diff --git a/db.sqlite3 b/db.sqlite3
index 84a7f50e08912e8476c470186a338b42043db3fe..49efc9c42bba66b81ac13a41bfbcfffeeaa2429c 100644
Binary files a/db.sqlite3 and b/db.sqlite3 differ
diff --git a/imagedb/models.py b/imagedb/models.py
index a2a487e9023793342c7e6fa5ccf81f4502005292..06cc9da57a5d5be7ae38c6e44d1c8a87f7b91717 100644
--- a/imagedb/models.py
+++ b/imagedb/models.py
@@ -75,6 +75,9 @@ class ImageBaseFrame(models.Model):
class Instrument(models.Model):
instrumentName = models.CharField(max_length=100)
telescopeName = models.CharField(max_length=100)
+
+ class Meta:
+ unique_together = (('instrumentName', 'telescopeName'))
class Pointing(CompositeField):
@@ -114,6 +117,8 @@ class NispDetector(models.Model):
rawFrame = models.ForeignKey('NispRawFrame',
related_name='detectors',
on_delete=models.CASCADE)
+ class Meta:
+ unique_together = (('detectorId', 'rawFrame'))
WCS_COORDINATE_TYPE = (
diff --git a/imagedb_objects.ipynb b/imagedb_objects.ipynb
index 6dff79e4a64000ab7faa3ed81efac85ab24ccfa5..2a2f3ea0aa0825d1fa5138260c90677098f04bdb 100644
--- a/imagedb_objects.ipynb
+++ b/imagedb_objects.ipynb
@@ -1,14 +1,12 @@
{
"cells": [
{
- "cell_type": "code",
- "execution_count": 1,
+ "cell_type": "markdown",
"metadata": {},
- "outputs": [],
"source": [
- "from imagedb.models import Instrument\n",
+ "## Data insertion and retrieval with Django models\n",
"\n",
- "instrument = Instrument.objects.get(instrumentName='NISP')\n"
+ "In the following we show some examples in order to perform insertions and retrievals of metadata "
]
},
{
@@ -20,24 +18,37 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "NISP\n"
+ "Euclid\n"
]
}
],
"source": [
- "print(instrument.instrumentName)"
+ "from imagedb.models import Instrument\n",
+ "\n",
+ "instrument = Instrument.objects.get(instrumentName='NISP')\n",
+ "\n",
+ "print(instrument.telescopeName)\n"
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
- "from imagedb.models import ImageType, Pointing, NispDetector, NispRawFrame\n",
+ "from imagedb.models import ImageType, Pointing, NispDetector, DataContainer, NispRawFrame\n",
"\n",
"from datetime import datetime\n",
- " \n",
+ "\n",
+ "dataFile = DataContainer(\n",
+ " fileFormat = 'fits',\n",
+ " formatIdentifier = 'le1.nisprawframe',\n",
+ " formatVersion = '1.0',\n",
+ " url = \"http://ia2-ownclud.oats.inaf.it/fake/7ff2f203/data/EUC_LE1_NISP_53892-Y-1_20170712T155430.1Z_00.00.fits\"\n",
+ ")\n",
+ "\n",
+ "# We have to save the data container to the DB before assigning it to a NispRawFrame\n",
+ "dataFile.save()\n",
"\n",
"image = NispRawFrame(exposureTime = 105,\n",
" imgNumber = 16,\n",
@@ -48,72 +59,121 @@
" 'secondType':'STD'},\n",
" observationDateTime = datetime.strptime(\"2025-06-21T18:27:23.000001\", \n",
" \"%Y-%m-%dT%H:%M:%S.%f\"),\n",
+ " observationId = 53892,\n",
+ " ditherNumber = 1,\n",
" instrument = instrument,\n",
" commandedPointing = {'rightAscension':8.48223045516,\n",
" 'declination':8.48223045516,\n",
- " 'pointingAngle':64.8793517547},\n",
+ " 'orientation':64.8793517547},\n",
" filterWheelPosition = \"Y\",\n",
" grismWheelPosition = \"OPEN\"\n",
- " )\n"
+ " )\n",
+ "\n",
+ "\n",
+ "\n",
+ "image.frameFile = dataFile"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 19,
"metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "None\n",
+ "3\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(image.id)\n",
+ "image.save()\n",
+ "print(image.id)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {
+ "scrolled": true
+ },
"outputs": [
{
"data": {
"text/plain": [
- "Pointing(rightAscension=8.48223045516, declination=8.48223045516, pointingAngle=64.8793517547)"
+ "<NispDetector: NispDetector object (4)>"
]
},
- "execution_count": 4,
+ "execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "image.commandedPointing"
+ "# We can start creating a detector\n",
+ "\n",
+ "d11 = NispDetector(detectorId = \"11\", gain = 1.0, readoutNoise = 0.0, rawFrame = image)\n",
+ "d11.save()\n",
+ "\n",
+ "# or we can create the detector starting from the NispRawFrame, using the reversed relationship.\n",
+ "# No need to save the detector in this case. It is done automatically\n",
+ "\n",
+ "image.detectors.create(\n",
+ " detectorId = \"12\",\n",
+ " gain = 1.0,\n",
+ " readoutNoise = 0.0\n",
+ ")"
]
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "8.48223045516"
+ "<QuerySet [<NispDetector: NispDetector object (1)>, <NispDetector: NispDetector object (2)>]>"
]
},
- "execution_count": 5,
+ "execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "image.commandedPointing.rightAscension"
+ "image.detectors.all()"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 27,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<QuerySet [<NispDetector: NispDetector object (1)>]>"
+ ]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "image = NispRawFrame.objects.filter(commandedPointing_rightAscension__lte=8.48223045516)[0]"
+ "image.detectors.all()"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"metadata": {},
"outputs": [],
- "source": [
- "d = NispDetector(detectorId = \"11\", gain = 1.0, readoutNoise = 0.0, rawFrame = image)"
- ]
+ "source": []
}
],
"metadata": {
@@ -132,7 +192,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.3"
+ "version": "3.7.0"
}
},
"nbformat": 4,
diff --git a/orm_example/settings.py b/orm_example/settings.py
index c651d61c07f8e7dbba34a9a3e2e716f1efbed291..d9fde8da3999e3f28da647394078cff9d88a94b9 100644
--- a/orm_example/settings.py
+++ b/orm_example/settings.py
@@ -121,7 +121,7 @@ USE_I18N = True
USE_L10N = True
-USE_TZ = True
+USE_TZ = False
# Static files (CSS, JavaScript, Images)