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+ + + + + + + + + + + + + + + + +
+ Bases: ChainConfig
The numerical chain with its configuration.
+ +src/chainconsumer/chain.py
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|
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶weight_column: ColumnName = Field(default='weight', description='The name of the weight column, if it exists')
+
class-attribute
+ instance-attribute
+
+
+¶posterior_column: ColumnName = Field(default='log_posterior', description='The name of the log posterior column, if it exists')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶num_free_params: int | None = Field(default=None, description='The number of free parameters in the chain', ge=0)
+
class-attribute
+ instance-attribute
+
+
+¶num_eff_data_points: float | None = Field(default=None, description='The number of effective data points', ge=0)
+
class-attribute
+ instance-attribute
+
+
+¶power: float = Field(default=1.0, description='Raise the posterior surface to this. Useful for inflating or deflating uncertainty for debugging.')
+
property
+
+
+¶The columns in the dataframe which are not weights or posteriors.
+property
+
+
+¶The subsection of the dataframe with data points (ie excluding weights and posterior)
+property
+
+
+¶The columns to be plotted, which are the dataframe columns +with the weights, posterior and colour coloumns removed.
+property
+
+
+¶If the chain will be skipped in plotting because it has nothing to plot.
+property
+
+
+¶The row of samples which correspond to the maximum posterior value. +None if the posterior is not supplied.
+property
+
+
+¶The column of weights in the samples.
+property
+
+
+¶The column of log posteriors in the samples. None if not set.
+property
+
+
+¶The data from the color column. None if not set.
+classmethod
+
+
+¶from_covariance(mean: np.ndarray | list[float], covariance: np.ndarray | list[list[float]], columns: list[ColumnName], name: ChainName, **kwargs: Any) -> Chain
+
Generate samples as per mean and covariance supplied. Useful for Fisher matrix forecasts.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
mean |
+
+ ndarray | list[float]
+ |
+
+
+
+ The an array of mean values. + |
+ + required + | +
covariance |
+
+ ndarray | list[list[float]]
+ |
+
+
+
+ The 2D array describing the covariance.
+Dimensions should agree with the |
+ + required + | +
columns |
+
+ list[ColumnName]
+ |
+
+
+
+ A list of parameter names, one for each column (dimension) in the mean array. + |
+ + required + | +
name |
+
+ ChainName
+ |
+
+
+
+ The name of the chain. + |
+ + required + | +
kwargs |
+
+ Any
+ |
+
+
+
+ Any other arguments to pass to the Chain constructor. + |
+
+ {}
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Chain
+ |
+
+
+
+ The generated chain. + |
+
src/chainconsumer/chain.py
Returns a ChainConsumer instance containing all the walks of a given chain +as individual chains themselves.
+This method might be useful if, for example, your chain was made using +MCMC with 4 walkers. To check the sampling of all 4 walkers agree, you could +call this to get a ChainConsumer instance with one chain for ech of the +four walks. If you then plot, hopefully all four contours +you would see agree.
