diff --git a/Franck_Hertz_Versuch/params/FrankcHertzKurve.csv~ b/Franck_Hertz_Versuch/params/FrankcHertzKurve.csv~
deleted file mode 100644
index f0ddb6ef6c28b16c9cc787e913b23cbf4f46350d..0000000000000000000000000000000000000000
--- a/Franck_Hertz_Versuch/params/FrankcHertzKurve.csv~
+++ /dev/null
@@ -1,52 +0,0 @@
-UB,IA
-0,02, 0,04
-1,00, 0,05
-1,99, 0,05
-2,98, 0,30
-4,01, 1,13
-4,61, 2,08
-5,01, 2,95
-5,47, 4,15
-5,89, 5,36
-6,21, 6,31
-6,62, 7,16
-7,07, 7,18
-7,49, 6,38
-7,86, 5,17
-8,22, 3,77
-8,50, 2,65
-8,70, 1,99
-9,03, 1,69
-9,47, 2,35
-9,80, 3,42
-10,05, 4,58
-10,30, 5,87
-10,48, 7,00
-10,67, 8,11
-10,85, 9,29
-11,07, 10,47
-11,30, 11,72
-11,60, 12,74
-11,88, 13,20
-12,23, 12,52
-12,45, 11,56
-12,64, 10,54
-12,80, 9,68
-13,00, 8,66
-13,19, 7,48
-13,46, 6,11
-13,78, 5,01
-14,23, 5,41
-14,52, 6,43
-14,86, 7,94
-15,17, 9,49
-15,46, 10,97
-15,75, 12,42
-16,08, 13,90
-16,38, 15,11
-16,71, 15,95
-17,07, 15,59
-17,34, 14,69
-17,56, 13,67
-17,76, 12,68
-
diff --git a/Franck_Hertz_Versuch/tools/csv2yml.py b/Franck_Hertz_Versuch/tools/csv2yml.py
deleted file mode 100755
index 8beca8301df8f711bbbbde4006aebef2e75efe3b..0000000000000000000000000000000000000000
--- a/Franck_Hertz_Versuch/tools/csv2yml.py
+++ /dev/null
@@ -1,95 +0,0 @@
-#!/usr/bin/env python3
-"""csv2yml.py
- read floating-point column-data in very general .txt formats
- and write an output block in yaml format
-
- keys taken from 1st header line
-
- Usage:
-
- ./cvs2yml [options] <input file name>
-
- Input:
-
- - file name
-
- Output:
-
- - yaml data block
-
-
-.. moduleauthor:: Guenter Quast <g.quast@kit.edu>
-
-"""
-
-if __name__ == "__main__": # -------------------------------------------
-
- import sys, os, yaml, argparse
- from PhyPraKit import csv2yaml
- if os.name == 'nt': # interactive mode on windows if error occurs
- os.environ['PYTHONINSPECT']='x'
-
- # - - - Parse command-line arguments
- # parser = argparse.ArgumentParser(usage=__doc__)
- parser = argparse.ArgumentParser(
- description="convert csv to yaml format")
-
- parser.add_argument('filename', type=str,
- help="name of input file in csv format")
- parser.add_argument('-s', '--save',
- action='store_const', const=True, default=False,
- help="save result in file")
- parser.add_argument('-H', '--Header',
- action='store_const', const=True, default=False,
- help="print csv Header lines")
- parser.add_argument('-q', '--quiet',
- action='store_const', const=True, default=False,
- help="quiet - no output to screen")
- parser.add_argument('-d','--delimiter',
- type=str, default=',',
- help="delimiter, default=','")
- parser.add_argument('-n','--header_lines',
- type=int, default=1,
- help="numer of header lines, default=1")
-
- if len(sys.argv)==1: # print help message if no input given
- parser.print_help()
- raise ValueError('!!! not input given -exit !')
