import os
from pathlib import Path
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from dataclasses import dataclass, field
from matplotlib import colors as mcolors
from ForMoSA.core.errors import ForMoSAError
# Default filter path (can be overridden by user)
FILTER_PATH = Path.home() / 'filters'
[docs]
def set_filter_path(path: str | os.PathLike) -> None:
'''
Set the global path used to store photometry filters.
Parameters
----------
path : str | os.PathLike
Path to the filters folder
Notes
-----
Authors: Allan Denis
'''
global FILTER_PATH
FILTER_PATH = Path(path).expanduser().resolve()
[docs]
def darken_color(color: str, factor: float = 0.7) -> str:
'''
Darken a matplotlib color.
Parameters
----------
color : str
Any matplotlib-compatible color.
factor : float
Multiplicative factor (<1 darker, >1 lighter)
Returns
-------
str : hex color
Notes
-----
Authors: Allan Denis
'''
rgb = mcolors.to_rgb(color)
dark_rgb = tuple(max(0, min(1, c * factor)) for c in rgb)
return mcolors.to_hex(dark_rgb)
# ==================================================
# General plotting configuration
# ==================================================
[docs]
@dataclass
class MainPlotConfig:
'''
Dataclass to handle main parameters for plotting.
Notes
-----
Authors: Allan Denis
'''
figsize: tuple[float, float] = (10.0, 7.0)
legend_ncol: int = 1
legend_hc_ncol: int = 1
legend_filt_ncol: int = 1
legend_fontsize: str = "small"
minor_ticks: bool = True
nb_minor_ticks: int = 5
MAIN_PLOT = MainPlotConfig()
# ==================================================
# Spectroscopic plotting configuration
# ==================================================
[docs]
@dataclass
class ObsPlotConfig:
'''
Dataclass to handle configurations for plotting data.
Notes
-----
Authors: Allan Denis
'''
# --- Color management
cmap: mcolors.Colormap = field(default_factory = lambda: cm.jet)
color: str = "#7A1E22"
edgecolor: str = None
norm: mcolors.Normalize = field(default_factory = lambda: plt.Normalize(vmin=1.0, vmax=15))
# --- Marker
marker: str = "s"
markersize: int = 40
linewidth: float = 1
# --- Errorbar
errorbar_fmt: str = "None"
errorbar_alpha: float = 1.0
errorbar_capsize: float = 4.0
# --- zorder
zorder_data: int = 3
zorder_error: int = 1
# ---- Legend
label: bool = True
def __post_init__(self):
if self.edgecolor is None or self.edgecolor == "auto":
self.edgecolor = darken_color(self.color)
[docs]
def to_dict(self) -> dict:
'''
Return configuration options as a dictionary.
Notes
-----
Authors: Allan Denis
'''
return {k: v for k, v in self.__dict__.items() if v is not None}
[docs]
def set_plot_config(self, **kwargs) -> None:
'''
Update global default plotting parameters for spectroscopic plots.
Parameters
----------
**kwargs : dict
Keyword arguments to override attributes of the config
Notes
-----
Authors: Allan Denis
'''
for key, value in kwargs.items():
if not hasattr(self, key):
raise ForMoSAError(f'Unknown spectral plot config key: {key}')
setattr(self, key, value)
self.edgecolor = darken_color(self.color)
[docs]
@dataclass
class SpectralPlotConfig(ObsPlotConfig):
'''
Dataclass to handle configurations for plotting spectroscopic data.
Notes
-----
Authors: Allan Denis
'''
color: str = "#7A1E22"
marker: str = "None"
# ==================================================
# Photometric plotting configuration
# ==================================================
[docs]
@dataclass
class PhotometricPlotConfig(ObsPlotConfig):
'''
Dataclass to handle configurations for plotting photometric data.
Notes
-----
Authors: Allan Denis
'''
color: str = "blue"
markersize: int = 70
linewidth: float = 2.0
label_filter: bool = False
label_data: bool = True
# ==================================================
# CornerPlot plotting configuration
# ==================================================
[docs]
@dataclass
class CornerPlotConfig:
'''
Dataclass to handle configurations for corner plots.
