Merge pull request #115 from slaclab/run_lint_format_script

ENH: apply linting and formatting script's changes

calibrationSuite/ancillaryMethods.py

@@ -107,16 +107,14 @@ def getClusterEnergies(clusters):
     ##print(clusters)
     return clusters[:, 0]
 
+
 class Histogram_1d(object):
     def __init__(self, data=[], nBins=None, xRange=None):
         self.nBins = nBins
         self.xRange = xRange
         self.hist, edges = np.histogram(data, bins=self.nBins, range=self.xRange)
-        self.bins = (edges[:-1] + edges[1:]) / 2.
+        self.bins = (edges[:-1] + edges[1:]) / 2.0
 
     def fill(self, value):
         hist, _ = np.histogram([value], bins=self.nBins, range=self.xRange)
         self.hist += hist
-
-
-

calibrationSuite/basicSuiteScript.py

@@ -56,7 +56,7 @@ def __init__(self, analysisType="scan"):
             pass
         self.ROIfileNames = None
         try:
-        ##if True:
+            ##if True:
             self.ROIfileNames = self.experimentHash["ROIs"]
             self.ROIs = []
             for f in self.ROIfileNames:
@@ -66,7 +66,7 @@ def __init__(self, analysisType="scan"):
             except Exception:
                 pass
         ##if False:
-        except:
+        except Exception:
             if self.ROIfileNames is not None:
                 print("had trouble finding", self.ROIfileNames)
                 for currName in self.ROIfileNames:
@@ -94,7 +94,7 @@ def __init__(self, analysisType="scan"):
         if self.detectorInfo.dimension == 2:
             self.regionSlice = self.regionSlice[0], self.regionSlice[2]
             print("remapping regionSlice to handle 1d case")
-            
+
         try:
             self.fluxSource = self.experimentHash["fluxSource"]
             try:
@@ -110,8 +110,8 @@ def __init__(self, analysisType="scan"):
 
         try:
             self.ignoreEventCodeCheck = self.experimentHash["ignoreEventCodeCheck"]
-            self.fakeBeamCode = True ## just in case
-        except:
+            self.fakeBeamCode = True  ## just in case
+        except Exception:
             self.ignoreEventCodeCheck = False
             self.fakeBeamCode = False
 
@@ -124,13 +124,12 @@ def __init__(self, analysisType="scan"):
         self.daqCode = 281
         self.beamCode = 283  ## per Matt
         ##self.beamCode = 281 ## don't see 283...
-        if not self.fakeBeamCode: ## defined in ignoreEventCodeCheck
+        if not self.fakeBeamCode:  ## defined in ignoreEventCodeCheck
             if self.special is not None:
                 self.fakeBeamCode = "fakeBeamCode" in self.special
 
-        print("ignoring event code check, faking beam code:",
-              self.ignoreEventCodeCheck, self.fakeBeamCode)
-
+        print("ignoring event code check, faking beam code:", self.ignoreEventCodeCheck, self.fakeBeamCode)
+
         ##mymodule = importlib.import_module(full_module_name)
 
         ## for standalone analysis
@@ -329,7 +328,8 @@ def colCommonModeCorrection(self, frame, arbitraryCut=1000):
         return frame
 
     def isBeamEvent(self, evt):
-        if self.ignoreEventCodeCheck: return True
+        if self.ignoreEventCodeCheck:
+            return True
         ec = self.getEventCodes(evt)
         ##print(ec[280], ec[281], ec[282], ec[283], ec[284], ec[285] )
         if ec[self.runCode]:
@@ -385,11 +385,12 @@ def addFakePhotons(self, frames, occupancy, E, width):
         shape = frames.shape
         occ = np.random.random(shape)
         fakes = np.random.normal(E, width, shape)
-        fakes[occ>occupancy] = 0
-        return frames + fakes, (fakes>0).sum()
-    
+        fakes[occ > occupancy] = 0
+        return frames + fakes, (fakes > 0).sum()
+
     def getNswitchedPixels(self, data, region=None):
-        return (((data>=self.g0cut)*1).sum())
+        return ((data >= self.g0cut) * 1).sum()
+
 
