CASCADE)
Origem_Documento = models.ForeignKey(Origem_Documento, on_delete=models.CASCADE)
descricao = models.TextField(max_length=1000, blank=True, null=True)
class Meta:
verbose_name = 'Tipo de Controle'
verbose_name_plural = 'Tipos de Controle'
def __str__(self):
return str(self.tipo)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,630 | cmoratobsb/conciergeapi | refs/heads/main | /regra_email/serialaizers.py | from rest_framework import serializers
from .models import Tipo_Regra, Regra_Email
class TipoRegraSerializer(serializers.ModelSerializer):
class Meta:
model = Tipo_Regra
fields = '__all__'
class RegraEmailSerializer(serializers.ModelSerializer):
Tipo_Regra = TipoRegraSerializer(many=True, read_only=True)
class Meta:
model = Regra_Email
fields = '__all__'
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,631 | cmoratobsb/conciergeapi | refs/heads/main | /administrativo/serialaizers.py | from rest_framework import serializers
from .models import Entidade, Diretoria, Gerencia
class EntidadeSerializer(serializers.ModelSerializer):
class Meta:
model = Entidade
fields = ('id', 'nome', 'descricao')
class DiretoriaSerializer(serializers.ModelSerializer):
#entidade = EntidadeSerializer(many=True, read_only=True)
class Meta:
model = Diretoria
fields = '__all__'
class GerenciaSerializer(serializers.ModelSerializer):
entidade = EntidadeSerializer(many=True, read_only=True)
class Meta:
model = Gerencia
fields = ('id', 'entidade', 'diretoria', 'nome', 'sigla', 'email', 'descricao', 'ativo')
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,632 | cmoratobsb/conciergeapi | refs/heads/main | /regra_email/views.py | from rest_framework import viewsets
from .models import Tipo_Regra, Regra_Email
from .serialaizers import TipoRegraSerializer, RegraEmailSerializer
class TipoRegraViewSet(viewsets.ModelViewSet):
queryset = Tipo_Regra.objects.all()
serializer_class = TipoRegraSerializer
class RegraEmailViewSet(viewsets.ModelViewSet):
queryset = Regra_Email.objects.all()
serializer_class = RegraEmailSerializer
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,633 | cmoratobsb/conciergeapi | refs/heads/main | /demanda/admin.py | from django.contrib import admin
from demanda.models import Documento, Historico_Documento, Csp, Ponto, Recomendacao
@admin.register(Documento)
class CargoAdmin(admin.ModelAdmin):
list_display = (
'id', 'titulo_documento', 'tipo_documento', 'situacao', 'responsavel',
'dat_ini', 'dat_fim', 'dat_prevista', 'dat_prorrogacao', 'qtd_prorrogacao', 'ativo')
list_display_links = ('titulo_documento', 'situacao')
# filter_horizontal = ('titulo_documento', 'situacao',)
search_fields = ('id',)
list_filter = ('id',)
list_per_page = 10
@admin.register(Historico_Documento)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'documento_hist', 'descricao', 'dat_incl', 'modificado', 'ativo')
list_display_links = ('id', 'documento_hist')
search_fields = ('id', 'dat_incl')
list_filter = ('id', 'dat_incl',)
list_per_page = 10
@admin.register(Csp)
class CargoAdmin(admin.ModelAdmin):
list_display = (
'id', 'documento', 'num_csp', 'descricao', 'dat_registro', 'dat_fim', 'dat_priorizacao', 'dat_prevista',
'modificado', 'ativo')
search_fields = ('id', 'num_csp',)
list_filter = ('id', 'num_csp',)
list_per_page = 10
@admin.register(Ponto)
class CargoAdmin(admin.ModelAdmin):
list_display = (
'id', 'nome', 'modificado', 'ativo')
search_fields = ('id', 'nome',)
list_filter = ('id', 'nome',)
list_per_page = 10
@admin.register(Recomendacao)
class CargoAdmin(admin.ModelAdmin):
list_display = (
'id', 'nome', 'responsavel', 'ponto', 'modificado', 'ativo')
search_fields = ('id', 'nome',)
list_filter = ('id', 'nome',)
list_per_page = 10 | {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,634 | cmoratobsb/conciergeapi | refs/heads/main | /core/admin.py | from django.contrib import admin
from .models import Agenda_Auditorias, Tipo_Documento
admin.site.site_header = 'Obrigações GAP'
admin.site.index_title = 'Obrigações GAP'
admin.site.site_title = 'Obrigações GAP'
@admin.register(Agenda_Auditorias)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'descricao', 'dat_ini', 'dat_fim', 'situacao', 'modificado', 'ativo')
list_display_links = ('id', 'descricao')
search_fields = ('id', 'descricao',)
list_filter = ('id', 'descricao',)
list_per_page = 10
@admin.register(Tipo_Documento)
class CargoAdmin(admin.ModelAdmin):
list_display = (
'id', 'tipo', 'usu_petros', 'contato', 'agenda_auditoria', 'Origem_Documento', 'descricao',
'modificado', 'ativo')
list_display_links = ('id', 'tipo')
search_fields = ('id',)
list_filter = ('id',)
list_per_page = 10
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,635 | cmoratobsb/conciergeapi | refs/heads/main | /Util/get_estilo.py | import os
import shutil
import re
from bs4 import BeautifulSoup
import uuid
import requests
rnd_str = uuid.uuid4().hex
main_name = "download_" + rnd_str
main_folder = main_name + "/"
dir = main_folder
if os.path.exists(dir):
shutil.rmtree(dir)
os.mkdir(main_folder)
site = 'https://www.petros.com.br/PortalPetros/faces/Petros?loginStatus=-1&_afrLoop=1792496918713510&_adf.ctrl-state=q1t3sd2tl_78'
response = requests.get(site)
soup = BeautifulSoup(response.text, 'html.parser')
# find all jpg,png,gif
img_tags = soup.find_all('img')
urls = [img['src'] for img in img_tags]
# print (urls)
for url in urls:
filename = re.search(r'/([\w_-]+[.](jpg|gif|png))$', url)
# with open( '/home/danesh20016/public_html/ts/'+main_folder+filename.group(1), 'wb') as f:
print(url)
with open('/home/danesh20016/public_html/ts/' + main_folder + filename.group(1), 'wb') as f:
# with open(main_folder+filename.group(1), 'wb') as f:
if 'http' not in url:
# sometimes an image source can be relative
# if it is provide the base url which also happens
# to be the site variable atm.
url = '{}{}'.format(site, url)
response = requests.get(url)
f.write(response.content)
# find all css
for link in soup.findAll('link', href=True):
# print ("Found the URL:", link['href'])
if re.search(".css", link['href']):
print(link['href'])
with open('/home/danesh20016/public_html/ts/' + main_folder + filename.group(1), 'wb') as f:
# with open(main_folder+filename.group(1), 'wb') as f:
if 'http' not in url:
# sometimes an image source can be relative
# if it is provide the base url which also happens
# to be the site variable atm.
url = '{}{}'.format(site, link['href'])
response = requests.get(url)
f.write(response.content)
# find all js
link_js = [sc["src"] for sc in soup.find_all("script", src=True)]
for link in link_js:
print("Found the URL:", link)
with open('/home/danesh20016/public_html/ts/' + main_folder + filename.group(1), 'wb') as f:
# with open(main_folder+filename.group(1), 'wb') as f:
if 'http' not in url:
