2nd initial commit to make it work in the first place

CHANGES.txt

@@ -1 +1,6 @@
+Version 0.0.1
+- The subpkg Measurement was added to the build
+
+Version 0.0.0
 - SpecModel.set_mathematical_constraints() now resets all mathematical constraints before new assignment, which can be deactivated by setting reset=False
+

build.sh

@@ -0,0 +1 @@
+python3 setup.py sdist bdist_wheel

build/lib/eNMRly/Phasefitting.py

@@ -299,17 +299,29 @@ def __init__(self, n_peaks, verbose=False, model='Lorentz'):
         if verbose:
             self.params.pretty_print()
 
-    def set_mathematical_constraints(self, expr):
+    def set_mathematical_constraints(self, expr=None, reset=True):
         """
         expr: mathematical expression without whitespace
         
+        reset: will reset all mathematical constraints
+        
         example 1:
             ph0 should be always equal to ph1
             set_mathematical_constraint('ph0=ph1')
         example 2:
             ph0 should be always ph1 - 90 degree
             set_mathematical_constraint('ph0=ph1-90')
         """
+
+        if (expr == None) and (reset):
+            print('model without constraints')
+            return
+
+        elif reset:
+            for i in self.params:
+                self.params[i].expr = None
+            print('constraints were reset before new assignment')
+
         if type(expr) == list:
             for e in expr:
                 a = e.split('=')
@@ -318,6 +330,8 @@ def set_mathematical_constraints(self, expr):
             a = expr.split('=')
             self.params[a[0]].expr = a[1]
 
+
+
     def set_initial_values(self, par, val):
         '''
         takes single parameter par or list of parameters

build/lib/eNMRly/__init__.py

@@ -1,2 +1,6 @@
-#__all__ = ['Measurement', 'Phasefitting', 'MOSY']
+__all__ = ['SpecModel']
 from .Phasefitting import SpecModel
+from .MOSY import MOSY
+from .Measurement import Pavel as Import_eNMR_Measurement 
+print('%s imported'%__name__)
+

eNMRly.egg-info/PKG-INFO → eNMRpy.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 1.0
-Name: eNMRly
-Version: 0.0.0
+Name: eNMRpy
+Version: 0.0.1
 Summary: nmrglue-based package for the import and analysis of electrophoretic NMR-data
 Home-page: UNKNOWN
 Author: Florian Ackermann

