merge of jvb master onto imageseries, with important bugfixes

Author: Joel Bernier

conda.recipe/meta.yaml

@@ -4,7 +4,7 @@ package:
   version: {{ environ.get('GIT_DESCRIBE_TAG', '')[1:] }}
 
 source:
-  git_url: ../
+  git_url: https://github.com/joelvbernier/hexrd.git
   git_tag: master # edit to point to specific branch or tag
 
 build:
@@ -20,21 +20,21 @@ app:
 
 requirements:
   build:
-    - numpy ==1.9.3
+    - numpy
     - python
     - setuptools
   run:
     - h5py
     - dill
     - matplotlib
     - numba
-    - numpy ==1.9.3
+    - numpy
     - progressbar >=2.3
     - python
     - python.app # [osx]
     - pyyaml
     - qtconsole
-    - scikit-learn ==0.15.2
+    - scikit-learn
     - scipy
     - wxpython
 

hexrd/__init__.py

@@ -72,7 +72,8 @@ def _readenv(name, ctor, default):
 del _readenv
 
 
-doc_url = 'latest' if 'dev' in __version__ else 'v%s' % __version__
+#doc_url = 'latest' if 'dev' in __version__ else 'v%s' % __version__
+doc_url = 'latest'
 doc_url = 'http://hexrd.readthedocs.org/en/%s' % doc_url
 
 

hexrd/cli/findorientations.py

@@ -79,8 +79,17 @@ def execute(args, parser):
     # load the configuration settings
     cfg = config.open(args.yml)[0]
 
+    # ...make this an attribute in cfg?
+    analysis_id = '%s_%s' %(
+        cfg.analysis_name.strip().replace(' ', '-'),
+        cfg.material.active.strip().replace(' ', '-'),
+        )
+    
     # prepare the analysis directory
-    quats_f = os.path.join(cfg.working_dir, 'accepted_orientations.dat')
+    quats_f = os.path.join(
+        cfg.working_dir,
+        'accepted_orientations_%s.dat' %analysis_id
+        )
     if os.path.exists(quats_f) and not (args.force or args.clean):
         logger.error(
             '%s already exists. Change yml file or specify "force" or "clean"', quats_f

hexrd/config/findorientations.py

@@ -69,7 +69,7 @@ class ClusteringConfig(Config):
     @property
     def algorithm(self):
         key = 'find_orientations:clustering:algorithm'
-        choices = ['dbscan', 'fclusterdata']
+        choices = ['dbscan', 'ort-dbscan', 'sph-dbscan', 'fclusterdata']
         temp = self._cfg.get(key, 'dbscan').lower()
         if temp in choices:
             return temp
@@ -164,9 +164,9 @@ def hkl_seeds(self):
         try:
             temp = self._cfg.get(key)
             if isinstance(temp, int):
-                temp = [temp]
+                temp = [temp,]
             return temp
-        except KeyError:
+        except:
             if self._cfg.find_orientations.use_quaternion_grid is None:
                 raise RuntimeError(
                     '"%s" must be defined for seeded search' % key

hexrd/config/fitgrains.py

@@ -95,6 +95,20 @@ def refit(self):
             return temp
 
 
+    """
+    PROBABLY JUST SCRAP THIS...s
+    """
+    @property
+    def skip_on_estimate(self):
+        key = 'fit_grains:skip_on_estimate'
+        temp = self._cfg.get(key, False)
+        if temp in (True, False):
+            return temp
+        raise RuntimeError(
+            '"%s" must be true or false, got "%s"' % (key, temp)
+            )
+
+
     @property
     def fit_only(self):
         key = 'fit_grains:fit_only'

hexrd/config/tests/test_find_orientations.py

@@ -28,7 +28,7 @@
     mask: 10
     tolerance: 2
   clustering:
-    algorithm: dbscan
+    algorithm: sph-dbscan
     completeness: 0.35
     radius: 1
 ---
@@ -128,7 +128,7 @@ def test_algorithm(self):
             )
         self.assertEqual(
             self.cfgs[1].find_orientations.clustering.algorithm,
-            'dbscan'
+            'sph-dbscan'
             )
         self.assertEqual(
             self.cfgs[2].find_orientations.clustering.algorithm,

hexrd/constants.py

@@ -30,43 +30,44 @@
 from scipy import constants as sc
 
 # pi related
-pi    = np.pi
+pi = np.pi
 piby2 = 0.5 * pi
 piby3 = pi / 3.
 piby4 = 0.25 * pi
 piby6 = pi / 6.
 
 # misc radicals
-sq2    = np.sqrt(2.)
-sq3    = np.sqrt(3.)
-sq3by2 = 0.5 * sq3
+sqrt2 = np.sqrt(2.)
+sqrt3 = np.sqrt(3.)
+sqrt3by2 = 0.5 * sqrt3
 