# sometimes an image source can be relative
# if it is provide the base url which also happens
# to be the site variable atm.
url = '{}{}'.format(site, link)
response = requests.get(url)
f.write(response.content)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,636 | cmoratobsb/conciergeapi | refs/heads/main | /demanda/apps.py | from django.apps import AppConfig
class DemandaConfig(AppConfig):
default_auto_field = 'django.db.models.BigAutoField'
name = 'demanda'
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,637 | cmoratobsb/conciergeapi | refs/heads/main | /administrativo/admin.py | from django.contrib import admin
from django.contrib.auth.admin import UserAdmin
from .forms import CustomUsuarioCreateForm, CustomUsuarioChangeForm
from .models import Situacao, Nivel_Prorrogacao, CustomUsuario, \
Usuario_Petros, Gerencia, Setor, Entidade, Diretoria, Origem_Documento, Contato
@admin.register(Entidade)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'descricao', 'modificado', 'ativo')
list_display_links = ('id', 'nome')
search_fields = ('id', 'nome')
list_filter = ('id', 'nome')
list_per_page = 10
@admin.register(Diretoria)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'sigla', 'email', 'entidade', 'modificado', 'ativo')
list_display_links = ('id', 'nome')
search_fields = ('nome', 'entidade',)
list_filter = ('id', 'nome', 'entidade',)
list_per_page = 10
@admin.register(Gerencia)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'sigla', 'email', 'diretoria', 'modificado', 'ativo')
list_display_links = ('nome', 'sigla')
search_fields = ('nome', 'sigla', 'diretoria',)
list_filter = ('nome', 'sigla', 'diretoria',)
list_per_page = 10
@admin.register(Setor)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'sigla', 'email', 'gerencia', 'modificado', 'ativo')
list_display_links = ('nome', 'sigla')
search_fields = ('nome', 'sigla', 'gerencia',)
list_filter = ('nome', 'sigla', 'gerencia',)
list_per_page = 10
@admin.register(Origem_Documento)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'descricao', 'modificado', 'ativo')
list_display_links = ('id', 'nome')
search_fields = ('id', 'nome',)
list_filter = ('id', 'nome',)
list_per_page = 10
@admin.register(CustomUsuario)
class CustomUsuarioAdmin(UserAdmin):
add_form = CustomUsuarioCreateForm
form = CustomUsuarioChangeForm
model = CustomUsuario
list_display = ('first_name', 'last_name', 'email', 'fone', 'id_petros', 'is_staff')
fieldsets = (
(None, {'fields': ('email', 'password')}),
('Informações Funcionais', {'fields': ('first_name', 'last_name', 'fone', 'id_petros')}),
('Permissões', {'fields': ('is_active', 'is_staff', 'is_superuser', 'groups', 'user_permissions')}),
('Datas Importantes', {'fields': ('last_login', 'date_joined')}),
)
@admin.register(Usuario_Petros)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id_usu_petros', 'setor_petros', 'nome_usu', 'user_sistem', 'modificado', 'ativo')
list_display_links = ('id_usu_petros', 'nome_usu')
search_fields = ('id_usu_petros',)
list_filter = ('id_usu_petros',)
list_per_page = 10
@admin.register(Contato)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'email', 'celular', 'modificado', 'ativo')
list_display_links = ('id', 'nome')
search_fields = ('nome', 'email', 'celular',)
list_filter = ('nome',)
list_per_page = 10
@admin.register(Situacao)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'modificado', 'ativo')
list_display_links = ('id', 'nome')
search_fields = ('id', 'nome',)
list_filter = ('id', 'nome',)
list_per_page = 10
@admin.register(Nivel_Prorrogacao)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'responsavel', 'descricao', 'modificado', 'ativo')
list_display_links = ('id', 'nome')
search_fields = ('id', 'nome',)
list_filter = ('id', 'nome',)
list_per_page = 10
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,638 | cmoratobsb/conciergeapi | refs/heads/main | /administrativo/views.py | from rest_framework import viewsets
from .models import Entidade, Diretoria
from .serialaizers import EntidadeSerializer, DiretoriaSerializer
class EntidadeViewSet(viewsets.ModelViewSet):
queryset = Entidade.objects.all()
serializer_class = EntidadeSerializer
class DiretoriaViewSet(viewsets.ModelViewSet):
queryset = Diretoria.objects.all()
serializer_class = DiretoriaSerializer
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,639 | cmoratobsb/conciergeapi | refs/heads/main | /regra_email/models.py | from django.db import models
class BaseModel(models.Model):
criados = models.DateField('Criação', auto_now_add=True)
modificado = models.DateField('Atualização', auto_now=True)
ativo = models.BooleanField('Ativo?', default=True)
class Meta:
abstract = True
class Tipo_Regra(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField(max_length=255, blank=True, null=False)
class Meta:
verbose_name = 'Tipo de Regra'
verbose_name_plural = 'Tipos de Regras'
def __str__(self):
return str(self.id) + ' | ' + str(self.nome)
class Regra_Email(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField(max_length=255, blank=True, null=False)
tipo = models.ForeignKey(Tipo_Regra, related_name='tipo_regra', on_delete=models.CASCADE,
verbose_name='tipo_regra')
class Meta:
verbose_name = 'Regra e-mail'
verbose_name_plural = 'Regras e-mail'
def __str__(self):
return str(self.id) + ' | ' + str(self.nome)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,640 | cmoratobsb/conciergeapi | refs/heads/main | /core/views.py | from django.urls import reverse_lazy
from django.views.generic import ListView
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from .forms import DocumentoForm
from demanda.models import Documento, Ponto
class IndexView(ListView):
model = Documento
template_name = 'index.html'
queryset = Documento.objects.order_by('id').all()
context_object_name = 'documentos'
class ListPontoView(ListView):
model = Documento
template_name = 'ponto_list.html'
queryset = Ponto.objects.order_by('id').all()
context_object_name = 'pontos'
class CreateDocumentoView(CreateView):
model = Documento
template_name = 'documento_form.html'
fields = ['id',
'diretoria',
# 'tipo_documento',
# 'historico_documento',
'titulo_documento',
'tipo_documento',
'situacao',
'responsavel',
'dat_ini',
'dat_fim',
'ativo']
success_url = reverse_lazy('index')
class UpdateDocumentoView(UpdateView):
model = Documento
template_name = 'documento_form.html'
fields = ['id',
'diretoria',
# 'tipo_documento',
# 'historico_documento',
'titulo_documento',
'tipo_documento',
'situacao',
'responsavel',
'dat_ini',
'dat_fim',
'ativo']
success_url = reverse_lazy('index')
class DeleteDocumentoView(DeleteView):
model = Documento
template_name = 'documento_del.html'
success_url = reverse_lazy('index')
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,641 | cmoratobsb/conciergeapi | refs/heads/main | /demanda/urls.py | from django.urls import path, include
from rest_framework.routers import SimpleRouter
from .views import DocumentoViewSet, HistoricoDocumentoViewSet
routerDemanda = SimpleRouter()
routerDemanda.register('documentos', DocumentoViewSet)
routerDemanda.register('historicosdocumento', HistoricoDocumentoViewSet)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,642 | cmoratobsb/conciergeapi | refs/heads/main | /demanda/views.py | from django.views import generic
from rest_framework import generics
from rest_framework import viewsets
from .models import Documento, Historico_Documento
from .serialaizers import DocumentoSerializer, HistoricoDocumentoSerializer
class ListaDemandas(generic.ListView):
model = Documento
context_object_name = 'demanda'
queryset = Documento.objects.order_by('?').all()
template_name = 'listaDemandas.html'
class DocumentoViewSet(viewsets.ModelViewSet):
queryset = Documento.objects.all()
serializer_class = DocumentoSerializer
class HistoricoDocumentoViewSet(viewsets.ModelViewSet):
queryset = Historico_Documento.objects.all()
serializer_class = HistoricoDocumentoSerializer
