CLUSTER_DISTRIBUTION
 This is part of the adjmat module It is only available if you configure PLUMED with ./configure –enable-modules=adjmat . Furthermore, this feature is still being developed so take care when using it and report any problems on the mailing list.

Calculate functions of the distribution of properties in your connected components.

This collective variable was developed for looking at nucleation phenomena, where you are interested in using studying the behavior of atoms in small aggregates or nuclei. In these sorts of problems you might be interested in the distribution of the sizes of the clusters in your system. A detailed description of this CV can be found in [66].

Description of components

When the label of this action is used as the input for a second you are not referring to a scalar quantity as you are in regular collective variables. The label is used to reference the full set of quantities calculated by the action. This is usual when using MultiColvar functions. Generally when doing this the previously calculated multicolvar will be referenced using the DATA keyword rather than ARG.

This Action can be used to calculate the following scalar quantities directly. These quantities are calculated by employing the keywords listed below. These quantities can then be referenced elsewhere in the input file by using this Action's label followed by a dot and the name of the quantity. Some amongst them can be calculated multiple times with different parameters. In this case the quantities calculated can be referenced elsewhere in the input by using the name of the quantity followed by a numerical identifier e.g. label.lessthan-1, label.lessthan-2 etc. When doing this and, for clarity we have made the label of the components customizable. As such by using the LABEL keyword in the description of the keyword input you can customize the component name

 Quantity Keyword Description altmin ALT_MIN the minimum value. This is calculated using the formula described in the description of the keyword so as to make it continuous. between BETWEEN the number/fraction of values within a certain range. This is calculated using one of the formula described in the description of the keyword so as to make it continuous. You can calculate this quantity multiple times using different parameters. lessthan LESS_THAN the number of values less than a target value. This is calculated using one of the formula described in the description of the keyword so as to make it continuous. You can calculate this quantity multiple times using different parameters. max MAX the maximum value. This is calculated using the formula described in the description of the keyword so as to make it continuous. min MIN the minimum value. This is calculated using the formula described in the description of the keyword so as to make it continuous. morethan MORE_THAN the number of values more than a target value. This is calculated using one of the formula described in the description of the keyword so as to make it continuous. You can calculate this quantity multiple times using different parameters.
Compulsory keywords
 CLUSTERS the label of the action that does the clustering TRANSFORM ( default=none ) the switching function to use to convert the crystallinity parameter to a number between zero and one
Options
 NUMERICAL_DERIVATIVES ( default=off ) calculate the derivatives for these quantities numerically NOPBC ( default=off ) ignore the periodic boundary conditions when calculating distances SERIAL ( default=off ) do the calculation in serial. Do not parallelize LOWMEM ( default=off ) lower the memory requirements TIMINGS ( default=off ) output information on the timings of the various parts of the calculation INVERSE_TRANSFORM ( default=off ) when TRANSFORM appears alone the input symmetry functions, $$x$$ are transformed used $$1-s(x)$$ where $$s(x)$$ is a switching function. When this option is used you instead transform using $$s(x)$$ only. MORE_THAN calculate the number of variables more than a certain target value. This quantity is calculated using $$\sum_i 1.0 - \sigma(s_i)$$, where $$\sigma(s)$$ is a switchingfunction. The final value can be referenced using label.morethan. You can use multiple instances of this keyword i.e. MORE_THAN1, MORE_THAN2, MORE_THAN3... The corresponding values are then referenced using label.morethan-1, label.morethan-2, label.morethan-3... LESS_THAN calculate the number of variables less than a certain target value. This quantity is calculated using $$\sum_i \sigma(s_i)$$, where $$\sigma(s)$$ is a switchingfunction. The final value can be referenced using label.lessthan. You can use multiple instances of this keyword i.e. LESS_THAN1, LESS_THAN2, LESS_THAN3... The corresponding values are then referenced using label.lessthan-1, label.lessthan-2, label.lessthan-3... BETWEEN calculate the number of values that are within a certain range. These quantities are calculated using kernel density estimation as described on histogrambead. The final value can be referenced using label.between. You can use multiple instances of this keyword i.e. BETWEEN1, BETWEEN2, BETWEEN3... The corresponding values are then referenced using label.between-1, label.between-2, label.between-3... HISTOGRAM calculate a discretized histogram of the distribution of values. This shortcut allows you to calculates NBIN quantites like BETWEEN. The final value can be referenced using label.histogram. You can use multiple instances of this keyword i.e. HISTOGRAM1, HISTOGRAM2, HISTOGRAM3... The corresponding values are then referenced using label.histogram-1, label.histogram-2, label.histogram-3... ALT_MIN calculate the minimum value. To make this quantity continuous the minimum is calculated using $$\textrm{min} = -\frac{1}{\beta} \log \sum_i \exp\left( -\beta s_i \right)$$ The value of $$\beta$$ in this function is specified using (BETA= $$\beta$$). The final value can be referenced using label.altmin. You can use multiple instances of this keyword i.e. ALT_MIN1, ALT_MIN2, ALT_MIN3... The corresponding values are then referenced using label.altmin-1, label.altmin-2, label.altmin-3... MIN calculate the minimum value. To make this quantity continuous the minimum is calculated using $$\textrm{min} = \frac{\beta}{ \log \sum_i \exp\left( \frac{\beta}{s_i} \right) }$$ The value of $$\beta$$ in this function is specified using (BETA= $$\beta$$) The final value can be referenced using label.min. You can use multiple instances of this keyword i.e. MIN1, MIN2, MIN3... The corresponding values are then referenced using label.min-1, label.min-2, label.min-3... MAX calculate the maximum value. To make this quantity continuous the maximum is calculated using $$\textrm{max} = \beta \log \sum_i \exp\left( \frac{s_i}{\beta}\right)$$ The value of $$\beta$$ in this function is specified using (BETA= $$\beta$$) The final value can be referenced using label.max. You can use multiple instances of this keyword i.e. MAX1, MAX2, MAX3... The corresponding values are then referenced using label.max-1, label.max-2, label.max-3...
Examples

