# Plot Types

PoPy’s grph and vpc are highly configurable, but for everyday use PoPy comes with a variety of preset plots that will be familiar to those working in PK/PD.

These presets are added in the grph_list option (for single populations) and vpc_list option (for simulated datasets of many populations).

## Individual Observations vs. Time

Adding “OBS_vs_TIME” to grph_list creates a plot of predictions (line on the y-axis) and observations (points on the y-axis) against Time (on the x-axis) for each individual in the population.

    GRPH:
        grph_list: ["OBS_vs_TIME"]

Table 71 Individual Observations vs Time for three individuals from a population

## Population Observations vs. Time

Adding “{OBS}_vs_TIME” to grph_list creates a single plot of predictions (line on the y-axis) and observations (points on the y-axis) against Time (on the x-axis) for the whole population, overlaying individual data on the same graph.

    GRPH:
        grph_list: ["{OBS}_vs_TIME"]

Fig. 53 Population Observations vs Time for a whole population

## Population Observations vs. Individual Predictions

Adding “{OBS}_vs_IPRED” to grph_list creates a scatter plot for the whole population with Observations on the y-axis against Individualised (i.e. incorporating random effects) Predictions on the x-axis.

    GRPH:
        grph_list: ["{OBS}_vs_IPRED"]

Fig. 54 Population Observations vs Individual Predictions for a whole population

## Population Observations vs. Population Predictions

Adding “{OBS}_vs_PRED” to grph_list creates a scatter plot for the whole population with Observations on the y-axis against Population (i.e. using only fixed effects) Predictions on the x-axis.

    GRPH:
        grph_list: ["{OBS}_vs_PRED"]

Fig. 55 Population Observations vs Population Predictions for a whole population

## Individual Residuals vs. Individual Predictions

Adding “{IRES}_vs_IPRED” to grph_list creates a scatter plot for the whole population with Individualised (i.e. incorporating random effects) Residuals on the y-axis against Individualised Predictions on the x-axis.

    GRPH:
        grph_list: ["{IRES}_vs_IPRED"]

Fig. 56 Individual Residuals vs. Individual Predictions for a whole population

## Individual Weighted Residuals vs. Individual Predictions

Adding “{IWRES}_vs_IPRED” to grph_list creates a scatter plot for the whole population with Individualised (i.e. incorporating random effects) Weighted (i.e. normalized with respect to the variance) Residuals on the y-axis against Individualised Predictions on the x-axis.

    GRPH:
        grph_list: ["{IWRES}_vs_IPRED"]

Fig. 57 Individual Weighted Residuals vs. Individual Predictions for a whole population

## Individual Observations vs Time (VPC)

Adding “OBS_vs_TIME_VPC” to vpc_list creates a Visual Predictive Check plot that shows the percentiles of predictions and observations, and gives you some indication of whether the estimated model parameters represent a distribution that is close to the observed data.

    VPC:
        vpc_list: ["OBS_vs_TIME_VPC"]

Fig. 58 Individual Observations vs Time VPC for 100 populations