+ + + +Returns:
+Type | +Description | +
---|---|
+ list[Chain]
+ |
+
+
+
+ One chain per walker, split evenly + |
+
src/chainconsumer/chain.py
Returns the maximum posterior point in the chain. If the posterior
+ + + +Returns:
+Name | Type | +Description | +
---|---|---|
MaxPosterior |
+ MaxPosterior | None
+ |
+
+
+
+ The maximum posterior point + |
+
src/chainconsumer/chain.py
Returns the covariance matrix of the chain.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
columns |
+
+ list[str] | None
+ |
+
+
+
+ The columns to use. None means all data columns. + |
+
+ None
+ |
+
Returns:
+Name | Type | +Description | +
---|---|---|
Named2DMatrix |
+ Named2DMatrix
+ |
+
+
+
+ The covariance matrix + |
+
src/chainconsumer/chain.py
Returns the correlation matrix of the chain.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
columns |
+
+ list[str] | None
+ |
+
+
+
+ The columns to use. None means all data columns. + |
+
+ None
+ |
+
Returns:
+Name | Type | +Description | +
---|---|---|
Named2DMatrix |
+ Named2DMatrix
+ |
+
+
+
+ The correlation matrix + |
+
src/chainconsumer/chain.py
classmethod
+
+
+¶from_emcee(sampler: emcee.EnsembleSampler, columns: list[str], name: str, thin: int = 1, discard: int = 0, **kwargs: Any) -> Chain
+
Constructor from an emcee sampler
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
sampler |
+
+ EnsembleSampler
+ |
+
+
+
+ The emcee sampler + |
+ + required + | +
columns |
+
+ list[str]
+ |
+
+
+
+ The names of the parameters + |
+ + required + | +
name |
+
+ str
+ |
+
+
+
+ The name of the chain + |
+ + required + | +
thin |
+
+ int
+ |
+
+
+
+ The thinning to apply to the chain + |
+
+ 1
+ |
+
discard |
+
+ int
+ |
+
+
+
+ The number of steps to discard from the start of the chain + |
+
+ 0
+ |
+
kwargs |
+
+ Any
+ |
+
+
+
+ Any other arguments to pass to the Chain constructor. + |
+
+ {}
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Chain
+ |
+
+
+
+ A ChainConsumer Chain made from the emcee samples + |
+
src/chainconsumer/chain.py
classmethod
+
+
+¶Constructor from numpyro samples
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
mcmc |
+
+ MCMC
+ |
+
+
+
+ The numpyro sampler + |
+ + required + | +
name |
+
+ str
+ |
+
+
+
+ The name of the chain + |
+ + required + | +
kwargs |
+
+ Any
+ |
+
+
+
+ Any other arguments to pass to the Chain constructor. + |
+
+ {}
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Chain
+ |
+
+
+
+ A ChainConsumer Chain made from numpyro samples + |
+
src/chainconsumer/chain.py
classmethod
+
+
+¶Constructor from an arviz InferenceData object
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
arviz_id |
+
+ InferenceData
+ |
+
+
+
+ The arviz inference data + |
+ + required + | +
name |
+
+ str
+ |
+
+
+
+ The name of the chain + |
+ + required + | +
kwargs |
+
+ Any
+ |
+
+
+
+ Any other arguments to pass to the Chain constructor. + |
+
+ {}
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Chain
+ |
+
+
+
+ A ChainConsumer Chain made from the arviz chain + |
+
src/chainconsumer/chain.py
+ Bases: BetterBase
The configuration for a chain. This is used to set the default values for +plotting chains, and is also used to store the configuration of a chain.
+Note that some attributes are defaulted to None instead of their type hint. +Like color. This indicates that this parameter should be inferred if not explicitly +set, and that this inference requires knowledge of the other chains. For example, +if you have two chains, you probably want them to be different colors.
+ +src/chainconsumer/chain.py
class-attribute
+ instance-attribute
+
+
+¶statistics: SummaryStatistic = Field(default=SummaryStatistic.MAX, description='The summary statistic to use')
+
class-attribute
+ instance-attribute
+
+
+¶summary_area: float = Field(default=0.6827, ge=0, le=1.0, description='The area to use for summary statistics')
+
class-attribute
+ instance-attribute
+
+
+¶sigmas: list[float] = Field(default=[0, 1, 2], description='The sigmas to use for summary statistics')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶smooth: int = Field(default=3, description='The smoothing for histograms. Set to 0 for no smoothing')
+
class-attribute
+ instance-attribute
+
+
+¶color_param: str | None = Field(default=None, description='The parameter (column) to use for coloring')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶shift_params: bool = Field(default=False, description='Whether to shift the parameters by subtracting each parameters mean')
+
The ChainConsumer acts as manager and state holder, to which you supply configured pydantic objects to dictate the behaviour of your plots and analyses.
+A class for consuming chains produced by an MCMC walk. Or grid searches. To make plots, +figures, tables, diagnostics, you name it.