# class DocumentoAPIView(APIView):
# def get(self, request):
# documentos = Documento.objects.all()
# serializer = DocumentoSerializer(documentos, many=True)
# return Response(serializer.data)
#
# def post(self, request):
# serializer = DocumentoSerializer(data=request.data)
# serializer.is_valid(raise_exception=True)
# serializer.save()
# return Response(serializer.data, status=status.HTTP_201_CREATED)
#
#
# class HistoricoDocumentoAPIView(APIView):
# def get(self, request):
# Historico_Documentos = Historico_Documento.objects.all()
# serializer = HistoricoDocumentoSerializer(Historico_Documentos, many=True)
# return Response(serializer.data)
#
# def post(self, request):
# serializer = HistoricoDocumentoSerializer(data=request.data)
# serializer.is_valid(raise_exception=True)
# serializer.save()
# return Response(serializer.data, status=status.HTTP_201_CREATED)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,643 | cmoratobsb/conciergeapi | refs/heads/main | /core/urls.py | from django.urls import path, include
from .views import IndexView, CreateDocumentoView, UpdateDocumentoView, DeleteDocumentoView, ListPontoView
urlpatterns = [
path('', IndexView.as_view(), name='index'),
path('add_documento/', CreateDocumentoView.as_view(), name='add_documento'),
path('<int:pk>/update/', UpdateDocumentoView.as_view(), name='upd_documento'),
path('<int:pk>/delete/', DeleteDocumentoView.as_view(), name='del_documento'),
path('pontos/', ListPontoView.as_view(), name='pontos'),
]
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,644 | cmoratobsb/conciergeapi | refs/heads/main | /regra_email/admin.py | from django.contrib import admin
from .models import Tipo_Regra, Regra_Email
@admin.register(Tipo_Regra)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'criados', 'modificado', 'ativo')
list_display_links = ('id', 'nome', 'criados', 'modificado', 'ativo')
# filter_horizontal = ('titulo_documento', 'situacao',)
search_fields = ('id',)
list_filter = ('id',)
list_per_page = 10
@admin.register(Regra_Email)
class CargoAdmin(admin.ModelAdmin):
list_display = ('id', 'nome', 'criados', 'tipo', 'modificado', 'ativo')
list_display_links = ('id', 'nome', 'criados', 'modificado', 'ativo')
# filter_horizontal = ('titulo_documento', 'situacao',)
search_fields = ('id',)
list_filter = ('id',)
list_per_page = 10
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,645 | cmoratobsb/conciergeapi | refs/heads/main | /demanda/models.py | import uuid
from django.db import models
from administrativo.models import Situacao, CustomUsuario, Contato, Diretoria, Usuario_Petros
from core.models import Tipo_Documento, Agenda_Auditorias
def get_file_path(_instance, filename):
ext = filename.split('.')[-1]
filename = f'{uuid.uuid4()}.{ext}'
return filename
class BaseModel(models.Model):
criados = models.DateField('Criação', auto_now_add=True)
modificado = models.DateField('Atualização', auto_now=True)
ativo = models.BooleanField('Ativo?', default=True)
class Meta:
abstract = True
class Documento(BaseModel):
id = models.AutoField(primary_key=True)
diretoria = models.ForeignKey(Diretoria, related_name='diretoria', on_delete=models.CASCADE,
verbose_name='diretoria')
titulo_documento = models.CharField('Descrição da Recomendação', max_length=255, blank=True, null=True)
tipo_documento = models.ForeignKey(Tipo_Documento, related_name='tipo_documento', on_delete=models.CASCADE)
situacao = models.ForeignKey(Situacao, on_delete=models.CASCADE)
responsavel = models.ForeignKey(Usuario_Petros, on_delete=models.CASCADE)
dat_ini = models.DateField('Data de Inicio', blank=True, null=True)
dat_fim = models.DateField('Data de Fim', blank=True, null=True)
dat_prevista = models.DateField('Previsão', blank=True, null=True)
dat_prorrogacao = models.DateField('Data de Prorrogação', blank=True, null=True)
qtd_prorrogacao = models.BigIntegerField(default=1, editable=False)
class Meta:
verbose_name = 'Documento'
verbose_name_plural = 'Documentos'
def __str__(self):
return str(self.titulo_documento)
class Historico_Documento(BaseModel):
id = models.AutoField(primary_key=True)
documento_hist = models.ForeignKey(Documento, related_name='documento_hist', on_delete=models.CASCADE,
verbose_name='documento_hist')
descricao = models.TextField('Histórico', max_length=1000, blank=True, null=True)
dat_incl = models.DateTimeField('Inclusão', auto_now_add=True)
class Meta:
verbose_name = 'Historico de Documento'
verbose_name_plural = 'Historicos de Documentos'
def __str__(self):
return str(self.id) + ' | ' + str(self.descricao)
class Csp(BaseModel):
id = models.AutoField(primary_key=True)
documento = models.ForeignKey(Documento, on_delete=models.CASCADE, verbose_name='documento')
num_csp = models.CharField('Número do CSP', max_length=9, blank=True, null=True)
descricao = models.TextField('Descrição do CSP', max_length=1000, blank=True, null=True)
dat_registro = models.DateField('Data de Registro', blank=True, null=True)
dat_fim = models.DateField('Data de Conclusão', blank=True, null=True)
dat_priorizacao = models.DateField('Data de Priorização', blank=True, null=True)
dat_prevista = models.DateField('Previsão', blank=True, null=True)
class Meta:
verbose_name = 'CSP'
verbose_name_plural = 'CSPs'
def __str__(self):
return str(self.num_csp)
class Ponto(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Ponto', max_length=255, blank=True, null=True)
documento_ponto = models.ForeignKey(Documento, related_name='documento_ponto', on_delete=models.CASCADE,
verbose_name='documento_ponto')
class Meta:
verbose_name = 'Ponto'
verbose_name_plural = 'Pontos'
def __str__(self):
return str(self.nome)
class Recomendacao(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Recomendação', max_length=255, blank=True, null=True)
responsavel = models.ForeignKey(Usuario_Petros, related_name='customusuario', on_delete=models.CASCADE,
verbose_name='Responsável')
ponto = models.ForeignKey(Ponto, related_name='ponto', on_delete=models.CASCADE,
verbose_name='ponto')
class Meta:
verbose_name = 'Recomendação'
verbose_name_plural = 'Recomendações'
def __str__(self):
return str(self.nome)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,646 | cmoratobsb/conciergeapi | refs/heads/main | /administrativo/models.py | import uuid
from django.contrib.auth.models import AbstractUser, BaseUserManager
from django.db import models
from django.db.models.signals import post_save
from django.dispatch import receiver
from rest_framework.authtoken.models import Token
from concierge import settings
def get_file_path(_instance, filename):
ext = filename.split('.')[-1]
filename = f'{uuid.uuid4()}.{ext}'
return filename
class BaseModel(models.Model):
criados = models.DateField('Criação', auto_now_add=True)
modificado = models.DateField('Atualização', auto_now=True)
ativo = models.BooleanField('Ativo?', default=True)
class Meta:
abstract = True
class Entidade(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Nome do Entidade', max_length=255)
descricao = models.TextField('Breve descição', max_length=500, blank=True, null=True)
class Meta:
verbose_name = 'Entidade'
verbose_name_plural = 'Entidades'
def __str__(self):
return str(self.id) + ' | ' + str(self.nome)
class Diretoria(BaseModel):
id = models.AutoField(primary_key=True)
entidade = models.ForeignKey(Entidade, on_delete=models.CASCADE)
nome = models.CharField('Diretoria', max_length=255)
sigla = models.CharField('Sigla Diretoria', max_length=6)
email = models.EmailField()
class Meta:
verbose_name = 'Diretoria'
verbose_name_plural = 'Diretorias'
def __str__(self):
return str(self.id) + ' | ' + str(self.sigla)
class Gerencia(BaseModel):
id = models.AutoField(primary_key=True)
entidade = models.ForeignKey(Entidade, on_delete=models.CASCADE)
diretoria = models.ForeignKey(Diretoria, on_delete=models.CASCADE)
nome = models.CharField('Nome Gerência', max_length=255, blank=True, null=True)
sigla = models.CharField('Sigla da Gerência', max_length=10)
email = models.EmailField()
class Meta:
verbose_name = 'Gerência'
verbose_name_plural = 'Gerências'
def __str__(self):
return str(self.id) + ' | ' + str(self.sigla)
class Setor(BaseModel):
id = models.AutoField(primary_key=True)
entidade = models.ForeignKey(Entidade, on_delete=models.CASCADE)
diretoria = models.ForeignKey(Diretoria, on_delete=models.CASCADE)
