cma.logger.CMADataLogger

Arguments

idx

indices corresponding to rows in the data file; if idx is a scalar (int), the first two, then every idx-th, and the last three rows are displayed. Too large index values are removed. If idx=='header', the header line is printed.

Example

>>> import cma, numpy as np
>>> res = cma.fmin(cma.ff.elli, 7 * [0.1], 1, {'verb_disp':1e9})  # generate data
...  #doctest: +ELLIPSIS
(4...
>>> assert res[1] < 1e-9
>>> assert res[2] < 4400
>>> l = cma.CMADataLogger()  # == res[-1], logger with default name, "points to" above data
>>> l.disp([0,-1])  # first and last
...  #doctest: +ELLIPSIS
Iterat Nfevals  function value    axis ratio maxstd  minstd...
>>> l.disp(20)  # some first/last and every 20-th line
...  #doctest: +ELLIPSIS
Iterat Nfevals  function value    axis ratio maxstd  minstd...
>>> l.disp(np.r_[0:999999:100, -1]) # every 100-th and last
...  #doctest: +ELLIPSIS
Iterat Nfevals  function value    axis ratio maxstd  minstd...
>>> l.disp(np.r_[0, -10:0]) # first and ten last
...  #doctest: +ELLIPSIS
Iterat Nfevals  function value    axis ratio maxstd  minstd...
>>> cma.disp(l.name_prefix, np.r_[0:9999999:100, -10:])  # the same as l.disp(...)
...  #doctest: +ELLIPSIS
Iterat Nfevals  function value    axis ratio maxstd  minstd...

Details

The data line with the best f-value is displayed as last line.

Use CMADataLogger.disp if the logger does not have the default name.

Arguments

• factor -- downsampling factor
• first -- keep first first entries

• switch -- switch the new logger to the downsampled logger

  original_name+'down'

Details

self.name_prefix+'down' files are written

Example

import cma
cma.downsampling()  # takes outcma/cma* files
cma.plot('outcma/cmadown')

Arguments

fig

figure number, by default starting from 325

iabscissa

0==plot versus iteration count, 1==plot versus function evaluation number

iteridx

iteration indices to plot, e.g. range(100) for the first 100 evaluations.

x_opt

If isscalar(x_opt) it is interpreted as iteration number and the difference of x to the respective iteration is plotted. If it is a negative scalar the respective index rather than the iteration is used. Namely in particular, x_opt=0 subtracts the initial solution X0 and x_opt=-1 subtracts the final solution of the data. If len(x_opt) == dimension, the difference to x_opt is plotted, otherwise the first row of x_opt are the indices of the variables to be plotted and the second row, if present, is used to take the difference.

fshift

is added to all displayed fitness values

Return CMADataLogger itself.

Examples

import cma
logger = cma.CMADataLogger()  # with default name
# try to plot the "default logging" data (e.g.
#   from previous fmin calls, which is essentially what
#   also cma.plot() does)
logger.plot()
cma.s.figsave('fig325.png')  # save current figure
logger.figclose()

Dependencies: matlabplotlib.pyplot

Arguments

fig

figure number, by default 425

iabscissa

0==plot versus iteration count, 1==plot versus function evaluation number

iteridx

iteration indices to plot

x_opt

If isscalar(x_opt) it is interpreted as iteration number and the difference of x to the respective iteration is plotted. If it is a negative scalar the respective index rather than the iteration is used. Namely in particular, x_opt=0 subtracts the initial solution X0 and x_opt=-1 subtracts the final solution of the data. If len(x_opt) == dimension, the difference to x_opt is plotted, otherwise the first row of x_opt are the indices of the variables to be plotted and the second row, if present, is used to take the difference.

Return CMADataLogger itself.

Examples

import cma
logger = cma.CMADataLogger()  # with default name
# try to plot the "default logging" data (e.g.
#   from previous fmin calls, which is essentially what
#   also cma.plot() does)
logger.plot_all()
cma.s.figsave('fig425.png')  # save current figure
logger.s.figclose()

Dependencies: matlabplotlib/pyplot.