+ +src/chainconsumer/chainconsumer.py
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|
instance-attribute
+
+
+¶Use this to access all the plotting functions
+instance-attribute
+
+
+¶Use this to access your diagnostics to see if chains have converged.
+instance-attribute
+
+
+¶Use this to compare chains to each other, like ranking the AIC, BIC, and DIC.
+instance-attribute
+
+
+¶Use this to access the analysis functions, like getting summary statistics from your chains.
+Add a truth to ChainConsumer.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
truth |
+
+ Truth
+ |
+
+
+
+ The truth to add. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ ChainConsumer
+ |
+
+
+
+ Itself, to allow chaining calls. + |
+
src/chainconsumer/chainconsumer.py
Add a chain to ChainConsumer.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
chain |
+
+ Chain
+ |
+
+
+
+ The chain to add. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ ChainConsumer
+ |
+
+
+
+ Itself, to allow chaining calls. + |
+
src/chainconsumer/chainconsumer.py
Set the plot config for ChainConsumer.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
plot_config |
+
+ PlotConfig
+ |
+
+
+
+ The plot config to use. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ ChainConsumer
+ |
+
+
+
+ Itself, to allow chaining calls. + |
+
src/chainconsumer/chainconsumer.py
add_marker(location: dict[ColumnName, float], name: str, color: ColorInput | None = None, marker_size: float = 20.0, marker_style: str = '.', marker_alpha: float = 1.0) -> ChainConsumer
+
Add a marker to the plot at the given location.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
location |
+
+ dict[ColumnName, float]
+ |
+
+
+
+ The location of the marker. + |
+ + required + | +
name |
+
+ str
+ |
+
+
+
+ The name of the marker. + |
+ + required + | +
color |
+
+ ColorInput | None
+ |
+
+
+
+ The colour of the marker. Defaults to None. + |
+
+ None
+ |
+
marker_size |
+
+ float
+ |
+
+
+
+ The size of the marker. Defaults to 20.0. + |
+
+ 20.0
+ |
+
marker_style |
+
+ str
+ |
+
+
+
+ The style of the marker. Defaults to ".". + |
+
+ '.'
+ |
+
marker_alpha |
+
+ float
+ |
+
+
+
+ The alpha of the marker. Defaults to 1.0. + |
+
+ 1.0
+ |
+
Returns:
+Type | +Description | +
---|---|
+ ChainConsumer
+ |
+
+
+
+ Itself, to allow chaining calls. + |
+
src/chainconsumer/chainconsumer.py
Removes a chain from ChainConsumer.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
remove |
+
+ str | Chain
+ |
+
+
+
+ The name of the chain to remove, or the chain itself. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ ChainConsumer
+ |
+
+
+
+ Itself, to allow chaining calls. + |
+
src/chainconsumer/chainconsumer.py
Apply a custom override config
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
override |
+
+ ChainConfig
+ |
+
+
+
+ The override config. Defaults to None. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ ChainConsumer
+ |
+
+
+
+ Itself, to allow chaining calls. + |
+
src/chainconsumer/chainconsumer.py
Get a chain by name.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
name |
+
+ str
+ |
+
+
+
+ The name of the chain. + |
+ + required + | +
Returns:
+Type | +Description | +
---|---|
+ Chain
+ |
+
+
+
+ The chain. + |
+
src/chainconsumer/chainconsumer.py
Get the names of all chains.
+Returns: +The names of all chains.
