Add plot command line option and method for projections

eos/normalization.py

@@ -26,7 +26,6 @@ class LZNormalisation:
         norm_lz, _, _ = np.histogram2d(lamda_e, detZ_e, bins=(grid.lamda(), grid.z()))
         norm_lz = np.where(norm_lz>2, norm_lz, np.nan)
         if normalisationMethod==NormalisationMethod.direct_beam:
-            # TODO: move flipping to projection
             self.norm = np.flip(norm_lz, 1)
         else:
             # correct for reference sm reflectivity

eos/options.py

@@ -434,6 +434,13 @@ class OutputFomatOption(StrEnum):
     Rlt = "Rlt"
 
 
+class PlotColormaps(StrEnum):
+    gist_ncar = "gist_ncar"
+    viridis = "viridis"
+    inferno = "inferno"
+    gist_rainbow = "gist_rainbow"
+    nipy_spectral = "nipy_spectral"
+
 @dataclass
 class OutputConfig(ArgParsable):
     outputFormats: List[OutputFomatOption] = field(
@@ -460,6 +467,22 @@ class OutputConfig(ArgParsable):
                 'help': '?',
                 },
             )
+    plot: bool = field(
+            default=False,
+            metadata={
+                'group': 'output',
+                'help': 'show matplotlib graphs of results',
+                },
+            )
+
+    plot_colormap: PlotColormaps = field(
+            default=PlotColormaps.gist_ncar,
+            metadata={
+                'short': 'pcmap',
+                'group': 'output',
+                'help': 'matplotlib colormap used in lambda-theta graphs when plotting',
+                },
+            )
 
     def _output_format_list(self, outputFormat):
         format_list = []
@@ -531,7 +554,7 @@ class EOSConfig:
             otpt += f' -of {" ".join(self.output.outputFormats)}'
             
         mask = ''
-        # TODO: Check if you want these parameters for the case of default call
+
         mask += f' -y {" ".join(str(ii) for ii in self.experiment.yRange)}'
         mask += f' -l {" ".join(str(ff) for ff in self.experiment.lambdaRange)}'
         mask += f' -t {" ".join(str(ff) for ff in self.reduction.thetaRange)}'

eos/projection.py

@@ -8,7 +8,7 @@ from dataclasses import dataclass
 
 from .event_data_types import EventDatasetProtocol
 from .instrument import Detector, LZGrid
-from .normalisation import LZNormalisation
+from .normalization import LZNormalisation
 
 @dataclass
 class ProjectedReflectivity:
@@ -68,6 +68,13 @@ class ProjectedReflectivity:
         self.R -= R
         self.dR = np.sqrt(self.dR**2+dR**2)
 
+    def plot(self, **kwargs):
+        from matplotlib import pyplot as plt
+        plt.errorbar(self.Q, self.R, xerr=self.dQ, yerr=self.dR, **kwargs)
+        plt.yscale('log')
+        plt.xlabel('Q / $\\AA^{-1}$')
+        plt.ylabel('R')
+
 class LZProjection:
     grid: LZGrid
     lamda: np.ndarray
@@ -283,3 +290,28 @@ class LZProjection:
         right_list = cls.devide_bin(lambda_e[right_region], position_e[right_region],
                                               lamda_edges[split_idx:], dimension)
         return left_list+right_list
+
+    def plot(self, **kwargs):
+        from matplotlib import pyplot as plt
+        from matplotlib.colors import LogNorm
+
+        if 'colorbar' in kwargs:
+            cmap=True
+            del(kwargs['colorbar'])
+        else:
+            cmap=False
+
+        if self.is_normalized:
+            if not 'norm' in kwargs:
+                kwargs['norm'] = LogNorm(2e-3, 2.0)
+            plt.pcolormesh(self.lamda, self.alphaF, self.data.ref, **kwargs)
+            if cmap:
+                plt.colorbar(label='R')
+        else:
+            if not 'norm' in kwargs:
+                kwargs['norm'] = LogNorm()
+            plt.pcolormesh(self.lamda, self.alphaF, self.data.I, **kwargs)
+            if cmap:
+                plt.colorbar(label='I / cpm')
+        plt.xlabel('$\\lambda$ / $\\AA$')
+        plt.ylabel('$\\Theta$ / °')