 """
 if __name__ == "__main__":

calibrationSuite/detectorInfo.py

@@ -99,6 +99,5 @@ def setup_rixsCCD(self, mode="1d", version=0):
         else:
             self.nRows = 1200
             self.clusterShape = [3, 5]  ## maybe
-        self.g0cut = 1<<16 
+        self.g0cut = 1 << 16
         self.dimension = 2
-

calibrationSuite/fitFunctions.py

@@ -125,25 +125,33 @@ def fitLinearUnSaturatedData(x, y, saturated=False):  ##, gainMode, label):
     return popt, pcov, y_fit, r2
 
 
+# not in use atm, and a + ds not def'd
+"""
 def fitMatrixOfLinearFits(x, y):
     if len(x.shape) != 1:
-        print("y data shape is %dd, not 1d" %(len(s)))
+        print("y data shape is %dd, not 1d" % (len(s)))
         raise Exception
     yShape = y.shape
     if len(yShape) != 4:
-        print("y data shape is %dd, not 4d" %(len(yShape)))
+        print("y data shape is %dd, not 4d" % (len(yShape)))
         raise Exception
-    slopesAndIntercepts = [fitLinearUnSaturatedData(a, ds[m, r, c, :])[0] for m in range(yShape[0]) for r in range(yShape[1]) for c in range(yShape[2])]
+    slopesAndIntercepts = [
+        fitLinearUnSaturatedData(a, ds[m, r, c, :])[0]
+        for m in range(yShape[0])
+        for r in range(yShape[1])
+        for c in range(yShape[2])
+    ]
     return np.array(slopesAndIntercepts)
+"""
 
 
 def linearFitTest():
     a = np.linspace(0, 9, 10)
-    d0 = np.random.normal(1, 1, [3,5])
+    d0 = np.random.normal(1, 1, [3, 5])
     d = np.array([d0 + i for i in range(10)])
     ds = np.stack(d, axis=-1)
     print("single pixel fit:")
-    print(np.ravel(fitLinearUnSaturatedData(a, ds[2,2,:])[0]))
+    print(np.ravel(fitLinearUnSaturatedData(a, ds[2, 2, :])[0]))
 
     print("array fit:")
     dss = ds.shape
@@ -159,7 +167,8 @@ def linearFitTest():
 
     ##print("matrix call:")
     ##print(fitMatrixOfLinearFits(a, ds))
-
+
+
 def twoGaussSilvermanModeTest(x0, x1):
     a = np.random.normal(0, 1, 1000)
     b = np.random.normal(x0, 1, 500)

config_files/archonSuiteConfig.py

@@ -27,12 +27,12 @@
         [0, 1000],
         [0, 2000],
     ],
-    "ignoreEventCodeCheck":True,
+    "ignoreEventCodeCheck": True,
     # 'ROIs':['module0', 'module2', 'module4', 'module6', 'module10','module12', 'module14']
     # 'ROIs':['roiFromSwitched_e557_rmfxx1005021']
     # 'ROIs':['allHRasicPixels', 'goodboxROI']#'roiAbove7k_raw_r123']
     # "ROIs": ["../data/XavierV4_2", "../data/OffXavierV4_2"],
-    "regionSlice": np.s_[0:1,0:1, 0:4800] ##[1d]
+    "regionSlice": np.s_[0:1, 0:1, 0:4800],  ##[1d]
 }
 # more complex approach allowing run ranges
 # fluxHash = {1:['MFX-USR-DIO', 11]}

suite_scripts/CalcNoiseAndMean.py

@@ -104,7 +104,7 @@
                     if bss.getPingPongParity(frames[0][144:224, 0:80]) == ("negative" in bss.special):
                         continue
                 ##print(frames)
-                
+
             if frames is None:
                 print("None frames on beam event, should not happen")
                 logger.info("None frames on beam event")

suite_scripts/DeltaTtest.py

@@ -94,7 +94,7 @@ def plotData(self, data, pixels, eventNumbers, dPulseId, label):
                 plt.close()
 
     # unused and not working atm
-    '''
+    """
     def analyzeData(self, delays, data, label):
         edge = np.zeros(data.shape[0])
         for m in range(data.shape[1]):
@@ -106,7 +106,7 @@ def analyzeData(self, delays, data, label):
                     coeff, var = curve_fit(f, delays, d, p0=p0)
                     edge[m, r, c] = coeff[1]
         return edge
-    ''' 
+    """
 
     def analyze_h5(self, dataFile, label):
         import h5py
@@ -151,7 +151,9 @@ def analyze_h5(self, dataFile, label):
 
     esp.setupPsana()
 