+ + +
+ Bases: BetterBase
src/chainconsumer/plotting/config.py
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶diagonal_tick_labels: bool = Field(default=True, description='Whether to show tick labels on the diagonal')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶contour_label_font_size: int = Field(default=10, ge=0, description='Font size for contour labels')
+
class-attribute
+ instance-attribute
+
+
+¶show_legend: bool | None = Field(default=None, description='Whether to show the legend. None means determine automatically')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶legend_location: tuple[int, int] | None = Field(default=None, description='Which subplot to put the legend in')
+
class-attribute
+ instance-attribute
+
+
+¶legend_artists: bool | None = Field(default=None, description='Whether to show artists in the legend')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶watermark_text_kwargs: dict[str, Any] = Field(default={}, description='Kwargs to pass to the watermark text')
+
class-attribute
+ instance-attribute
+
+
+¶summarise: bool = Field(default=True, description='Whether to annotate the plot with summary statistics')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶sigma2d: bool = Field(default=False, description='Whether to use 2D sigmas for summary statistics. Ie in 2D a 1sigma contour does *not* encapsulate 68% of the volume, it covers 39.3% of the volume.')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶log_scales: list[ColumnName] = Field(default=[], description='Whether to use log scales for some parameters')
+
class-attribute
+ instance-attribute
+
+
+¶extents: dict[ColumnName, tuple[float, float]] = Field(default={}, description="Extents for parameters. Any you don't specify are determined automatically")
+
class-attribute
+ instance-attribute
+
+
+¶property
+
+
+¶property
+
+
+¶Generally accessible via:
+ + + +src/chainconsumer/plotter.py
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772 + 773 + 774 + 775 + 776 + 777 + 778 + 779 + 780 + 781 + 782 + 783 + 784 + 785 + 786 + 787 + 788 + 789 + 790 + 791 + 792 + 793 + 794 + 795 + 796 + 797 + 798 + 799 + 800 + 801 + 802 + 803 + 804 + 805 + 806 + 807 + 808 + 809 + 810 + 811 + 812 + 813 + 814 + 815 + 816 + 817 + 818 + 819 + 820 + 821 + 822 + 823 + 824 + 825 + 826 + 827 + 828 + 829 + 830 + 831 + 832 + 833 + 834 + 835 + 836 + 837 + 838 + 839 + 840 + 841 + 842 + 843 + 844 + 845 + 846 + 847 + 848 + 849 + 850 + 851 + 852 + 853 + 854 + 855 + 856 + 857 + 858 + 859 + 860 + 861 + 862 + 863 + 864 + 865 + 866 + 867 + 868 + 869 + 870 + 871 + 872 + 873 + 874 + 875 + 876 + 877 + 878 + 879 + 880 + 881 + 882 + 883 + 884 + 885 + 886 + 887 + 888 + 889 + 890 + 891 + 892 + 893 + 894 + 895 + 896 + 897 + 898 + 899 + 900 + 901 + 902 + 903 + 904 + 905 + 906 + 907 + 908 + 909 + 910 + 911 + 912 + 913 + 914 + 915 + 916 + 917 + 918 + 919 + 920 + 921 + 922 + 923 + 924 + 925 + 926 + 927 + 928 + 929 + 930 + 931 + 932 + 933 + 934 + 935 + 936 + 937 + 938 + 939 + 940 + 941 + 942 + 943 + 944 + 945 + 946 + 947 + 948 + 949 + 950 + 951 + 952 + 953 + 954 + 955 + 956 + 957 + 958 + 959 + 960 + 961 + 962 + 963 + 964 + 965 + 966 + 967 + 968 + 969 + 970 + 971 + 972 + 973 + 974 + 975 + 976 + 977 + 978 + 979 + 980 + 981 + 982 + 983 + 984 + 985 + 986 + 987 + 988 + 989 + 990 + 991 + 992 + 993 + 994 + 995 + 996 + 997 + 998 + 999 +1000 +1001 +1002 +1003 +1004 +1005 +1006 +1007 +1008 +1009 +1010 +1011 +1012 +1013 +1014 +1015 +1016 +1017 |
|
plot(chains: list[ChainName | Chain] | None = None, columns: list[ColumnName] | None = None, filename: list[str | Path] | str | Path | None = None, figsize: FigSize | float | int | tuple[float, float] = FigSize.GROW) -> Figure
+
Plot the chain!
