From 5c66bb3ff17f8152f789945f578e3fd905078659 Mon Sep 17 00:00:00 2001 From: Jonathan Anns Date: Tue, 7 Jan 2025 15:25:19 +0800 Subject: [PATCH 1/3] Forest plot updates - major code changes, tutorial updates, image tests, --- dabest/_modidx.py | 6 +- dabest/forest_plot.py | 662 ++++++++++++------ dabest/plot_tools.py | 2 +- dabest/plotter.py | 2 +- nbs/API/forest_plot.ipynb | 660 +++++++++++------ nbs/API/plot_tools.ipynb | 2 +- nbs/API/plotter.ipynb | 2 +- nbs/tests/data/mocked_data_test_forestplot.py | 17 +- .../test_13_multi_2group_color.png | Bin 44443 -> 44208 bytes .../test_15_change_palette_a.png | Bin 47126 -> 46885 bytes .../test_201_forest_plot_no_colorpalette.png | Bin 15885 -> 0 bytes ...test_202_forest_plot_with_colorpalette.png | Bin 15945 -> 0 bytes ...horizontal_forest_plot_no_colorpalette.png | Bin 15278 -> 0 bytes ...rizontal_forest_plot_with_colorpalette.png | Bin 15381 -> 0 bytes .../test_205_forest_mini_meta_horizontal.png | Bin 15780 -> 0 bytes .../test_206_forest_mini_meta.png | Bin 15365 -> 0 bytes .../test_315_multi2group_color.png | Bin 33253 -> 33051 bytes ..._multi2group_unpaired_change_palette_a.png | Bin 33301 -> 33078 bytes .../test_500_deltadelta_forest.png | Bin 0 -> 14167 bytes ..._501_deltadelta_with_deltas_idx_forest.png | Bin 0 -> 23778 bytes .../test_502_minimeta_forest.png | Bin 0 -> 15306 bytes ...st_503_deltadelta_custompalette_forest.png | Bin 0 -> 14247 bytes .../test_504_deltadelta_horizontal_forest.png | Bin 0 -> 13735 bytes .../test_505_deltadelta_insert_ax_forest.png | Bin 0 -> 137219 bytes .../test_506_deltadelta_mediandiff_forest.png | Bin 0 -> 13668 bytes .../test_507_deltadelta_fig_size_forest.png | Bin 0 -> 19010 bytes .../test_508_deltadelta_fig_size_forest.png | Bin 0 -> 19010 bytes ...eltadelta_halfviolin_aesthetics_forest.png | Bin 0 -> 14012 bytes ...lta_labels_and_title_aesthetics_forest.png | Bin 0 -> 14383 bytes ...t_511_deltadelta_lims_and_ticks_forest.png | Bin 0 -> 12898 bytes .../test_512_deltadelta_spines_forest.png | Bin 0 -> 14297 bytes ...est_513_deltadelta_violinkwargs_forest.png | Bin 0 -> 15065 bytes ...t_514_deltadelta_zerolinekwargs_forest.png | Bin 0 -> 14183 bytes ...t_515_deltadelta_esmarkerkwargs_forest.png | Bin 0 -> 13858 bytes ...516_deltadelta_eserrorbarkwargs_forest.png | Bin 0 -> 14365 bytes .../mpl_image_tests/test_05_forest_plot.py | 182 ++++- nbs/tests/test_forest_plot.py | 43 +- nbs/tutorials/07-forest_plot.ipynb | 360 +++++----- 38 files changed, 1272 insertions(+), 666 deletions(-) delete mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_201_forest_plot_no_colorpalette.png delete mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_202_forest_plot_with_colorpalette.png delete mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_203_horizontal_forest_plot_no_colorpalette.png delete mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_204_horizontal_forest_plot_with_colorpalette.png delete mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_205_forest_mini_meta_horizontal.png delete mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_206_forest_mini_meta.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_500_deltadelta_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_501_deltadelta_with_deltas_idx_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_502_minimeta_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_503_deltadelta_custompalette_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_504_deltadelta_horizontal_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_505_deltadelta_insert_ax_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_506_deltadelta_mediandiff_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_507_deltadelta_fig_size_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_508_deltadelta_fig_size_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_509_deltadelta_halfviolin_aesthetics_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_510_deltadelta_labels_and_title_aesthetics_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_511_deltadelta_lims_and_ticks_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_512_deltadelta_spines_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_513_deltadelta_violinkwargs_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_514_deltadelta_zerolinekwargs_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_515_deltadelta_esmarkerkwargs_forest.png create mode 100644 nbs/tests/mpl_image_tests/baseline_images/test_516_deltadelta_eserrorbarkwargs_forest.png diff --git a/dabest/_modidx.py b/dabest/_modidx.py index 4635ac43..f183f720 100644 --- a/dabest/_modidx.py +++ b/dabest/_modidx.py @@ -71,9 +71,11 @@ 'dabest/_stats_tools/effsize.py')}, 'dabest._stats_tools.precompile': { 'dabest._stats_tools.precompile.precompile_all': ( 'API/precompile.html#precompile_all', 'dabest/_stats_tools/precompile.py')}, - 'dabest.forest_plot': { 'dabest.forest_plot.extract_plot_data': ( 'API/forest_plot.html#extract_plot_data', - 'dabest/forest_plot.py'), + 'dabest.forest_plot': { 'dabest.forest_plot.check_for_errors': ( 'API/forest_plot.html#check_for_errors', + 'dabest/forest_plot.py'), + 'dabest.forest_plot.color_palette': ('API/forest_plot.html#color_palette', 'dabest/forest_plot.py'), 'dabest.forest_plot.forest_plot': ('API/forest_plot.html#forest_plot', 'dabest/forest_plot.py'), + 'dabest.forest_plot.get_kwargs': ('API/forest_plot.html#get_kwargs', 'dabest/forest_plot.py'), 'dabest.forest_plot.load_plot_data': ('API/forest_plot.html#load_plot_data', 'dabest/forest_plot.py'), 'dabest.forest_plot.map_effect_attribute': ( 'API/forest_plot.html#map_effect_attribute', 'dabest/forest_plot.py')}, diff --git a/dabest/forest_plot.py b/dabest/forest_plot.py index f87ffe7f..b2ff793f 100644 --- a/dabest/forest_plot.py +++ b/dabest/forest_plot.py @@ -3,7 +3,7 @@ # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/API/forest_plot.ipynb. # %% auto 0 -__all__ = ['load_plot_data', 'extract_plot_data', 'map_effect_attribute', 'forest_plot'] +__all__ = ['load_plot_data', 'map_effect_attribute', 'check_for_errors', 'get_kwargs', 'color_palette', 'forest_plot'] # %% ../nbs/API/forest_plot.ipynb 5 import matplotlib.pyplot as plt @@ -14,7 +14,11 @@ # %% ../nbs/API/forest_plot.ipynb 6 def load_plot_data( - contrasts: List, effect_size: str = "mean_diff", contrast_type: str = "delta2" + data: List, + effect_size: str = "mean_diff", + contrast_type: str = "delta2", + + idx: Optional[List[int]] = None ) -> List: """ Loads plot data based on specified effect size and contrast type. @@ -27,6 +31,9 @@ def load_plot_data( Type of effect size ('mean_diff', 'median_diff', etc.). contrast_type: str Type of contrast ('delta2', 'mini_meta'). + idx: Optional[List[int]], default=None + List of indices to select from the contrast objects if delta-delta experiment. + If None, only the delta-delta objects are plotted. Returns ------- @@ -40,40 +47,64 @@ def load_plot_data( "hedges_g": "hedges_g", "delta_g": "delta_g" } - - contrast_attr_map = {"delta2": "delta_delta", "mini_meta": "mini_meta_delta"} - effect_attr = effect_attr_map.get(effect_size) - contrast_attr = contrast_attr_map.get(contrast_type) - if not effect_attr: raise ValueError(f"Invalid effect_size: {effect_size}") - if not contrast_attr: - raise ValueError(f"Invalid contrast_type: {contrast_type}. Available options: [`delta2`, `mini_meta`]") - return [ - getattr(getattr(contrast, effect_attr), contrast_attr) for contrast in contrasts - ] + # Contrast type + first_contrast = data[0] + if first_contrast.delta2 is True: + contrast_type = "delta2" + elif first_contrast.mini_meta is True: + contrast_type = "mini_meta" + else: + raise ValueError("The `contrast_type` parameter must be specified as either `delta2` or `mini_meta`.") + contrast_attr_map = {"delta2": "delta_delta", "mini_meta": "mini_meta_delta"} + contrast_attr = contrast_attr_map.get(contrast_type) -def extract_plot_data(contrast_plot_data, contrast_type): - """Extracts bootstrap, difference, and confidence intervals based on contrast labels.""" - if contrast_type == "mini_meta": - attribute_suffix = "weighted_delta" + if idx is not None and contrast_type == 'delta2': + bootstraps, differences, bcalows, bcahighs = [], [], [], [] + for current_idx, index_group in enumerate(idx): + current_contrast = data[current_idx] + if len(index_group)>0: + for index in index_group: + if index == 2: + current_plot_data = getattr(getattr(current_contrast, effect_attr), contrast_attr) + bootstraps.append(current_plot_data.bootstraps_delta_delta) + differences.append(current_plot_data.difference) + bcalows.append(current_plot_data.bca_low) + bcahighs.append(current_plot_data.bca_high) + elif index == 0 or index == 1: + current_plot_data = getattr(current_contrast, effect_attr) + bootstraps.append(current_plot_data.results.bootstraps[index]) + differences.append(current_plot_data.results.difference[index]) + bcalows.append(current_plot_data.results.bca_low[index]) + bcahighs.append(current_plot_data.results.bca_high[index]) + else: + raise ValueError("The selected indices must be 0, 1, or 2.") else: - attribute_suffix = "delta_delta" + contrast_plot_data = [ + getattr(getattr(contrast, effect_attr), contrast_attr) for contrast in data + ] + + if contrast_type == "mini_meta": + attribute_suffix = "weighted_delta" + else: + attribute_suffix = "delta_delta" + + bootstraps = [ + getattr(result, f"bootstraps_{attribute_suffix}") + for result in contrast_plot_data + ] + + differences = [result.difference for result in contrast_plot_data] + bcalows = [result.bca_low for result in contrast_plot_data] + bcahighs = [result.bca_high for result in contrast_plot_data] - bootstraps = [ - getattr(result, f"bootstraps_{attribute_suffix}") - for result in contrast_plot_data - ] - - differences = [result.difference for result in contrast_plot_data] - bcalows = [result.bca_low for result in contrast_plot_data] - bcahighs = [result.bca_high for result in contrast_plot_data] - return bootstraps, differences, bcalows, bcahighs + def map_effect_attribute(attribute_key): # Check if the attribute key exists in the dictionary effect_attr_map = { @@ -89,74 +120,294 @@ def map_effect_attribute(attribute_key): else: raise TypeError("The `effect_size` argument must be a string. Please choose from the following effect sizes: `mean_diff`,`median_diff`,`cliffs_delta`,`cohens_d``, and `hedges_g`.") # Return a default value or message if the key is not found + +def check_for_errors( + data, + idx, + ax, + fig_size, + effect_size, + horizontal, + marker_size, + custom_palette, + halfviolin_alpha, + halfviolin_desat, + labels, + labels_rotation, + labels_fontsize, + title, + title_fontsize, + ylabel, + ylabel_fontsize, + ylim, + yticks, + yticklabels, + remove_spines, + ): + + # Contrasts + if not isinstance(data, list) or not data: + raise ValueError("The `data` argument must be a non-empty list of dabest objects.") + + # Idx + if idx is not None and not isinstance(idx, (tuple, list)): + raise TypeError("`idx` must be a tuple or list of integers.") + + # Axes + if ax is not None and not isinstance(ax, plt.Axes): + raise TypeError("The `ax` must be a `matplotlib.axes.Axes` instance or `None`.") + + # Figure size + if fig_size is not None and not isinstance(fig_size, (tuple, list)): + raise TypeError("`fig_size` must be a tuple or list of two integers.") + + # Effect size + effect_size_options = ['mean_diff', 'median_diff', 'cliffs_delta', 'cohens_d', 'hedges_g'] + if not isinstance(effect_size, str) or effect_size not in effect_size_options: + raise TypeError("The `effect_size` argument must be a string and please choose from the following effect sizes: `mean_diff`, `median_diff`, `cliffs_delta`, `cohens_d`, and `hedges_g`.") + + # Horizontal + if not isinstance(horizontal, bool): + raise TypeError("`horizontal` must be a boolean value.") + + # Marker size + if not isinstance(marker_size, (int, float)) or marker_size <= 0: + raise TypeError("`marker_size` must be a positive integer or float.") + + # Custom palette + if custom_palette is not None and not isinstance(custom_palette, (dict, list, str, type(None))): + raise TypeError("The `custom_palette` must be either a dictionary, list, string, or `None`.") + + + # Halfviolin alpha and desat + if not isinstance(halfviolin_alpha, float) or not 0 <= halfviolin_alpha <= 1: + raise TypeError("`halfviolin_alpha` must be a float between 0 and 1.") + + if not isinstance(halfviolin_desat, (float, int)) or not 0 <= halfviolin_desat <= 1: + raise TypeError("`halfviolin_desat` must be a float between 0 and 1 or an int (1).") + + + # Contrast labels + if labels is not None and not all(isinstance(label, str) for label in labels): + raise TypeError("The `labels` must be a list of strings or `None`.") + + number_of_curves_to_plot = sum([len(i) for i in idx]) if idx is not None else len(data) + if labels is not None and len(labels) != number_of_curves_to_plot: + raise ValueError("`labels` must match the number of `data` provided.") + + if not isinstance(labels_fontsize, (int, float)): + raise TypeError("`labels_fontsize` must be an integer or float.") + + if labels_rotation is not None and (not isinstance(labels_rotation, (int, float)) or not 0 <= labels_rotation <= 360): + raise TypeError("`labels_rotation` must be an integer or float between 0 and 360.") + + # Title + if not isinstance(title, str): + raise TypeError("The `title` argument must be a string.") + + if not isinstance(title_fontsize, (int, float)): + raise TypeError("`title_fontsize` must be an integer or float.") + + # Y-label + if ylabel is not None and not isinstance(ylabel, str): + raise TypeError("The `ylabel` argument must be a string.") + + if not isinstance(ylabel_fontsize, (int, float)): + raise TypeError("`ylabel_fontsize` must be an integer or float.") + + # Y-lim + if ylim is not None and not isinstance(ylim, (tuple, list)): + raise TypeError("`ylim` must be a tuple or list of two floats.") + if ylim is not None and len(ylim) != 2: + raise ValueError("`ylim` must be a tuple or list of two