-    smd = esp.ds.smalldata(filename="%s/%s_c%d_r%d_n%d.h5" % (esp.outputDir, esp.className, esp.camera, esp.run, esp.size))
+    smd = esp.ds.smalldata(
+        filename="%s/%s_c%d_r%d_n%d.h5" % (esp.outputDir, esp.className, esp.camera, esp.run, esp.size)
+    )
 
     esp.fluxTS = 0
     esp.nGoodEvents = 0

suite_scripts/LinearityPlotsParallelSlice.py

@@ -18,7 +18,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 from calibrationSuite.basicSuiteScript import BasicSuiteScript
-from scipy.optimize import curve_fit
 
 # for logging from current file
 logger = logging.getLogger(__name__)
@@ -101,7 +100,7 @@ def plotAutorangingData_profile(self, g0s, g1s, g0Fluxes, g1Fluxes, label, parti
                 ##try:## using truncate instead
                 ##yMaxPlot = max(y.max(), yMaxPlot)
                 ##except:
-                    ##yMaxPlot = y.max()
+                ##yMaxPlot = y.max()
                 sns.regplot(
                     x=x, y=y, x_bins=40, marker=".", ax=ax, order=order, truncate=True
                 )  ##add fit_reg=None for no plot
@@ -207,12 +206,12 @@ def analyze_h5_slice(self, dataFile, label):
         for module in [1, 2]:
             for i in range(rows):
                 # so we can end early on testing runs:
-                if self.special is not None and 'testing' in self.special and i >= self.maxNevents:
+                if self.special is not None and "testing" in self.special and i >= self.maxNevents:
                     break
 
                 for j in range(cols):
                     # so we can end early on testing runs:
-                    if self.special is not None and 'testing' in self.special and j >= self.maxNevents:
+                    if self.special is not None and "testing" in self.special and j >= self.maxNevents:
                         break
 
                     iDet, jDet = self.sliceToDetector(i, j)
@@ -235,9 +234,11 @@ def analyze_h5_slice(self, dataFile, label):
                                 logger.info("empty profile for %d, %d" % (i, j))
                                 continue
                         if x is not None:
-                            fitPar, covar, fitFunc, r2 = fitFunctions.fitLinearUnSaturatedData(x, y, saturated=self.saturated)
+                            fitPar, covar, fitFunc, r2 = fitFunctions.fitLinearUnSaturatedData(
+                                x, y, saturated=self.saturated
+                            )
                             if True:
-                                if i%10==0 and j%10==0:
+                                if i % 10 == 0 and j % 10 == 0:
                                     print(i, j, fitPar, r2, 0)
                             ##np.save("temp_r%dc%d_x.py" %(i,j), fluxes[g0])
                             ##np.save("temp_r%dc%d_y.py" %(i,j), y)
@@ -316,7 +317,16 @@ def analyze_h5_slice(self, dataFile, label):
 
                         if self.residuals:
                             plt.figure(2)
-                            figFileName = "%s/%s_slice_m%d_r%d_c%d_r%d_c%d_residuals_%s.png" % (self.outputDir, self.className, module, i, j, self.run, self.camera, label)
+                            figFileName = "%s/%s_slice_m%d_r%d_c%d_r%d_c%d_residuals_%s.png" % (
+                                self.outputDir,
+                                self.className,
+                                module,
+                                i,
+                                j,
+                                self.run,
+                                self.camera,
+                                label,
+                            )
                             plt.savefig(figFileName)
                             logger.info("Wrote file: " + figFileName)
                             plt.close()
@@ -332,16 +342,15 @@ def analyze_h5_slice(self, dataFile, label):
     print("have built an LPP")
     logger.info("have built an LPP")
     lpp.useNswitchedAsFlux = False
-    lpp.fluxLabel = "wave8 flux (ADU)" 
-    if lpp.special is not None and 'useNswitchedAsFlux' in lpp.special:
+    lpp.fluxLabel = "wave8 flux (ADU)"
+    if lpp.special is not None and "useNswitchedAsFlux" in lpp.special:
         lpp.useNswitchedAsFlux = True
         lpp.fluxLabel = "number of low-gain pixels"
 
