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Vorversuch/figures/Logo_KIT.svg

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Vorversuch/params/parameters_task_3.py

-"""
-Parameters required for task 3.
-
-The only parameter required for the model of the mathematical pendulum of task 
-3 is the distance l of the center of mass of the smartphone from the pivotal 
-point of the pendulum. It is a derived quantity, since it implies knowledge of 
-the center of mass of the smartphone, but its derivation is not too evolved. 
-The value of l is given in SI units  
-"""
-
-l = 0.6285                   # Distance of the center of mass of the smartphone from the pivotal point of the pendulum (in m)
-l_UPPER = 0.6280             # +uncertainty
-l_LOWER = 0.6290             # -uncertainty
-
-__version__ = 1.0

Vorversuch/params/parameters_task_4.py

-"""
-Parameters required for task 4.
-
-The momentum of inertia (I), mass (m), and distance (ell) of the center of mass 
-to the pivotal point of the physical pendulum. All quantities have been derived 
-from direct parameter estimates and rounded within their estimated uncertainties. 
-They have been derived assuming simplified shapes of the corresponding objects, 
-e.g. the smartphone has been approximated by a homogeneous box. All quantities 
-are given in SI units.   
-"""
-
-I = 0.23523                  # Momentum of inertia in kg*m**2
-I_UPPER = 0.2378             # +uncertainty
-I_LOWER = 0.2328             # -uncertatiny
-
-m = 0.789                    # Mass of the pendulum in kg
-m_UPPER = 0.794              # +uncertainty
-m_LOWER = 0.784              # -uncertainty
-
-ell = 0.473                  # Distance of the center of mass from the pivotal point of the pendulum in m 0.473
-ell_UPPER = 0.480            # +uncertainty
-ell_LOWER = 0.466            # -uncertainty
-
-__version__ = 1.0

Vorversuch/tools/csv2yml.py

-#!/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) 

Vorversuch/tools/plotCSV.py

-#!/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()

Vorversuch/tools/plotData.py

-#!/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)

Vorversuch/tools/run_phyFit.py

-#!/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)