floats.") + + # Y-ticks + if yticks is not None and not isinstance(yticks, (tuple, list)): + raise TypeError("`yticks` must be a tuple or list of floats.") + + # Y-ticklabels + if yticklabels is not None and not isinstance(yticklabels, (tuple, list)): + raise TypeError("`yticklabels` must be a tuple or list of strings.") + + if yticklabels is not None and not all(isinstance(label, str) for label in yticklabels): + raise TypeError("`yticklabels` must be a list of strings.") + + # Remove spines + if not isinstance(remove_spines, bool): + raise TypeError("`remove_spines` must be a boolean value.") + + +def get_kwargs( + violin_kwargs, + zeroline_kwargs, + horizontal, + es_marker_kwargs, + es_errorbar_kwargs, + marker_size + ): + from .misc_tools import merge_two_dicts + + + default_violin_kwargs = { + "widths": 0.5, + "showextrema": False, + "showmedians": False, + "vert": not horizontal + } + + if violin_kwargs is None: + violin_kwargs = default_violin_kwargs + else: + violin_kwargs = merge_two_dicts(default_violin_kwargs, violin_kwargs) + + + default_zeroline_kwargs = { + "linewidth": 1, + "color": "black" + } + if zeroline_kwargs is None: + zeroline_kwargs = default_zeroline_kwargs + else: + zeroline_kwargs = merge_two_dicts(default_zeroline_kwargs, zeroline_kwargs) + + # Effect size marker kwargs + default_es_marker_kwargs = { + 'marker': 'o', + 'markersize': marker_size, + 'color': 'black', + 'alpha': 1, + 'zorder': 2, + } + if es_marker_kwargs is None: + es_marker_kwargs = default_es_marker_kwargs + else: + es_marker_kwargs = merge_two_dicts(default_es_marker_kwargs, es_marker_kwargs) + + # Effect size error bar kwargs + default_es_errorbar_kwargs = { + 'color': 'black', + 'lw': 2.5, + 'linestyle': '-', + 'alpha': 1, + 'zorder': 1, + } + if es_errorbar_kwargs is None: + es_errorbar_kwargs = default_es_errorbar_kwargs + else: + es_errorbar_kwargs = merge_two_dicts(default_es_errorbar_kwargs, es_errorbar_kwargs) + + return violin_kwargs, zeroline_kwargs, es_marker_kwargs, es_errorbar_kwargs + + +def color_palette( + custom_palette, + labels, + number_of_curves_to_plot + ): + if isinstance(custom_palette, dict): + violin_colors = [ + custom_palette.get(c, sns.color_palette()[0]) for c in labels + ] + elif isinstance(custom_palette, list): + violin_colors = custom_palette[: number_of_curves_to_plot] + elif isinstance(custom_palette, str): + if custom_palette in plt.colormaps(): + violin_colors = sns.color_palette(custom_palette, number_of_curves_to_plot) + else: + raise ValueError( + f"The specified `custom_palette` {custom_palette} is not a recognized Matplotlib palette." + ) + return violin_colors + + def forest_plot( - contrasts: List, - selected_indices: Optional[List] = None, - contrast_type: str = "delta2", + data: List, + idx: Optional[List[int]] = None, + ax: Optional[plt.Axes] = None, + fig_size: tuple[int, int] = None, effect_size: str = "mean_diff", - contrast_labels: List[str] = None, - ylabel: str = "effect size", - plot_elements_to_extract: Optional[List] = None, - title: str = "ΔΔ Forest", + horizontal: bool = False, + + marker_size: int = 12, custom_palette: Optional[Union[dict, list, str]] = None, - fontsize: int = 12, - title_font_size: int =16, - violin_kwargs: Optional[dict] = None, - marker_size: int = 20, - ci_line_width: float = 2.5, - desat_violin: float = 1, + halfviolin_alpha: float = 0.8, + halfviolin_desat: float = 1, + + labels: List[str] = None, + labels_rotation: int = None, + labels_fontsize: int = 10, + title: str = "ΔΔ Forest", + title_fontsize: int = 16, + ylabel: str = None, + ylabel_fontsize: int = 12, + ylim: Optional[tuple[float, float] | list[float, float]] = None, + yticks: Optional[tuple[float] | list[float]] = None, + yticklabels: Optional[tuple[str] | list[str]] = None, remove_spines: bool = True, - ax: Optional[plt.Axes] = None, - additional_plotting_kwargs: Optional[dict] = None, - rotation_for_xlabels: int = 45, - alpha_violin_plot: float = 0.8, - horizontal: bool = False # New argument for horizontal orientation + + violin_kwargs: Optional[dict] = None, + zeroline_kwargs: Optional[dict] = None, + es_marker_kwargs: Optional[dict] = None, + es_errorbar_kwargs: Optional[dict] = None, )-> plt.Figure: """ Custom function that generates a forest plot from given contrast objects, suitable for a range of data analysis types, including those from packages like DABEST-python. Parameters ---------- - contrasts : List + data : List List of contrast objects. - selected_indices : Optional[List], default=None - Indices of specific contrasts to plot, if not plotting all. - analysis_type : str - the type of analysis (e.g., 'delta2', 'mini_meta'). + idx : Optional[List[int]], default=None + List of indices to select from the contrast objects if delta-delta experiment. + If None, only the delta-delta objects are plotted. + ax : Optional[plt.Axes], default=None + Matplotlib Axes object for the plot; creates new if None. + additional_plotting_kwargs : Optional[dict], default=None + Further customization arguments for the plot. + fig_size : Tuple[int, int], default=None + Figure size for the plot. effect_size : str Type of effect size to plot (e.g., 'mean_diff', 'median_diff', `cliffs_delta`,`cohens_d``, and `hedges_g`). - contrast_labels : List[str] - Labels for each contrast. - ylabel : str - Label for the y-axis, describing the plotted data or effect size. - plot_elements_to_extract : Optional[List], default=None - Elements to extract for detailed plot customization. + horizontal : bool, default=False + If True, the plot will be horizontal. + marker_size : int, default=12 + Marker size for plotting effect size dots. + custom_palette : Optional[Union[dict, list, str]], default=None + Custom color palette for the plot. + halfviolin_alpha : float, default=0.8 + Transparency level for violin plots. + halfviolin_desat : float, default=1 + Saturation level for violin plots. + labels : List[str] + Labels for each contrast. If None, defaults to 'Contrast 1', 'Contrast 2', etc. + labels_rotation : int, default=45 for vertical, 0 for horizontal + Rotation angle for contrast labels. + labels_fontsize : int, default=10 + Font size for contrast labels. title : str Plot title, summarizing the visualized data. - ylim : Tuple[float, float] + title_fontsize : int, default=16 + Font size for the plot title. + ylabel : str + Label for the y-axis, describing the plotted data or effect size. + ylabel_fontsize : int, default=12 + Font size for the y-axis label. + ylim : Optional[Tuple[float, float]] Limits for the y-axis. - custom_palette : Optional[Union[dict, list, str]], default=None - Custom color palette for the plot. - fontsize : int - Font size for text elements in the plot. - title_font_size: int =16 - Font size for text of plot title. + yticks : Optional[List[float]] + Custom y-ticks for the plot. + yticklabels : Optional[List[str]] + Custom y-tick labels for the plot. + remove_spines : bool, default=True + If True, removes plot spines (except the relevant dependent variable spine). violin_kwargs : Optional[dict], default=None Additional arguments for violin plot customization. - marker_size : int - Marker size for plotting mean differences or effect sizes. - ci_line_width : float - Width of confidence interval lines. - remove_spines : bool, default=False - If True, removes top and right plot spines. - ax : Optional[plt.Axes], default=None - Matplotlib Axes object for the plot; creates new if None. - additional_plotting_kwargs : Optional[dict], default=None - Further customization arguments for the plot. - rotation_for_xlabels : int, default=0 - Rotation angle for x-axis labels, improving readability. - alpha_violin_plot : float, default=1.0 - Transparency level for violin plots. + zeroline_kwargs : Optional[dict], default=None + Additional arguments for the zero line customization. + es_marker_kwargs : Optional[dict], default=None + Additional arguments for the effect size marker customization. + es_errorbar_kwargs : Optional[dict], default=None + Additional arguments for the effect size error bar customization. Returns ------- @@ -165,161 +416,150 @@ def forest_plot( """ from .plot_tools import halfviolin - # Validate inputs - if contrasts is None: - raise ValueError("The `contrasts` parameter cannot be None") - - if not isinstance(contrasts, list) or not contrasts: - raise ValueError("The `contrasts` argument must be a non-empty list.") - - if selected_indices is not None and not isinstance(selected_indices, (list, type(None))): - raise TypeError("The `selected_indices` must be a list of integers or `None`.") - - # For the 'contrast_type' parameter - if not isinstance(contrast_type, str): - raise TypeError("The `contrast_type` argument must be a string. Please choose from `delta2` and `mini_meta`.") - - # For the 'effect_size' parameter - if not isinstance(effect_size, str): - raise TypeError("The `effect_size` argument must be a string. Please choose from the following effect sizes: `mean_diff`, `median_diff`, `cliffs_delta`, `cohens_d`, and `hedges_g`.") - - if contrast_labels is not None and not all(isinstance(label, str) for label in contrast_labels): - raise TypeError("The `contrast_labels` must be a list of strings or `None`.") - - if contrast_labels is not None and len(contrast_labels) != len(contrasts): - raise ValueError("`contrast_labels` must match the number of `contrasts` if provided.") - - if not isinstance(ylabel, str): - raise TypeError("The `ylabel` argument must be a string.") - - if custom_palette is not None and not isinstance(custom_palette, (dict, list, str, type(None))): - raise TypeError("The `custom_palette` must be either a dictionary, list, string, or `None`.") - - if not isinstance(fontsize, (int, float)): - raise TypeError("`fontsize` must be an integer or float.") - - if not isinstance(marker_size, (int, float)) or marker_size <= 0: - raise TypeError("`marker_size` must be a positive integer or float.") - - if not isinstance(ci_line_width, (int, float)) or ci_line_width <= 0: - raise TypeError("`ci_line_width` must be a positive integer or float.") - - if not isinstance(remove_spines, bool): - raise TypeError("`remove_spines` must be a boolean value.") - - if ax is not None and not isinstance(ax, plt.Axes): - raise TypeError("`ax` must be a `matplotlib.axes.Axes` instance or `None`.") - - if not isinstance(rotation_for_xlabels, (int, float)) or not 0 <= rotation_for_xlabels <= 360: - raise TypeError("`rotation_for_xlabels` must be an integer or float between 0 and 360.") - - if not isinstance(alpha_violin_plot, float) or not 0 <= alpha_violin_plot <= 1: - raise TypeError("`alpha_violin_plot` must be a float between 0 and 1.") - if not isinstance(horizontal, bool): - raise TypeError("`horizontal` must be a boolean value.") - - if (effect_size and isinstance(effect_size, str)): - ylabel = map_effect_attribute(effect_size) - # Load plot data - contrast_plot_data = load_plot_data(contrasts, effect_size, contrast_type) + # Check for errors in the input arguments + check_for_errors( + data = data, + idx = idx, + ax = ax, + fig_size = fig_size, + effect_size = effect_size, + horizontal = horizontal, + marker_size = marker_size, + custom_palette = custom_palette, + halfviolin_alpha = halfviolin_alpha, + halfviolin_desat = halfviolin_desat, + labels = labels, + labels_rotation = labels_rotation, + labels_fontsize = labels_fontsize, + title = title, + title_fontsize = title_fontsize, + ylabel = ylabel, + ylabel_fontsize = ylabel_fontsize, + ylim = ylim, + yticks = yticks, + yticklabels = yticklabels, + remove_spines = remove_spines, + + ) - # Extract data for plotting - bootstraps, differences, bcalows, bcahighs = extract_plot_data( - contrast_plot_data, contrast_type + # Load plot data and extract info + bootstraps, differences, bcalows, bcahighs = load_plot_data( + data = data, + effect_size = effect_size, + idx = idx ) + # Adjust figure size based on orientation - all_groups_count = len(contrasts) - if horizontal: - fig_size = (4, 1.5 * all_groups_count) + number_of_curves_to_plot = sum([len(i) for i in idx]) if idx is not None else len(data) + if ax is not None: + fig = ax.figure else: - fig_size = (1.5 * all_groups_count, 4) - - if ax is None: + if fig_size is None: + fig_size = (4, 1.3 * number_of_curves_to_plot) if horizontal else (1.3 * number_of_curves_to_plot, 4) fig, ax = plt.subplots(figsize=fig_size) - else: - fig = ax.figure - - # Adjust violin plot orientation based on the 'horizontal' argument - violin_kwargs = violin_kwargs or { - "widths": 0.5, - "showextrema": False, - "showmedians": False, - } - violin_kwargs["vert"] = not horizontal - v = ax.violinplot(bootstraps, **violin_kwargs) - # Adjust the halfviolin function call based on 'horizontal' - if horizontal: - half = "top" - else: - half = "right" # Assuming "right" is the default or another appropriate value + # Get Kwargs + violin_kwargs, zeroline_kwargs, es_marker_kwargs, es_errorbar_kwargs = get_kwargs( + violin_kwargs = violin_kwargs, + zeroline_kwargs = zeroline_kwargs, + horizontal = horizontal, + es_marker_kwargs = es_marker_kwargs, + es_errorbar_kwargs = es_errorbar_kwargs, + marker_size = marker_size + ) + + # Plot the violins and make adjustments + v = ax.violinplot( + bootstraps, + **violin_kwargs + ) + halfviolin( + v, + alpha = halfviolin_alpha, + half = "bottom" if horizontal else "right", - # Assuming halfviolin has been updated to accept a 'half' parameter - halfviolin(v, alpha=alpha_violin_plot, half=half) + ) + + ## Plotting the effect sizes and confidence intervals + for k in range(1, number_of_curves_to_plot + 1): + if horizontal: + ax.plot(differences[k - 1], k, **es_marker_kwargs) + ax.plot([bcalows[k - 1], bcahighs[k - 1]], [k, k], **es_errorbar_kwargs) + else: + ax.plot(k, differences[k - 1], **es_marker_kwargs) + ax.plot([k, k], [bcalows[k - 1], bcahighs[k - 1]], **es_errorbar_kwargs) - # Handle the custom color palette + # Aesthetic Adjustments + ## Handle the custom color palette if custom_palette: - if isinstance(custom_palette, dict): - violin_colors = [ - custom_palette.get(c, sns.color_palette()[0]) for