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
chains |
+
+ list[ChainName | Chain] | None
+ |
+
+
+
+ Used to specify which chain to show if more than one chain is loaded in. +Can be an integer, specifying the +chain index, or a str, specifying the chain name. + |
+
+ None
+ |
+
columns |
+
+ list[ColumnName] | None
+ |
+
+
+
+ If set, only creates a plot for those specific parameters (if list). If an +integer is given, only plots the fist so many parameters. + |
+
+ None
+ |
+
filename |
+
+ list[str | Path] | str | Path | None
+ |
+
+
+
+ If set, saves the figure to this location + |
+
+ None
+ |
+
figsize |
+
+ FigSize | float | int | tuple[float, float]
+ |
+
+
+
+ The figure size to generate. Accepts a regular two tuple of size in inches,
+or one of several key words. The default value of |
+
+ GROW
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Figure
+ |
+
+
+
+ the matplotlib figure + |
+
src/chainconsumer/plotter.py
130 +131 +132 +133 +134 +135 +136 +137 +138 +139 +140 +141 +142 +143 +144 +145 +146 +147 +148 +149 +150 +151 +152 +153 +154 +155 +156 +157 +158 +159 +160 +161 +162 +163 +164 +165 +166 +167 +168 +169 +170 +171 +172 +173 +174 +175 +176 +177 +178 +179 +180 +181 +182 +183 +184 +185 +186 +187 +188 +189 +190 +191 +192 +193 +194 +195 +196 +197 +198 +199 +200 +201 +202 +203 +204 +205 +206 +207 +208 +209 +210 +211 +212 +213 +214 +215 +216 +217 +218 +219 +220 +221 +222 +223 +224 +225 +226 +227 +228 +229 +230 +231 +232 +233 +234 +235 +236 +237 +238 +239 +240 +241 +242 +243 +244 +245 +246 +247 +248 +249 +250 +251 +252 +253 +254 +255 +256 +257 +258 +259 +260 +261 +262 +263 +264 +265 +266 |
|
Sets the plot config to the chosen PlotConfig
model.
Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
config |
+
+ PlotConfig
+ |
+
+
+
+ The config to use + |
+ + required + | +
plot_walks(chains: list[ChainName | Chain] | None = None, columns: list[ColumnName] | None = None, filename: list[str | Path] | str | Path | None = None, figsize: float | tuple[float, float] | None = None, convolve: int | None = None, plot_weights: bool = True, plot_posterior: bool = True, log_weight: bool = False) -> Figure
+
Plots the chain walk; the parameter values as a function of step index.
+This plot is more for a sanity or consistency check than for use with final results.
+Plotting this before plotting with :func:plot
allows you to quickly see if the
+chains are well behaved, or if certain parameters are suspect
+or require a greater burn in period.
The desired outcome is to see an unchanging distribution along the x-axis of the plot. +If there are obvious tails or features in the parameters, you probably want +to investigate.