-
- # collect input from ArgumentParser
- args = parser.parse_args()
- fnam = args.filename
-
- nlhead = args.header_lines
- delim = args.delimiter
- showHeader = args.Header
- sav_flg = args.save
- quiet = args.quiet
- if quiet: sav_flg = True
-
- # ---- end argument parsing -------------------
-
- f = open(fnam, 'r')
- hlines, ylines = csv2yaml(f, nlhead, delim)
-
- if not quiet:
- print('-->', fnam, 'to yaml', end='')
-
- if showHeader:
- print(' csv header:')
- for l in hlines:
- print(l)
-
- # print results to screen
- if not quiet:
- print(' yaml block:')
- for l in ylines:
- print(l)
-
- # write to file
- if sav_flg:
- ymlfn = fnam.split('.')[0] + '.yaml'
- with open(ymlfn, 'w') as f:
- for l in ylines:
- print(l, file=f)
- print(' -> yaml saved in file',ymlfn)
diff --git a/Franck_Hertz_Versuch/tools/plotCSV.py b/Franck_Hertz_Versuch/tools/plotCSV.py
deleted file mode 100755
index 7739f8212d7bb91d0bd3b296aea0f7b1c99f0c78..0000000000000000000000000000000000000000
--- a/Franck_Hertz_Versuch/tools/plotCSV.py
+++ /dev/null
@@ -1,100 +0,0 @@
-#!/usr/bin/python3
-
-"""plotCSV.py
- uses PhyPraKkt.readtxt() to read floating-point column-data in csv format
-
-
- usage:
-
- ./plotCSV.py [options] <input file name>
-
- Input:
-
- - input file in csv format
-
- Options:
-
- - s : character used as field separator, default ','
- - H : number of header lines, default 1
-
- Output:
-
- - figure
-
-
-
-"""
-
-from PhyPraKit import readtxt
-
-# --- helper function
-def wexit(code):
- # keep Python window open on MS Windows
- import os, sys
- if os.name == 'nt':
- _ = input('\n ==> type <ret> to end > ')
- sys.exit(code)
-
-if __name__ == "__main__":
- import sys, argparse, numpy as np, matplotlib.pyplot as plt
-
- # - - - Parse command-line arguments
- parser = argparse.ArgumentParser(description = \
- "plot contents of CSV file")
-
- parser.add_argument('filename', type=str, nargs='+',
- help="name of csv file")
- parser.add_argument('-v', '--verbose',
- action='store_const', const=True, default=False,
- help="full printout to screen")
- parser.add_argument('-s', '--separator',
- type=str, default=',',
- help="character used as field separator ")
- parser.add_argument('-H', '--Headerlines',
- type=int, default = 1,
- help="number of header lines")
-
- if len(sys.argv)==1: # print help message if no input given
- parser.print_help()
- print(" \n !!! no input file given - exiting \n")
- wexit(1)
-
- # collect input from ArgumentParser
- args = parser.parse_args()
- fname = args.filename[0]
- quiet_flg = not args.verbose
- separator = args.separator # field separator: , or \t, or \_ or ; etc.
- nHlines = args.Headerlines # number of header lines
- # print(args)
-
- # end parsing input ------------------------------------------
-
- # read data from file in .txt format
- hlines, data = readtxt(fname, delim=separator, nlhead=nHlines)
- nColumns = data.shape[0]
- nRows = data.shape[1]
- keys = hlines[0].split(separator)[:]
- # output to terminal
- print(hlines)
- print(" --> number of columns", nColumns)
- print(" --> number of data points", nRows)
-
-# make plots - columns 1, 2, 3, ... vs. column 0
- fig=plt.figure(1, figsize=(10, 2.25*nColumns))
- fig.tight_layout()
- fig.suptitle('contents of file '+fname, size='x-large', color='b')
- fig.subplots_adjust(left=0.14, bottom=0.1, right=0.97, top=0.93,
- wspace=None, hspace=.33)#
- x = data[0]
- axes = []
- ncol = nColumns - 1
- for i in range(1, ncol+1):
- axes.append(fig.add_subplot(ncol, 1, i))
- ax = axes[i-1]
- ax.plot(x, data[i], alpha=0.3, label='Column' + str(i))
- ax.set_ylabel(keys[i], size='large')
- ax.set_xlabel(keys[0], size='large')
- ax.legend(loc='best', numpoints=1, prop={'size':10})
- ax.grid()
-
- plt.show()
diff --git a/Franck_Hertz_Versuch/tools/plotData.py b/Franck_Hertz_Versuch/tools/plotData.py
deleted file mode 100755
index 009b9ddf09743389e68b0e77a88460219b02cce4..0000000000000000000000000000000000000000
--- a/Franck_Hertz_Versuch/tools/plotData.py
+++ /dev/null
@@ -1,171 +0,0 @@
-#!/usr/bin/env python3
-"""**plotData.py** [options] <input file name>
-
- Plot (several) data set(s) with error bars in x- and y- directions
- or histograms from file in yaml format
-
- usage:
-
- ./plotData.py [options] <input file name>
-
- Input:
-
- - input file in yaml format
-
- Output:
-
- - figure
-
- yaml-format for (x-y) data:
-
- .. code-block:: yaml
-
- title: <title of plot>
- x_label: <label for x-axis>
- y_label: <label for y-axis>
-
- label: <name of data set>
- x_data: [ x values ]
- y_data: [ y values ]
- x_errors: x-uncertainty or [x-uncertainties]
- y_errors: y-uncertainty or [y-uncertainties]
-
- *Remark*: more than one input data sets are also possible.