c in contrast_labels - ] - elif isinstance(custom_palette, list): - violin_colors = custom_palette[: len(contrasts)] - elif isinstance(custom_palette, str): - if custom_palette in plt.colormaps(): - violin_colors = sns.color_palette(custom_palette, len(contrasts)) - else: - raise ValueError( - f"The specified `custom_palette` {custom_palette} is not a recognized Matplotlib palette." - ) + violin_colors = color_palette( + custom_palette = custom_palette, + labels = labels, + number_of_curves_to_plot = number_of_curves_to_plot + ) else: - violin_colors = sns.color_palette(n_colors=len(contrasts)) - - violin_colors = [sns.desaturate(color, desat_violin) for color in violin_colors] + violin_colors = sns.color_palette(n_colors=number_of_curves_to_plot) + violin_colors = [sns.desaturate(color, halfviolin_desat) for color in violin_colors] for patch, color in zip(v["bodies"], violin_colors): patch.set_facecolor(color) - patch.set_alpha(alpha_violin_plot) + + ## Add a zero line to the plot if horizontal: - ax.plot([0, 0], [0, len(contrasts)+1], 'k', linewidth = 1) + ax.plot([0, 0], [0, number_of_curves_to_plot+1], **zeroline_kwargs) else: - ax.plot([0, len(contrasts)+1], [0, 0], 'k', linewidth = 1) - - # Flipping the axes for plotting based on 'horizontal' - for k in range(1, len(contrasts) + 1): - if horizontal: - ax.plot(differences[k - 1], k, "k.", markersize=marker_size) # Flipped axes - ax.plot([bcalows[k - 1], bcahighs[k - 1]], [k, k], "k", linewidth=ci_line_width) # Flipped axes - else: - ax.plot(k, differences[k - 1], "k.", markersize=marker_size) - ax.plot([k, k], [bcalows[k - 1], bcahighs[k - 1]], "k", linewidth=ci_line_width) + ax.plot([0, number_of_curves_to_plot+1], [0, 0], **zeroline_kwargs) - # Adjusting labels, ticks, and limits based on 'horizontal' + ## lims + ### Indepedent variable if horizontal: - ax.set_yticks(range(1, len(contrasts) + 1)) - ax.set_yticklabels(contrast_labels, rotation=0, fontsize=fontsize) - ax.set_xlabel(ylabel, fontsize=fontsize) - ax.set_ylim([0.7, len(contrasts) + 0.5]) + ax.set_ylim([0.7, number_of_curves_to_plot + 0.2]) else: - ax.set_xticks(range(1, len(contrasts) + 1)) - ax.set_xticklabels(contrast_labels, rotation=rotation_for_xlabels, fontsize=fontsize) - ax.set_ylabel(ylabel, fontsize=fontsize) - ax.set_xlim([0.7, len(contrasts) + 0.5]) + ax.set_xlim([0.7, number_of_curves_to_plot + 0.5]) + + ## Depedent variable + if ylim is not None: + lim_key = ax.set_xlim if horizontal else ax.set_ylim + lim_key(ylim) + + ## Ticks + ### Indepedent variable + lim_key = ax.set_yticks if horizontal else ax.set_xticks + lim_key(range(1, number_of_curves_to_plot + 1)) - # Setting the title and adjusting spines as before - ax.set_title(title, fontsize=title_font_size) + if labels_rotation == None: + labels_rotation = 0 if horizontal else 45 + if labels is None: + labels = [f"Contrast {i}" for i in range(1, number_of_curves_to_plot + 1)] + lim_key = ax.set_yticklabels if horizontal else ax.set_xticklabels + lim_key(labels, rotation=labels_rotation, fontsize=labels_fontsize, ha="right") + + ### Depedent variable + if yticks is not None: + lim_key = ax.set_xticks if horizontal else ax.set_yticks + lim_key(yticks) + + if yticklabels is not None: + lim_key = ax.set_xticklabels if horizontal else ax.set_yticklabels + lim_key(yticklabels) + + ## y-label + if ylabel is None: + ylabel = map_effect_attribute(effect_size) + lim_key = ax.set_xlabel if horizontal else ax.set_ylabel + lim_key(ylabel, fontsize=ylabel_fontsize) + + ## Setting the title + ax.set_title(title, fontsize=title_fontsize) + + ## Adjust Spines if remove_spines: - if horizontal: - ax.spines['left'].set_visible(False) - ax.spines['right'].set_visible(False) - ax.spines['top'].set_visible(False) - else: - ax.spines['top'].set_visible(False) - ax.spines['bottom'].set_visible(False) - ax.spines['right'].set_visible(False) - # Apply additional customizations if provided - if additional_plotting_kwargs: - ax.set(**additional_plotting_kwargs) + spines = ["top", "right", "left"] if horizontal else ["top", "right", "bottom"] + ax.spines[spines].set_visible(False) + + ## Invert Y-axis if horizontal + if horizontal: + ax.invert_yaxis() return fig diff --git a/dabest/plot_tools.py b/dabest/plot_tools.py index 2448241b..b046e958 100644 --- a/dabest/plot_tools.py +++ b/dabest/plot_tools.py @@ -2937,7 +2937,7 @@ def plot( ax.scatter( [], [], - c=self.__palette[cmap_group_i], + color=self.__palette[cmap_group_i], label=cmap_group_i, ) diff --git a/dabest/plotter.py b/dabest/plotter.py index aa825b2d..7641b5df 100644 --- a/dabest/plotter.py +++ b/dabest/plotter.py @@ -364,7 +364,7 @@ def effectsize_df_plotter(effectsize_df: object, **plot_kwargs) -> matplotlib.fi (current_group, current_control, current_effsize, contrast_xtick_labels) = effect_size_curve_plotter( ticks_to_plot = ticks_to_plot, - ticks_for_baseline_ec=ticks_for_baseline_ec, + ticks_for_baseline_ec = ticks_for_baseline_ec, results = results, ci_type = ci_type, contrast_axes = contrast_axes, diff --git a/nbs/API/forest_plot.ipynb b/nbs/API/forest_plot.ipynb index ea7d94ab..606903a9 100644 --- a/nbs/API/forest_plot.ipynb +++ b/nbs/API/forest_plot.ipynb @@ -73,7 +73,11 @@ "source": [ "#| export\n", "def load_plot_data(\n", - " contrasts: List, effect_size: str = \"mean_diff\", contrast_type: str = \"delta2\"\n", + " data: List, \n", + " effect_size: str = \"mean_diff\", \n", + " contrast_type: str = \"delta2\",\n", + "\n", + " idx: Optional[List[int]] = None\n", ") -> List:\n", " \"\"\"\n", " Loads plot data based on specified effect size and contrast type.\n", @@ -86,6 +90,9 @@ " Type of effect size ('mean_diff', 'median_diff', etc.).\n", " contrast_type: str\n", " Type of contrast ('delta2', 'mini_meta').\n", + " idx: Optional[List[int]], default=None\n", + " List of indices to select from the contrast objects if delta-delta experiment. \n", + " If None, only the delta-delta objects are plotted.\n", "\n", " Returns\n", " -------\n", @@ -99,40 +106,64 @@ " \"hedges_g\": \"hedges_g\",\n", " \"delta_g\": \"delta_g\"\n", " }\n", - "\n", - " contrast_attr_map = {\"delta2\": \"delta_delta\", \"mini_meta\": \"mini_meta_delta\"}\n", - "\n", " effect_attr = effect_attr_map.get(effect_size)\n", - " contrast_attr = contrast_attr_map.get(contrast_type)\n", - "\n", " if not effect_attr:\n", " raise ValueError(f\"Invalid effect_size: {effect_size}\") \n", - " if not contrast_attr:\n", - " raise ValueError(f\"Invalid contrast_type: {contrast_type}. Available options: [`delta2`, `mini_meta`]\")\n", "\n", - " return [\n", - " getattr(getattr(contrast, effect_attr), contrast_attr) for contrast in contrasts\n", - " ]\n", + " # Contrast type\n", + " first_contrast = data[0]\n", + " if first_contrast.delta2 is True:\n", + " contrast_type = \"delta2\"\n", + " elif first_contrast.mini_meta is True:\n", + " contrast_type = \"mini_meta\"\n", + " else:\n", + " raise ValueError(\"The `contrast_type` parameter must be specified as either `delta2` or `mini_meta`.\")\n", "\n", + " contrast_attr_map = {\"delta2\": \"delta_delta\", \"mini_meta\": \"mini_meta_delta\"}\n", + " contrast_attr = contrast_attr_map.get(contrast_type)\n", "\n", - "def extract_plot_data(contrast_plot_data, contrast_type):\n", - " \"\"\"Extracts bootstrap, difference, and confidence intervals based on contrast labels.\"\"\"\n", - " if contrast_type == \"mini_meta\":\n", - " attribute_suffix = \"weighted_delta\"\n", + " if idx is not None and contrast_type == 'delta2':\n", + " bootstraps, differences, bcalows, bcahighs = [], [], [], []\n", + " for current_idx, index_group in enumerate(idx):\n", + " current_contrast = data[current_idx]\n", + " if len(index_group)>0:\n", + " for index in index_group:\n", + " if index == 2:\n", + " current_plot_data = getattr(getattr(current_contrast, effect_attr), contrast_attr)\n", + " bootstraps.append(current_plot_data.bootstraps_delta_delta)\n", + " differences.append(current_plot_data.difference)\n", + " bcalows.append(current_plot_data.bca_low)\n", + " bcahighs.append(current_plot_data.bca_high)\n", + " elif index == 0 or index == 1:\n", + " current_plot_data = getattr(current_contrast, effect_attr)\n", + " bootstraps.append(current_plot_data.results.bootstraps[index])\n", + " differences.append(current_plot_data.results.difference[index])\n", + " bcalows.append(current_plot_data.results.bca_low[index])\n", + " bcahighs.append(current_plot_data.results.bca_high[index])\n", + " else:\n", + " raise ValueError(\"The selected indices must be 0, 1, or 2.\")\n", " else:\n", - " attribute_suffix = \"delta_delta\"\n", + " contrast_plot_data = [\n", + " getattr(getattr(contrast, effect_attr), contrast_attr) for contrast in data\n", + " ]\n", + "\n", + " if contrast_type == \"mini_meta\":\n", + " attribute_suffix = \"weighted_delta\"\n", + " else:\n", + " attribute_suffix = \"delta_delta\"\n", + "\n", + " bootstraps = [\n", + " getattr(result, f\"bootstraps_{attribute_suffix}\")\n", + " for result in contrast_plot_data\n", + " ]\n", + "\n", + " differences = [result.difference for result in contrast_plot_data]\n", + " bcalows = [result.bca_low for result in contrast_plot_data]\n", + " bcahighs = [result.bca_high for result in contrast_plot_data]\n", "\n", - " bootstraps = [\n", - " getattr(result, f\"bootstraps_{attribute_suffix}\")\n", - " for result in contrast_plot_data\n", - " ]\n", - " \n", - " differences = [result.difference for result in contrast_plot_data]\n", - " bcalows = [result.bca_low for result in contrast_plot_data]\n", - " bcahighs = [result.bca_high for result in contrast_plot_data]\n", - " \n", " return bootstraps, differences, bcalows, bcahighs\n", "\n", + "\n", "def map_effect_attribute(attribute_key):\n", " # Check if the attribute key exists in the dictionary\n", " effect_attr_map = {\n", @@ -148,74 +179,294 @@ " else:\n", " raise TypeError(\"The `effect_size` argument must be a string. Please choose from the following effect sizes: `mean_diff`,`median_diff`,`cliffs_delta`,`cohens_d``, and `hedges_g`.\") # Return a default value or message if the key is not found\n", "\n", + "\n", + "def check_for_errors(\n", + " data,\n", + " idx,\n", + " ax,\n", + " fig_size,\n", + " effect_size,\n", + " horizontal,\n", + " marker_size,\n", + " custom_palette,\n", + " halfviolin_alpha,\n", + " halfviolin_desat,\n", + " labels,\n", + " labels_rotation,\n", + " labels_fontsize,\n", + " title,\n", + " title_fontsize,\n", + " ylabel,\n", + " ylabel_fontsize,\n", + " ylim,\n", + " yticks,\n", + " yticklabels,\n", + " remove_spines,\n", + " ):\n", + "\n", + " # Contrasts\n", + " if not isinstance(data, list) or not data:\n", + " raise ValueError(\"The `data` argument must be a non-empty list of dabest objects.\")\n", + " \n", + " # Idx\n", + " if idx is not None and not isinstance(idx, (tuple, list)):\n", + " raise TypeError(\"`idx` must be a tuple or list of integers.\")\n", + "\n", + " # Axes\n", + " if ax is not None and not isinstance(ax, plt.Axes):\n", + " raise TypeError(\"The `ax` must be a `matplotlib.axes.Axes` instance or `None`.\")\n", + " \n", + " # Figure size\n", + " if fig_size is not None and not isinstance(fig_size, (tuple, list)):\n", + " raise TypeError(\"`fig_size` must be a tuple or list of two integers.\")\n", + "\n", + " # Effect size\n", + " effect_size_options = ['mean_diff', 'median_diff', 'cliffs_delta', 'cohens_d', 'hedges_g']\n", + " if not isinstance(effect_size, str) or effect_size not in effect_size_options:\n", + " raise TypeError(\"The `effect_size` argument must be a string and please choose from the following effect sizes: `mean_diff`, `median_diff`, `cliffs_delta`, `cohens_d`, and `hedges_g`.\")\n", + " \n", + " # Horizontal\n", + " if not isinstance(horizontal, bool):\n", + " raise TypeError(\"`horizontal` must be a boolean value.\")\n", + "\n", + " # Marker size\n", + " if not isinstance(marker_size, (int, float)) or marker_size <= 0:\n", + " raise TypeError(\"`marker_size` must be a positive integer or float.\")\n", + "\n", + " # Custom palette\n", + " if custom_palette is not None and not isinstance(custom_palette, (dict, list, str, type(None))):\n", + " raise TypeError(\"The `custom_palette` must be either a dictionary, list, string, or `None`.\")\n", + "\n", + "\n", + " # Halfviolin alpha and desat\n", + " if not isinstance(halfviolin_alpha, float) or not 0 <= halfviolin_alpha <= 1:\n", + " raise TypeError(\"`halfviolin_alpha` must be a float between 0 and 1.\")\n", + " \n", + " if not isinstance(halfviolin_desat, (float, int)) or not 0 <= halfviolin_desat <= 1:\n", + " raise TypeError(\"`halfviolin_desat` must be a float between 0 and 1 or an int (1).\")\n", + " \n", + "\n", + " # Contrast labels\n", + " if labels is not None and not all(isinstance(label, str) for label in labels):\n", + " raise TypeError(\"The `labels` must be a list of strings or `None`.\")\n", + " \n", + " number_of_curves_to_plot = sum([len(i) for i in idx]) if idx is not None else len(data)\n", + " if labels is not None and len(labels) != number_of_curves_to_plot:\n", + " raise ValueError(\"`labels` must match the number of `data` provided.\")\n", + " \n", + " if not isinstance(labels_fontsize, (int, float)):\n", + " raise TypeError(\"`labels_fontsize` must be an integer or float.\")\n", + " \n", + " if labels_rotation is not None and (not isinstance(labels_rotation, (int, float)) or not 0 <= labels_rotation <= 360):\n", + " raise TypeError(\"`labels_rotation` must be an integer or float between 0 and 360.\") \n", + "\n", + " # Title\n", + " if not isinstance(title, str):\n", + " raise TypeError(\"The `title` argument must be a string.\")\n", + " \n", + " if not isinstance(title_fontsize, (int, float)):\n", + " raise TypeError(\"`title_fontsize` must be an integer or float.\")\n", + " \n", + " # Y-label\n", + " if ylabel is not None and not isinstance(ylabel, str):\n", + " raise TypeError(\"The `ylabel` argument must be a string.\")\n", + "\n", + " if not isinstance(ylabel_fontsize, (int, float)):\n", + " raise TypeError(\"`ylabel_fontsize` must be an integer or float.