+ + + +Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
chains |
+
+ list[ChainName | Chain] | None
+ |
+
+
+
+ Used to specify which chain to show if more than one chain is loaded in. +Can be an integer, specifying the +chain index, or a str, specifying the chain name. + |
+
+ None
+ |
+
columns |
+
+ list[ColumnName] | None
+ |
+
+
+
+ If set, only creates a plot for those specific parameters (if list). If an +integer is given, only plots the fist so many parameters. + |
+
+ None
+ |
+
filename |
+
+ list[str | Path] | str | Path | None
+ |
+
+
+
+ If set, saves the figure to this location + |
+
+ None
+ |
+
figsize |
+
+ float | tuple[float, float] | None
+ |
+
+
+
+ Scale horizontal and vertical figure size. + |
+
+ None
+ |
+
col_wrap |
+ + | +
+
+
+ How many columns to plot before wrapping. + |
+ + required + | +
convolve |
+
+ int | None
+ |
+
+
+
+ If set, overplots a smoothed version of the steps using |
+
+ None
+ |
+
plot_weights |
+
+ bool
+ |
+
+
+
+ If true, plots the weight if they are available + |
+
+ True
+ |
+
plot_posterior |
+
+ bool
+ |
+
+
+
+ If true, plots the log posterior if they are available + |
+
+ True
+ |
+
log_weight |
+
+ bool
+ |
+
+
+
+ Whether to display weights in log space or not. If None, the value is +inferred by the mean weights of the plotted chains. + |
+
+ False
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Figure
+ |
+
+
+
+ the matplotlib figure created + |
+
src/chainconsumer/plotter.py
275 +276 +277 +278 +279 +280 +281 +282 +283 +284 +285 +286 +287 +288 +289 +290 +291 +292 +293 +294 +295 +296 +297 +298 +299 +300 +301 +302 +303 +304 +305 +306 +307 +308 +309 +310 +311 +312 +313 +314 +315 +316 +317 +318 +319 +320 +321 +322 +323 +324 +325 +326 +327 +328 +329 +330 +331 +332 +333 +334 +335 +336 +337 +338 +339 +340 +341 +342 +343 +344 +345 +346 +347 +348 +349 +350 +351 +352 +353 +354 +355 +356 +357 +358 +359 +360 +361 +362 +363 +364 +365 +366 +367 +368 +369 +370 +371 +372 +373 +374 +375 +376 +377 +378 +379 +380 +381 +382 +383 +384 +385 +386 +387 +388 +389 +390 +391 +392 +393 +394 +395 +396 +397 +398 +399 +400 +401 +402 +403 +404 +405 +406 +407 +408 +409 +410 +411 +412 |
|
plot_distributions(chains: list[ChainName | Chain] | None = None, columns: list[ColumnName] | None = None, filename: list[str | Path] | str | Path | None = None, col_wrap: int = 4, figsize: float | tuple[float, float] | None = None) -> Figure
+
Plots the 1D parameter distributions for verification purposes.
+This plot is more for a sanity or consistency check than for use with final results.
+Plotting this before plotting with :func:plot
allows you to quickly see if the
+chains give well behaved distributions, or if certain parameters are suspect
+or require a greater burn in period.
Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
chains |
+
+ list[ChainName | Chain] | None
+ |
+
+
+
+ Used to specify which chain to show if more than one chain is loaded in. +Can be an integer, specifying the +chain index, or a str, specifying the chain name. + |
+
+ None
+ |
+
columns |
+
+ list[ColumnName] | None
+ |
+
+
+
+ If set, only creates a plot for those specific parameters (if list). If an +integer is given, only plots the fist so many parameters. + |
+
+ None
+ |
+
filename |
+
+ list[str | Path] | str | Path | None
+ |
+
+
+
+ If set, saves the figure to this location + |
+
+ None
+ |
+
figsize |
+
+ float | tuple[float, float] | None
+ |
+
+
+
+ Scale horizontal and vertical figure size. + |
+
+ None
+ |
+
col_wrap |
+
+ int
+ |
+
+
+
+ How many columns to plot before wrapping. + |
+
+ 4
+ |
+
Returns:
+Type | +Description | +
---|---|
+ Figure
+ |
+
+
+
+ the matplotlib figure created + |
+
src/chainconsumer/plotter.py
414 +415 +416 +417 +418 +419 +420 +421 +422 +423 +424 +425 +426 +427 +428 +429 +430 +431 +432 +433 +434 +435 +436 +437 +438 +439 +440 +441 +442 +443 +444 +445 +446 +447 +448 +449 +450 +451 +452 +453 +454 +455 +456 +457 +458 +459 +460 +461 +462 +463 +464 +465 +466 +467 +468 +469 +470 +471 +472 +473 +474 +475 +476 +477 +478 +479 +480 +481 +482 +483 +484 +485 +486 +487 +488 +489 +490 +491 +492 +493 +494 +495 +496 +497 +498 +499 +500 +501 +502 +503 +504 +505 +506 +507 +508 +509 +510 +511 +512 +513 +514 |
|
plot_summary(chains: list[ChainName | Chain] | None = None, columns: list[ColumnName] | None = None, filename: list[str | Path] | str | Path | None = None, figsize: float = 1.0, errorbar: bool = False, extra_parameter_spacing: float = 1.0, vertical_spacing_ratio: float = 1.0) -> Figure
+
Plots parameter summaries
+This plot is more for a sanity or consistency check than for use with final results.