eNMRly.egg-info/top_level.txt → eNMRpy.egg-info/top_level.txt

@@ -1 +1,2 @@
 eNMRly
+eNMRpy

eNMRpy/Measurement/Emma.py

@@ -0,0 +1,179 @@
+## coding: utf-8
+# This is the eNMR class. THE library for the evaluation of bruker-eNMR-spectra based on the VC-PowerSource of the
+# Schönhoff working group.
+# It works with the volt-increment method which calculates the respective voltage with the VC-list
+# Further Implementation can be asked for at [email protected]
+
+
+
+class eNMR_Emma(eNMR_Measurement):
+    #'''
+    #This is the subsubclass of Masurement() and subclass of eNMR_Methods specialised to process data obtained from the experimental Schönhoff set-up
+
+    #path:
+        #relative or absolute path to the measurements folder
+    #measurement:
+        #the to the experiment corresponding EXPNO
+    #alias:
+        #Here you can place an individual name relevant for plotting. If None, the path is taken instead.    
+    #Uink:
+        #voltage increment. Usually extracted from the title file if defined with e.g. "Uink = 10V"
+        #If Uink cannot be found or is wrong it can be entered manually during the data import.
+        #The voltage list is calculated from the voltage increment and the vc list when the incrementation loop is used in the pulse program
+    #dependency:
+        #'U': voltage dependent eNMR measurement
+        #'G': fieldgradient dependent eNMR measurement
+
+    #linebroadening:
+        #setting a standard-value for the linebroadening.
+    #'''
+    def __init__(self, path, expno, Uink=None, dependency="U", alias=None, linebroadening=0.5, electrode_distance=2.2e-2):
+        Measurement.__init__(self, path, expno, linebroadening=linebroadening, alias=alias)
+        self.dependency = dependency.upper()
+
+        self._x_axis = {"U": "U / [V]",
+                   "G": "g in T/m",
+                   "I": "I / mA",
+                   'RI': 'RI / V'
+                   }[self.dependency.upper()]
+
+        #self._x_axis = {"G": "g in T/m",
+                        #"U": "U / [V]"}[self.dependency.upper()]
+
+        self.difflist = pd.read_csv(self.dateipfad+"/difflist",
+                            names=["g in T/m"])*0.01
+
+        self.vcList = pd.DataFrame()
+
+        if self.dic['acqus']['PULPROG'][-3:] == 'var':
+            polarity = 1
+            print('this is a regular measurement! (non-_pol)')
+        elif self.dic['acqus']['PULPROG'][-3:] == 'pol':
+            polarity = -1
+            print('this is a _pol-Measurement!')
+        else:
+            print("no var or pol PULPROG")
+
+        if dependency.upper() == "U":
+            try:
+                # takes the title page to extract the volt increment
+                title = open(self.dateipfad+"/pdata/1/title").read()
+                # gets the voltage increment using a regular expression
+                #uimport = findall('[U|u]in[k|c]\s*=?\s*\d+', title)[0]
+                uimport = findall('[U|u]in[k|c]\s*=+\s*\d+', title)[0]
+                self.uInk = int(findall('\d+', uimport)[0])
+            except ValueError:
+                print('no volt increment found\nyou may want to put it in manually')
+                self.uInk = Uink
+            except IndexError:
+                print('No Uink found! May not be an eNMR experiment.')
+                self.uInk = Uink
+
+            self.vcList["U / [V]"] = [i*self.uInk*polarity for i in range(len(self.difflist))]
+
+        elif dependency.upper() == "G":
+            try:
+                # takes the title page to extract the volt increment
+                title = open(self.dateipfad+"/pdata/1/title").read()
+                # gets the voltage increment using a regular expression
+                uimport = findall('[U|u]\s*=?\s*\d+', title)[0]
+                self.uInk = int(findall('\d+', uimport)[0])
+
+            except ValueError:
+                print('no volt increment found\nyou may want to put it in manually')
+                self.uInk = Uink
+            except IndexError:
+                print('No Uink found! May not be an eNMR experiment.')
+                self.uInk = Uink # Uinktext
+
+            #if Uink is not None:
+                #self.uInk = Uink
+
+            self.vcList["U / [V]"] = [self.uInk*polarity for i in range(len(self.difflist))]
+            #self.vcList["U / [V]"] = [self.vcList["vc"][n]/2*self.uInk if self.vcList["vc"][n] % 2 == 0
+                                    #else (self.vcList["vc"][n]+1)/2*self.uInk*-1
+                                    #for n in range(len(self.data[:, 0]))]
+
+        #if self.dependency.upper() == "U":
+            #try:
+                #self.vcList = pd.read_csv(self.dateipfad+"/vclist",
+                                          #names=["vc"]).loc[:len(self.data[:, 0])-1]
+
+            #except:
+                #print("There is a Problem with the VC-list or you performed a gradient dependent measurement")
+        #elif self.dependency.upper() == "G":
+            #self.vcList = pd.DataFrame(np.ones((len(self.data[:, 0]), 1)),
+                                       #columns=["vc"])
+        #else:
+            #print("The dependency is not properly selected, try again!")
+
+        #self.difflist = pd.read_csv(self.dateipfad+"/difflist",
+                                    #names=["g in T/m"])*0.01
+
+            #if Uink is not None:
+                #self.uInk = Uink
+
+            #self.vcList["U / [V]"] = [self.vcList["vc"][n]/2*self.uInk if self.vcList["vc"][n] % 2 == 0
+                                    #else (self.vcList["vc"][n]+1)/2*self.uInk*-1
+                                    #for n in range(len(self.data[:, 0]))]
+
+        # try to open phase data, otherwise create new
+        try:
+            self.eNMRraw = pd.read_csv(self.path+"phase_data_"+self.expno+".csv",
+                                       index_col=0, sep=" ")
+            # --> update voltage list
+            self.eNMRraw["U / [V]"] = self.vcList["U / [V]"]
+        except:
+            print("eNMRraw was missing and is generated")
+            self.vcList["ph0"] = np.zeros(len(self.data.real[:, 0]))
+            self.eNMRraw = self.vcList
+        finally:
+            self.eNMRraw["g in T/m"] = self.difflist
+
+        self.p1 = self.dic["acqus"]["P"][1]
+        self.d1 = self.dic["acqus"]["D"][1]
+
+        try:
+            # import of diffusion parameters for newer Spectrometers
+            import xml.etree.ElementTree as etree
+            diffpar = etree.parse(self.dateipfad+'/diff.xml')
+            root = diffpar.getroot()
+            self.Delta = float(root.findall('DELTA')[0].text)*1e-3
+            self.delta = float(root.findall('delta')[0].text)*1e-3  # it should be read as in microseconds at this point due to bruker syntax
+            print('The diffusion parameters were read from the respectie .XML!')
+        except:
+            # determination of the diffusion parameters for Emma
+            self._d2 = self.dic["acqus"]["D"][2]
+            self._d5 = self.dic["acqus"]["D"][5]
+            self._d9 = self.dic["acqus"]["D"][9]
+            self._d11 = self.dic["acqus"]["D"][11]
+            self._p19, self._p18, self._p17 = self.dic["acqus"]["P"][19],\
+                                            self.dic["acqus"]["P"][18],\
+                                            self.dic["acqus"]["P"][17]
+            print('That did not work. Your data is from an old spectrometer!')
+            # calculating usable parameters
+            self.delta = self._p17+self._p18
+            self._Delta_1 = 0.001*(self._p17*2+self._p18)+(self._d2+self._d9+self._d5+self._d11)*1000+0.001*self.p1+self._d11
+            self._Delta_2 = 0.001*(self._p17*2+self._p18)+(self._d2+self._d9+self._d5+self._d11)*1000+0.001*self.p1*2
+            self._spoiler = (self._d11+self._p17+self._p19+self._p17)*0.001+self._d2*1000
+            self.Delta = self._Delta_1+self._Delta_2+2*self._spoiler
+            self.Delta *=1e-3
+            self.delta *=1e-6
+
+
+        # Elektrodenabstand in m
+        self.d = electrode_distance
+        self.g = self.eNMRraw["g in T/m"][0]
+
+    def __add__(self, other):
+
+        for obj in [self, other]:
+            for k in obj.eNMRraw.columns:
+                if k[:2] == 'ph':
+                    obj.eNMRraw[k] -= obj.eNMRraw.loc[0, k]
+                    print('%s normalized to 0V'%k)
+                else:
+                    pass
+        self.eNMRraw = self.eNMRraw.append(other.eNMRraw)
+        self.eNMRraw.sort_values('U / [V]', inplace=True)
+        return self