- Data sets and models can be overlayed in one plot if option
- `showplots = False` ist specified. Either provide more than
- one input file, or use yaml syntax, as shown here:
-
- .. code-block:: yaml
-
- # several input sets to be separated by
- ...
- ---
-
- yaml-format for histogram:
-
- .. code-block:: yaml
-
- title: <title of plot>
- x_label: <label for x-axis>
- y_label: <label for y-axis>
-
- label: <name of data set>
- raw_data: [x1, ... , xn]
- # define binning
- n_bins: n
- bin_range: [x_min, x_max]
- # alternatively:
- # bin edges: [e0, ..., en]
-
- several input sets to be separated by
- ...
- ---
-
- In case a model function is supplied, it is overlayed in the
- output graph. The corresponding *yaml* block looks as follows:
-
- .. code-block:: yaml
-
- # optional model specification
- model_label: <model name>
- model_function: |
- <Python code of model function>
-
- If no `y_data` or `raw_data` keys are provided, only the model function
- is shown. Note that minimalistic `x_data` and `bin_range` or `bin_edges`
- information must be given to define the x-range of the graph.
-
-"""
-
-from PhyPraKit import plot_xy_from_yaml,plot_hist_from_yaml
-
-# --- helper function
-def wexit(code):
- # keep Python window open on MS Windows
- import os, sys
- if os.name == 'nt':
- _ = input('\n ==> type <ret> to end > ')
- sys.exit(code)
-
-if __name__ == "__main__": # --------------------------------------
-
- import os, sys, yaml, argparse, matplotlib.pyplot as plt
- if os.name == 'nt': # interactive mode on windows if error occurs
- os.environ['PYTHONINSPECT']='x'
-
- # - - - Parse command-line arguments
- parser = argparse.ArgumentParser(description = \
- "Plot data with error bars or a histrogram from file in yaml format")
- # parser = argparse.ArgumentParser(usage=__doc__)
-
- parser.add_argument('filename', type=str, nargs='+',
- help="name(s) of input file(s) in yaml format")
- parser.add_argument('-s', '--saveplot',
- action='store_const', const=True, default=False,
- help="save plot(s) in file(s)")
- parser.add_argument('-f','--format',
- type=str, default='pdf',
- help="graphics output format, default=pdf")
- parser.add_argument('-n', '--noplot',
- action='store_const', const=True, default=False,
- help="suppress ouput of plots on screen")
-
- if len(sys.argv)==1: # print help message if no input given
- parser.print_help()
- print(" \n !!! no input file given - exiting \n")
- wexit(1)
-
- # collect input from ArgumentParser
- args = parser.parse_args()
- fnames = args.filename
- sav_flg = args.saveplot
- pltfmt = args.format
- plt_flg = not args.noplot
-
- ddata = []
- for fnam in fnames:
- f = open(fnam,'r')
- try:
- ymldata = yaml.load_all(f, Loader=yaml.Loader)
- except (OSError, yaml.YAMLError) as exception:
- print('!!! failed to read configuration file ' + fnam)
- print(str(exception))
- wexit(1)
-
- data_type = 'xy'
- for d in ymldata:
- if 'type' in d:
- data_type = d['type']
- ddata.append(d)
-
- # create a figure
- if data_type == 'xy':
- fignam = 'plotxyData'
- elif data_type == 'histogram':
- fignam = 'plothistData'
- else:
- print('!!! invalid data type', data_type)
- wexit(1)
-
- # create figure
- figsize = (7.5, 6.5)
- figure = plt.figure(num=fignam, figsize=figsize)
-
- # decode yaml input and plot data for each yaml file
- for d in ddata:
- if data_type == 'xy':
- plot_xy_from_yaml(d)
- elif data_type == 'histogram':
- plot_hist_from_yaml(d)
- f.close()
-
- # output to file or screen
- if (sav_flg):
- oname = fnames[0].split('.')[0] + '.'+pltfmt
- plt.savefig( oname )
- print(' -> graph saved to file ', oname)
- # show plot on screen
- if plt_flg:
- plt.show()
-
- wexit(0)
diff --git a/Franck_Hertz_Versuch/tools/run_phyFit.py b/Franck_Hertz_Versuch/tools/run_phyFit.py
deleted file mode 100755
index b3898cd957743e65b42736985da84e0deb1b68ce..0000000000000000000000000000000000000000
--- a/Franck_Hertz_Versuch/tools/run_phyFit.py
+++ /dev/null
@@ -1,277 +0,0 @@
-#!/usr/bin/env python3
-"""**run_phyFit.py** [options] <input file name>
-
- Perform fit with data and model from yaml file
-
- Uses functions xyFit and hFit from PhyPraKit.phyFit
-
- This code performs fits
-
- - to x-y data with independent and correlated, absolute
- and relative uncertainties in the x and y directions
-
- - and to histogram data with a binned likelihood fit.