Notes
-----
Authors: Allan Denis
'''
figsize: tuple[float, float] = (15.0, 15.0)
color: str = '#A12A1F'
bins: int = 80
smooth: float = 1
smooth1d: float | None = None
plot_datapoints: bool = False
plot_density: bool = True
plot_contours: bool = True
fill_contours: bool = True
quantiles: tuple = (0.16, 0.5, 0.84)
# levels: list = field(default_factory = lambda: [0.997, 0.95, 0.68]) # 3-sigma, 2-sigma, 1-sigma but for 1D Gaussian
levels: list = field(default_factory = lambda: [0.3935, 0.8647, 0.9889]) # 1-sigma, 2-sigma, 2-sigma for 2D Gaussian
show_titles: bool = True
title_fmt: str = " .2f"
hist_kwargs: dict = field(default_factory = lambda: dict(color='#A12A1F', histtype='stepfilled', alpha=0.6, edgecolor='#5B1218', linewidth=0.8))
# contour_kwargs: dict | None = None
contour_kwargs: dict = field(default_factory = lambda: dict(colors='#A12A1F', linewidths=0.8))
pcolor_kwargs: dict = field(default_factory = lambda: dict(color='#5B1218'))
title_kwargs: dict = field(default_factory = lambda: dict(fontsize=14))
label_kwargs: dict = field(default_factory= lambda: dict(fontsize=14))
max_n_ticks: int = 4
@property
def to_dict(self) -> dict:
'''
Return configuration options as a dictionary.
Notes
-----
Authors: Allan Denis
'''
return {k: v for k, v in self.__dict__.items() if v is not None}
[docs]
def set_corner_plot_config(self, **kwargs) -> None:
'''
Update global default plotting parameters for corner plot.
Parameters
----------
**kwargs : dict
Keyword arguments to override attributes of the config
Notes
-----
Authors: Allan Denis
'''
for key, value in kwargs.items():
if not hasattr(self, key):
raise ForMoSAError(f'<Unknown corner plot config key: {key}>')
setattr(self, key, value)
CORNER_PLOT = CornerPlotConfig()
# ==================================================
# Chains plotting configuration
# ==================================================
[docs]
@dataclass
class ChainsPlotConfig:
'''
Dataclass to handle configurations for chains plot.
Notes
-----
Authors: Allan Denis
'''
figsize: tuple[float, float] = (18.0, 12.0)
color_chains: str = "violet"
alpha_chains: float = 0.8
color_plot_burn_in: str = '#A12A1F'
fontsize_burn_in: int = 14
text_burn_in: tuple[float, float] = 0.8, 0.8
color_text_burn_in: str = '#A12A1F'
linestyle_burn_in: str = '--'
show_weights: bool = True
color_plot_weights: str = '#1F1F1F'
fontsize_weights: int = 14
alpha_weights: float = 0.4
text_weights: tuple[float, float] = 0.8, 0.7
color_text_weights: str = '#1F1F1F'
plot_best_value: bool = True
color_best_value: str = 'black'
linestyle_best_value: str = '-.'
@property
def to_dict(self) -> dict:
'''
Return configuration options as a dictionary.
Notes
-----
Authors: Allan Denis
'''
return {k: v for k, v in self.__dict__.items() if v is not None}
[docs]
def set_chains_plot_config(self, **kwargs) -> None:
'''
Update global default plotting parameters for chains plot.
Parameters
----------
**kwargs : dict
Keyword arguments to override attributes of the config
Notes
-----
Authors: Allan Denis
'''
for key, value in kwargs.items():
if not hasattr(self, key):
raise ForMoSAError(f'<Unknown chains plot config key: {key}>')
setattr(self, key, value)
CHAINS_PLOT = ChainsPlotConfig()
# ==================================================
# Radar plotting configuration
# ==================================================
[docs]
@dataclass
class RadarPlotConfig:
'''
Dataclass to handle configurations for radar plot.