gerencia = models.ForeignKey(Gerencia, on_delete=models.CASCADE)
sigla = models.CharField('Sigla da Setor', max_length=10)
nome = models.CharField('Nome Setor', max_length=255, blank=True, null=True)
email = models.EmailField()
class Meta:
verbose_name = 'Setor'
verbose_name_plural = 'Setores'
def __str__(self):
return str(self.id) + ' | ' + self.sigla
class UsuarioManager(BaseUserManager):
use_in_migrations = True
def _create_user(self, email, password, **extra_fields):
if not email:
raise ValueError('O e-mail é obrigatório')
email = self.normalize_email(email)
user = self.model(email=email, username=email, **extra_fields)
user.set_password(password)
user.save(using=self._db)
return user
def create_user(self, email, password=None, **extra_fields):
# extra_fields.setdefault('is_staff', True)
extra_fields.setdefault('is_superuser', False)
return self._create_user(email, password, **extra_fields)
def create_superuser(self, email, password, **extra_fields):
extra_fields.setdefault('is_superuser', True)
extra_fields.setdefault('is_staff', True)
if extra_fields.get('is_superuser') is not True:
raise ValueError('Superuser precisa ter is_superuser=True')
if extra_fields.get('is_staff') is not True:
raise ValueError('Superuser precisa ter is_staff=True')
return self._create_user(email, password, **extra_fields)
class CustomUsuario(AbstractUser):
email = models.EmailField('E-mail', unique=True)
fone = models.CharField('Telefone', max_length=15)
id_petros = models.CharField('id_petros', max_length=7)
is_staff = models.BooleanField('Membro da equipe', default=True)
USERNAME_FIELD = 'email'
REQUIRED_FIELDS = ['first_name', 'last_name', 'fone', 'id_petros', ]
def __str__(self):
return self.id_petros + ' | ' + self.email
objects = UsuarioManager()
class Origem_Documento(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Origem do Documento', max_length=255)
descricao = models.TextField(max_length=1000, blank=True, null=True)
class Meta:
verbose_name = 'Origem do Controle'
verbose_name_plural = 'Origems dos Controles'
def __str__(self):
return str(self.descricao)
class Usuario_Petros(BaseModel):
entidade = models.ForeignKey(Entidade, on_delete=models.CASCADE)
diretoria = models.ForeignKey(Diretoria, on_delete=models.CASCADE)
gerencia = models.ForeignKey(Gerencia, on_delete=models.CASCADE)
id_usu_petros = models.AutoField(primary_key=True)
nome_usu = models.CharField('Nome', max_length=255)
setor_petros = models.ForeignKey(Setor, on_delete=models.CASCADE)
user_sistem = models.ForeignKey(CustomUsuario, on_delete=models.CASCADE)
class Meta:
verbose_name = 'Usuario Petros'
verbose_name_plural = 'Usuarios Petros'
def __str__(self):
return str(self.nome_usu)
@receiver(post_save, sender=settings.AUTH_USER_MODEL)
def create_auth_token(sender, instance=None, created=False, **kwargs):
if created:
Token.objects.create(user=instance)
class Contato(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Contato da Demanda', max_length=255, blank=True, null=True)
email = models.EmailField('e-mail Contato', max_length=255)
celular = models.CharField(max_length=11, blank=True, null=True, verbose_name='Nº telefone celular')
class Meta:
verbose_name = 'Contato'
verbose_name_plural = 'Contatos'
def __str__(self):
return str(self.nome)
class Situacao(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Situação', max_length=255)
class Meta:
verbose_name = 'situação'
verbose_name_plural = 'situações'
def __str__(self):
return str(self.id) + ' | ' + str(self.nome)
class Nivel_Prorrogacao(BaseModel):
id = models.AutoField(primary_key=True)
nome = models.CharField('Prorrogação', max_length=255)
responsavel = models.ForeignKey(CustomUsuario, on_delete=models.CASCADE, verbose_name='Autorizador Responsável')
descricao = models.CharField('Nivel de Prorrogação', max_length=1000, blank=True, null=True)
class Meta:
verbose_name = 'Nivél de Prorrogação'
verbose_name_plural = 'Niveis de Prorrogação'
def __str__(self):
return str(self.id) + ' | ' + self.nome
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,647 | cmoratobsb/conciergeapi | refs/heads/main | /core/forms.py | from django import forms
from demanda.models import Documento
class DocumentoForm(forms.ModelForm):
id = forms.IntegerField(label='id_documento')
diretoria = forms.CharField(label='Diretoria', max_length=255)
titulo_documento = forms.CharField(label='Titulo do Documento', max_length=255)
tipo_documento = forms.CharField(label='Tipo de Documento', max_length=255)
situacao = forms.CharField(label='Situação do Documento', max_length=255)
responsavel = forms.CharField(label='Responsavel Pelo Documento', max_length=255)
dat_ini = forms.DateField(label='Data de Inicio', widget=forms.DateField)
dat_fim = forms.DateField(label='Data de Inicio', widget=forms.DateField)
dat_prevista = forms.DateField(label='Data de Inicio', widget=forms.DateField)
dat_prorrogacao = forms.DateField(label='Data de Prorrogação', widget=forms.DateField, disabled=True)
qtd_prorrogacao = forms.IntegerField(label='Quantidade de Prorrogações', disabled=True)
class Meta:
model = Documento
fields = '__all__'
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,648 | cmoratobsb/conciergeapi | refs/heads/main | /concierge/urls.py | from django.conf import settings
from django.contrib import admin
from django.urls import path, include
from django.conf.urls.static import static
from demanda.urls import routerDemanda
from administrativo.urls import routerAdministrativo
from regra_email.urls import routerEmail
urlpatterns = [
path('', include('core.urls')),
path('api/demanda/', include(routerDemanda.urls)),
path('api/administrativo/', include(routerAdministrativo.urls)),
path('painel/', admin.site.urls),
path('api/regraemail/', include(routerEmail.urls)),
path('api-auth/', include('rest_framework.urls')),
path('auths/', include('django.contrib.auth.urls'))
] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,649 | cmoratobsb/conciergeapi | refs/heads/main | /administrativo/urls.py | from rest_framework.routers import SimpleRouter
from administrativo.views import EntidadeViewSet, DiretoriaViewSet
routerAdministrativo = SimpleRouter()
routerAdministrativo.register('entidade', EntidadeViewSet)
routerAdministrativo.register('diretoria', DiretoriaViewSet) | {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,650 | cmoratobsb/conciergeapi | refs/heads/main | /demanda/serialaizers.py | from rest_framework import serializers
from .models import Documento, Historico_Documento
class HistoricoDocumentoSerializer(serializers.ModelSerializer):
class Meta:
model = Historico_Documento
fields = '__all__'
class DocumentoSerializer(serializers.ModelSerializer):
# nested relationship
historico_documento = HistoricoDocumentoSerializer(many=True, read_only=True)
class Meta:
extra_kargs = {
'qtd_prorrogacao': {'write_only': True}
}
model = Documento
fields = ('id',
'diretoria',
'tipo_documento',
'historico_documento',
'titulo_documento',
'tipo_documento',
'situacao',
'responsavel',
'dat_ini',
'dat_fim',
'dat_prorrogacao',
'qtd_prorrogacao',
'ativo')
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,651 | cmoratobsb/conciergeapi | refs/heads/main | /regra_email/urls.py | from django.urls import path, include
from rest_framework.routers import SimpleRouter
from .views import TipoRegraViewSet, RegraEmailViewSet
routerEmail = SimpleRouter()
routerEmail.register('tipo_regra', TipoRegraViewSet)
routerEmail.register('regraemail', RegraEmailViewSet)
| {"/core/models.py": ["/administrativo/models.py"], "/regra_email/serialaizers.py": ["/regra_email/models.py"], "/administrativo/serialaizers.py": ["/administrativo/models.py"], "/regra_email/views.py": ["/regra_email/models.py", "/regra_email/serialaizers.py"], "/demanda/admin.py": ["/demanda/models.py"], "/core/admin.py": ["/core/models.py"], "/administrativo/admin.py": ["/administrativo/models.py"], "/administrativo/views.py": ["/administrativo/models.py", "/administrativo/serialaizers.py"], "/core/views.py": ["/core/forms.py", "/demanda/models.py"], "/demanda/urls.py": ["/demanda/views.py"], "/demanda/views.py": ["/demanda/models.py", "/demanda/serialaizers.py"], "/core/urls.py": ["/core/views.py"], "/regra_email/admin.py": ["/regra_email/models.py"], "/demanda/models.py": ["/administrativo/models.py", "/core/models.py"], "/core/forms.py": ["/demanda/models.py"], "/concierge/urls.py": ["/demanda/urls.py", "/administrativo/urls.py", "/regra_email/urls.py"], "/administrativo/urls.py": ["/administrativo/views.py"], "/demanda/serialaizers.py": ["/demanda/models.py"], "/regra_email/urls.py": ["/regra_email/views.py"]} |