\")\n", + " \n", + " # Y-lim\n", + " if ylim is not None and not isinstance(ylim, (tuple, list)):\n", + " raise TypeError(\"`ylim` must be a tuple or list of two floats.\")\n", + " if ylim is not None and len(ylim) != 2:\n", + " raise ValueError(\"`ylim` must be a tuple or list of two floats.\")\n", + "\n", + " # Y-ticks\n", + " if yticks is not None and not isinstance(yticks, (tuple, list)):\n", + " raise TypeError(\"`yticks` must be a tuple or list of floats.\")\n", + " \n", + " # Y-ticklabels\n", + " if yticklabels is not None and not isinstance(yticklabels, (tuple, list)):\n", + " raise TypeError(\"`yticklabels` must be a tuple or list of strings.\")\n", + " \n", + " if yticklabels is not None and not all(isinstance(label, str) for label in yticklabels):\n", + " raise TypeError(\"`yticklabels` must be a list of strings.\")\n", + " \n", + " # Remove spines\n", + " if not isinstance(remove_spines, bool):\n", + " raise TypeError(\"`remove_spines` must be a boolean value.\")\n", + " \n", + "\n", + "def get_kwargs(\n", + " violin_kwargs,\n", + " zeroline_kwargs,\n", + " horizontal,\n", + " es_marker_kwargs,\n", + " es_errorbar_kwargs,\n", + " marker_size\n", + " ):\n", + " from .misc_tools import merge_two_dicts\n", + "\n", + "\n", + " default_violin_kwargs = {\n", + " \"widths\": 0.5,\n", + " \"showextrema\": False,\n", + " \"showmedians\": False,\n", + " \"vert\": not horizontal\n", + " }\n", + "\n", + " if violin_kwargs is None:\n", + " violin_kwargs = default_violin_kwargs\n", + " else:\n", + " violin_kwargs = merge_two_dicts(default_violin_kwargs, violin_kwargs)\n", + "\n", + "\n", + " default_zeroline_kwargs = {\n", + " \"linewidth\": 1,\n", + " \"color\": \"black\"\n", + " }\n", + " if zeroline_kwargs is None:\n", + " zeroline_kwargs = default_zeroline_kwargs\n", + " else:\n", + " zeroline_kwargs = merge_two_dicts(default_zeroline_kwargs, zeroline_kwargs)\n", + "\n", + " # Effect size marker kwargs\n", + " default_es_marker_kwargs = {\n", + " 'marker': 'o',\n", + " 'markersize': marker_size,\n", + " 'color': 'black',\n", + " 'alpha': 1,\n", + " 'zorder': 2,\n", + " }\n", + " if es_marker_kwargs is None:\n", + " es_marker_kwargs = default_es_marker_kwargs\n", + " else:\n", + " es_marker_kwargs = merge_two_dicts(default_es_marker_kwargs, es_marker_kwargs)\n", + "\n", + " # Effect size error bar kwargs\n", + " default_es_errorbar_kwargs = {\n", + " 'color': 'black',\n", + " 'lw': 2.5,\n", + " 'linestyle': '-',\n", + " 'alpha': 1,\n", + " 'zorder': 1,\n", + " }\n", + " if es_errorbar_kwargs is None:\n", + " es_errorbar_kwargs = default_es_errorbar_kwargs\n", + " else:\n", + " es_errorbar_kwargs = merge_two_dicts(default_es_errorbar_kwargs, es_errorbar_kwargs)\n", + "\n", + " return violin_kwargs, zeroline_kwargs, es_marker_kwargs, es_errorbar_kwargs\n", + "\n", + "\n", + "def color_palette(\n", + " custom_palette, \n", + " labels, \n", + " number_of_curves_to_plot\n", + " ):\n", + " if isinstance(custom_palette, dict):\n", + " violin_colors = [\n", + " custom_palette.get(c, sns.color_palette()[0]) for c in labels\n", + " ]\n", + " elif isinstance(custom_palette, list):\n", + " violin_colors = custom_palette[: number_of_curves_to_plot]\n", + " elif isinstance(custom_palette, str):\n", + " if custom_palette in plt.colormaps():\n", + " violin_colors = sns.color_palette(custom_palette, number_of_curves_to_plot)\n", + " else:\n", + " raise ValueError(\n", + " f\"The specified `custom_palette` {custom_palette} is not a recognized Matplotlib palette.\"\n", + " )\n", + " return violin_colors\n", + "\n", + "\n", "def forest_plot(\n", - " contrasts: List,\n", - " selected_indices: Optional[List] = None,\n", - " contrast_type: str = \"delta2\",\n", + " data: List,\n", + " idx: Optional[List[int]] = None,\n", + " ax: Optional[plt.Axes] = None,\n", + " fig_size: tuple[int, int] = None,\n", " effect_size: str = \"mean_diff\",\n", - " contrast_labels: List[str] = None,\n", - " ylabel: str = \"effect size\",\n", - " plot_elements_to_extract: Optional[List] = None,\n", - " title: str = \"ΔΔ Forest\",\n", + " horizontal: bool = False, \n", + "\n", + " marker_size: int = 12,\n", " custom_palette: Optional[Union[dict, list, str]] = None,\n", - " fontsize: int = 12,\n", - " title_font_size: int =16,\n", - " violin_kwargs: Optional[dict] = None,\n", - " marker_size: int = 20,\n", - " ci_line_width: float = 2.5,\n", - " desat_violin: float = 1,\n", + " halfviolin_alpha: float = 0.8,\n", + " halfviolin_desat: float = 1,\n", + "\n", + " labels: List[str] = None,\n", + " labels_rotation: int = None,\n", + " labels_fontsize: int = 10,\n", + " title: str = \"ΔΔ Forest\",\n", + " title_fontsize: int = 16,\n", + " ylabel: str = None,\n", + " ylabel_fontsize: int = 12,\n", + " ylim: Optional[tuple[float, float] | list[float, float]] = None,\n", + " yticks: Optional[tuple[float] | list[float]] = None,\n", + " yticklabels: Optional[tuple[str] | list[str]] = None,\n", " remove_spines: bool = True,\n", - " ax: Optional[plt.Axes] = None,\n", - " additional_plotting_kwargs: Optional[dict] = None,\n", - " rotation_for_xlabels: int = 45,\n", - " alpha_violin_plot: float = 0.8,\n", - " horizontal: bool = False # New argument for horizontal orientation\n", + "\n", + " violin_kwargs: Optional[dict] = None,\n", + " zeroline_kwargs: Optional[dict] = None,\n", + " es_marker_kwargs: Optional[dict] = None,\n", + " es_errorbar_kwargs: Optional[dict] = None,\n", ")-> plt.Figure:\n", " \"\"\" \n", " Custom function that generates a forest plot from given contrast objects, suitable for a range of data analysis types, including those from packages like DABEST-python.\n", "\n", " Parameters\n", " ----------\n", - " contrasts : List\n", + " data : List\n", " List of contrast objects.\n", - " selected_indices : Optional[List], default=None\n", - " Indices of specific contrasts to plot, if not plotting all.\n", - " analysis_type : str\n", - " the type of analysis (e.g., 'delta2', 'mini_meta').\n", + " idx : Optional[List[int]], default=None\n", + " List of indices to select from the contrast objects if delta-delta experiment. \n", + " If None, only the delta-delta objects are plotted.\n", + " ax : Optional[plt.Axes], default=None\n", + " Matplotlib Axes object for the plot; creates new if None.\n", + " additional_plotting_kwargs : Optional[dict], default=None\n", + " Further customization arguments for the plot.\n", + " fig_size : Tuple[int, int], default=None\n", + " Figure size for the plot.\n", " effect_size : str\n", " Type of effect size to plot (e.g., 'mean_diff', 'median_diff', `cliffs_delta`,`cohens_d``, and `hedges_g`).\n", - " contrast_labels : List[str]\n", - " Labels for each contrast.\n", - " ylabel : str\n", - " Label for the y-axis, describing the plotted data or effect size.\n", - " plot_elements_to_extract : Optional[List], default=None\n", - " Elements to extract for detailed plot customization.\n", + " horizontal : bool, default=False\n", + " If True, the plot will be horizontal.\n", + " marker_size : int, default=12\n", + " Marker size for plotting effect size dots.\n", + " custom_palette : Optional[Union[dict, list, str]], default=None\n", + " Custom color palette for the plot.\n", + " halfviolin_alpha : float, default=0.8\n", + " Transparency level for violin plots.\n", + " halfviolin_desat : float, default=1\n", + " Saturation level for violin plots.\n", + " labels : List[str]\n", + " Labels for each contrast. If None, defaults to 'Contrast 1', 'Contrast 2', etc.\n", + " labels_rotation : int, default=45 for vertical, 0 for horizontal\n", + " Rotation angle for contrast labels.\n", + " labels_fontsize : int, default=10\n", + " Font size for contrast labels.\n", " title : str\n", " Plot title, summarizing the visualized data.\n", - " ylim : Tuple[float, float]\n", + " title_fontsize : int, default=16\n", + " Font size for the plot title.\n", + " ylabel : str\n", + " Label for the y-axis, describing the plotted data or effect size.\n", + " ylabel_fontsize : int, default=12\n", + " Font size for the y-axis label.\n", + " ylim : Optional[Tuple[float, float]]\n", " Limits for the y-axis.\n", - " custom_palette : Optional[Union[dict, list, str]], default=None\n", - " Custom color palette for the plot.\n", - " fontsize : int\n", - " Font size for text elements in the plot.\n", - " title_font_size: int =16\n", - " Font size for text of plot title.\n", + " yticks : Optional[List[float]]\n", + " Custom y-ticks for the plot.\n", + " yticklabels : Optional[List[str]]\n", + " Custom y-tick labels for the plot.\n", + " remove_spines : bool, default=True\n", + " If True, removes plot spines (except the relevant dependent variable spine).\n", " violin_kwargs : Optional[dict], default=None\n", " Additional arguments for violin plot customization.\n", - " marker_size : int\n", - " Marker size for plotting mean differences or effect sizes.\n", - " ci_line_width : float\n", - " Width of confidence interval lines.\n", - " remove_spines : bool, default=False\n", - " If True, removes top and right plot spines.\n", - " ax : Optional[plt.Axes], default=None\n", - " Matplotlib Axes object for the plot; creates new if None.\n", - " additional_plotting_kwargs : Optional[dict], default=None\n", - " Further customization arguments for the plot.\n", - " rotation_for_xlabels : int, default=0\n", - " Rotation angle for x-axis labels, improving readability.\n", - " alpha_violin_plot : float, default=1.0\n", - " Transparency level for violin plots.\n", + " zeroline_kwargs : Optional[dict], default=None\n", + " Additional arguments for the zero line customization.\n", + " es_marker_kwargs : Optional[dict], default=None\n", + " Additional arguments for the effect size marker customization.\n", + " es_errorbar_kwargs : Optional[dict], default=None\n", + " Additional arguments for the effect size error bar customization.\n", "\n", " Returns\n", " -------\n", @@ -224,162 +475,151 @@ " \"\"\"\n", " from .plot_tools import halfviolin\n", "\n", - " # Validate inputs\n", - " if contrasts is None:\n", - " raise ValueError(\"The `contrasts` parameter cannot be None\")\n", - " \n", - " if not isinstance(contrasts, list) or not contrasts:\n", - " raise ValueError(\"The `contrasts` argument must be a non-empty list.\")\n", - " \n", - " if selected_indices is not None and not isinstance(selected_indices, (list, type(None))):\n", - " raise TypeError(\"The `selected_indices` must be a list of integers or `None`.\")\n", - " \n", - " # For the 'contrast_type' parameter\n", - " if not isinstance(contrast_type, str):\n", - " raise TypeError(\"The `contrast_type` argument must be a string. Please choose from `delta2` and `mini_meta`.\")\n", - "\n", - " # For the 'effect_size' parameter\n", - " if not isinstance(effect_size, str):\n", - " raise TypeError(\"The `effect_size` argument must be a string. Please choose from the following effect sizes: `mean_diff`, `median_diff`, `cliffs_delta`, `cohens_d`, and `hedges_g`.\")\n", - " \n", - " if contrast_labels is not None and not all(isinstance(label, str) for label in contrast_labels):\n", - " raise TypeError(\"The `contrast_labels` must be a list of strings or `None`.\")\n", - " \n", - " if contrast_labels is not None and len(contrast_labels) != len(contrasts):\n", - " raise ValueError(\"`contrast_labels` must match the number of `contrasts` if provided.\")\n", - " \n", - " if not isinstance(ylabel, str):\n", - " raise TypeError(\"The `ylabel` argument must be a string.\")\n", - " \n", - " if custom_palette is not None and not isinstance(custom_palette, (dict, list, str, type(None))):\n", - " raise TypeError(\"The `custom_palette` must be either a dictionary, list, string, or `None`.\")\n", - " \n", - " if not isinstance(fontsize, (int, float)):\n", - " raise TypeError(\"`fontsize` must be an integer or float.\")\n", - " \n", - " if not isinstance(marker_size, (int, float)) or marker_size <= 0:\n", - " raise TypeError(\"`marker_size` must be a positive integer or float.\")\n", - " \n", - " if not isinstance(ci_line_width, (int, float)) or ci_line_width <= 0:\n", - " raise TypeError(\"`ci_line_width` must be a positive integer or float.\")\n", - " \n", - " if not isinstance(remove_spines, bool):\n", - " raise TypeError(\"`remove_spines` must be a boolean value.\")\n", - " \n", - " if ax is not None and not isinstance(ax, plt.Axes):\n", - " raise TypeError(\"`ax` must be a `matplotlib.axes.Axes` instance or `None`.\")\n", - " \n", - " if not isinstance(rotation_for_xlabels, (int, float)) or not 0 <= rotation_for_xlabels <= 360:\n", - " raise TypeError(\"`rotation_for_xlabels` must be an integer or float between 0 and 360.\")\n", - " \n", - " if not isinstance(alpha_violin_plot, float) or not 0 <= alpha_violin_plot <= 1:\n", - " raise TypeError(\"`alpha_violin_plot` must be a float between 0 and 1.\")\n", " \n", - " if not isinstance(horizontal, bool):\n", - " raise TypeError(\"`horizontal` must be a boolean value.