 # tolerancing
-epsf      = np.finfo(float).eps      # ~2.2e-16
-ten_epsf  = 10 * epsf                # ~2.2e-15
-sqrt_epsf = np.sqrt(epsf)            # ~1.5e-8
+epsf = np.finfo(float).eps      # ~2.2e-16
+ten_epsf = 10 * epsf            # ~2.2e-15
+sqrt_epsf = np.sqrt(epsf)       # ~1.5e-8
 
 # for angles
-periodDict = {'degrees': 360.0, 'radians': 2*pi}
-angularUnits = 'radians' # module-level angle units
-d2r = deg2rad = pi / 180.
-r2d = rad2deg = 180. / pi
+period_dict  = {'degrees': 360.0, 'radians': 2*pi}
+angular_units = 'radians' # module-level angle units
+d2r = pi / 180.
+r2d = 180. / pi
+
+# identity arrays
+identity_3x3 = np.eye(3) # (3, 3) identity
+identity_6x1 = np.r_[1., 1., 1., 0., 0., 0.]
 
 # basis vectors
-I3    = np.eye(3) # (3, 3) identity
-X = np.array(I3[:, 0].reshape(3, 1), order='C') # X in the lab frame
-Y = np.array(I3[:, 1].reshape(3, 1), order='C') # Y in the lab frame
-Z = np.array(I3[:, 2].reshape(3, 1), order='C') # Z in the lab frame
+lab_x = np.r_[1., 0., 0.] # X in the lab frame
+lab_y = np.r_[0., 1., 0.] # Y in the lab frame
+lab_z = np.r_[0., 0., 1.] # Z in the lab frame
 
+zeros_3   = np.zeros(3)
 zeros_3x1 = np.zeros((3, 1))
 zeros_6x1 = np.zeros((6, 1))
 
 # reference beam direction and eta=0 ref in LAB FRAME for standard geometry
-bVec = -Z
-eVec =  X
-
-# for strain
-vInv = np.array(np.r_[1., 1., 1., 0., 0., 0.].reshape(6, 1), order='C')
+beam_vec = -lab_z
+eta_vec = lab_x
 
 # for energy/wavelength conversions
-keVToAngstrom = lambda x: (1e7*sc.c*sc.h/sc.e) / x
+keVToAngstrom = lambda x: (1e7*sc.c*sc.h/sc.e) / float(x)

hexrd/coreutil.py

@@ -16,10 +16,10 @@
 from hexrd.xrd import experiment as expt
 from hexrd.xrd.transforms import makeDetectorRotMat, unitVector, vInv_ref
 from hexrd.xrd import transforms_CAPI as xfcapi
+from hexrd.xrd import distortion as dFuncs
 
 from hexrd.xrd.detector import ReadGE
 
-
 logger = logging.getLogger('hexrd')
 
 
@@ -195,3 +195,55 @@ def initialize_experiment(cfg):
         detector = None
 
     return pd, reader, detector
+
+def get_instrument_parameters(cfg):
+    # TODO: this needs to be
+    det_p = cfg.instrument.parameters
+    if not os.path.exists(det_p):
+        migrate_detector_to_instrument_config(
+            np.loadtxt(cfg.instrument.detector.parameters_old),
+            cfg.instrument.detector.pixels.rows,
+            cfg.instrument.detector.pixels.columns,
+            cfg.instrument.detector.pixels.size,
+            detID='GE',
+            chi=0.,
+            tVec_s=np.zeros(3),
+            filename=cfg.instrument.parameters
+            )
+    with open(cfg.instrument.parameters, 'r') as f:
+        # only one panel for now
+        # TODO: configurize this
+        return [cfg for cfg in yaml.load_all(f)][0]
+
+
+def get_detector_parameters(instr_cfg):
+    return np.hstack([
+        instr_cfg['detector']['transform']['tilt_angles'],
+        instr_cfg['detector']['transform']['t_vec_d'],
+        instr_cfg['oscillation_stage']['chi'],
+        instr_cfg['oscillation_stage']['t_vec_s'],
+        ])
+
+
+def get_distortion_correction(instrument_cfg):
+    # ***FIX***
+    # at this point we know we have a GE and hardwire the distortion func;
+    # need to pull name from yml file in general case
+    return (
+        dFuncs.GE_41RT,
+        instrument_cfg['detector']['distortion']['parameters']
+        )
+
+
+def get_saturation_level(instr_cfg):
+    return instr_cfg['detector']['saturation_level']
+
+
+def set_planedata_exclusions(cfg, detector, pd):
+    tth_max = cfg.fit_grains.tth_max
+    if tth_max is True:
+        pd.exclusions = np.zeros_like(pd.exclusions, dtype=bool)
+        pd.exclusions = pd.getTTh() > detector.getTThMax()
+    elif tth_max > 0:
+        pd.exclusions = np.zeros_like(pd.exclusions, dtype=bool)
+        pd.exclusions = pd.getTTh() >= np.radians(tth_max)