+Plotting this before plotting with :func:plot
allows you to quickly see if the
+chains give well behaved distributions, or if certain parameters are suspect
+or require a greater burn in period.
Parameters:
+Name | +Type | +Description | +Default | +
---|---|---|---|
chains |
+
+ list[ChainName | Chain] | None
+ |
+
+
+
+ Used to specify which chain to show if more than one chain is loaded in. +Can be an integer, specifying the +chain index, or a str, specifying the chain name. + |
+
+ None
+ |
+
columns |
+
+ list[ColumnName] | None
+ |
+
+
+
+ If set, only creates a plot for those specific parameters (if list). If an +integer is given, only plots the fist so many parameters. + |
+
+ None
+ |
+
filename |
+
+ list[str | Path] | str | Path | None
+ |
+
+
+
+ If set, saves the figure to this location + |
+
+ None
+ |
+
figsize |
+
+ float
+ |
+
+
+
+ Scale horizontal and vertical figure size. + |
+
+ 1.0
+ |
+
errorbar |
+
+ bool
+ |
+
+
+
+ Whether to onle plot an error bar, instead of the marginalised distribution. + |
+
+ False
+ |
+
include_truth_chain |
+ + | +
+
+
+ If you specify another chain as the truth chain, determine if it should still +be plotted. + |
+ + required + | +
extra_parameter_spacing |
+
+ float
+ |
+
+
+
+ Increase horizontal space for parameter values + |
+
+ 1.0
+ |
+
vertical_spacing_ratio |
+
+ float
+ |
+
+
+
+ Increase vertical space for each model + |
+
+ 1.0
+ |
+
Returns: + the matplotlib figure created
+ +src/chainconsumer/plotter.py
516 +517 +518 +519 +520 +521 +522 +523 +524 +525 +526 +527 +528 +529 +530 +531 +532 +533 +534 +535 +536 +537 +538 +539 +540 +541 +542 +543 +544 +545 +546 +547 +548 +549 +550 +551 +552 +553 +554 +555 +556 +557 +558 +559 +560 +561 +562 +563 +564 +565 +566 +567 +568 +569 +570 +571 +572 +573 +574 +575 +576 +577 +578 +579 +580 +581 +582 +583 +584 +585 +586 +587 +588 +589 +590 +591 +592 +593 +594 +595 +596 +597 +598 +599 +600 +601 +602 +603 +604 +605 +606 +607 +608 +609 +610 +611 +612 +613 +614 +615 +616 +617 +618 +619 +620 +621 +622 +623 +624 +625 +626 +627 +628 +629 +630 +631 +632 +633 +634 +635 +636 +637 +638 +639 +640 +641 +642 +643 +644 +645 +646 +647 +648 +649 +650 +651 +652 +653 +654 +655 +656 +657 +658 +659 +660 +661 +662 +663 +664 +665 +666 |
|
+ Bases: BetterBase
src/chainconsumer/truth.py
class-attribute
+ instance-attribute
+
+
+¶location: dict[str, float] = Field(default=..., description='The truth value, either as dictionary or pandas series which will be converted to a dict)')
+
class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶class-attribute
+ instance-attribute
+
+
+¶{"use strict";/*!
+ * escape-html
+ * Copyright(c) 2012-2013 TJ Holowaychuk
+ * Copyright(c) 2015 Andreas Lubbe
+ * Copyright(c) 2015 Tiancheng "Timothy" Gu
+ * MIT Licensed
+ */var Ha=/["'&<>]/;Un.exports=$a;function $a(e){var t=""+e,r=Ha.exec(t);if(!r)return t;var o,n="",i=0,s=0;for(i=r.index;i