-
- usage:
-
- ./run_phyFit.py [options] <input file name>
-
- ./run_phyFit.py --help for help
-
-
- Input:
-
- - input file in yaml format
-
- output:
-
- - text and/or file, graph depending on options
-
-
- **yaml format for x-y fit:**
-
- .. code-block:: yaml
-
- label: <str data-set name>
-
- x_label: <str name x-data>
- x_data: [ list of float ]
-
- y_label: <str name y-data>
- y_data: [ list of float ]
-
- x_errors: <float>, [list of floats], or {dictionary/ies}
- y_errors: <float>, [list of floats], or {dictionary/ies}
-
- # optionally, add Gaussian constraints on parameters
- parameter_constraints:
- <parameter name>:
- value: <value>
- uncertaintiy: <value>
-
- model_label: <str model name>
- model_function: |
- <Python code>
-
- format of uncertainty dictionary:
- - error_value: <float> or [list of floats]
- - correlation_coefficient: 0. or 1.
- - relative: true or false
- relative errors may be spcified as <float>%
-
-
- Simple example of *yaml* input:
-
- .. code-block:: yaml
-
- label: 'Test Data'
-
- x_data: [.05,0.36,0.68,0.80,1.09,1.46,1.71,1.83,2.44,2.09,3.72,4.36,4.60]
- x_errors: 3%
- x_label: 'x values'
-
- y_data: [0.35,0.26,0.52,0.44,0.48,0.55,0.66,0.48,0.75,0.70,0.75,0.80,0.90]
- y_errors: [.06,.07,.05,.05,.07,.07,.09,.1,.11,.1,.11,.12,.1]
- y_label: 'y values'
-
- model_label: 'Parabolic Fit'
- model_function: |
- def quadratic_model(x, a=0., b=1., c=0. ):
- return a * x*x + b*x + c
-
-
- **Example of yaml input for histogram fit:**
-
- .. code-block:: yaml
-
- # Example of a fit to histogram data
- type: histogram
-
- label: example data
- x_label: 'h'
- y_label: 'pdf(h)'
-
- # data:
- raw_data: [ 79.83,79.63,79.68,79.82,80.81,79.97,79.68,80.32,79.69,79.18,
- 80.04,79.80,79.98,80.15,79.77,80.30,80.18,80.25,79.88,80.02 ]
-
- n_bins: 15
- bin_range: [79., 81.]
- # alternatively an array for the bin edges can be specified
- #bin_edges: [79., 79.5, 80, 80.5, 81.]
-
- model_density_function: |
- def normal_distribution(x, mu=80., sigma=1.):
- return np.exp(-0.5*((x - mu)/sigma)** 2)/np.sqrt(2.*np.pi*sigma** 2)
-
-
- *Remark*: more than one input data sets are also possible.
- Data sets and models can be overlayed in one plot if option
- `showplots = False` ist specified. Either provide more than
- one input file, or use yaml syntax, as shown here:
-
- .. code-block:: yaml
-
- # several input sets to be separated by
- ...