eos/reduction.py

@@ -10,7 +10,7 @@ from .header import Header
 from .path_handling import PathResolver
 from .options import EOSConfig, IncidentAngle, MonitorType, NormalisationMethod
 from .instrument import Detector, LZGrid
-from .normalisation import LZNormalisation
+from .normalization import LZNormalisation
 from . import event_handling as eh, event_analysis as ea
 from .projection import LZProjection
 
@@ -113,6 +113,13 @@ class AmorReduction:
         if 'Rlt.ort' in self.output_config.outputFormats:
             self.save_Rtl()
 
+        if self.output_config.plot:
+            import matplotlib.pyplot as plt
+            if 'Rqz.ort' in self.output_config.outputFormats:
+                plt.figure(num=99)
+                plt.legend()
+            plt.show()
+
     def read_file_block(self, i, short_notation):
         logging.warning('reading input:')
         file_list = self.path_resolver.resolve(short_notation)
@@ -149,7 +156,7 @@ class AmorReduction:
 
         if self.reduction_config.timeSlize:
             if i>0:
-                logging.warning("    time slizing should only be used for on set of datafiles, check parameters")
+                logging.warning("    time slizing should only be used for one set of datafiles, check parameters")
             self.analyze_timeslices(i)
         else:
             self.analyze_unsliced(i)
@@ -188,6 +195,12 @@ class AmorReduction:
             orso_data = fileio.OrsoDataset(headerRqz, result.data)
             self.last_result = result
             self.datasetsRqz.append(orso_data)
+
+            if self.output_config.plot:
+                import matplotlib.pyplot as plt
+                # plot all reflectivity results in same graph
+                plt.figure(num=99)
+                result.plot(label=f'{self.reduction_config.fileIdentifier[i]}')
         if 'Rlt.ort' in self.output_config.outputFormats:
             columns = [
                 fileio.Column('Qz', '1/angstrom', 'normal momentum transfer'),
@@ -230,6 +243,12 @@ class AmorReduction:
                 self.datasetsRlt.append(orso_data)
                 j += 1
 
+            if self.output_config.plot:
+                import matplotlib.pyplot as plt
+                plt.figure()
+                proj.plot(colorbar=True, cmap=str(self.output_config.plot_colormap))
+                plt.title(f'{self.reduction_config.fileIdentifier[i]}')
+
     def analyze_timeslices(self, i):
         wallTime_e = np.float64(self.dataset.data.events.wallTime)/1e9
         pulseTimeS = np.float64(self.dataset.data.pulses.time)/1e9
@@ -283,6 +302,13 @@ class AmorReduction:
             headerRqz.data_set = f'{i}_{ti}: time = {time:8.1f} s  to {time+interval:8.1f} s'
             orso_data = fileio.OrsoDataset(headerRqz, result.data_for_time(time))
             self.datasetsRqz.append(orso_data)
+
+            if self.output_config.plot:
+                import matplotlib.pyplot as plt
+                # plot all reflectivity results in same graph
+                plt.figure(num=99)
+                result.plot(label=f'{self.reduction_config.fileIdentifier[i]} @ {time:.1f}s')
+
         self.last_result = result
         # reset normal logging behavior
         #logging.StreamHandler.terminator = "\n"

tests/test_full_analysis.py

@@ -7,7 +7,7 @@ from eos import options, reduction, logconfig
 logconfig.setup_logging()
 logconfig.update_loglevel(1)
 
-# TODO: add test for new features like proton charge normalization
+# TODO: add unit tests for individual parts of reduction
 
 class FullAmorTest(TestCase):
     @classmethod