\")\n", - "\n", - " if (effect_size and isinstance(effect_size, str)):\n", - " ylabel = map_effect_attribute(effect_size)\n", - " # Load plot data\n", - " contrast_plot_data = load_plot_data(contrasts, effect_size, contrast_type)\n", + " # Check for errors in the input arguments\n", + " check_for_errors(\n", + " data = data,\n", + " idx = idx,\n", + " ax = ax,\n", + " fig_size = fig_size,\n", + " effect_size = effect_size,\n", + " horizontal = horizontal,\n", + " marker_size = marker_size,\n", + " custom_palette = custom_palette,\n", + " halfviolin_alpha = halfviolin_alpha,\n", + " halfviolin_desat = halfviolin_desat,\n", + " labels = labels,\n", + " labels_rotation = labels_rotation,\n", + " labels_fontsize = labels_fontsize,\n", + " title = title,\n", + " title_fontsize = title_fontsize,\n", + " ylabel = ylabel,\n", + " ylabel_fontsize = ylabel_fontsize,\n", + " ylim = ylim,\n", + " yticks = yticks,\n", + " yticklabels = yticklabels,\n", + " remove_spines = remove_spines,\n", + " \n", + " )\n", "\n", - " # Extract data for plotting\n", - " bootstraps, differences, bcalows, bcahighs = extract_plot_data(\n", - " contrast_plot_data, contrast_type\n", + " # Load plot data and extract info\n", + " bootstraps, differences, bcalows, bcahighs = load_plot_data(\n", + " data = data, \n", + " effect_size = effect_size, \n", + " idx = idx\n", " )\n", + "\n", " # Adjust figure size based on orientation\n", - " all_groups_count = len(contrasts)\n", - " if horizontal:\n", - " fig_size = (4, 1.5 * all_groups_count)\n", + " number_of_curves_to_plot = sum([len(i) for i in idx]) if idx is not None else len(data)\n", + " if ax is not None:\n", + " fig = ax.figure\n", " else:\n", - " fig_size = (1.5 * all_groups_count, 4)\n", - "\n", - " if ax is None:\n", + " if fig_size is None:\n", + " fig_size = (4, 1.3 * number_of_curves_to_plot) if horizontal else (1.3 * number_of_curves_to_plot, 4)\n", " fig, ax = plt.subplots(figsize=fig_size)\n", - " else:\n", - " fig = ax.figure\n", - "\n", - " # Adjust violin plot orientation based on the 'horizontal' argument\n", - " violin_kwargs = violin_kwargs or {\n", - " \"widths\": 0.5,\n", - " \"showextrema\": False,\n", - " \"showmedians\": False,\n", - " }\n", - " violin_kwargs[\"vert\"] = not horizontal\n", - " v = ax.violinplot(bootstraps, **violin_kwargs)\n", "\n", - " # Adjust the halfviolin function call based on 'horizontal'\n", - " if horizontal:\n", - " half = \"top\"\n", - " else:\n", - " half = \"right\" # Assuming \"right\" is the default or another appropriate value\n", + " # Get Kwargs\n", + " violin_kwargs, zeroline_kwargs, es_marker_kwargs, es_errorbar_kwargs = get_kwargs(\n", + " violin_kwargs = violin_kwargs,\n", + " zeroline_kwargs = zeroline_kwargs,\n", + " horizontal = horizontal,\n", + " es_marker_kwargs = es_marker_kwargs,\n", + " es_errorbar_kwargs = es_errorbar_kwargs,\n", + " marker_size = marker_size\n", + " )\n", + " \n", + " # Plot the violins and make adjustments\n", + " v = ax.violinplot(\n", + " bootstraps, \n", + " **violin_kwargs\n", + " )\n", + " halfviolin(\n", + " v, \n", + " alpha = halfviolin_alpha, \n", + " half = \"bottom\" if horizontal else \"right\",\n", "\n", - " # Assuming halfviolin has been updated to accept a 'half' parameter\n", - " halfviolin(v, alpha=alpha_violin_plot, half=half)\n", + " )\n", + " \n", + " ## Plotting the effect sizes and confidence intervals\n", + " for k in range(1, number_of_curves_to_plot + 1):\n", + " if horizontal:\n", + " ax.plot(differences[k - 1], k, **es_marker_kwargs) \n", + " ax.plot([bcalows[k - 1], bcahighs[k - 1]], [k, k], **es_errorbar_kwargs) \n", + " else:\n", + " ax.plot(k, differences[k - 1], **es_marker_kwargs)\n", + " ax.plot([k, k], [bcalows[k - 1], bcahighs[k - 1]], **es_errorbar_kwargs)\n", " \n", - " # Handle the custom color palette\n", + " # Aesthetic Adjustments\n", + " ## Handle the custom color palette\n", " if custom_palette:\n", - " if isinstance(custom_palette, dict):\n", - " violin_colors = [\n", - " custom_palette.get(c, sns.color_palette()[0]) for c in contrast_labels\n", - " ]\n", - " elif isinstance(custom_palette, list):\n", - " violin_colors = custom_palette[: len(contrasts)]\n", - " elif isinstance(custom_palette, str):\n", - " if custom_palette in plt.colormaps():\n", - " violin_colors = sns.color_palette(custom_palette, len(contrasts))\n", - " else:\n", - " raise ValueError(\n", - " f\"The specified `custom_palette` {custom_palette} is not a recognized Matplotlib palette.\"\n", - " )\n", + " violin_colors = color_palette(\n", + " custom_palette = custom_palette, \n", + " labels = labels, \n", + " number_of_curves_to_plot = number_of_curves_to_plot\n", + " )\n", " else:\n", - " violin_colors = sns.color_palette(n_colors=len(contrasts))\n", - "\n", - " violin_colors = [sns.desaturate(color, desat_violin) for color in violin_colors]\n", + " violin_colors = sns.color_palette(n_colors=number_of_curves_to_plot)\n", + " violin_colors = [sns.desaturate(color, halfviolin_desat) for color in violin_colors]\n", " \n", " for patch, color in zip(v[\"bodies\"], violin_colors):\n", " patch.set_facecolor(color)\n", - " patch.set_alpha(alpha_violin_plot)\n", + "\n", + " ## Add a zero line to the plot\n", " if horizontal:\n", - " ax.plot([0, 0], [0, len(contrasts)+1], 'k', linewidth = 1)\n", + " ax.plot([0, 0], [0, number_of_curves_to_plot+1], **zeroline_kwargs) \n", " else:\n", - " ax.plot([0, len(contrasts)+1], [0, 0], 'k', linewidth = 1)\n", - " \n", - " # Flipping the axes for plotting based on 'horizontal'\n", - " for k in range(1, len(contrasts) + 1):\n", - " if horizontal:\n", - " ax.plot(differences[k - 1], k, \"k.\", markersize=marker_size) # Flipped axes\n", - " ax.plot([bcalows[k - 1], bcahighs[k - 1]], [k, k], \"k\", linewidth=ci_line_width) # Flipped axes\n", - " else:\n", - " ax.plot(k, differences[k - 1], \"k.\", markersize=marker_size)\n", - " ax.plot([k, k], [bcalows[k - 1], bcahighs[k - 1]], \"k\", linewidth=ci_line_width)\n", + " ax.plot([0, number_of_curves_to_plot+1], [0, 0], **zeroline_kwargs)\n", "\n", - " # Adjusting labels, ticks, and limits based on 'horizontal'\n", + " ## lims\n", + " ### Indepedent variable\n", " if horizontal:\n", - " ax.set_yticks(range(1, len(contrasts) + 1))\n", - " ax.set_yticklabels(contrast_labels, rotation=0, fontsize=fontsize)\n", - " ax.set_xlabel(ylabel, fontsize=fontsize)\n", - " ax.set_ylim([0.7, len(contrasts) + 0.5])\n", + " ax.set_ylim([0.7, number_of_curves_to_plot + 0.2])\n", " else:\n", - " ax.set_xticks(range(1, len(contrasts) + 1))\n", - " ax.set_xticklabels(contrast_labels, rotation=rotation_for_xlabels, fontsize=fontsize)\n", - " ax.set_ylabel(ylabel, fontsize=fontsize)\n", - " ax.set_xlim([0.7, len(contrasts) + 0.5])\n", + " ax.set_xlim([0.7, number_of_curves_to_plot + 0.5])\n", + "\n", + " ## Depedent variable\n", + " if ylim is not None:\n", + " lim_key = ax.set_xlim if horizontal else ax.set_ylim\n", + " lim_key(ylim)\n", + "\n", + " ## Ticks\n", + " ### Indepedent variable\n", + " lim_key = ax.set_yticks if horizontal else ax.set_xticks\n", + " lim_key(range(1, number_of_curves_to_plot + 1))\n", "\n", - " # Setting the title and adjusting spines as before\n", - " ax.set_title(title, fontsize=title_font_size)\n", + " if labels_rotation == None:\n", + " labels_rotation = 0 if horizontal else 45\n", + " if labels is None:\n", + " labels = [f\"Contrast {i}\" for i in range(1, number_of_curves_to_plot + 1)]\n", + " lim_key = ax.set_yticklabels if horizontal else ax.set_xticklabels\n", + " lim_key(labels, rotation=labels_rotation, fontsize=labels_fontsize, ha=\"right\")\n", + "\n", + " ### Depedent variable\n", + " if yticks is not None:\n", + " lim_key = ax.set_xticks if horizontal else ax.set_yticks\n", + " lim_key(yticks)\n", + "\n", + " if yticklabels is not None:\n", + " lim_key = ax.set_xticklabels if horizontal else ax.set_yticklabels\n", + " lim_key(yticklabels)\n", + "\n", + " ## y-label \n", + " if ylabel is None:\n", + " ylabel = map_effect_attribute(effect_size)\n", + " lim_key = ax.set_xlabel if horizontal else ax.set_ylabel\n", + " lim_key(ylabel, fontsize=ylabel_fontsize)\n", + "\n", + " ## Setting the title\n", + " ax.set_title(title, fontsize=title_fontsize)\n", + "\n", + " ## Adjust Spines\n", " if remove_spines:\n", - " if horizontal:\n", - " ax.spines['left'].set_visible(False)\n", - " ax.spines['right'].set_visible(False)\n", - " ax.spines['top'].set_visible(False)\n", - " else:\n", - " ax.spines['top'].set_visible(False)\n", - " ax.spines['bottom'].set_visible(False)\n", - " ax.spines['right'].set_visible(False)\n", - " # Apply additional customizations if provided\n", - " if additional_plotting_kwargs:\n", - " ax.set(**additional_plotting_kwargs)\n", + " spines = [\"top\", \"right\", \"left\"] if horizontal else [\"top\", \"right\", \"bottom\"]\n", + " ax.spines[spines].set_visible(False)\n", + "\n", + " ## Invert Y-axis if horizontal \n", + " if horizontal:\n", + " ax.invert_yaxis()\n", "\n", " return fig" ] diff --git a/nbs/API/plot_tools.ipynb b/nbs/API/plot_tools.ipynb index 3f72e633..6ff3fdc3 100644 --- a/nbs/API/plot_tools.ipynb +++ b/nbs/API/plot_tools.ipynb @@ -2995,7 +2995,7 @@ " ax.scatter(\n", " [],\n", " [],\n", - " c=self.__palette[cmap_group_i],\n", + " color=self.__palette[cmap_group_i],\n", " label=cmap_group_i,\n", " )\n", "\n", diff --git a/nbs/API/plotter.ipynb b/nbs/API/plotter.ipynb index 8d661f96..4b13539d 100644 --- a/nbs/API/plotter.ipynb +++ b/nbs/API/plotter.ipynb @@ -421,7 +421,7 @@ " (current_group, current_control,\n", " current_effsize, contrast_xtick_labels) = effect_size_curve_plotter(\n", " ticks_to_plot = ticks_to_plot, \n", - " ticks_for_baseline_ec=ticks_for_baseline_ec,\n", + " ticks_for_baseline_ec = ticks_for_baseline_ec,\n", " results = results, \n", " ci_type = ci_type, \n", " contrast_axes = contrast_axes, \n", diff --git a/nbs/tests/data/mocked_data_test_forestplot.py b/nbs/tests/data/mocked_data_test_forestplot.py index 888f6850..f80227ed 100644 --- a/nbs/tests/data/mocked_data_test_forestplot.py +++ b/nbs/tests/data/mocked_data_test_forestplot.py @@ -37,23 +37,18 @@ # Default forestplot params for unit testing default_forestplot_kwargs = { - "contrasts": dummy_contrasts, # Ensure this is a list of contrast objects. - "selected_indices": None, # Valid as None or a list of integers. - "contrast_type": "delta2", # Ensure it's a string and one of the allowed contrast types. + "data": dummy_contrasts, # Ensure this is a list of contrast objects. + "idx": None, # Valid as None or a list of lists of integers. "effect_size": "mean_diff", # Ensure it's a string. - "contrast_labels": ["Drug1"], # This should be a list of strings. + "labels": ["Drug1"], # This should be a list of strings. "ylabel": "Effect Size", # Ensure it's a string. - #"plot_elements_to_extract": None, # No specific checks needed based on your tests. - #"title": "ΔΔ Forest Plot", # Ensure it's a string. + "title": "ΔΔ Forest Plot", # Ensure it's a string. "custom_palette": None, # Valid as None, a dictionary, list, or string. - "fontsize": 20, # Ensure it's an integer or float. "violin_kwargs": None, # No specific checks needed based on your tests. "marker_size": 20, # Ensure it's a positive integer or float. - "ci_line_width": 2.5, # Ensure it's a positive integer or float. "remove_spines": True, # Ensure it's a boolean. - "additional_plotting_kwargs": None, # No specific checks needed based on your tests. - "rotation_for_xlabels": 45, # Ensure it's an integer or float between 0 and 360. - "alpha_violin_plot": 0.8, # Ensure it's a float between 0 and 1. + "labels_rotation": 45, # Ensure it's an integer or float between 0 and 360. + "halfviolin_alpha": 0.8, # Ensure it's a float between 0 and 1. 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zd#bF!lX{p1tIx$oXkOl%;Z>dgOt?H&qFwNM00*?m?6)0EmhDoIGHfqA8C#F6@%QgM zKv<#Sg%UVpRIIG5Q#hCL{_W=Bj*VrsuR)nv7o3RMg@q7Uq#Vfe`97pGns32)4X^D` zo*d1b;&L_V`wdG6`m8xk&LLZgR=V#2fA%=UGY}i-!GeMmp1|E%y)gI{-q+J33l0{? z@zVPuan8n*|27};L=+B}-)_L(#9fH@Fscq9ZTgqHySsCMeP8`j&K4x|gRe`pMC#uX dDk`2ZH!H141PN0zz^i&FRYgrqsl3JG{{dW+X&V3l literal 0 HcmV?d00001 diff --git a/nbs/tests/mpl_image_tests/test_05_forest_plot.py b/nbs/tests/mpl_image_tests/test_05_forest_plot.py index 430a4eb3..1c83e508 100644 --- a/nbs/tests/mpl_image_tests/test_05_forest_plot.py +++ b/nbs/tests/mpl_image_tests/test_05_forest_plot.py @@ -157,42 +157,174 @@ def create_mini_meta_dataset(N=20, seed=9999, control_locs=[3, 3.5, 3.25], contr from dabest.forest_plot import forest_plot @pytest.mark.mpl_image_compare(tolerance=8) -def test_201_forest_plot_no_colorpalette(): - return forest_plot(contrasts, - contrast_labels=['Drug1', 'Drug2', 'Drug3']) +def test_500_deltadelta_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'] + ) @pytest.mark.mpl_image_compare(tolerance=8) -def test_202_forest_plot_with_colorpalette(): - return forest_plot(contrasts, - contrast_labels=['Drug1', 'Drug2', 'Drug3'], - custom_palette=['gray', 'blue', 'green']) +def test_501_deltadelta_with_deltas_idx_forest(): + return forest_plot( + contrasts, + labels=['Drug1 Delta', 'Drug1 Delta-Delta', + 'Drug2 Delta', 'Drug2 Delta-Delta', + 'Drug3 Delta', 'Drug3 Delta-Delta' + ], + idx = [(0, 2), (0, 2), (0, 2)] + ) @pytest.mark.mpl_image_compare(tolerance=8) -def test_203_horizontal_forest_plot_no_colorpalette(): - return forest_plot(contrasts, - contrast_labels=['Drug1', 'Drug2', 'Drug3'], - horizontal=True) +def test_502_minimeta_forest(): + return forest_plot( + contrasts_mini_meta, + labels=['mini_meta1', 'mini_meta2', 'mini_meta3'] + ) + + + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_503_deltadelta_custompalette_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + custom_palette=['gray', 'blue', 'green'] + ) + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_504_deltadelta_horizontal_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + horizontal=True + ) + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_505_deltadelta_insert_ax_forest(): + f_forest_drug_profiles, axes = plt.subplots(2, 2, figsize=[15, 14]) + f_forest_drug_profiles.subplots_adjust(hspace=0.3, wspace=0.3) + + for ax, contrast in zip(axes.flatten(), [unpaired_delta_01, unpaired_delta_02, unpaired_delta_03]): + contrast.mean_diff.plot( + contrast_label='Mean Diff', + raw_marker_size = 1, + es_marker_size = 5, + color_col='Genotype', + ax = ax + ) + forest_plot( + data = contrasts, + labels = ['Drug1', 'Drug2', 'Drug3'], + ax = axes[1,1], + ) + + for ax, title in zip(axes.flatten(), ['Drug 1', 'Drug 2', 'Drug 3', 'Forest plot']): + ax.set_title(title, fontsize = 12) + + return f_forest_drug_profiles + + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_506_deltadelta_mediandiff_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + effect_size='median_diff' + ) @pytest.mark.mpl_image_compare(tolerance=8) -def test_204_horizontal_forest_plot_with_colorpalette(): - return forest_plot(contrasts, - contrast_labels=['Drug1', 'Drug2', 'Drug3'], - custom_palette=['gray', 'blue', 'green'], - horizontal=True) +def test_507_deltadelta_fig_size_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + fig_size=[6, 6] + ) @pytest.mark.mpl_image_compare(tolerance=8) -def test_206_forest_mini_meta(): - return