The input provided below calculates the local q6 Steinhardt parameter on each atom. The coordination number that atoms with a high value for the local q6 Steinhardt parameter have with other atoms that have a high value for the local q6 Steinhardt parameter is then computed. A contact matrix is then computed that measures whether atoms atoms $$i$$ and $$j$$ have a high value for this coordination number and if they are within 3.6 nm of each other. The connected components of this matrix are then found using a depth first clustering algorithm on the corresponding graph. The number of componets in this graph that contain more than 27 atoms is then computed. As discussed in [66] this input was used to analyse the formation of a polycrystal of GeTe from amorphous GeTe.

q6: Q6 SPECIES=1-32768 SWITCH={GAUSSIAN D_0=5.29 R_0=0.01 D_MAX=5.3} LOWMEM
lq6: LOCAL_Q6 SPECIES=q6 SWITCH={GAUSSIAN D_0=5.29 R_0=0.01 D_MAX=5.3} LOWMEM
flq6: MFILTER_MORE DATA=lq6 SWITCH={GAUSSIAN D_0=0.19 R_0=0.01 D_MAX=0.2}
cc: COORDINATIONNUMBER SPECIES=flq6 SWITCH={GAUSSIAN D_0=3.59 R_0=0.01 D_MAX=3.6}
fcc: MFILTER_MORE DATA=cc SWITCH={GAUSSIAN D_0=5.99 R_0=0.01 D_MAX=6.0}
mat: CONTACT_MATRIX ATOMS=fcc SWITCH={GAUSSIAN D_0=3.59 R_0=0.01 D_MAX=3.6}
dfs: DFSCLUSTERING MATRIX=mat
nclust: CLUSTER_DISTRIBUTION CLUSTERS=dfs TRANSFORM={GAUSSIAN D_0=5.99 R_0=0.01 D_MAX=6.0} MORE_THAN={GAUSSIAN D_0=26.99 R_0=0.01 D_MAX=27}
PRINT ARG=nclust.* FILE=colvar