46,652 | nieiwona/phylogenetic_pipeline | refs/heads/main | /main.py | #!/bin/usr/env python3
from phylogenetic_pipeline import cluster_sequences, calculate_gene_trees_ml, get_protein_id_to_sequence, \
calculate_constenus_tree, calculate_supertree, select_best_supertree, visualize_newick, bootstrap_supertree
import argparse
from pathlib import Path
parser = argparse.ArgumentParser(description='Phylogenetic pipeline')
parser.add_argument('-cluster', type=Path,
help='Provide path to file with accessions of genomes to be clustered')
parser.add_argument('-approach', choices={'one_to_one', 'allow_paralogs', 'bootstrap'},
help='Select approach')
parser.add_argument('-consensus_tree', nargs=2,
help='Calculate consensus tree, provide path to dir containing PhyML ML trees and name for file')
parser.add_argument('-supertree', nargs=1,
help='Calculate supertree, provide path to dir containing PhyML ML trees')
parser.add_argument('-supertree_bootstrap', nargs=2,
help='Calculate supertree for bootstrap trees, provide path to dir containing PhyML ML trees and bootstrap cutoff (percent)')
parser.add_argument('-select_best_supertree', nargs=3,
help='Select best supertree, provide path to Fasturec output file and name to the file, index of selected tree')
parser.add_argument('-visualize_newick', type=Path,
help='Visualize newick tree, provide path to file containing tree in newick format')
if __name__ == '__main__':
ncbi_dir = './data/ncbi_genomes/'
db_dir = './data/db'
clusters_dir = './data/clusters'
consensus_dir = './data/consensus'
args = parser.parse_args()
if args.cluster:
accessions_to_names_dict, accession_to_protein_id_list_dict, protein_id_to_sequence_dict = cluster_sequences(args.cluster)
if args.approach == 'one_to_one':
protein_id_to_sequence_dict = get_protein_id_to_sequence(ncbi_dir)
calculate_gene_trees_ml(0, protein_id_to_sequence_dict, args)
if args.approach == 'allow_paralogs':
protein_id_to_sequence_dict = get_protein_id_to_sequence(ncbi_dir)
calculate_gene_trees_ml(0, protein_id_to_sequence_dict, args)
if args.approach == 'bootstrap':
protein_id_to_sequence_dict = get_protein_id_to_sequence(ncbi_dir)
calculate_gene_trees_ml(100, protein_id_to_sequence_dict, args)
if args.consensus_tree:
calculate_constenus_tree(args.consensus_tree[0], args.consensus_tree[1])
if args.supertree:
calculate_supertree(args.supertree[0])
if args.supertree_bootstrap:
bootstrap_supertree(args.supertree_bootstrap[0], args.supertree_bootstrap[1])
if args.select_best_supertree:
select_best_supertree(args.select_best_supertree[0], args.select_best_supertree[1], int(args.select_best_supertree[2]))
if args.visualize_newick:
visualize_newick(args.visualize_newick)
| {"/main.py": ["/phylogenetic_pipeline.py"]} |
46,653 | nieiwona/phylogenetic_pipeline | refs/heads/main | /phylogenetic_pipeline.py | from Bio import Entrez, SeqIO, Phylo, AlignIO
import gzip
import os
import shutil
import urllib.request as request
from contextlib import closing
import pandas as pd
import logging
import sys
from statistics import median
from shutil import copyfile
from collections import Counter
import time
import matplotlib.pyplot as plt
from io import StringIO
from Bio import Phylo
from Bio.Phylo.Consensus import majority_consensus, strict_consensus
import re
from itertools import permutations
ncbi_dir = './data/ncbi_genomes/'
db_dir = './data/db'
clusters_dir = './data/clusters'
consensus_dir = './data/consensus'
def setup_logging(arg):
logging.basicConfig(filename='pipeline.log',
filemode='a',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
datefmt='%H:%M:%S',
level=logging.INFO)
logging.info(f'Start with argument {arg}')
# Stage 1
def parse_genomes_ids(path):
path = os.path.relpath(path)
accessions_to_names_dict = {}
with open(path, 'r') as f:
for line in f:
words = line.strip().split()
acc = words[0]
name = words[1]
accessions_to_names_dict[acc] = name
logging.info(f"Path to accessions file {path}")
logging.info(f"Accessions of genomes to be analysed and organisms names: {accessions_to_names_dict}")
return accessions_to_names_dict
def make_empty_folder(dir_name):
if not os.path.exists(dir_name):
os.makedirs(dir_name)
print(f"Directory {dir_name} created")
logging.info(f"Directory {dir_name} created")
def download_file_from_ftp(remote_path, local_path):
with closing(request.urlopen(remote_path)) as remote_file:
with open(local_path, "wb") as local_file:
shutil.copyfileobj(remote_file, local_file)
def unzip_file(input_file_path, output_file_path):
with gzip.open(input_file_path, "rb") as input_file:
with open(output_file_path, "wb") as output_file:
shutil.copyfileobj(input_file, output_file)
def get_ncbi_genomes(base_path, accessions_to_names_dict):
start_time = time.time()
make_empty_folder(base_path)
Entrez.email = "iwonaa.gozdziewska@gamil.com"
for assembly in accessions_to_names_dict.keys():
output_file_name = assembly + ".fna"
if os.path.isfile(base_path + output_file_name):
print(f"Assembly {assembly} is already downloaded")
logging.info(f"Assembly {assembly} is already downloaded")
continue
try:
search_handle = Entrez.esearch(db="assembly", term=assembly)
assembly_id = Entrez.read(search_handle)["IdList"][0]
except IndexError:
print(f"Entrez.esearch did not find assembly {assembly}, ignoring")
logging.info(f"Entrez.esearch did not find assembly {assembly}, ignoring")
continue
summary_handle = Entrez.esummary(db="assembly", id=assembly_id, report="full")
assembly_info = Entrez.read(summary_handle)
remote_folder_path = assembly_info["DocumentSummarySet"]["DocumentSummary"][0]["FtpPath_RefSeq"] # FtpPath_GeneBank
print(remote_folder_path)
remote_file_name = remote_folder_path.rsplit("/", 1)[-1] + "_protein.faa.gz"
print(remote_file_name)
remote_file_path = remote_folder_path + "/" + remote_file_name
print(remote_file_path)
print(f"Downloading: {remote_file_path}")
logging.info(f"Downloading: {remote_file_path}")
download_file_from_ftp(remote_file_path, base_path + remote_file_name)
unzip_file(base_path + remote_file_name, base_path + output_file_name)
os.remove(base_path + remote_file_name)
logging.info(f'Downloading completed. Execution time {round((time.time() - start_time) / 60, 2)} min')
def get_accession_to_protein_id_list(ncbi_dir):
accession_to_protein_id_list_dict = {}
for fn in os.listdir(ncbi_dir):
if fn.endswith('.fna'):
accession = os.path.splitext(fn)[0]
protein_id_lst = set()
fn_path = f'{ncbi_dir}/{fn}'
with open(fn_path, 'r') as f:
for line in f:
if line.startswith('>'):
protein_id = line.split()[0]
protein_id = protein_id.split('>')[1]
protein_id_lst.add(protein_id)
logging.info(f"Genome {accession} include {len(protein_id_lst)} proteins")
accession_to_protein_id_list_dict[accession] = protein_id_lst
return accession_to_protein_id_list_dict
def conacatenate_fasta_files(ncbi_dir):
outfile_path = f'{ncbi_dir}/concatenated_fasta_files.faa'
with open(outfile_path, 'w') as outfile:
for filename in os.listdir(ncbi_dir):
if filename.endswith('.fna'):
filename_path = f'{ncbi_dir}/{filename}'
with open(filename_path) as infile:
for line in infile:
outfile.write(line)
logging.info(f"File {ncbi_dir}/concatenated_fasta_files.faa created")
def get_protein_id_to_sequence(ncbi_dir):
outfile_path = f'./{ncbi_dir}concatenated_fasta_files.faa'
protein_id_to_sequence_dict = {}
for record in SeqIO.parse(outfile_path, "fasta"):
protein_id_to_sequence_dict[record.id] = str(record.seq)
return protein_id_to_sequence_dict
def clustering(ncbi_dir, db_dir, clusters_dir):
outfile_path = f'./{ncbi_dir}concatenated_fasta_files.faa'
make_empty_folder(db_dir)
make_empty_folder(clusters_dir)
start_time = time.time()
print('Clustering...')