forest_plot(contrasts_mini_meta, - contrast_type='mini_meta', - contrast_labels=['mini_meta1', 'mini_meta2', 'mini_meta3']) +def test_508_deltadelta_fig_size_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + fig_size=[6, 6] + ) @pytest.mark.mpl_image_compare(tolerance=8) -def test_205_forest_mini_meta_horizontal(): - return forest_plot(contrasts_mini_meta, - contrast_type='mini_meta', - contrast_labels=['mini_meta1', 'mini_meta2', 'mini_meta3'], - horizontal=True) +def test_509_deltadelta_halfviolin_aesthetics_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + halfviolin_alpha=0.2, + halfviolin_desat=0.2 + ) +@pytest.mark.mpl_image_compare(tolerance=8) +def test_510_deltadelta_labels_and_title_aesthetics_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + labels_fontsize=12, + labels_rotation=0, + ylabel='Effect Size', + ylabel_fontsize=14, + title='Drug Efficacy', + title_fontsize=20 + ) + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_511_deltadelta_lims_and_ticks_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + ylim=[-1, 1], + yticks=[-1, 0, 1], + yticklabels=['Negative', 'Zero', 'Positive'] + ) +@pytest.mark.mpl_image_compare(tolerance=8) +def test_512_deltadelta_spines_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + remove_spines=False + ) + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_513_deltadelta_violinkwargs_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + violin_kwargs={ + "widths": 0.8, "showextrema": True, + "showmedians": True, "vert": True + } + ) +@pytest.mark.mpl_image_compare(tolerance=8) +def test_514_deltadelta_zerolinekwargs_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + zeroline_kwargs={"linewidth": 2, "color": "red"} + ) + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_515_deltadelta_esmarkerkwargs_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + es_marker_kwargs={ + 'marker': '^', 'markersize': 15,'color': 'blue', + 'alpha': 0.5, + } + ) + +@pytest.mark.mpl_image_compare(tolerance=8) +def test_516_deltadelta_eserrorbarkwargs_forest(): + return forest_plot( + contrasts, + labels=['Drug1', 'Drug2', 'Drug3'], + es_errorbar_kwargs={ + 'color': 'red', 'lw': 4, 'linestyle': '--', 'alpha': 0.6, + } + ) \ No newline at end of file diff --git a/nbs/tests/test_forest_plot.py b/nbs/tests/test_forest_plot.py index e2b469ec..e3af8bf6 100644 --- a/nbs/tests/test_forest_plot.py +++ b/nbs/tests/test_forest_plot.py @@ -2,33 +2,42 @@ import pandas as pd import numpy as np import matplotlib.pyplot as plt -from dabest.forest_plot import load_plot_data, extract_plot_data, forest_plot -from data.mocked_data_test_forestplot import dummy_contrasts, default_forestplot_kwargs +from dabest.forest_plot import forest_plot +from data.mocked_data_test_forestplot import default_forestplot_kwargs def test_forest_plot_no_input_parameters(): - error_msg = "The `contrasts` parameter cannot be None" + error_msg = "The `data` argument must be a non-empty list of dabest objects." with pytest.raises(ValueError) as excinfo: - forest_plot(contrasts = None) + forest_plot(data = None) assert error_msg in str(excinfo.value) @pytest.mark.parametrize("param_name, param_value, error_msg, error_type", [ - ("contrasts", None, "The `contrasts` parameter cannot be None", ValueError), - ("contrasts", [], "The `contrasts` argument must be a non-empty list.", ValueError), - ("selected_indices", "not a list or None", "The `selected_indices` must be a list of integers or `None`.", TypeError), - ("contrast_type", 123, "The `contrast_type` argument must be a string. Please choose from `delta2` and `mini_meta`.", TypeError), - ("effect_size", 456, "The `effect_size` argument must be a string. Please choose from the following effect sizes: `mean_diff`, `median_diff`, `cliffs_delta`, `cohens_d`, and `hedges_g`.", TypeError), - ("contrast_labels", ["valid", 123], "The `contrast_labels` must be a list of strings or `None`.", TypeError), - ("ylabel", 789, "The `ylabel` argument must be a string.", TypeError), - ("custom_palette", 123, "The `custom_palette` must be either a dictionary, list, string, or `None`.", TypeError), - ("fontsize", "big", "`fontsize` must be an integer or float.", TypeError), + ("data", [], "The `data` argument must be a non-empty list of dabest objects.", ValueError), + ("idx", 123, "`idx` must be a tuple or list of integers.", TypeError), + ("ax", "axes", "The `ax` must be a `matplotlib.axes.Axes` instance or `None`.", TypeError), + ("effect_size", 456, "The `effect_size` argument must be a string and please choose from the following effect sizes: `mean_diff`, `median_diff`, `cliffs_delta`, `cohens_d`, and `hedges_g`.", TypeError), + ("horizontal", "sideways", "`horizontal` must be a boolean value.", TypeError), ("marker_size", "large", "`marker_size` must be a positive integer or float.", TypeError), - ("ci_line_width", "thick", "`ci_line_width` must be a positive integer or float.", TypeError), + ("custom_palette", 123, "The `custom_palette` must be either a dictionary, list, string, or `None`.", TypeError), + ("halfviolin_alpha", "opaque", "`halfviolin_alpha` must be a float between 0 and 1.", TypeError), + ("halfviolin_desat", "yes", "`halfviolin_desat` must be a float between 0 and 1 or an int (1).", TypeError), + ("labels", ["valid", 123], "The `labels` must be a list of strings or `None`.", TypeError), + ("labels", ['valid', 'valid'], "`labels` must match the number of `data` provided.", ValueError), + ("labels_fontsize", "big", "`labels_fontsize` must be an integer or float.", TypeError), + ("labels_rotation", "right", "`labels_rotation` must be an integer or float between 0 and 360.", TypeError), + ("title", 123, "The `title` argument must be a string.", TypeError), + ("title_fontsize", "big", "`title_fontsize` must be an integer or float.", TypeError), + ("ylabel", 789, "The `ylabel` argument must be a string.", TypeError), + ("ylabel_fontsize", "big", "`ylabel_fontsize` must be an integer or float.", TypeError), + ("ylim", "auto", "`ylim` must be a tuple or list of two floats.", TypeError), + ("ylim", [0, 1, 2], "`ylim` must be a tuple or list of two floats.", ValueError), + ("yticks", "auto", "`yticks` must be a tuple or list of floats.", TypeError), + ("yticklabels", "auto", "`yticklabels` must be a tuple or list of strings.", TypeError), + ("yticklabels", [532, 123], "`yticklabels` must be a list of strings.", TypeError), ("remove_spines", "yes", "`remove_spines` must be a boolean value.", TypeError), - ("rotation_for_xlabels", "right", "`rotation_for_xlabels` must be an integer or float between 0 and 360.", TypeError), - ("alpha_violin_plot", "opaque", "`alpha_violin_plot` must be a float between 0 and 1.", TypeError), - ("horizontal", "sideways", "`horizontal` must be a boolean value.", TypeError), ]) + def test_forest_plot_input_error_handling(param_name, param_value, error_msg, error_type): # Setup: Define a base set of valid inputs to forest_plot valid_inputs = default_forestplot_kwargs.copy() diff --git a/nbs/tutorials/07-forest_plot.ipynb b/nbs/tutorials/07-forest_plot.ipynb index a8ac32a0..fd6b7e29 100644 --- a/nbs/tutorials/07-forest_plot.ipynb +++ b/nbs/tutorials/07-forest_plot.ipynb @@ -17,7 +17,9 @@ "id": "cfdb7e31", "metadata": {}, "source": [ - "In DABEST version xx.xx.xx, we introduce a new function to plot separately calculated effect sizes in the same axes to allow direct visual comparisons. Currently you can make a forest plot for delta-delta and mini-meta effect sizes. " + "In DABEST version xx.xx.xx, we introduce a new function to plot separately calculated effect sizes in the same axes to allow direct visual comparisons. \n", + "\n", + "Currently you can make a forest plot for delta-delta and mini-meta effect sizes. In addition, for delta-delta experiments, you can also plot the effect sizes of the original comparisons alongside the delta-delta measurement." ] }, { @@ -95,7 +97,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "We're using DABEST v2024.03.29\n" + "Pre-compiling numba functions for DABEST...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Compiling numba functions: 100%|██████████| 11/11 [00:03<00:00, 3.58it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Numba compilation complete!\n", + "We're using DABEST v2024.03.30\n" ] } ], @@ -227,21 +244,9 @@ "id": "36a5e3fd", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathananns/GitHub/DABEST-python/dabest/plot_tools.py:2882: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n", - " ax.scatter(\n", - "/Users/jonathananns/GitHub/DABEST-python/dabest/plot_tools.py:2882: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n", - " ax.scatter(\n", - "/Users/jonathananns/GitHub/DABEST-python/dabest/plot_tools.py:2882: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n", - " ax.scatter(\n" - ] - }, { "data": { - "image/png": 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", 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", 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", + "image/png": 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", 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", 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", 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" ] @@ -277,7 +282,6 @@ " fig_size = (7, 4),\n", " raw_marker_size = 1,\n", " es_marker_size = 5,\n", - " color_col='Genotype'\n", ");\n", "f1.suptitle('Delta-delta plot for Drug 1');\n", "\n", @@ -287,7 +291,6 @@ " fig_size = (7, 4),\n", " raw_marker_size = 1,\n", " es_marker_size = 5,\n", - " color_col='Genotype'\n", ");\n", "f2.suptitle('Delta-delta plot for Drug 2');\n", "\n", @@ -297,7 +300,6 @@ " fig_size = (7, 4),\n", " raw_marker_size = 1,\n", " es_marker_size = 5,\n", - " color_col='Genotype'\n", ");\n", "f3.suptitle('Delta-delta plot for Drug 3');\n" ] @@ -307,7 +309,7 @@ "id": "bb289b05", "metadata": {}, "source": [ - "## Plot all the delta-delta plots into a forest plot for comparisons of different ``Drug`` effects" + "## Plot the delta-delta effect sizes together" ] }, { @@ -315,40 +317,74 @@ "id": "982afbdb", "metadata": {}, "source": [ + "This will allow for comparisons of different ``Drug`` effects.\n", + "\n", "Key Parameters:\n", "\n", - "- ``contrasts``: A list of contrast objects \n", + "- ``data``: A list of dabest objects \n", "\n", - "- ``contrast_type``: Select between ``\"delta2\"`` (for delta-delta) or ``\"mini_meta\"`` for mini-meta \n", + "- ``labels``: A list of labels for the dabest objects. E.g., ``['Drug1', 'Drug2', 'Drug3']``\n", "\n", - "- ``contrast_labels``: A list of labels for the contrast objects. E.g., ``['Drug1', 'Drug2', 'Drug3']``\n", + "- ``effect_size``: Select the effect size metric from ``\"mean_diff\", \"median_diff\", \"cliffs_delta\", \"cohens_d\", \"hedges_g\", or \"delta_g\"``. The default is ``\"mean_diff\"``. Not all effect sizes are available for all situations.\n", "\n", - "- ``effect_size``: Select the effect size metric from ``\"mean_diff\", \"median_diff\", \"cliffs_delta\", \"cohens_d\", \"hedges_g\", or \"delta_g\"``. The default is ``\"mean_diff\"``\n", + "- ``horizontal``: A boolean input (``True``/ ``False``) to adjust the plot orientation. The default is vertical orientation (``False``) \n", "\n", - "- ``ylabel``: The axis label of dependent variable (Y-axis for vertical layout, X-axis for horizontal layout). The default is ``\"value\"``\n", + "- ``ax``: Optional: To specify an existing matplotlib axes (otherwise a standalone figure will be created) \n", "\n", - "- ``title``: The plot title. The default is ``\"ΔΔ Forest\"``\n", + "See the [Controlling Aesthetics](#Controlling-Aesthetics) section for more information on how to alter the aesthetics of the plots.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a424896-05cd-4c72-a004-b40c9056b292", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f_forest_delta2 = forest_plot(\n", + " data = contrasts, \n", + " labels = ['Drug1', 'Drug2', 'Drug3']\n", + ");" + ] + }, + { + "cell_type": "markdown", + "id": "b632c462", + "metadata": {}, + "source": [ + "## Plot delta effect sizes alongside the delta-delta effect sizes\n", "\n", - "- ``ax``: Specify a matplotlib axes to put the plot into existing figures \n", + "If you want to plot the original effect sizes alongside the delta-delta effect sizes, you can do so by utilising the `idx` parameter. \n", "\n", - "- ``horizontal``: A boolean input (``True``/ ``False``) to adjust the plot orientation. The default is vertical orientation (``False``) \n", + "This parameter takes a tuple/list of indices of the original effect sizes you want to plot. This `idx` parameter is only available for delta-delta dabest objetcs. \n", "\n", - "- ``custom_palette``: A list or dictionary of colors, one for each contrast object. E.g., ``['gray', 'blue', 'green']`` or ``{'Drug1':'gray', 'Drug2':'blue', 'Drug3':'green'}``\n", + "For example, if you want to plot only the first effect size and the delta-delta effect size for each of the three dabest object supplied, you can do so by setting `idx=[[0, 2],[0, 2],[0, 2]]`.