- ---
-"""
-
-from PhyPraKit.phyFit import xyFit_from_yaml, hFit_from_yaml
-from pprint import pprint
-
-# --- helper function
-def wexit(code):
- # keep Python window open on MS Windows
- import os, sys
- if os.name == 'nt':
- _ = input('\n ==> type <ret> to end > ')
- sys.exit(code)
-
-if __name__ == "__main__": # --------------------------------------
- #
- # xyFit.py: Example of an application of PhyPraKit.phyFit.xyFit_from_yaml()
- #
-
- # package imports
- import os, sys, argparse, yaml, numpy as np, matplotlib.pyplot as plt
- if os.name == 'nt': # interactive mode on windows if error occurs
- os.environ['PYTHONINSPECT']='x'
-
- # - - - Parse command-line arguments
- parser = argparse.ArgumentParser(description = \
- "Perform a fit with PhyPraKit.phyFit package driven by input file")
- # parser = argparse.ArgumentParser(usage=__doc__)
-
- parser.add_argument('filename', type=str, nargs='+',
- help="name(s) of fit input file(s) in yaml format")
- parser.add_argument('-v', '--verbose',
- action='store_const', const=True, default=False,
- help="full printout to screen")
- parser.add_argument('-r', '--result_to_file',
- action='store_const', const=True, default=False,
- help="store results to file")
- parser.add_argument('-n', '--noplot',
- action='store_const', const=True, default=False,
- help="suppress ouput of plots on screen")
- parser.add_argument('-s', '--saveplot',
- action='store_const', const=True, default=False,
- help="save plot(s) in file(s)")
- parser.add_argument('-c', '--contour',
- action='store_const', const=True, default=False,
- help="plot contours and profiles")
- parser.add_argument('--noband',
- action='store_const', const=True, default=False,
- help="suppress 1-sigma band around function")
- parser.add_argument('-f','--format',
- type=str, default='pdf',
- help="graphics output format, default=pdf")
-
- if len(sys.argv)==1: # print help message if no input given
- parser.print_help()
- print(" \n !!! no input file given - exiting \n")
- wexit(1)
-
- # collect input from ArgumentParser
- args = parser.parse_args()
- fnames=args.filename
- quiet_flg = not args.verbose
- store_result = args.result_to_file
- plt_flg= not args.noplot
- sav_flg=args.saveplot
- cont_flg=args.contour
- band_flg=not args.noband
- pltfmt=args.format
-
- # - - - End: Parse command-line arguments
-
- ddata = []
- # open and read input yaml file
- for fnam in fnames:
- f = open(fnam, 'r')
- try:
- ymldata = yaml.load_all(f, Loader=yaml.Loader)
- except (OSError, yaml.YAMLError) as exception:
- print('!!! failed to read configuration file ' + fnam)
- print(str(exception))
- wexit(1)
-
- fitType = 'xy'
- for d in ymldata:
- if 'type' in d:
- fitType = d['type']
- ddata.append(d)
- f.close()
-
- # select appropriate wrapper
- if fitType == 'xy':
- fit = xyFit_from_yaml
- elif fitType == 'histogram':
- fit = hFit_from_yaml
- else:
- print('!!! unsupported type of fit:', fitType)
- wexit(1)
-
- for fd in ddata:
- if 'type' in fd.keys():
- fitType = fd['type']
- print("*==*", sys.argv[0], "received valid yaml data for fit:")
- if 'parametric_model' in fd: # for complex kafe2go format
- pprint(fd, compact=True)
- else: # "nice" printout for simple xyFit format
- print(' ** Type of Fit:', fitType)
- for key in fd:
- if type(fd[key]) is not type([]): # got a scalar or string
- print(key + ': ', fd[key])
- elif type(fd[key][0]) is not type({}): # got list of scalars
- print(key + ': ', fd[key])
- else: # got list of uncertainty dictionaries
- print(key+':')
- for d in fd[key]:
- for k in d:
- print(' '+ k +': ', d[k], end=' ')
- print()
- # run fit
- rdict = fit(fd, # the input dictionary defining the fit
- plot=plt_flg, # show plot of data and model
- plot_band=band_flg, # plot model confidence-band
- plot_cor=cont_flg, # plot profiles likelihood and contours
- showplots= False, # show plots on screen
- quiet=quiet_flg, # suppress informative printout
- return_fitObject=False
- )
-
- # print results to illustrate how to use output
- print('\n*==* Fit Result:')
- pvals, perrs, cor, chi2, pnams= rdict.values()
- print(" chi2: {:.3g}".format(chi2))
- print(" parameter names: ", pnams)
- print(" parameter values: ", pvals)
- np.set_printoptions(precision=3)
- print(" neg. parameter errors: ", perrs[:,0])
- print(" pos. parameter errors: ", perrs[:,1])
- print(" correlation matrix : \n", cor)
-
- if store_result:
- outfile = (fnames[0].split('.')[0]+ '.result')
- with open(outfile, 'a') as outf:
- for key in rdict:
- print("{}\n".format(key), rdict[key], file=outf)
- print(' -> result saved to file ', outfile)
-
- if (sav_flg):
- # save all figures to file(s)
- n_fig = 0
- tag = ''
- for n in plt.get_fignums():
- plt.figure(n)
- oname = (fnames[0].split('.')[0] + '%s.' + pltfmt) %(tag)
- plt.savefig( oname)
- print(' -> figure saved to file ', oname)
- n_fig += 1
- tag = '_'+str(n_fig)
- else:
- # show on screen
- plt.show()
-
- wexit(0)