logging.info('Clustering with parameters -min-seq-id 0.5 -c 0.8 --cov-mode 1')
create_db = os.system(f'mmseqs createdb {outfile_path} {db_dir}/db')
execute_clustering = os.system(f'mmseqs cluster {db_dir}/db {clusters_dir}/db_clu {clusters_dir}/tmp -c 0.8 --cov-mode 0 --min-seq-id 0.5') # default
output_to_tsv = os.system(f'mmseqs createtsv {db_dir}/db {db_dir}/db {clusters_dir}/db_clu {clusters_dir}/DB_clu.tsv')
logging.info(f'Clustering completed. Execution time {round((time.time() - start_time) / 60, 2)} min')
print('Clustering completed')
def file_for_cluster(clusters_dir):
logging.info('Writting clusters to .cluster files')
db_clu_tsv_path = f'{clusters_dir}/DB_clu.tsv'
db_clu_tsv = pd.read_csv(db_clu_tsv_path, sep='\t', header=None, names=['representative', 'elements'])
logging.info(f"Number of clusters: {len(db_clu_tsv.representative.unique())}")
logging.info(f"Number of proteins clustered: {len(db_clu_tsv.elements.unique())}")
make_empty_folder(f'{clusters_dir}/cluster')
previous = None
i = 0
for index, row in db_clu_tsv.iterrows():
if row[0] == previous:
fn = f'{i}.cluster'
file_path = f'{clusters_dir}/cluster/{fn}'
with open(file_path, 'a') as f:
f.write(f'\n>{row[1]}')
if row[0] != previous:
i += 1
fn = f'{i}.cluster'
file_path = f'{clusters_dir}/cluster/{fn}'
with open(file_path, 'w') as nf:
nf.write(f'>{row[1]}') # row[0] will always be the first in cluster as row[1]
previous = row[0]
logging.info("Writting clusters to .cluster files completed")
def add_accession_to_protein_id_in_cluster(clusters_dir, accession_to_protein_id_list_dict, accessions_to_names_dict):
cluster_files_path = f'{clusters_dir}/cluster'
for filename in os.listdir(cluster_files_path):
f = open(f'{cluster_files_path}/{filename}', 'r+')
protein_ids_with_acccessions = []
for line in f:
line = line.rstrip()
protein_id = line.split('>')[1]
for acc in accession_to_protein_id_list_dict.keys():
if protein_id in accession_to_protein_id_list_dict[acc]:
protein_ids_with_acccessions.append(f'{accessions_to_names_dict[acc]} {protein_id}')
f.seek(0)
for el in protein_ids_with_acccessions:
f.write(f'>{el}\n')
f.truncate()
f.close()
def filter_clusters(clusters_dir):
cluster_files_path = f'{clusters_dir}/cluster'
allow_paralogs_path = f'{clusters_dir}/cluster_allow_paralogs'
one_to_one_path = f'{clusters_dir}/cluster_one_to_one'
bootstrap_path = f'{clusters_dir}/cluster_bootstrap'
make_empty_folder(allow_paralogs_path)
make_empty_folder(one_to_one_path)
make_empty_folder(bootstrap_path)
stats = []
for rm_fn in os.listdir(cluster_files_path): # filter remaining
if rm_fn.endswith('.cluster'):
with open(f'{cluster_files_path}/{rm_fn}', 'r') as rf:
accessions_lst = []
for line in rf:
line = line.rstrip()
line_els = line.replace('>', '').split(' ')
org = line_els[0]
accessions_lst.append(org)
acc_counts = Counter(accessions_lst)
stats.append(len(accessions_lst))
# Allow paralogs
if len(set(accessions_lst)) == 10:
if all(i <= 2 for i in list(acc_counts.values())): # up to 2 paralogs
copyfile(f'{cluster_files_path}/{rm_fn}', f'{allow_paralogs_path}/{rm_fn}')
# One to one
if all(i == 1 for i in list(acc_counts.values())):
copyfile(f'{cluster_files_path}/{rm_fn}', f'{one_to_one_path}/{rm_fn}')
copyfile(f'{cluster_files_path}/{rm_fn}', f'{bootstrap_path}/{rm_fn}')
stats_dict = Counter(stats)
plt.bar(range(len(stats_dict)), list(stats_dict.values()), align='center')
plt.xlabel('Size of clusters')
plt.ylabel('Frequency')
plt.title('Frequency of the size of clusters')
plt.savefig('clusters_histogram.png')
logging.info(f'Cluster size frequency: {stats_dict}')
print(f'Mean size of clusters: {sum(stats) / len(stats)}')
logging.info(f'Mean size of clusters: {sum(stats) / len(stats)}')
print(f'Median size of clusters: {median(stats)}')
logging.info(f'Median size of clusters: {median(stats)}')
def cluster_sequences(Path):
ncbi_dir = './data/ncbi_genomes/'
db_dir = './data/db'
clusters_dir = './data/clusters'
setup_logging('clustering')
accessions_to_names_dict = parse_genomes_ids(Path)
get_ncbi_genomes(ncbi_dir, accessions_to_names_dict)
accession_to_protein_id_list_dict = get_accession_to_protein_id_list(ncbi_dir)
conacatenate_fasta_files(ncbi_dir)
protein_id_to_sequence_dict = get_protein_id_to_sequence(ncbi_dir)
clustering(ncbi_dir, db_dir, clusters_dir)
file_for_cluster(clusters_dir)
add_accession_to_protein_id_in_cluster(clusters_dir, accession_to_protein_id_list_dict, accessions_to_names_dict)
filter_clusters(clusters_dir)
return accessions_to_names_dict, accession_to_protein_id_list_dict, protein_id_to_sequence_dict
# Stage 2
def cluster_to_fasta(cluster_dir, protein_id_to_sequence_dict):
fasta_path = f'{cluster_dir}/fasta'
make_empty_folder(fasta_path)
for cluster_fn in os.listdir(cluster_dir):
if cluster_fn.endswith('.cluster'):
cluster_number = os.path.splitext(cluster_fn)[0]
faa_name = f'{cluster_number}.faa'
with open(f'{cluster_dir}/{cluster_fn}', 'r') as cluster_f:
with open(f'{fasta_path}/{faa_name}', 'a') as fasta_f:
orgs = []
for line in cluster_f:
els = line.replace('>', '').rstrip().split(' ')
protein_id = els[1]
org = els[0]
protein_seq = protein_id_to_sequence_dict[protein_id]
if org not in orgs:
fasta_f.write(f'>{org} {protein_id}\n{protein_seq}\n')
orgs.append(org)
else:
fasta_f.write(f'>{org}_ {protein_id}\n{protein_seq}\n')
def calculate_multialignment_for_cluster(cluster_dir):
logging.info('Calculating multialignment')
start_time = time.time()
clustalw2_path = './tools/clustalw-2.1-linux-x86_64-libcppstatic/clustalw2'
aln_path = f'{cluster_dir}/aln'
make_empty_folder(aln_path)
fasta_files_path = f'{cluster_dir}/fasta'
for fasta_fn in os.listdir(fasta_files_path):
fasta_fn_path = f'{fasta_files_path}/{fasta_fn}'
cluster_number = os.path.splitext(fasta_fn)[0]
aln_fn = f'{cluster_number}.aln'
aln_fn_path = f'{aln_path}/{aln_fn}'
print(aln_fn_path)
mln_command = os.system(f'{clustalw2_path} -align -TYPE=PROTEIN -infile={fasta_fn_path} -outfile={aln_fn_path}')
print(f'Multialignment completed. Execution time {round((time.time() - start_time) / 60, 2)} min')
logging.info(f'Multialignment completed. Execution time {round((time.time() - start_time) / 60, 2)} min')
def aln_to_phylip(clusters_dir, ml_dir):
aln_path = f'{clusters_dir}/aln'
make_empty_folder(ml_dir)
for aln_fn in os.listdir(aln_path):
aln_fn_path = f'{aln_path}/{aln_fn}'
with open(aln_fn_path, 'r') as file:
filedata = file.read()
filedata = filedata.replace('_', ' ')
with open(aln_fn_path, 'w') as file:
file.write(filedata)
cluster_number = os.path.splitext(aln_fn)[0]
cluster_fn = f'{cluster_number}.phylip'
phylip_fn_path = f'{ml_dir}/{cluster_fn}'
seqret_command = os.system(f'seqret -sequence aln::{aln_fn_path} -outseq phylip::{phylip_fn_path}')
def calculate_ml_trees(bootstrap, ml_dir):
logging.info('Calculating ML trees with parameters phyml -i -d aa -m LG -b 0 -c 4 --run_id=lg')
start_time = time.time()
for phylip_fn in os.listdir(ml_dir):
phylip_fn_path = f'{ml_dir}/{phylip_fn}'
phyml_command = os.system(f'phyml -i {phylip_fn_path} -d aa -m LG -b {bootstrap} -c 4 --run_id=lg')
logging.info(f'ML trees calculated. Execution time {round((time.time() - start_time) / 60, 2)} min')
def calculate_gene_trees_ml(bootstrap, protein_id_to_sequence_dict, args):
setup_logging(args.approach)
cluster_to_fasta(f'{clusters_dir}/cluster_{args.approach}', protein_id_to_sequence_dict)
calculate_multialignment_for_cluster(f'{clusters_dir}/cluster_{args.approach}')
aln_to_phylip(f'{clusters_dir}/cluster_{args.approach}', f'{clusters_dir}/cluster_{args.approach}/ml')
calculate_ml_trees(bootstrap, f'{clusters_dir}/cluster_{args.approach}/ml')
# Stage 3
def calculate_constenus_tree(ml_dir, name):
make_empty_folder(f'./data/consensus')
newicks = {}
for fn in os.listdir(ml_dir):
if fn.endswith('.phylip_phyml_tree_lg.txt'):
cluster = int(fn.split('.')[0])
with open(f'{ml_dir}/{fn}') as newick:
for line in newick:
line = line.rstrip()
newicks[cluster] = line
def read_newick(treedata):
handle = StringIO(treedata)
return Phylo.read(handle, "newick")
trees = [read_newick(newicks[key]) for key in newicks.keys()]
majority_tree = majority_consensus(trees, 0.5)
Phylo.write(majority_tree, f'./data/consensus/majority_consensus_{name}.newick', "newick")
def calculate_supertree(ml_trees_path):
all_trees_path = f'{ml_trees_path}/all_ml_trees.txt'
for fn in os.listdir(ml_trees_path):
if fn.endswith('.phylip_phyml_tree_lg.txt'):
with open(all_trees_path, 'a') as outfile:
with open(f'{ml_trees_path}/{fn}', 'r') as infile:
for line in infile:
outfile.write(line)
os.system(f'./tools/fasturec32bit/fasturec -G {all_trees_path} -Y -r10 -k1 -j10')
def select_best_supertree(supertrees_path, name, number):
with open(supertrees_path, 'r') as f:
number = number - 1
best = f.readlines()
best = best[number]
score_and_tree = best.split()
score = score_and_tree[0]
tree = score_and_tree[1]
with open(f'./best_supertree_{name}_score{score}.txt', 'w') as infile:
infile.write(tree)
def visualize_newick(path):
tree = Phylo.read(path, "newick")
