BPM improved

megaradrp/recipes/calibration/tests/test_bpm.py

@@ -26,28 +26,12 @@
 import pytest
 from numina.core import DataFrame, ObservationResult
 
-from megaradrp.tests.simulation import simulate_flat, simulate_bias
+from megaradrp.tests.simulation import simulate_flat
 from megaradrp.tests.simulation import ReadParams, MegaraDetectorSat
 from megaradrp.recipes.calibration.bpm import BadPixelsMaskRecipe
-from megaradrp.recipes.calibration.bias import BiasRecipe
 
+from megaradrp.recipes.calibration.tests.test_bpm_common import generate_bias
 
-def generate_bias(detector, number, temporary_path):
-    fs = [simulate_bias(detector) for i in range(number)]
-    for aux in range(len(fs)):
-        fits.writeto('%s/bias_%s.fits' % (temporary_path, aux), fs[aux],
-                     clobber=True)
-
-    fs = ["%s/bias_%s.fits" % (temporary_path, i) for i in range(number)]
-
-    ob = ObservationResult()
-    ob.instrument = 'MEGARA'
-    ob.mode = 'bias_image'
-    ob.frames = [DataFrame(filename=f) for f in fs]
-
-    recipe = BiasRecipe()
-    ri = recipe.create_input(obresult=ob)
-    return recipe.run(ri)
 
 # @pytest.mark.remote
 def test_bpm():
@@ -56,11 +40,6 @@ def test_bpm():
     DSHAPE = (2056 * 2, 2048 * 2)
     OSCAN = 50
 
-    BINR = 1
-    BINC = 1
-
-    SHAPE = DSHAPE[0] // BINR, DSHAPE[1] // BINC
-
     ron = 2.0
     gain = 1.0
     bias = 1000.0

megaradrp/recipes/calibration/tests/test_bpm_common.py

@@ -0,0 +1,102 @@
+#
+# Copyright 2015 Universidad Complutense de Madrid
+#
+# This file is part of Megara DRP
+#
+# Megara DRP is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# Megara DRP is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with Megara DRP.  If not, see <http://www.gnu.org/licenses/>.
+#
+
+"""Tests for the bpm mode recipe module."""
+
+from numina.core import DataFrame, ObservationResult
+import astropy.io.fits as fits
+import numpy as np
+
+
+def generate_bias(detector, number, temporary_path):
+    from megaradrp.tests.simulation import simulate_bias
+    from megaradrp.recipes.calibration.bias import BiasRecipe
+
+    fs = [simulate_bias(detector) for i in range(number)]
+    for aux in range(len(fs)):
+        fits.writeto('%s/bias_%s.fits' % (temporary_path, aux), fs[aux],
+                     clobber=True)
+
+    fs = ["%s/bias_%s.fits" % (temporary_path, i) for i in range(number)]
+
+    ob = ObservationResult()
+    ob.instrument = 'MEGARA'
+    ob.mode = 'bias_image'
+    ob.frames = [DataFrame(filename=f) for f in fs]
+
+    recipe = BiasRecipe()
+    ri = recipe.create_input(obresult=ob)
+    return recipe.run(ri)
+
+def crear_archivos(temporary_path):
+    from megaradrp.tests.simulation import simulate_flat
+    from megaradrp.tests.simulation import ReadParams, MegaraDetectorSat
+    from megaradrp.recipes.calibration.bpm import BadPixelsMaskRecipe
+
+    number = 5
+    PSCAN = 50
+    DSHAPE = (2056 * 2, 2048 * 2)
+    OSCAN = 50
+    ron = 2.0
+    gain = 1.0
+    bias = 1000.0
+
+    eq = 0.8 * np.ones(DSHAPE)
+    eq[0:15, 0:170] = 0.0
+
+    readpars1 = ReadParams(gain=gain, ron=ron, bias=bias)
+    readpars2 = ReadParams(gain=gain, ron=ron, bias=bias)
+
+    detector = MegaraDetectorSat(DSHAPE, OSCAN, PSCAN, eq=eq,
+                                 dark=(3.0 / 3600.0),
+                                 readpars1=readpars1, readpars2=readpars2,
+                                 bins='11')
+
+    source2 = 1.0
+
+    fs = [simulate_flat(detector, exposure=1.0, source=5000 * source2) for i in
+          range(number)]
+
+    for aux in range(len(fs)):
+        fits.writeto('%s/flat_%s.fits' % (temporary_path, aux), fs[aux],
+                     clobber=True)
+
+    master_bias = generate_bias(detector, number, temporary_path)
+    master_bias_data = master_bias.biasframe.frame[0].data
+
+    fits.writeto('%s/master_bias_data0.fits' % temporary_path,
+                 master_bias_data, clobber=True)  # Master Bias
+
+    ob = ObservationResult()
+    ob.instrument = 'MEGARA'
+    ob.mode = 'bias_image'
+    names = []
+
+    for aux in range(number):
+        names.append('%s/flat_%s.fits' % (temporary_path, aux))
+    ob.frames = [DataFrame(filename=open(nombre).name) for nombre in names]
+
+    recipe = BadPixelsMaskRecipe()
+    ri = recipe.create_input(obresult=ob, master_bias=DataFrame(
+        filename=open(temporary_path + '/master_bias_data0.fits').name))
+    aux = recipe.run(ri)
+    fits.writeto('%s/master_bpm.fits' % temporary_path, aux.bpm_image.frame[0].data[1], clobber=True)
+
+    return names
+