-    noSwitchedOnly = lpp.special is not None and 'noSwitchedOnly' in lpp.special
+    noSwitchedOnly = lpp.special is not None and "noSwitchedOnly" in lpp.special
+
+    print("using switched pixels as flux? only events with no switch?", lpp.useNswitchedAsFlux, noSwitchedOnly)
 
-    print("using switched pixels as flux? only events with no switch?",
-          lpp.useNswitchedAsFlux, noSwitchedOnly)
-
     if lpp.file is not None:
         print("using flux label:", lpp.fluxLabel)
         lpp.fitInfo = None
@@ -359,7 +368,6 @@ def analyze_h5_slice(self, dataFile, label):
         print("not doing Kaz events")
         logger.info("not doing Kaz events")
 
-
     lpp.setupPsana()
 
     size = 666
@@ -433,7 +441,7 @@ def analyze_h5_slice(self, dataFile, label):
             if nSwitched > 0:
                 ##print('nSwitched: %d' %(nSwitched))
                 continue
-            
+
         roiMeans = []
         for i, roi in enumerate(lpp.ROIs):
             ##m = np.multiply(roi, frames).mean()
@@ -453,12 +461,13 @@ def analyze_h5_slice(self, dataFile, label):
         for j, p in enumerate(lpp.singlePixels):
             singlePixelData.append([int(rawFrames[tuple(p)] >= lpp.g0cut), rawFrames[tuple(p)] & lpp.gainBitsMask])
 
-        eventDict = {'fluxes':flux,
-                     'rois':np.array(roiMeans),
-                     'pixels':np.array(singlePixelData),
-                     'slice':rawFrames[lpp.regionSlice]
+        eventDict = {
+            "fluxes": flux,
+            "rois": np.array(roiMeans),
+            "pixels": np.array(singlePixelData),
+            "slice": rawFrames[lpp.regionSlice],
         }
-        
+
         smd.event(
             evt,
             eventDict,

suite_scripts/PersistenceCheckParallel.py

@@ -56,7 +56,9 @@ def analyze_h5(self, dataFile, label):
         sys.exit(0)
 
     pcp.setupPsana()
-    smd = pcp.ds.smalldata(filename="%s/%s_c%d_r%d_n%d.h5" % (pcp.outputDir, pcp.className, pcp.camera, pcp.run, pcp.size))
+    smd = pcp.ds.smalldata(
+        filename="%s/%s_c%d_r%d_n%d.h5" % (pcp.outputDir, pcp.className, pcp.camera, pcp.run, pcp.size)
+    )
 
     nEvent = -1
     nGoodEvents = 0

suite_scripts/simplePhotonCounter.py

@@ -32,7 +32,7 @@
     thresholded = None
     energyHistogramBins = 1000
     energyHistogram = np.zeros(energyHistogramBins)
-    energyHistogramRange = [-100,900]## should get this from somewhere
+    energyHistogramRange = [-100, 900]  ## should get this from somewhere
     gain = None
     if spc.fakePedestal is not None:
         if spc.detectorInfo is not None:
@@ -77,8 +77,8 @@
 
         if False and gain is not None:
             for e in frames.flatten():
-                energyHistogram[((e-energyHistogramRange[0])/energyHistogramBins).clip(0, energyHistogramBins)] += 1
-        
+                energyHistogram[((e - energyHistogramRange[0]) / energyHistogramBins).clip(0, energyHistogramBins)] += 1
+
         nGoodEvents += 1
         if nGoodEvents % 100 == 0:
             print("n good events analyzed: %d" % (nGoodEvents))
@@ -104,8 +104,14 @@
     logger.info("total photons in detector using cut %0.2f is %0.3f" % (spc.photonCut, (thresholded).sum()))
 
     if False:
-        spectrumFileName = "%s/%s_%s_r%d_c%d_%s_spectrum.npy" % (spc.outputDir, scriptType, spc.label, spc.run, spc.camera, spc.exp)
+        spectrumFileName = "%s/%s_%s_r%d_c%d_%s_spectrum.npy" % (
+            spc.outputDir,
+            scriptType,
+            spc.label,
+            spc.run,
+            spc.camera,
+            spc.exp,
+        )
         np.save(spectrumFileName, energyHistogram)
 
-
     spc.dumpEventCodeStatistics()