tree.ladderize() # Flip branches so deeper clades are displayed at top
Phylo.draw(tree)
def bootstrap_supertree(ml_trees_path, cutoff):
cutoff = int(cutoff)
all_trees_path = f'{ml_trees_path}/all_ml_trees.txt'
for fn in os.listdir(ml_trees_path):
if fn.endswith('.phylip_phyml_tree_lg.txt'):
with open(all_trees_path, 'a') as outfile:
with open(f'{ml_trees_path}/{fn}', 'r') as infile:
for line in infile:
bootstrap_support = [x for x in re.findall(r'\)(.*?)\:', str(line))]
bootstrap_support = list(map(int, bootstrap_support))
if all(i >= cutoff for i in bootstrap_support):
without_branch_support = re.sub(r'(?<=\)).+?(?=\:)', '', str(line))
outfile.write(without_branch_support)
os.system(f'./tools/fasturec32bit/fasturec -G {all_trees_path} -Y -r10 -k1 -j10' | {"/main.py": ["/phylogenetic_pipeline.py"]} |
46,659 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/migrations/0003_contacto.py | # Generated by Django 3.1.2 on 2020-11-01 21:33
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Menu', '0002_auto_20201026_2333'),
]
operations = [
migrations.CreateModel(
name='Contacto',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('email', models.EmailField(max_length=254)),
('nombre', models.CharField(max_length=100)),
('apellido', models.CharField(max_length=100)),
('fono', models.IntegerField()),
('direccion', models.CharField(max_length=100)),
('fecha', models.DateField()),
('motivo', models.CharField(choices=[('VentadePizzas', 'Freshman'), ('EventosCorporativos', 'Sophomore'), ('Alianzas', 'Junior'), ('ProblemasConTuPedido', 'Senior'), ('Comentarios', 'Graduate')], max_length=100)),
],
),
]
| {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,660 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/migrations/0002_auto_20201026_2333.py | # Generated by Django 3.1.2 on 2020-10-27 02:33
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Menu', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='menu',
name='precio',
field=models.IntegerField(blank=True, default=1, null=True),
),
]
| {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,661 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/forms.py | from django import forms
from .models import Contacto
class Peticiones(forms.Form):
nombre = forms.CharField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
Direccion = forms.CharField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
Apellido =forms.CharField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
fono = forms.IntegerField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
email = forms.EmailField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
fecha = forms.DateField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
motivo = forms.CharField(required=True, max_length=100, widget=forms.TextInput(
attrs = {
'class':'form-control p-4'
}
))
| {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,662 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/views.py | from django.shortcuts import render, get_object_or_404, redirect
from . models import Menu,Contacto
from django.views import generic
from django.http import HttpResponse
# Create your views here.
def index(request):
num = Menu.objects.all()
return render(
request,
'index.html',
context={'num':num}
)
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.urls import reverse_lazy
class PizzaDetalles(generic.DetailView):
model = Menu
def contacto(request):
if request.method=="POST":
contacto=Contacto()
nombre=request.POST.get('nombre')
email=request.POST.get('email')
apellido=request.POST.get('apellido')
fono=request.POST.get('fono')
direccion=request.POST.get('direccion')
fecha=request.POST.get('fecha')
motivo=request.POST.get('motivo')
contacto.nombre=nombre
contacto.email=email
contacto.apellido=apellido
contacto.fono=fono
contacto.direccion=direccion
contacto.motivo=motivo
contacto.save()
return HttpResponse("<h1>GRACIAS POR CONTACTARNOS</h1>")
return render(request,'Contacto.html')
def sobre_nosotros(request):
return render(request,'Sobre_Nosotros.html') | {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,663 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/migrations/0001_initial.py | # Generated by Django 3.1.2 on 2020-10-27 02:27
from django.db import migrations, models
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Menu',
fields=[
('id', models.UUIDField(default=uuid.uuid4, primary_key=True, serialize=False)),
('promociones', models.CharField(max_length=100, null=True)),
('acompañamientos', models.CharField(max_length=100, null=True)),
('bebidas', models.CharField(max_length=50, null=True)),
('precio', models.IntegerField(max_length=15, null=True)),
],
),
]
| {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,664 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/templates/test/test.py | from django.test import SimpleTestCase
from Menu.forms import Contacto
class testFormulario(SimpleTestCase):
def test_Contacto_valid_data(self):
form=Contacto(data={
'email':'uwuwuwu@ggmail.com'
'nombre':'el tunas'
'apellido':'el mufas'
'fono':'+569696969'
'direccion':'calle falsa 123'
'fecha':'01-11-2020'
'motivo':'Problemas con tu Pedido'
})
self.assertTrue(form.is_valid())
def test_Contacto_no_data(sellf):
form=Contacto(data={})
self.assertFalse(form.is_valid())
self.assertEquals(len(form.errors),3) | {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,665 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/admin.py | from django.contrib import admin
from . models import Menu,Contacto
admin.site.register(Menu)
admin.site.register(Contacto)
| {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,666 | Javihmc49/-Fase2RiosUrzuaEscobarSeccion002 | refs/heads/main | /Fase_2/Menu/models.py | from django.db import models
from django.urls import reverse
import uuid
# Create your models here.
class Menu(models.Model):
id = models.UUIDField(primary_key=True, default=uuid.uuid4)
promociones=models.CharField(max_length=100, null=True)
acompañamientos=models.CharField(max_length=100, null=True)
bebidas=models.CharField(max_length=50, null=True)
precio=models.IntegerField(default=1, blank=True, null=True )
def get_absolute_url(self):
return reverse('pizza-detail', args=[str(self.id)])
def __str__(self):
return self.promociones
class Contacto(models.Model):
email=models.EmailField()
nombre=models.CharField(max_length=100)
apellido=models.CharField(max_length=100)
fono=models.IntegerField()
direccion=models.CharField(max_length=100)
fecha=models.DateField(auto_now=True)
motivo_cotacto=[
('VentadePizzas', 'Freshman'),
('EventosCorporativos', 'Sophomore'),
('Alianzas', 'Junior'),
('ProblemasConTuPedido', 'Senior'),
('Comentarios', 'Graduate'),
]
motivo=models.CharField(max_length=100, choices=motivo_cotacto)
def __str__(self):
return self.nombre, self.apellido | {"/Fase_2/Menu/forms.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/views.py": ["/Fase_2/Menu/models.py"], "/Fase_2/Menu/admin.py": ["/Fase_2/Menu/models.py"]} |
46,670 | GoodManWEN/ComparePictureOnline | refs/heads/master | /test/__init__.py | __all__ = ['testing']
from .testing import pic1 , pic2 | {"/test/__init__.py": ["/test/testing.py"], "/app.py": ["/test/__init__.py"]} |
46,671 | GoodManWEN/ComparePictureOnline | refs/heads/master | /test/testing.py | from flask import Response
from functools import partial
from functools import update_wrapper
# solve partial not copy '__name__' property problem
from os import getcwd , path
def testpics(imgPath):
print(imgPath ,'called')
with open(imgPath, 'rb') as f:
image = f.read()
return Response(image , mimetype='image/jpeg')
def testpics2():
# avoid overwriting an existing endpoint function: testpics in flask
pass
if __name__ == 'test.testing':
cwd = getcwd()
pic1 = partial(testpics ,path.join(cwd , 'test/20191017163234957.jpg'))
update_wrapper(pic1, testpics)
pic2 = partial(testpics ,path.join(cwd , 'test/20191017163234957_2.jpg'))
update_wrapper(pic2, testpics2)
| {"/test/__init__.py": ["/test/testing.py"], "/app.py": ["/test/__init__.py"]} |
46,672 | GoodManWEN/ComparePictureOnline | refs/heads/master | /app.py | from flask import Flask
from flask import render_template, request ,abort
from flask_cors import CORS
app = Flask(__name__)
CORS(app, supports_credentials=True)
@app.route('/app' ,methods=['GET'])
def index():
try:
url1 = request.args.get("url1")
url2 = request.args.get("url2")
if url1 is None or url2 is None:
return 'Usage: compare.nazorip.site/app?url1=[PICTURE1_WEB_ADDR]&url2=[PICTURE2_WEB_ADDR]'
url1 , url2 = str(url1) , str(url2)
except:
abort(404);return
return render_template("index.html" ,pic_url1 = url1 , pic_url2 = url2)
if __name__ == '__main__':
debug = True
if debug:
from test import pic1 , pic2
pic1 = app.route('/pic1.jpg')(pic1)
pic2 = app.route('/pic2.jpg')(pic2)
app.run(port='5441',debug=debug)
| {"/test/__init__.py": ["/test/testing.py"], "/app.py": ["/test/__init__.py"]} |
46,676 | pynucastro/pynucastro | refs/heads/main | /pynucastro/reduction/__init__.py | """Routines for nuclear reaction network reduction."""