megaradrp/recipes/calibration/tests/test_bpm_corrector.py

@@ -21,22 +21,22 @@
 
 from numina.core import DataFrame, ObservationResult
 import astropy.io.fits as fits
-import numpy as np
-import os
 from numina.core.requirements import ObservationResultRequirement
 from numina.flow.processing import BadPixelCorrector
 
 from megaradrp.core.recipe import MegaraBaseRecipe
 from megaradrp.requirements import MasterBiasRequirement, MasterBPMRequirement
 from megaradrp.processing.trimover import OverscanCorrector, TrimImage
 
+from megaradrp.recipes.calibration.tests.test_bpm_common import crear_archivos
 
 class TestRecipe(MegaraBaseRecipe):
     obresult = ObservationResultRequirement()
     master_bias = MasterBiasRequirement()
     master_bpm = MasterBPMRequirement()
 
-    def __init__(self):
+    def __init__(self, directorio):
+        self.directorio = directorio
         super(TestRecipe, self).__init__(version="0.1.0")
         self._MegaraBaseRecipe__flow['TestRecipe'] = [OverscanCorrector,
                                                       TrimImage,
@@ -45,8 +45,6 @@ def __init__(self):
     def run(self, rinput):
         import copy
 
-        directorio = os.path.dirname(os.path.abspath(__file__))
-
         N = len(rinput.obresult.frames)
         obresult1 = copy.copy(rinput.obresult)
         obresult1.frames = rinput.obresult.frames[:N]
@@ -59,7 +57,8 @@ def run(self, rinput):
         params['biasmap'] = mbias
 
         reduced1 = self.bias_process_common(obresult1, params)
-        fits.writeto(directorio + '/tmp2/reduced_flat.fits', reduced1[0].data, clobber=True)
+        fits.writeto(self.directorio + '/reduced_flat.fits', reduced1[0].data,
+                     clobber=True)
 
         try:
             with rinput.master_bpm.open() as hdul:
@@ -69,37 +68,32 @@ def run(self, rinput):
             pass
 
         reduced1 = self.bias_process_common(obresult1, params)
-        fits.writeto(directorio + '/tmp2/reduced_flat_bpm.fits', reduced1[0].data, clobber=True)
+        fits.writeto(self.directorio + '/reduced_flat_bpm.fits',
+                     reduced1[0].data, clobber=True)
 
         return True
 
 
 def test_bpm_corrector():
-    number = 5
-    DSHAPE = (2056 * 2, 2048 * 2)
+    import shutil
+    from tempfile import mkdtemp
 
-    eq = 0.8 * np.ones(DSHAPE)
-    eq[0:15, 0:170] = 0.0
+    directorio = mkdtemp()
+    names = crear_archivos(directorio)
 
     ob = ObservationResult()
     ob.instrument = 'MEGARA'
     ob.mode = 'bias_image'
-    names = []
-
-    directorio = os.path.dirname(os.path.abspath(__file__))
-
-    for aux in range(number):
-        names.append('%s/tmp2/flat_%s.fits' % (directorio,aux))
     ob.frames = [DataFrame(filename=open(nombre).name) for nombre in names]
 
-    recipe = TestRecipe()
+    recipe = TestRecipe(directorio)
     ri = recipe.create_input(obresult=ob, master_bias=DataFrame(
-        filename=open(directorio + '/tmp2/master_bias_data0.fits').name),
+        filename=open(directorio + '/master_bias_data0.fits').name),
                              master_bpm=DataFrame(filename=open(
-                                 directorio+ '/tmp2/master_bpm.fits').name))
+                                 directorio + '/master_bpm.fits').name))
 
     recipe.run(ri)
-
+    shutil.rmtree(directorio)
 
 if __name__ == "__main__":
     test_bpm_corrector()