Notes
-----
Authors: Allan Denis
'''
figsize: tuple[float, float] = (6.0, 6.0)
# Improved color scheme - using a sophisticated blue-purple gradient
main_color = '#4A5FD9' # Deep blue
fill_color = '#6B7FE8' # Lighter blue
uncertainty_color = '#A8B3F5' # Very light blue
color_radar: str = '#4A5FD9'
color_uncertainty: str = '#4A5FD9' # Use the same deep blue for quantiles
linewidth: float = 2.0
fontsize_names: int = 11
fontsize_ticks: int = 11
color_ticks: str = '#24292E'
show_ticks: bool = False
alpha_fill: float = 0.35
quantiles: tuple[float, float] = (0.16, 0.84)
size_quantiles: int = 80
color_quantiles: str = '#4A5FD9'
lw_quantiles: float = 2.0
@property
def to_dict(self) -> dict:
'''
Return configuration options as a dictionary.
Notes
-----
Authors: Allan Denis
'''
return {k: v for k, v in self.__dict__.items() if v is not None}
[docs]
def set_radar_plot_config(self, **kwargs) -> None:
'''
Update global default plotting parameters for radar plot.
Parameters
----------
**kwargs : dict
Keyword arguments to override attributes of the config
Notes
-----
Authors: Allan Denis
'''
for key, value in kwargs.items():
if not hasattr(self, key):
raise ForMoSAError(f'<Unknown radar plot config key: {key}>')
setattr(self, key, value)
RADAR_PLOT = RadarPlotConfig()
# ==================================================
# Best fit plotting configuration
# ==================================================
[docs]
@dataclass
class BestFitPlotConfig:
'''
Dataclass to handle configurations for best fit plot.
Notes
-----
Authors: Allan Denis
'''
color_fit: str = 'black'
color_residuals: str = "#2C2C2C"
linewidth: float = 1.0
zorder: int = 200
@property
def to_dict(self) -> dict:
'''
Return configuration options as a dictionary.
Notes
-----
Authors: Allan Denis
'''
return {k: v for k, v in self.__dict__.items() if v is not None}
[docs]
def set_best_fit_plot_config(self, **kwargs) -> None:
'''
Update global default plotting parameters for best fit plot.
Parameters
----------
**kwargs : dict
Keyword arguments to override attributes of the config
Notes
-----
Authors: Allan Denis
'''
for key, value in kwargs.items():
if not hasattr(self, key):
raise ForMoSAError(f'<Unknown best fit plot config key: {key}>')
setattr(self, key, value)
BEST_FIT_PLOT = BestFitPlotConfig()
[docs]
@dataclass
class PlotsConfig:
'''
Dataclass to handle configurations for plots.
Notes
-----
Authors: Allan Denis
'''
CornerPlot: CornerPlotConfig = field(default_factory = lambda: CORNER_PLOT)
ChainsPlot: ChainsPlotConfig = field(default_factory = lambda: CHAINS_PLOT)
RadarPlot: RadarPlotConfig = field(default_factory = lambda: RADAR_PLOT)
BestFitPlot: BestFitPlotConfig = field(default_factory = lambda: BEST_FIT_PLOT)
def __post_init__(self):
for name, instance in zip(['CornerPlot', 'ChainsPlot', 'RadarPlot', 'BestFitPlot'], [CornerPlotConfig, ChainsPlotConfig, RadarPlotConfig, BestFitPlotConfig]):
value = getattr(self, name)
if not isinstance(value, instance):
raise ForMoSAError(f'Wrong type for {name}. Expected {instance}')
@property
def to_dict(self) -> dict:
data = {}
for name in ['CornerPlot', 'ChainsPlot', 'RadarPlot', 'BestFitPlot']:
value = getattr(self, name).to_dict
data[name] = value
return data
PLOTS_CONFIG = PlotsConfig()