from .drgep import drgep
from .reduction_utils import FailedMPIImport, mpi_importer, mpi_numpy_decomp
from .sensitivity_analysis import binary_search_trim, sens_analysis
| {"/pynucastro/reduction/__init__.py": ["/pynucastro/reduction/drgep.py", "/pynucastro/reduction/reduction_utils.py", "/pynucastro/reduction/sensitivity_analysis.py"], "/pynucastro/networks/tests/_python_reference/network.py": ["/pynucastro/rates/__init__.py", "/pynucastro/screening/__init__.py", "/pynucastro/__init__.py"], "/pynucastro/networks/tests/test_screening.py": ["/pynucastro/__init__.py", "/pynucastro/screening/__init__.py"], "/pynucastro/nucdata/PartitionFunction/convert_rathpf_2000.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/networks/tests/test_python_net2.py": ["/pynucastro/__init__.py"], "/pynucastro/networks/tests/test_approx_screening.py": ["/pynucastro/__init__.py"], "/pynucastro/networks/python_network.py": ["/pynucastro/networks/rate_collection.py", "/pynucastro/rates/rate.py"], "/pynucastro/rates/library.py": ["/pynucastro/nucdata/__init__.py", "/pynucastro/rates/rate.py"], "/pynucastro/rates/tests/test_library.py": ["/pynucastro/__init__.py"], "/pynucastro/nucdata/__init__.py": ["/pynucastro/nucdata/binding_table.py", "/pynucastro/nucdata/elements.py", "/pynucastro/nucdata/mass_table.py", "/pynucastro/nucdata/nucleus.py", "/pynucastro/nucdata/partition_function.py", "/pynucastro/nucdata/spin_table.py"], "/logo/logo_base.py": ["/pynucastro/__init__.py"], "/examples/triple-alpha/triple-alpha.py": ["/pynucastro/networks/__init__.py"], "/pynucastro/networks/tests/test_full_python_net.py": ["/pynucastro/__init__.py"], "/examples/rp-process/rp_process.py": ["/pynucastro/rates/__init__.py", "/pynucastro/nucdata/__init__.py", "/pynucastro/networks/__init__.py"], "/pynucastro/rates/tests/conftest.py": ["/pynucastro/networks/tests/conftest.py"], "/pynucastro/networks/base_cxx_network.py": ["/pynucastro/networks/rate_collection.py", "/pynucastro/networks/sympy_network_support.py"], "/pynucastro/networks/tests/conftest.py": ["/pynucastro/__init__.py"], "/pynucastro/rates/tests/test_ratefilter.py": ["/pynucastro/__init__.py"], "/pynucastro/screening/tests/test_screen.py": ["/pynucastro/__init__.py", "/pynucastro/screening/__init__.py"], "/pynucastro/nucdata/tests/test_partition.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/screening/screen.py": ["/pynucastro/rates/rate.py"], "/pynucastro/networks/simple_cxx_network.py": ["/pynucastro/networks/base_cxx_network.py"], "/pynucastro/__init__.py": ["/pynucastro/screening/__init__.py", "/pynucastro/networks/__init__.py", "/pynucastro/nucdata/__init__.py", "/pynucastro/rates/__init__.py"], "/pynucastro/reduction/generate_data.py": ["/pynucastro/__init__.py", "/pynucastro/reduction/load_network.py"], "/pynucastro/nucdata/tests/test_nucleus.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/nucdata/PartitionFunction/convert_rathpf_2003.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/nucdata/nucleus.py": ["/pynucastro/nucdata/binding_table.py", "/pynucastro/nucdata/elements.py", "/pynucastro/nucdata/mass_table.py", "/pynucastro/nucdata/partition_function.py", "/pynucastro/nucdata/spin_table.py"], "/pynucastro/networks/tests/test_validate.py": ["/pynucastro/__init__.py"], "/pynucastro/networks/__init__.py": ["/pynucastro/networks/amrexastro_cxx_network.py", "/pynucastro/networks/base_cxx_network.py", "/pynucastro/networks/python_network.py", "/pynucastro/networks/rate_collection.py", "/pynucastro/networks/simple_cxx_network.py", "/pynucastro/networks/sympy_network_support.py"], "/pynucastro/rates/tests/test_jacobian_term.py": ["/pynucastro/networks/__init__.py", "/pynucastro/nucdata/__init__.py"], "/pynucastro/networks/tests/test_nse.py": ["/pynucastro/__init__.py"], "/pynucastro/reduction/load_network.py": ["/pynucastro/networks/__init__.py", "/pynucastro/nucdata/__init__.py", "/pynucastro/rates/__init__.py"], "/pynucastro/rates/tests/test_approx_rate.py": ["/pynucastro/__init__.py"], "/pynucastro/reduction/drgep.py": ["/pynucastro/reduction/reduction_utils.py"], "/pynucastro/networks/sympy_network_support.py": ["/pynucastro/rates/__init__.py"], "/pynucastro/rates/tests/test_rates.py": ["/pynucastro/__init__.py", "/pynucastro/nucdata/__init__.py"], "/pynucastro/networks/tests/test_dupes.py": ["/pynucastro/__init__.py"], "/.github/workflows/simple_cxx_network/test_simple_cxx.py": ["/pynucastro/__init__.py"], "/pynucastro/screening/__init__.py": ["/pynucastro/screening/screen.py"], "/pynucastro/networks/tests/test_python_net.py": ["/pynucastro/__init__.py"], "/examples/CNO/cno.py": ["/pynucastro/networks/__init__.py"], "/pynucastro/networks/rate_collection.py": ["/pynucastro/nucdata/__init__.py", "/pynucastro/rates/__init__.py", "/pynucastro/rates/library.py", "/pynucastro/screening/__init__.py", "/pynucastro/screening/screen.py"], "/pynucastro/nucdata/tests/test_spin.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/networks/tests/test_rc_jacobian.py": ["/pynucastro/__init__.py"], "/pynucastro/networks/tests/test_cxx_amrexastro_approx_net.py": ["/pynucastro/__init__.py", "/pynucastro/networks/tests/helpers.py"], "/pynucastro/nucdata/tests/test_mass.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/reduction/sensitivity_analysis.py": ["/pynucastro/reduction/reduction_utils.py"], "/pynucastro/networks/tests/test_approx_python_net.py": ["/pynucastro/__init__.py", "/pynucastro/screening/__init__.py"], "/pynucastro/rates/__init__.py": ["/pynucastro/rates/library.py", "/pynucastro/rates/rate.py"], "/pynucastro/networks/tests/test_cxx_amrexastro_net.py": ["/pynucastro/__init__.py", "/pynucastro/networks/tests/helpers.py"], "/pynucastro/networks/tests/test_simple_cxx_net.py": ["/pynucastro/__init__.py", "/pynucastro/networks/tests/helpers.py"], "/pynucastro/networks/tests/test_rate_collection.py": ["/pynucastro/__init__.py"], "/examples/triple-alpha/triple-alpha-cxx.py": ["/pynucastro/networks/__init__.py"], "/pynucastro/networks/amrexastro_cxx_network.py": ["/pynucastro/networks/base_cxx_network.py", "/pynucastro/nucdata/__init__.py", "/pynucastro/rates/__init__.py"], "/pynucastro/nucdata/tests/test_binding.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/rates/rate.py": ["/pynucastro/nucdata/__init__.py"], "/pynucastro/networks/tests/test_python_partition_functions.py": ["/pynucastro/__init__.py"], "/pynucastro/networks/tests/test_networks.py": ["/pynucastro/__init__.py", "/pynucastro/nucdata/__init__.py"], "/pynucastro/reduction/reduction.py": ["/pynucastro/__init__.py", "/pynucastro/reduction/__init__.py", "/pynucastro/reduction/generate_data.py", "/pynucastro/reduction/load_network.py"], "/pynucastro/networks/tests/test_derived_network.py": ["/pynucastro/__init__.py"], "/pynucastro/networks/tests/test_cxx_amrexastro_derived_net.py": ["/pynucastro/__init__.py", "/pynucastro/networks/tests/helpers.py"]} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.