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"numbagg", "opt-einsum", "scipy"] complete = ["xarray[accel,dev,io,parallel,viz]"] -dev = ["hypothesis", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "xarray[complete]"] +dev = ["hypothesis", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "xarray[complete]"] io = ["cftime", "fsspec", "h5netcdf", "netCDF4", "pooch", "pydap", "scipy", "zarr"] parallel = ["dask[complete]"] viz = ["matplotlib", "nc-time-axis", "seaborn"] diff --git a/src/chainconsumer/analysis.py b/src/chainconsumer/analysis.py index 0e81688c..68260392 100644 --- a/src/chainconsumer/analysis.py +++ b/src/chainconsumer/analysis.py @@ -6,7 +6,7 @@ import numpy as np from pydantic import Field -from scipy.integrate import simps +from scipy.integrate import simpson as simps from scipy.interpolate import interp1d from scipy.ndimage import gaussian_filter @@ -320,7 +320,7 @@ def _get_2d_latex_table(self, named_matrix: Named2DMatrix, caption: str, label: for p, row in zip(parameters, matrix): table += format_string % p for r in row: - table += " & %5.2f" % r + table += f" & {r:5.2f}" table += " \\\\ \n" table += hline_text return latex_table % (column_def, table) @@ -396,7 +396,7 @@ def get_parameter_text(self, bound: Bound, wrap: bool = False): if factor != 0: text = r"\left( %s \right) \times 10^{%d}" % (text, -factor) if wrap: - text = "$%s$" % text + text = f"${text}$" return text def get_parameter_summary_mean(self, chain: Chain, column: ColumnName) -> Bound | None: diff --git a/src/chainconsumer/comparisons.py b/src/chainconsumer/comparisons.py index 876162de..70a9ae58 100644 --- a/src/chainconsumer/comparisons.py +++ b/src/chainconsumer/comparisons.py @@ -39,7 +39,7 @@ def dic(self) -> dict[str, float]: for name, chain in self.parent._chains.items(): p = chain.log_posterior if p is None: - logger.warning("You need to set the posterior for chain %s to get the DIC" % chain.name) + logger.warning(f"You need to set the posterior for chain {chain.name} to get the DIC") else: means = np.array([np.average(chain.samples[c], weights=chain.weights) for c in chain.data_columns]) d = -2 * p diff --git a/src/chainconsumer/diagnostic.py b/src/chainconsumer/diagnostic.py index 16765776..9335e0cf 100644 --- a/src/chainconsumer/diagnostic.py +++ b/src/chainconsumer/diagnostic.py @@ -29,7 +29,7 @@ def _sanitise_chains( class Diagnostic: def __init__(self, parent: "ChainConsumer"): - self.parent: "ChainConsumer" = parent + self.parent: ChainConsumer = parent def gelman_rubin( self, chains: list[Chain | ChainName] | Chain | ChainName | None = None, threshold: float = 0.05 @@ -87,7 +87,7 @@ def gelman_rubin( r: float = np.sqrt(v / w) passed = np.abs(r - 1) < threshold - logger.info("Gelman-Rubin Statistic values for chain %s" % name) + logger.info(f"Gelman-Rubin Statistic values for chain {name}") for p, v, pas in zip(parameters, r, passed): param = "Param %d" % p if isinstance(p, int) else p logger.info(f"{param}: {v:7.5f} ({'Passed' if pas else 'Failed'})") diff --git a/src/chainconsumer/plotter.py b/src/chainconsumer/plotter.py index f6a31e0b..620dd236 100644 --- a/src/chainconsumer/plotter.py +++ b/src/chainconsumer/plotter.py @@ -107,7 +107,7 @@ def get_artists_from_chains(chains: list[Chain]) -> list[Artist]: class Plotter: def __init__(self, parent: "ChainConsumer") -> None: - self.parent: "ChainConsumer" = parent + self.parent: ChainConsumer = parent self._config: PlotConfig | None = None self._default_config = PlotConfig() @@ -983,7 +983,7 @@ def _plot_bars( r"${} = {}$".format(label.strip("$"), t), fontsize=self.config.summary_font_size ) else: - ax.set_title(r"$%s$" % t, fontsize=self.config.summary_font_size) + ax.set_title(rf"${t}$", fontsize=self.config.summary_font_size) return float(ys.max()) def _plot_walk(