\n", "\n", - "- Additional kwargs are supported such as ``violin_kwargs``, ``fontsize``, ``marker_size``, ``ci_line_width``, ``rotation_for_xlabels``, ``alpha_violin_plot``, ``remove_spines``, ``desat_violin``, and ``additional_plotting_kwargs``\n" + "See example below." ] }, { "cell_type": "code", "execution_count": null, - "id": "9a424896-05cd-4c72-a004-b40c9056b292", + "id": "cb420b0f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -356,8 +392,11 @@ } ], "source": [ - "f_forest_delta2 = forest_plot(contrasts, \n", - " contrast_labels =['Drug1', 'Drug2', 'Drug3']);" + "f_forest_delta2 = forest_plot(\n", + " data = contrasts, \n", + " labels = ['Drug1 Delta1', 'Drug1 Delta-Delta', 'Drug2 Delta1', 'Drug2 Delta-Delta', 'Drug3 Delta1', 'Drug3 Delta-Delta'],\n", + " idx=[[0, 2], [0, 2], [0, 2]]\n", + ");" ] }, { @@ -473,9 +512,9 @@ "outputs": [ { "data": { - "image/png": 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TCk0LCwvDli1biv2cnJwc5OT87x6r9PRH3dMjIyPh5uZWhm9gGCEEPvnkE6PWjdm7Hs9Ub2CWwDl3E/jJIx21/dxNvm0iIgBo2rRpqcsoNszu3buH/Px8+Pr6Fpru6+uLK1euFLlOQkJCkcsnJCQU+znz5s3DzJkzn5reoUMHI6qWg8CDtCQc+WSU2T7h8CKzbZqISK+zUYoNs/IyZcqUQkdz6enpCAoKwsGDB8v1yCw+Ph4vvvii0ev/6435cPKoaMKK/sfPwwmTn69nlm0TEelDsWFWsWJFqNVqJCYmFpqemJgIPz+/Itfx8/MzaHkAcHR0hKOj41PTGzduXK7XzKpUqVKm9Z+p3gAOrh4mqqYwN3dHvU4DEBGZi2J7Mzo4OKBZs2bYu3evbppWq8XevXvRqlWrItdp1apVoeUBYPfu3cUub0m8vb0RHBxsxHUvCS4VK8PexXzBG/iMs9m2TUSkD8WGGQBMmDABK1aswNq1a3H58mW8+eabuH//PoYPHw4AGDJkSKEOIu+++y527tyJxYsX48qVK5gxYwZOnz6Nd955R66voDdJkjBmzBij1q3eoZ9Zext2rlvJbNsmItKHosPslVdewSeffIKPPvoIjRs3RmRkJHbu3Knr5BEXF4c7d+7olm/dujXWr1+Pb7/9Fo0aNcKvv/6KLVu2oEGDBnJ9BYMMHToULi4uUKn0bDbp0Ugggf8KM1tNtSq5oX0tH7Ntn4hIH4q+z0wOcg9nVTACSKk3TksSJEho/u9F8KnX3Cy1ONmrsOTlxgjycjHL9omI9KXoIzNbFBYWhu3bt8PZ2bmEU4cS1PZOZg0ylQRM6laHQUZEFoFHZgaS+8isQFpaGtatW4cFCxYgPj5eN93RoyJqdn0Vgc27w97ZPLcOqCRg3HO10akOr5URkWVgmBnIUsKswOHDh9G+fXvd+1Zjv4R3zUZm+zxHOxUmhdVByxreZvsMIiJDKfY+M3rkyVON5uy16FvBER/0qIcaPuV3szgRkT4YZqSX1sHeeKdzTbg72ctdChHRUxhmVCJHOxVeb1cdYfX9ODI+EVkshhkVq2YlN0wKq4PKnhzhg4gsG8OMitS7cQCGtq4GezXv3iAiy8cwo0Kc7dUY/1xttApmb0UiUg6GGekEeTnjgx71EPgMb4QmImVhmBEAoFMdH7zZsSacHdRyl0JEZDCGmY1zd7LDvzsEo31tDhZMRMrFMLNhbWtVxOj2NeDp4iB3KUREZcIws0GeLvZ4u1NNDklFRFaDYWZjnq32DMZ1rQ0PZ47kQUTWg2FmQwY2r4IB/wqCSsWRPIjIujDMbMTbnYLRvYG/3GUQEZkFh3ewAa+3q84gIyKrxjCzcj1C/dG7cWW5yyAiMiuGmRWr7euO19tVl7sMIiKzY5hZKWd7Nf4TVocDBRORTWAHEIULDQ3F4cOHcePefXxzIAbuATUAAENaV4Wfh5PM1RERlQ+GmcJ5eHigbdu28IpPh9dNVwBAFS8X9GCHDyKyIUafg8rPz8eGDRswevRo9O3bFxcuXAAAaDQabNq0CYmJiSYrkgzzCu8lIyIbY1SYpaWloU2bNhg0aBB+/PFHbN26FUlJSQAANzc3jB07FkuXLjVpoaQfTxd7tOazyIjIxhgVZpMnT0ZUVBQiIiJw/fp1CCF089RqNfr164cdO3aYrEjSX8c6lWDHTh9EZGOM+q23ZcsWjBkzBs899xwk6enTWbVr10ZsbGxZayMjtKtVUe4SiIjKnVFhptFoUL168fcvPXz4EHl5eUYXRcbxdLFHTR83ucsgIip3RoVZcHAwzp49W+z8Xbt2ISQkxOiiyDj1AzzY8YOIbJJRYfb666/ju+++w08//aS7XiZJEnJycvDhhx9i586dGD16tEkLpdIF+7jKXQIRkSyMus/s3XffRVRUFAYOHAhPT08AwKBBg5CcnIy8vDyMHj0aI0eONGWdpIfKzzjLXQIRkSwk8XhXRAMdOXIEv/76K65evQqtVovg4GC8/PLLaN++vSlrtCjp6enw8PCARqNBhQoV5C5H51J8OhzsJNSs5C53KURE5a5MYWaLLDnMKlVwREU3R7lLISIqd0ZdM7tx4wZ+//33Yuf//vvv7JovgwpO9nKXQEQkC6OumU2aNAnp6el48cUXi5z/1VdfwdPTExs2bChTcaQ/BzsVHOx4szQR2SajfvsdP34czz33XLHzu3TpgsOHDxtdFBnOyZ5BRkS2y6jfgKmpqXB3L76jgZubG5KTk40uigzH55YRkS0z6jdglSpVcPTo0WLnHz58GIGBgUYXRYaz483SRGTDjAqzgQMH4scff8Tnn38OrVarm56fn4+lS5fip59+wqBBg0xWJJXOzYmPpiMi22VU1/ycnBz07NkT+/btg4+PD+rUqQMAiI6ORlJSEjp27Ig//vgDjo7W103cUrvmExHZMqPvM9NqtVi7di02bdqEmJgYAI/GbAwPD8eQIUOgUlnnNRyGGRGR5eFN0wZimBERWR7rPHwiIiKbYnSvgYiICKxatQrXr19HamoqnjzAkyRJd/qRiIjInIwKs0WLFmHy5Mnw9fVF8+bNERoaauq6iIiI9GbUNbPAwEDUq1cPO3bsgL29bY0HyGtmRESWx+gRQPr162dzQUZERJbJqDBr3rw5oqOjTV2LQVJSUvDqq6+iQoUK8PT0xMiRI5GZmVniOh07doQkSYVe//73v8upYiIiMhejwmzZsmXYtGkT1q9fb+p69Pbqq68iKioKu3fvxrZt23Do0CG88cYbpa43atQo3LlzR/dauHBhOVRLRETmZNQ1s4YNGyIlJQV37tyBm5sbAgMDoVarC29YknDu3DmTFfq4y5cvIyQkBKdOncKzzz4LANi5cyd69OiBW7duISAgoMj1OnbsiMaNG+Ozzz4z+rN5zYyIyPIY1ZvRy8sL3t7eqFWrlqnr0cvx48fh6empCzIA6Nq1K1QqFU6cOIG+ffsWu+4PP/yA//73v/Dz88OLL76IadOmwcXFpdjlc3JykJOTo3ufnp5umi9BREQmY1SYHThwwMRlGCYhIQGVKlUqNM3Ozg5eXl5ISEgodr1BgwahatWqCAgIwPnz5/H+++8jOjoamzZtKnadefPmYebMmSarnYiITM+ihlqfPHkyFixYUOIyly9fNnr7j19TCw0Nhb+/P7p06YKYmBgEBwcXuc6UKVMwYcIE3fv09HQEBQUZXQMREZme0WGWnp6OZcuWYf/+/bh79y6WL1+O5s2bIyUlBWvWrEGvXr1Qs2ZNg7Y5ceJEDBs2rMRlatSoAT8/P9y9e7fQ9Ly8PKSkpMDPz0/vz2vRogUA4Nq1a8WGmaOjo1WO/k9EZE2MCrNbt26hQ4cOuHnzJmrVqoUrV67ousV7eXlh+fLl+Oeff7B06VKDtuvj4wMfH59Sl2vVqhXS0tJw5swZNGvWDACwb98+aLVaXUDpIzIyEgDg7+9vUJ1ERGRZjOqa/5///AcZGRmIjIzEwYMHnxqXsU+fPtizZ49JCixKvXr10L17d4waNQonT57E0aNH8c4772DAgAG6noy3b99G3bp1cfLkSQBATEwMZs2ahTNnziA2NhZbt27FkCFD0L59ezRs2NBstRIRkfkZFWa7du3C2LFjERISAkmSnppfo0YN3Lx5s8zFleSHH35A3bp10aVLF/To0QNt27bFt99+q5v/8OFDREdHIysrCwDg4OCAPXv2oFu3bqhbty4mTpyI8PBw/P7772atk4iIzM+o04zZ2dklng7MyMgwuiB9eXl5lXjTdrVq1QodMQYFBeHgwYNmr4uIiMqfUUdmISEhOHToULHzt2zZgiZNmhhdFBERkSGMCrNx48Zhw4YNWLBgATQaDQBAq9Xi2rVreO2113D8+HGMHz/epIUSEREVx6jhrABgzpw5mDFjBoQQ0Gq1UKlUEEJApVJh9uzZeP/9901dq0XgcFZERJbH6DADgLi4OGzcuBHXrl2DVqtFcHAwXnrpJdSoUcOUNVoUhhkRkeUxOMyysrLQrl07jBo1yiYfn8IwIyKyPAZfM3NxccGNGzeK7JJPREQkB6M6gHTv3h0RERGmroWIiMgoRl0zu3z5Mvr3748mTZpg9OjRqF69OpydnZ9azsvLyyRFWhKeZiQisjxGhZlK9b8DupJON+bn5xtXlQVjmBERWR6jRgD56KOPeM2MiIgsRpm65tsiHpkREVkeozqAPEmj0VjlKUUiIlIGo8Ps9OnT6N69O1xcXODt7a0bxPfevXvo3bs3Dhw4YKoaiYiISmRUmB07dgxt27bF1atXMXjwYGi1Wt28ihUrQqPRYPny5SYrkoiIqCRGhdkHH3yAevXq4dKlS5g7d+5T8zt16oQTJ06UuTgiIiJ9GBVmp06dwvDhw+Ho6Fhkr8bKlSsjISGhzMURERHpw6gws7e3L3Rq8Um3b9+Gm5ub0UUREREZwqgwa9myJX799dci592/fx+rV69Ghw4dylQYERGRvowKs5kzZ+L06dPo2bMn/vjjDwDAuXPnsHLlSjRr1gxJSUmYNm2aSQslIiIqjtE3Te/btw9vvvkmrl69Wmh6cHAwVq5cabVHZrxpmojI8ugVZunp6XB1dYVarX5qXmRkJK5evap7OGezZs2seqgrhhkRkeXRK8zUajW+//57DBo0CAAwYsQIjB49Gi1atDB7gZaGYUZEZHn0umbm4OCAnJwc3fs1a9YgJibGbEUREREZQq9R8+vWrYuVK1eiWrVq8PDwAADExsbi7NmzJa7XtGnTsldIRERUCr1OM+7cuROvvPIKMjMz9dqoEAKSJFnl4MM8zUhEZHn0OjLr3r07bty4gVOnTiExMRHDhg3DG2+8gVatWpm7PiIiolLpFWbnz59H1apVERYWBgBYvXo1+vfvjy5dupi1OCIiIn3o1QGkSZMm2L59u7lrISIiMopeYebs7IysrCzd+4MHDyIxMdFsRRERERlCr9OMjRo1wpIlS6BWq3W9GU+dOgUnJ6cS13vppZfKXiEREVEp9OrNePr0afTr1w9xcXGPVpIklLYaezMSEVF50evI7Nlnn8W1a9cQExODxMREdOzYER9++CG6du1q7vqIiIhKpVeYAYCdnR3q1KmDOnXqYOjQoXjhhRdscjgrIiKyPEaPmm+reJqRiMjy6HVk9vHHH0OSJHz44YdQqVT4+OOPS11HkiQ+04yIiMqFXkdmKpUKkiQhOzsbDg4OUKlK79HPDiBERFRe9Doy02q1Jb4nIiKSk143TRMREVkyvXszPuny5cuIiYlBRkYG3N3dUbNmTdStW9eUtREREenF4DBbvnw55syZg9u3bz81r0qVKvjwww/x+uuvm6Q4IiIifRgUZpMmTcKSJUvg5eWFESNGoEGDBnBzc0NmZiYuXLiALVu2YPTo0bh69SoWLFhgrpqJiIgK0fs+s5MnT6Jly5bo27cv1q1bB1dX16eWuX//PgYPHoytW7fixIkTePbZZ01esNzYm5GIyPLo3QFk1apV8Pf3x/r164sMMgBwdXXFjz/+CF9fX6xatcpkRRIREZVE7zA7fvw4+vfvD0dHxxKXc3JyQv/+/XH06NEyF0dERKQPvcPs5s2bqFevnl7LhoSE4ObNm0YXRUREZAi9wyw9PR3u7u56Levm5oaMjAyjiyIiIjKE3mEmhIAkSXpvmOMXExFRedG7N6NKpUKTJk1QuXLlUpe9ffs2IiMjzTo245w5c7B9+3ZERkbCwcEBaWlppa4jhMD06dOxYsUKpKWloU2bNvj6669Rq1YtvT+XvRmJiCyP3veZValSBSkpKUhJSdF7eXPKzc1F//790apVK717Ti5cuBCff/451q5di+rVq2PatGkICwvDpUuX4OTkZNZ6iYjIfBT/PLM1a9Zg3LhxpR6ZCSEQEBCAiRMnYtKkSQAAjUYDX19frFmzBgMGDNDr83hkRkRkeWxmoOEbN24gISEBXbt21U3z8PBAixYtcPz48WLXy8nJQXp6eqEXERFZFpsJs4SEBACAr69voem+vr66eUWZN28ePDw8dK+goCCz1klERIazqDCbPHkyJEkq8XXlypVyrWnKlCnQaDS6F++fIyKyPEY/AsYcJk6ciGHDhpW4TI0aNYzatp+fHwAgMTER/v7+uumJiYlo3Lhxses5OjqWOuoJERHJy6LCzMfHBz4+PmbZdvXq1eHn54e9e/fqwis9PR0nTpzAm2++aZbPJCKi8mFRpxkNERcXh8jISMTFxSE/Px+RkZGIjIxEZmambpm6deti8+bNAABJkjBu3DjMnj0bW7duxYULFzBkyBAEBASgT58+Mn0LIiIyBYs6MjPERx99hLVr1+reN2nSBACwf/9+dOzYEQAQHR0NjUajW+a9997D/fv38cYbbyAtLQ1t27bFzp07eY8ZEZHCGX2fWUREBFatWoXr168jNTX1qeGrJElCTEyMSYq0JLzPjIjI8hh1ZLZo0SJMnjwZvr6+aN68OUJDQ01dFxGVRpsPqNRyV0FkEYw6MgsMDES9evWwY8cO2Nvbm6Mui8UjM7IYUZuB+n3lroLIIhjVASQ1NRX9+vWzuSAjsiip/8hdAZHFMCrMmjdvjujoaFPXQkSGyEoGstPkroLIIhgVZsuWLcOmTZuwfv16U9dDRIZIvSF3BUQWwahrZg0bNkRKSgru3LkDNzc3BAYGQq0ufCFakiScO3fOZIVaCl4zI4uxaxoQ0ARo8JLclRDJzqjejF5eXvD29jbooZZEZAbJ1+SugMgiGBVmBw4cMHEZRGSUu5flroDIIih2OCsiApByHcjS7+nvRNasTMNZPXz4EFeuXIFGo4FWq31qfvv27cuyeSLSR+xhIKS33FUQycqoMNNqtZgyZQqWLVuGrKysYpfLz883ujAi0tOl34B6vQBJkrsSItkYdZpx7ty5WLRoEQYPHox169ZBCIH58+fjm2++QcOGDdGoUSNERESYulYiAqDRaHDkyBEcuRiHI9c00NyKBmL2yV0WkayM6ppfs2ZNPPvss9iwYQOSk5Ph4+ODPXv2oHPnzsjNzUWrVq0QFhaGuXPnmqNmWbFrPsntyJEjaNeune794UmN0Da0GtB/DeDsKVdZRLIy6sjs1q1b6Ny5MwDonsL84MEDAICDgwMGDx6M77//3kQlElGpslOBA/OAIq5dE9kCo8LM29tb9xBMNzc3VKhQAdevXy+0TGpqatmrIyL9xf0JnFohdxVEsjCqA0iTJk1w6tQp3ftOnTrhs88+Q5MmTaDVavH555+jUaNGJiuSiPQUuR5wrAA0Hih3JUTlyqgjszfeeAM5OTnIyckBAMyZMwdpaWlo3749OnTogPT0dCxevNikhRKRnk58A5xcwVOOZFOMOjLr1asXevXqpXsfEhKCmJgYHDhwAGq1Gq1bt4aXl5fJiiQiA/31X+DeVaDTFMD5GbmrITK7Mt00/TgPDw/07s0bN4ksxs0TwC/DgbbjgRod5K6GyKyMHs4qPz8fGzZswOjRo9G3b19cuHABwKN7YDZt2oTExESTFUlERspOBXZ/BOz8AEi/I3c1RGZjVJilpaWhTZs2GDRoEH788Uds3boVSUlJAB71bhw7diyWLl1q0kKJqAz+OQr8MhQ4uw7Iy5W7GjLCw/yHcpdg0YwKs8mTJyMqKgoRERG4fv06Hr/vWq1Wo1+/ftixY4fJiiQiE8jLAU6tAn4dDtw6I3c1ZCBNrgZawU49xTEqzLZs2YIxY8bgueeeg1TEeHC1a9dGbGxsWWsjInPQ3AK2TwD2zQEeaOSuhvQkhEBOfo7cZVgso8JMo9GgevXqxc5/+PAh8vLyjC6KiMrB1V3Az0OB6wfkroT0dP/hfblLsFhGhVlwcDDOnj1b7Pxdu3YhJCTE6KKIqJxkpwK7pwO7pvG5aAqQkZshdwkWy6gwe/311/Hdd9/hp59+0l0vkyQJOTk5+PDDD7Fz506MHj3apIUSkRndOAT8PASI3gkYPvY4lZPM3Ey5S7BYRt1n9u677yIqKgoDBw6Ep6cnAGDQoEFITk5GXl4eRo8ejZEjR5qyTiIyt5yMR4MVX9sDtJsIVPCXuyJ6QnpuutwlWCyjwkySJKxYsQJDhw7Fr7/+iqtXr0Kr1SI4OBgvv/wynzBNZEZPPrXJiKc4lezWqUc9HluMBkL68KGfFiQtJ03uEiyWUc8zs2V8nhnJJS0tDWvXrsXChQsRHx+vmx7g6YD3ngvC0Fa+8HQx2aA+j1RtDXScAjhxX5dbUlYSdtzYgaH1h8pdikUyegQQIio/ERERCAwMxPjx4wsFGQDEp+Vi/C8xCJzyJyKiTNyJ459jwNYxQGaSabdLRrmdeVvuEiyW3n/GPT6wsD4kScJvv/1mcEFEVFhERAR69uwJIUSxpxQFgOxcLXp+dRHb326AsPomHOg7NRbYNg7o9QXgwgHE5RSriYUQosj7e22d3mG2bds2ODk5wc/PT69z9PxhE5VdWloawsPDIYSAtpRHumjFo1Mt4d9ewq15LU17ylFzC9g5GXjhM8DBxXTbJYNocjVIeZACb2dvuUuxOHrv7ZUrV8bt27dRsWJFDBo0CAMGDICfn585ayOyeWvXrkVWVpbenTy0AsjK0WLdn4kY27myaYtJigYOzge6zmSnEBnd0NxgmBVB72tmN2/exP79+9GkSRPMmjULQUFB6Nq1K1avXo2MDN7IR2RqQgh88cUXRq37+f7bpu/lCADXDwIx+0y/XdLbjfQbcpdgkQzqANKhQwcsX74cCQkJ+PXXX+Ht7Y133nkHlSpVwksvvYRff/1V9/RpIiqb5ORkxMTEGBxKAkBM0gOk3DfTkHLnfzbPdkkvNzQMs6IY1ZvR3t4evXv3xk8//YTExERdwL3yyitYuHChqWskskmZmWUb7SHjQb6JKnlC0hUOfSWj62nXzXPUrXBl6pqfk5ODiIgI/Pbbb/jrr7/g5OSEatWqmag0Itvm5uZWpvXdndQmqqQICefNt20qUWpOKpKyeavEkwwOM61Wi4iICAwbNgy+vr4YOHAgsrOzsWLFCty9exevvfaaOeoksjne3t4IDg42uGewBCDYxwleria+gfpxmXfNt20qVdS9KLlLsDh6h9mxY8fwzjvvwN/fHz179sS1a9cwd+5cxMfHY8eOHRg8eDBcXV3NWSuRTZEkCWPGjDFq3bGdKpvv9hhJAvwammfb9BSNRoMjR47gz2N/IikqCbn3c3E68bTcZVkcvYezUqlUcHZ2Ro8ePTBw4EC9Tic2bdq0rPVZHA5nReUpLS0NgYGByM7OLvU+MwBQSYCzg8r095k9rs1YoEG4ebZNTzly5AjatWune99pfif4N/DHV12+gqeTp3yFWRiD9vbs7Gxs3LgRmzZtKnG5gjvU8/PNdAGayEZ4enpi48aN6NmzJ1QqVYmBppIeHTRtGh1iniBzdH80TmO1NqbfNhkkT+Rh07VNGNFghNylWAy99/jVq1ebsw4iKkZYWBi2b9+O8PDwYm+glvDoiGzT6BB0CzHDkFMVawHPzeJjYSzIrthdaOHfAvW968tdikXQO8yGDuVIzURyCQsLw61bt7Bu3TosWLDgqVHz3+/2aNR8D2czHJEFdwI6TAbsnUy/bTKagMCnpz/F9NbTEeQeJHc5suOo+UQK4enpibFjx2LDhg2Fpm8YWRdjO1c2fZBJqkfPNOsynUFmoTIeZmD2n7PxT/o/cpciO4YZkcI82UvRLL0WvaoDvb8CGg/iOIwWLi0nDTOOzcCFpAtylyIrhhkR/Y+jO9DqHeClFYBviNzVkJ6y8rIw7+Q87IrdJXcpsjHjXZVEpBhqh0fd7RsP4lOlFSpf5GPVxVWITY/F8PrDYa+2l7ukcsUwI7JlkgTU7g48OwJwqyR3NWQCe+P24mbGTYxvNh5eTrbzMFXFnmacM2cOWrduDRcXF3h6euq1zrBhwyBJUqFX9+7dzVsokaXyrQ/0/RboOJlBZmX+Tv0bUw5PQXRKtNyllBvFhllubi769++PN99806D1unfvjjt37uheP/74o5kqJLJQ9i5A2/FAry8Bn9pyV0NmkpaThpnHZ2JX7C6bGGVfsacZZ86cCQBYs2aNQes5OjryCdlkuyo3Bdq/x5ufbUSh62gNhsNeZb3X0RR7ZGasAwcOoFKlSqhTpw7efPNNJCcnl7h8Tk4O0tPTC72IFMfeGWg7DuixmEFmg/bG7cWs47OgydHIXYrZ2FSYde/eHevWrcPevXuxYMECHDx4EM8//3yJY0jOmzcPHh4euldQEO+0J4Wp3BTotxqo3xdQ2dQ/eXpMdGo0ph6ZipsZN+UuxSwsas+ePHnyUx00nnxduXLF6O0PGDAAvXr1QmhoKPr06YNt27bh1KlTOHDgQLHrTJkyBRqNRve6edM6dwSyQmoHoM27PBojnbvZd/HR0Y8QlWx9z0OzqGtmEydOxLBhw0pcpkaNGib7vBo1aqBixYq4du0aunTpUuQyjo6OcHR0NNlnEpULj0DguY8B72C5KyELk5WXhbkn5uKdxu+gVUArucsxGYsKMx8fH/j4+JTb5926dQvJycnw9+dfrWRFKoUAz88HnDzkroQsVJ42D0vPLoUmV4Pu1azj9iSLOs1oiLi4OERGRiIuLg75+fmIjIxEZGQkMjMzdcvUrVsXmzdvBgBkZmbiP//5D/7880/ExsZi79696N27N2rWrImwsDC5vgaRaXnXBHosYpBRqQQEVl9cjR8u/wCtKP3Br5bOoo7MDPHRRx9h7dq1uvdNmjQBAOzfvx8dO3YEAERHR0OjedR7R61W4/z581i7di3S0tIQEBCAbt26YdasWTyNSNbB2RPoPg9wdJO7ElKQrTFbcS/7Ht5q9Jaih8CShC3cTWdC6enp8PDwgEajQYUKHMOOyp9Go8GFCxeAkyuAO+cQWtn10eNfus8DqraWuzwysSNHjqBdu3a6953md4JPfdNfjqnrVReTnp0Edwd3k2+7PCj2NCORrfLw8EDbtm3RtkEVtK3p8SjIanVjkFGZXEm5go+OfoS7WXflLsUoDDMipXNwA1oaNqwbKUd5njyLvx+PaUenKfJhnwwzIqVr+hrgYjujo9uKtLQ0LF26FAMGDCg0/fjC4/h769/Izcw1z+f+/8M+r6QYf0+vHBhmRErm5AGE9JG7CjKxiIgIBAYGYvz48YiPjy8070HKA0SujMTvw39HwtkEs3x+Vl4W5vw5BxfvXTTL9s2BYUakZLW6AfZOcldBJhQREYGePXsiOzu7+FOMAsjPycfhmYfNFmi52lwsOrUINzQ3zLJ9U2OYESlZtTZyV0AmlJaWhvDwcAghoNWWcu+XeHQ97ei8o2Y75fgg/wGWnl2Kh/kPzbJ9U2KYESmVyu7RaB9kNdauXYusrKzSg6zA/x+hxe6LNVtNd+7fwaFbh8y2fVNhmBEplUcgYMcb/q2FEAJffPGFUete/f2qWXs9nkg4YbZtmwrDjEipPPg4ImuSnJyMmJgYw0NJAPcT7iM3wzynGgEgVhNrtm2bCsOMSKlcvOWugEzo8XFljZGXnWeiSp6mydVY/PiNDDMipeIYjFbFza1s7WnnbL6hdlVQQYJktu2bAsOMSKl4vcyqeHt7Izg4GJJkYGhIgKufKxzcHcxTGAA/Vz/D6ypnDDMipVIzzKyJJEkYM2aMUevWerGWWcOmoU9Ds23bVBhmREqlUuwTnKgYQ4cOhYuLC1QqPX81S4DaUY1qnauZrSYVVOhatavZtm8qDDMipbIz32klkoenpyc2btwISZJKDzTp0dFcmylt4OBmvn2he/XuCHK3/J6zDDMipeLTpK1SWFgYtm/fDmdn5+JPHf7/EVm76e3g19TPbLU0rNgQg+oOMtv2TYkP5zQQH85JROUhLS0N69atw4IFCwoNNuzk5YS64XVRrUs1OLia74isuV9zjGkyBg5qZZwBYJgZiGFGROXp8OHDaN++ve69uZ40/bjwWuHoV7sfVJJyTt7xCjIRkQUrzy7xbvZueLvx22jq27TcPtNUGGZERISanjUxruk4+LiY96jPXBhmREQ2rlvVbhgSMgT2anu5SzEaw4yIyEY5qh3xRsM30LZyW7lLKTOGGRGRDarsVhnjm41XxD1k+mCYERHZmJb+LfHvRv+Gs52z3KWYDMOMiMhGqKDCoHqD8EKNFyx+4GBDMcyIiGyAp6MnxjYdi/re9eUuxSwYZkREVq6xT2O81fgteDha7xBoDDMiIivloHLAqyGvIqxqmNWdVnwSw4yIyArV8qyFtxu/DX83f7lLKRcMMyIiK6KCCi/Vfgkv1XwJapVa7nLKDcOMiMhKuDu4Y1zTcWhQsYHcpZQ7hhkRkRXwd/XHlOZT4OvqK3cpsmCYEREpXIBrAKa3mg5PJ0+5S5GNch5WQ0RET/Fw8MAHLT6w6SADGGZERIqlggrjmin3sS2mxDAjIlKoPjX7IMQ7RO4yLAKvmRERWbDQ0FAcPnwYqQ9S8emZT+FR7dEoHoFugXip9ksyV2c5GGZERBbMw8MDbdu2RVJWEnwe/O904sjQkbBXKfdhmqbG04xERArT2KcxTy8+gWFGRKQwLwa/KHcJFodhRkSkIJWcK1ntY1zKgmFGRKQgLQNaWv0I+MZgmBERKcizvs/KXYJFYpgRESmEq70raj1TS+4yLBLDjIhIIWp51oJK4q/tovCnQkSkEFUqVJG7BIvFMCMiUghfF9t8vIs+FBlmsbGxGDlyJKpXrw5nZ2cEBwdj+vTpyM3NLXG9Bw8e4O2334a3tzfc3NwQHh6OxMTEcqqaiKhsPB095S7BYikyzK5cuQKtVovly5cjKioKn376Kb755ht88MEHJa43fvx4/P777/jll19w8OBBxMfH46WXOLYZESmDu4O73CVYLEkIIeQuwhQWLVqEr7/+GtevXy9yvkajgY+PD9avX49+/foBeBSK9erVw/Hjx9GyZUu9Pic9PR0eHh7QaDSoUKGCyeonIipJUlYS8rR58Hfzl7sUi6TII7OiaDQaeHl5FTv/zJkzePjwIbp27aqbVrduXVSpUgXHjx8vdr2cnBykp6cXehERycHZzlnuEiyWVYTZtWvX8MUXX2D06NHFLpOQkAAHBwd4enoWmu7r64uEhIRi15s3bx48PDx0r6CgIFOVTURkEEc7R7lLsFgWFWaTJ0+GJEklvq5cuVJondu3b6N79+7o378/Ro0aZfKapkyZAo1Go3vdvHnT5J9BRKQPB5WD3CVYLIt6ntnEiRMxbNiwEpepUaOG7v/j4+PRqVMntG7dGt9++22J6/n5+SE3NxdpaWmFjs4SExPh5+dX7HqOjo5wdORfQ0QkL0mSoFap5S7DYllUmPn4+MDHx6f0BfHoiKxTp05o1qwZVq9eDZWq5IPMZs2awd7eHnv37kV4eDgAIDo6GnFxcWjVqlWZayciMidXe1e5S7BoFnWaUV+3b99Gx44dUaVKFXzyySdISkpCQkJCoWtft2/fRt26dXHy5EkAj57WOnLkSEyYMAH79+/HmTNnMHz4cLRq1UrvnoxERHJh54+SWdSRmb52796Na9eu4dq1awgMDCw0r+BOg4cPHyI6OhpZWVm6eZ9++ilUKhXCw8ORk5ODsLAwLFu2rFxrJyIi07Oa+8zKC+8zIyKyPIo8zUhERPQ4hhkRESkew4yIiBSPYUZERIrHMCMiIsVjmBERkeIxzIiISPEYZkREpHgMMyIiUjyGGRERKR7DzArk5ORgxowZyMnJkbsUKidsc9vC9i4dx2Y0kBACGRkZcHd3hyRJcpcDgONF2iK2uW1he5dOkaPmy0mSJO5MREQWhqcZiYhI8RhmRESkeAwzK+Do6Ijp06fD0dFR7lKonLDNbQvbu3TsAEJERIrHIzMiIlI8hhkRESkew4yIiBSPYUZERIrHMCMiIsVjmBERkeIxzIioVAV38PBOHuv2ePsqra0ZZqSX/Pz8Et+TddFqtYX+m5ycDAAWM7g2mZ5Wq4UkScjNzUVGRgYuXbokd0kGYZhRqbRaLdRqNZKSkvDll18CANRqNQPNSmm1WqhUKiQnJ2Py5Mno3LkzWrdujffeew9xcXFyl0dmUNDmSUlJGDFiBJo1a4bQ0FD07NkTe/fulbs8vXAEECqREAKSJCElJQWtWrXC1atXMX36dEyfPh3AoyM0tVotc5VkKgXtfffuXbRv3x75+fmoUqUKAODAgQPo2bMn1qxZAy8vL92ypGwF7ZiYmIjWrVvjmWeeQevWrVGlShUsWrQIDRs2xPbt2+Hg4CB3qSUTRKXIzs4Ww4cPFy4uLiI0NFS4urqKqVOn6ubn5eXJWB2ZWnp6uujSpYto3bq1OHDggBBCiMzMTLF69WqhVqvFJ598InOFZGqpqamidevWomXLluLIkSO66bNnzxaSJIlz584VWl6r1ZZ3iaXiaUYq1YkTJ7Blyxb06tUL33//PTp37owlS5Zg2rRpAHjK0dps3boVf//9N0aNGoU2bdoAAFxdXREWFoaQkBDs3r0b+fn5iusgQEXTarX47rvvkJmZiQkTJqBVq1a6eZIkoWbNmoiOjsbJkydx8+ZN3ZGcpbU/H85JpXJxcUHPnj2xdOlSeHl5Yc6cOcjPz8eSJUsAALNmzdIFGk85Kt+tW7eg1Wrx8ssvw87OTvfLy9/fH82bN8fevXuRmZkJDw8PuUslE1CpVKhRowbat2+Pvn37QqV6dIxz7do1fPvtt0hNTcXKlStx5swZVKhQAa+++ipmzJhhef/W5T0wJKVIS0sTQgiRm5srhBAiKipK9OjRQ7i4uBQ65Zifn19oPUs8HUElS0tLE1FRUUKI/7VnwX+nTp0qfH19xb1794pcl+2tXAVtrNVqxd27d4Wzs7No1aqV2LVrl9BoNCI6Olq0a9dOODs7i2XLlslc7dN4mpH0UvBXuL29PYQQCAkJwaJFi9CxY0csWbIEU6dOBfDor7zY2Fjs3btX19WXlMXDwwN169YFAN1f6QWqVq2KnJwcpKen604zZWRk4MqVK+wQonAFbS1JEjw8PPD+++9j1apVeO6551ChQgXUrl0bP//8Mzw9PbFnzx6Zq30aw4wMVnC+/PFA+/TTT/Hxxx/j7t27WLBgAV5//XWcPn1a7lLJSE+GWMF7Z2dnXZAV9HJdunQpRo4cicuXL8tRKpmBg4MDpk+fjnr16gF4dF0tPz8ffn5+CAkJQWRkJB48eGBR180YZvSUkjpzFOy8TwZaly5dsHjxYoSFhWH58uV4/fXX0bx58/IqmcpAn/Yu4OTkpAuyzMxMrFixAh999BGee+45hISEmLtUMhFD2lwIAZVKBbVajejoaNy6dQudO3eGk5OTucs0CDuAUCF5eXmws3u0W2zatAkxMTEICAhAw4YNERoaqguxx08nhYSE4J133sGZM2dw7tw5LFq0CBMnTgTwv5sxyTLp297Aoz9gKlasCLVajaioKJw7dw7Tpk3DrFmz8OGHHwIATzUqgCH/xh9vz/j4eKxZswaJiYno2bMnAAsbEabcr9KRxXr8frHevXsLV1dXYW9vL1xcXERgYKDYuHGjbv7jF/pjYmLEv//9byFJkli8eLFu+pOdQciyGNLeBW15/PhxIUmSGDBggLCzsxOzZs16ahmyXMb+Gz9y5IiYOHGisLe3F/Pnzy/XmvXFMKOnDB48WFSuXFl89dVXIjExURw9elS0aNFCSJIkfv75Z91yWq1W5Ofni23btgkHBwcxY8YM3Tz+YlMOfdtbCCH+/PNPIUmSkCSp0C81trey6NvmOTk5Yvv27cLe3l5UrVpVfPbZZ7p5ltbmDDMq5JdffhH169cXK1as0HXHP3LkiHB3dxcVK1YUkiSJn376qdA6cXFxhUYNsLSdnIpnaHtnZmaKfv36FRoFhO2tLIa2eVJSkvjuu+/E/v37ddMssc0ZZjbmyfuAcnJyCr3/8ssvRbVq1cStW7eEEEKcPHlSuLi4iNdee03s2LFDhIaGCkmSxJYtW4rcviXu5LbM1O2t1WpFSkqKbn22t+UxVZtv3rxZr+1bCoaZDXrw4IG4evVqoWnffPON7v+vXbsmhBDin3/+EUFBQaJv377i9u3bQgghlixZojvN9N1335Vf0WQ0U7X3ypUrC23DUn+pkenafNWqVeVXdBmxm5kN2rdvH/r06YMNGzYAALp27Yo333wT586dAwDUqFEDwKNR0vPy8jBmzBj4+PgAAOzs7FC/fn106dIFGo1Gni9ABjFVe2dkZBTarkX1ZKNCTNXm6enp8nwBI7Brvg3y9fWFt7c3Bg0ahLlz5yI1NRWbNm1C7dq1Afzvl9TNmzeRkJCAtm3bwt7eHgkJCfjrr7/w/PPPY9KkSahUqZKcX4P0xPa2PTbZ5nIfGpI8Tp48KTw8PIQkSWLcuHG66Y933d27d6+oUKGC6NWrl/j555/FW2+9JZycnMR///tf3TI81aQMbG/bY2ttzjCzMQUX7NevXy8aNmwoGjRoICRJEj/88MNTy2RkZIgZM2aIwMBAIUmSqFixoli0aJEsdZNx2N62x1bbnE+athHiiZEZHjx4gLt37yImJgazZ8/G/v37sWbNGgwZMgRCCOTn58POzg65ubmIj4/HtWvX4Ovri9DQUAAc2cPSsb1tj623Oa+Z2YDHh6/Jzs5GcnIyAgMDUaVKFVSpUkU3bM2wYcMAAEOGDIGdnR2Sk5Nx8eJFdOjQAdWqVdNtT2k7ua1he9setjl4zczaPX5+/K233hJNmjQRjo6OokuXLmLhwoW6eYcOHRKdOnUSkiSJdevWiZs3b4r58+cLSZLErl27FHPe3NaxvW0P2/wRhpmNeOGFF0SlSpXEkCFDxPz580X79u2FJElixIgRumWOHTsmwsLChCRJokqVKsLBwUF8/PHHMlZNxmJ72x5bb3OeZrQBK1aswMmTJ/HZZ5+hR48e8PDwQFBQEA4fPgyVSoWUlBR4eXmhVatW+OSTT7Bnzx5cuHABXbp0waBBgwAo9LSDjWJ72x62OXia0Ra89dZbonHjxiIrK0sIIcSePXuEq6urGDJkiIiLixNCFD5VIUTh7rgcskhZ2N62h23OEUBsQmZmJry9veHs7Ix9+/ahV69e6NOnD+bPn4+goCAAwLp16/Drr7/q1nm8V5Si/1qzQWxv28M255OmrYp47C6Lx/8/MDAQ586dw/r163U7+aJFi+Dv7w8AOHHiBObNm4fExESLegw6lYztbXvY5sVjmFmJvLy8Qn9pPb7DvvPOO/D29sbgwYMRFhaGpUuX6nbyO3fuYMuWLcjPz9c9ZZYsH9vb9rDNS8YwswJarVZ3j8mkSZPQv3//QoOKent747333kPVqlXx999/4/z587h//z5Onz6NTz75BIsXL8aYMWPQvn17Ob8G6YntbXvY5nqQ51IdmUOfPn2Ek5OTqF69uvDw8BAODg5i/fr1QohHD1Vcu3atqFu3rpAkSbi5uQlXV1fh6+tb6EGLSr/XxJawvW0P27x4DDMrcfLkSdGwYUOxYcMGodFoxL59+8Tzzz8vHBwcdM8xysvLExqNRixbtkzMnj1brF27Vvz555+6bVhDjyZbwfa2PWzzkjHMFOrJbrZ//fWX6Nq1q9BoNLppFy5cEC+99JKwt7cX33777VPrPM6ad3JrwPa2PWxzw/CmaQXKz8+HWq0GACxevBjp6emIjo6GEALu7u665Ro0aICPP/4YQgi8/fbbUKvVGDp0qG7dx1lD11xrxfa2PWxzI8iZpFQ2PXr0EPb29sLV1VV4eXkJlUolNm3aJB4+fFhouYsXL4r+/fsLSZLEl19+KVO1VFZsb9vDNtcfj8wU5PGRsXfv3o24uDisW7cOderUwfnz5zFjxgxMnToV3t7eaNOmje6vs/r16+Ojjz5CWloatFqtnF+BDMD2tj1sc+PxeWYKtHLlSvz99984efIktm7digoVKiA3NxfHjx/HsGHD4Obmhq+++qrQzg5ANz4bKQvb2/awzY0g96EhGea3334TkiSJypUrizfeeKPQPK1WKw4cOCCqVasmGjRoIA4dOlTkBWFr7ZprjdjetodtbhyGmQJ9+eWXQpIk4enpKY4dO1ZonlarFQcPHhQ1a9YUtWvXFnv27JGpSjIVtrftYZsbzsq7t1int99+G19++SU0Gg0+++wzREVF6eZJkoR27dphxYoVuHv3Lu7cuSNjpWQKbG/bwzY3gtxpSsZbsmSJkCRJDBw4UFy8eLHQPK1WK27duiVTZWQObG/bwzbXH3szKtj48eMBABMnToQkSfjwww8REhIC4NFfb5UrVwZgBQ/dIwBsb1vENtcfw8wCXLhwAQEBAfD29jZ43YKd/b333sPDhw8xdepUNGzYsNAytr6TWxq2t+1hm5cDuQ8Nbd3+/fuFJEliypQpIjs72+jtLFq0SEiSJP744w8TVkemxva2PWzz8sH7zCxAp06d0K1bN0yZMkU3TQhh8HOH/vrrLzRp0sTU5ZGJsb1tD9vc/BhmMnr8bv8CGzduRIcOHVCxYkWjt8vz55aJ7W172Oblhz8NGdnZ2RV6WuzChQvRv39/rFy5EikpKUZvlzu5ZWJ72x62eTmS6/wmFa1///7CwcFBzJ07VyQnJxu8/t69e8WNGzdMXxiZBdvb9rDNzYNhJpMnny30+CjY4eHhws7OzuCdfcaMGaJixYri4MGDJquTTIPtbXvY5uWLYSaDx3fqy5cvi6SkJJGZmVloGUN39rlz5wo7Ozsxf/78px4PQfJie9setnn5Y5iVs8cHAB08eLAICAgQ1atXF/369RNXrlwptKy+O/ucOXOESqUSixcvFrm5uWarnQzH9rY9bHN5MMzK0eOnHV599VXh7e0tRo0aJQYNGiQCAwNFQECA+OuvvwqtEx4eLpycnMSsWbPEvXv3ntomd3LLxfa2PWxz+TDMyoFWq33q/HmvXr3EsmXLdI9v2Lx5s2jatKlwdXV9amfv3bu3kCRJnDp1qtD0jz/+WDg4OHAntzBsb9vDNpcfw8xMfvvtNxEREfHUs4b69Okj2rRpI5o0aSIuXbpUaN7u3bt1O/vZs2cLzdu+fXuh9wcPHhSSJImFCxdyJ7cAbG/bwza3LAwzM0hLSxPu7u7Cx8dH/PPPP7rpCQkJolevXqJSpUrC399fREVFCSGEyMnJ0S2ze/du0axZM+Hp6SnOnDnz1LYL/vrTarXi6NGj3MktANvb9rDNLQ/DzEwiIyPFF198oXtfsIP+/fffYvjw4UKSJDF06FDd/Md39j179ojQ0FAhSZK4e/euTT41VmnY3raHbW5ZGGbl4N133xU7duzQdae9du2aGDp0qJAkSbz11lu65R7f2Xfs2CHWr19f7rVS2bG9bQ/bXH4MMzOLi4sTTk5OomHDhmLfvn1F7uxvv/22bvnHd/YCT15YJsvF9rY9bHPLwDAzsaJ2yqioKFGtWjURGhpa7M4+ZsyYErdBlontbXvY5paJYWZCj/dqunz5srh375548OCBEEKIixcviipVqojQ0FCxd+/eQjv7iBEjhCRJYtiwYbLUTcZhe9setrnlYpiZyOMXcAcOHCj8/f1FQECAGD16tDhx4oQQQogLFy6IoKCgp3b2q1evivDwcPHpp5/KUToZge1te9jmlo1hZmJvvPGG8PX1FcOGDRMvv/yycHZ2Fk2aNBG7d+8WQhTe2ffv36/b2dPS0nTbYM8m5WB72x62uWVimJXRk+e++/btK77++muRlZUlhBBi+fLlonr16iI4OFjs2rVLCPFoZ69evbqoU6eOiIiIKLRjcye3bGxv28M2VwaGWRk8PnL1vXv3RHx8vKhdu7Y4duxYoeXWrVsnqlWrJmrWrKnb2c+fPy/c3d3F999/X641k/HY3raHba4cdqU/vpOKotVqdY9Df+utt3DixAlUr14darUaeXl5AIAHDx7AyckJr732GoQQmD59OsaMGYOlS5ciLCwMsbGx8PLykvNrkJ7Y3raHba4wMoepIj15IdjV1VV07txZ1KxZU0iSJNq0aaObX9DTSQghvv/+exEQECAqVqwo4uLidKcv2E3XsrG9bQ/bXHkYZgZ6fKfMyMgQrVu3Ft99950Q4tHNkOPHjxf29vaia9euun8Qj+/sK1asEKtXry7Xmsl4bG/bwzZXJkkIIeQ+OlSi3r17w93dHbdu3cKPP/4If39/AIBGo8HChQuxePFitGvXDrt37wYA5OTkwNHRsdA2tFotVCpVuddOhmN72x62ubLwp2yEtLQ0ZGdnY+PGjYiJiUFqaiq0Wi3y8/Ph4eGB9957DxMmTMDhw4fRvXt3CCHg6OgIrVZbaDvcyZWB7W172OYKJOtxoYLFx8frhqmZMWOGbnrBCAEajUZMnTpVSJIkWrRoIVeZZCJsb9vDNlcW9mY0kr+/P+bPn4/s7GzMnDkTHh4eGDduHNRqNfLz81GhQgVMmjQJmZmZqFmzptzlUhmxvW0P21xh5E5TpUtISBD9+/cXkiQVGqqm4K+3xx+sx5sllY/tbXvY5srAI7My8vX1xRdffAEAmDBhAlQqFcaOHQu1Wg0AsLe31y0rSZIsNZLpsL1tD9tcGRhmJlCws6vVaowbNw5ZWVmYPHmy3GWRmbC9bQ/b3PIxzEzE19cXn376KTQaDZycnOQuh8yM7W172OaWjfeZmVhWVhZcXFzkLoPKCdvb9rDNLRPDzEyEEDx/bkPY3raHbW5ZGGZERKR4vD2diIgUj2FGRESKxzAjIiLFY5gREZHiMcyIiEjxGGZERKR4DDMiIlI8hhkRESkew4yIiBSPYUZERIr3f5hVCqjc37lsAAAAAElFTkSuQmCC", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -483,7 +522,10 @@ } ], "source": [ - "f_forest_minimeta = forest_plot(contrasts_mini_meta, contrast_type='mini_meta', contrast_labels=['mini_meta1', 'mini_meta2', 'mini_meta3']);" + "f_forest_minimeta = forest_plot(\n", + " data = contrasts_mini_meta, \n", + " labels=['mini_meta1', 'mini_meta2', 'mini_meta3']\n", + ");" ] }, { @@ -491,7 +533,63 @@ "id": "5f9587c0-fbe8-474d-97ce-bd99d27ddf96", "metadata": {}, "source": [ - "# Control of aesthetics" + "# Controlling Aesthetics" + ] + }, + { + "cell_type": "markdown", + "id": "5cae78ef", + "metadata": {}, + "source": [ + "The main aesthetic parameters for the forest_plot function are:\n", + "\n", + "- `fig_size`: The size of the figure\n", + "\n", + "- ``horizontal``: A boolean input (``True``/ ``False``) to adjust the plot orientation. The default is vertical orientation (``False``) \n", + "\n", + "- `custom_palette`: A list or dictionary of colors, one for each contrast object. E.g., `['gray', 'blue', 'green']` or `{'Drug1':'gray', 'Drug2':'blue', 'Drug3':'green'}` or a set of colors from seaborn color palettes.\n", + "\n", + "- `marker_size`: The size of the markers for the effect sizes. The default is 12.\n", + "\n", + "- ``halfviolin_alpha``: Transparency level for violin plots. The default is 0.8.\n", + "\n", + "- ``halfviolin_desat``: Saturation level for violin plots. The default is 1.\n", + "\n", + "- `labels_rotation`: Rotation angle for contrast labels. The default is 45.\n", + "\n", + "- `labels_fontsize`: Font size for contrast labels. The default is 10.\n", + "\n", + "- ``title``: The plot title. The default is ``\"ΔΔ Forest\"``\n", + "\n", + "- ``title_fontsize``: Font size for the plot title. The default is 16.\n", + "\n", + "- ``ylabel``: The axis label of dependent variable (Y-axis for vertical layout, X-axis for horizontal layout). The default will be given via the effect size selected. (eg., ``\"Mean Difference\"`` for ``\"mean_diff\"``)\n", + "\n", + "- ``ylabel_fontsize``: Font size for the axis label (Y-axis for vertical layout, X-axis for horizontal layout). The default is 12.\n", + "\n", + "- ``ylim``: Limits for the dependent variable (Y-axis for vertical layout, X-axis for horizontal layout). The default is None.\n", + "\n", + "- ``yticks``: Custom ticks (Y-axis for vertical layout, X-axis for horizontal layout) for the plot. The default is None.\n", + "\n", + "- ``yticklabels``: Custom tick labels (Y-axis for vertical layout, X-axis for horizontal layout) for the plot. The default is None.\n", + "\n", + "- ``remove_spines``: If True, removes plot spines (except the relevant dependent variable spine). The default is True.\n", + "\n", + "- `violins_kwargs`: A dictionary of keyword arguments for the violin plots. \n", + " \n", + " The default violin kwargs = {\"widths\": 0.5, \"showextrema\": False, \"showmedians\": False, \"vert\": not horizontal}\n", + "\n", + "- `zeroline_kwargs`: A dictionary of keyword arguments for the zero line. The default is None.\n", + " \n", + " The default zeroline kwargs = {\"linewidth\": 1, \"color\": \"black\"}\n", + "\n", + "- `es_marker_kwargs`: A dictionary of keyword arguments for the effect size markers. The default is None.\n", + " \n", + " The default es marker kwargs = {'marker': 'o', 'markersize': 12, 'color': 'black', 'alpha': 1, 'zorder': 2}\n", + "\n", + "- `es_errorbar_kwargs`: A dictionary of keyword arguments for the effect size error bars. The default is None.\n", + " \n", + " The default es errorbar kwargs = {'color': 'black', 'lw': 2.5, 'linestyle': '-', 'alpha': 1, 'zorder': 1}" ] }, { @@ -499,7 +597,7 @@ "id": "06b93055", "metadata": {}, "source": [ - "### Changing layout \n", + "### Changing layout with `horizontal`\n", "Forest plot assumes a vertical layout by default, but you can change it to a horizontal layout by setting ```horizontal``` to be ```True```:" ] }, @@ -511,9 +609,9 @@ "outputs": [ { "data": { - "image/png": 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vYrJSrDD2qbF4vvXzOtdJZAgnT55EQEAA4uPj8fTTT5u6nEbFoAek+/Tpg+nTpyMtLQ3r1q0DAIwZMwYODg5ITk7GwIED4ejoiNdffx0A0KZNG4wZM0aaJygoCEFBQVptaWlpCAkJgb29Pdzd3TFx4kTExMRAURTs37//vnW5u7vDzs4Oubm5BlhL47l05xIWxC9AxJEIvYIBAFJjU2sfDIBmCyI1NlXnZVWKSqw8vRJLTi7hPZiIGhmDH5AeNWoUpk2bhr1792LcuHEAgMrKSgQHB6NHjx6YN28e7OzsdJqzqKgIffr0wfXr1zFhwgR4eHhg/fr1iIuLq3FMbm4uKioqcOPGDSxatAj5+fno27dvndbNGEoqS3A08yh+SvsJyXnJKC8qR15qnt7zJW1Oqn0wVBF3x7n4uui1zG1nt+FE6gkMeXIInvN8Dt4O3lAURa+5iKhhMHg4eHt7w8nJCcnJyZq2srIyDBs2DHPnztVrzq+++gopKSnYtm0bhg4dCgAICwtD586daxzz7LPP4sKFuwdNHRwc8PHHH+Ott96qsX9ZWRnKysq02qytrWFtba1XzTVRCzUyCzNx8c5FJNxKQEJWAspUvy83LzUPcR/WHHrGUppTWqfl9v6/3tjcdDM2X9oM+yb28HH0gbeDN3ya+aCVYyv4OPrAsamjASsmImMyyqmsDg4O0llL7733nt7z7dmzB15eXggJCdG02djYYNy4cQgPD692zJo1a5Cfn4+UlBSsWbMGJSUlUKlUsLCofk/a3LlzMXPmTK22iIgIzJgxQ+d6VWoVSipLUKYqQ3FFMfLK85BXloec0hzcLrmtOfvIsYkjenr11Bp76fYlxKH+w6GuurTogg6tOkjt1/Kv4Vr+NQCAY1NHeNh74BHbR/CY62NoYtGkvsskoloySjgUFhbC3d3994VYWcHb21vv+dLS0uDr6yvtqmjfvn2NY5577jnN/x8xYgSeeOIJAMC8efOq7T916lRMmjRJq03frQZLC0s4NHWAAxzgZusGH/jUeuzh/MP4Al/otVxTCmkfgh5/6mHqMojIQAweDunp6cjLy9P64ra2tq72L/aa9kurVCpYWloarCYXFxf06dMH0dHRNYaDMXYh6cPPzw+HDh3Sa6wQAiNGjEBmZqbOYz09PbFhwwa9jxX4+fnpNY6IGiaDh0NUVBQAIDg4+IF9XVxcqj2DKC0tDe3atdP83Lp1a5w7dw5CCK0vr8uXL9e6rpKSEuTl6X+gt744OTmhRw/9/wKfPHkyJk6cqNMtMhRFwZQpU9CzZ88Hdyaih4JBT2WNjY3F7Nmz0bZtW83pqvfj6+uLY8eOoby8XNO2a9cuXLt2TatfcHAwMjIysGPHDk1baWkpVq5cKc2ZlSVfNJaamop9+/ZJ12U0RqGhobCzs6vx2MofWVhYwM7ODqNHjzZyZURkTvTecti9ezeSkpJQWVmJmzdvIjY2Fj/++CNat26NHTt2wMbG5oFzvP3229i0aRP69++P4cOHIzk5GevWrYOvr69Wv7CwMCxbtgwjR47EhAkT0LJlS0RHR2uWce/WhJ+fH/r27Qt/f3+4uLjg0qVLWL16NSoqKvB///d/+q6u2XB2dsbmzZsxaNAgWFhYQK1W19jXwsICiqJgy5YtcHZ2rr8iiajhEzpas2ZN1Q0ZBADRtGlT4eHhIfr16ycWL14s8vPztfqHhoYKe3v7GuebP3++8PLyEtbW1qJ79+7i119/FYGBgSIwMFCrX0pKihg0aJCwtbUVzZs3F+Hh4WLz5s0CgDh27JimX0REhOjSpYtwcXERVlZWwtPTU4wYMUIkJibquqpmbc+ePcLe3l4oiiIURdH6nVW12dvbi5iYGFOXSqS3+Ph4AUDEx8ebupRGR+fbZzQkixYtwsSJE5Geng4vLy9Tl9Pg5ObmYu3atViyZInWdSe+vr4YP348QkND4eTkZMIKieqGt88wHrMJh5KSEq17NZWWlqJz585QqVS4ePGiCStr+IQQyMnJQUFBARwdHeHq6sormKlRYDgYj9k8z+Gll15Cq1at4O/vj7y8PKxbtw5JSUmIjo42dWkNnqIocHNzg5ubm6lLISIzYTbhEBwcjFWrViE6OhoqlQodO3bEhg0b8Oqrr5q6NCKiRsdsdisREf0RdysZD58hTUREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEoYDERFJGA5ERCRhOBARkYThQEREEitTF0BEZBaKc4BLe4GSXKBDP8DN19QVGRXDgYjofirLgVP/BRLWA5Wld9tObwR6TwPa9zVtbUbEcCAiqknWeSDuUyD3qna7uhLYPxdw9ABaPGma2oyMxxyIiKpzbgew/e9yMFRRVQD7ZgPlRfVbVz1hOBAR/VHid8Ch+Xe3EO6n4DpweFG9lFTfGA5ERPe6egw49u/a97+0F7iwx3j1mAjDgYioSnkRcOBzQAjdxh1eANy6YJyaTIThQERU5bdooDhb93GVZUDMNKDwluFrMhGGAxERcPc6hjOb9B9fdPtuQFSWGa4mE2I4EBEBQEJ03b/Yb18Eji4zTD0mxnAgIiq6fffUVUM4twPIiDfMXCbEcCAiio8EVOWGm+/wQkCtMtx8JsBwIKKHW3YycOEHw86Zew04t92wc9YzhgMRPbzU6v9d7GaEv/JPrgUqSgw/bz1hOBDRw+vkN8DNs8aZu+QOcLoOZz+ZGMOBiB5O6b/e/evemBK/BUrzjbsMI2E4ENHDpzgHiJ0NCLVxl1NWcPd232aI4UBED58Dn999aE99OL0JKLhZP8syIIYDET1ckuOAq0frb3mqct1u5NdAMByI6OFRWWaaL+qU/cDV4/W/3DpgOBDRwyPxW6AwyzTLPjTPrB4MxHAgoodDUfbd50CbSmEW8PNi0y1fRwwHIno4HF9h+ovSLsYAl38ybQ21xHAgosYvPf7uE9v0JITA7cIKpN4uxe3CCghdHwZ0r4Pz795eo4GzMnUBRERGVZIL7J+r19Dc4kp8c/Qmlu7PQPKtUk27b3MbvB/khdDnWsDZTsev0YpiYO/HwNDlgLWDXnXVB523HCIjI6EoiuZlY2MDT09PBAcHY8mSJSgoKDBGnbW2ZcsWvPrqq2jXrh3s7Ozw2GOPITw8HLm5uSati4hMoLIc+CkCKNL9CW0xZ3PgPfUYJm5MRso9wQAAKbdKMXFjMrynHkPM2Rzd67qTevfBQBWlD+xqKnrvVpo1axaioqLw5Zdf4v333wcAfPDBB/Dz80NiYqLBCtTVO++8g/Pnz+ONN97AkiVL0L9/fyxbtgzPPfccSkrM9yZYRKSj8v/9hZ6ZoPPQmLM5GLT8DErK1RAA/rgTqaqtpFyNQcvP6BcQ108B34fX38V4OtJ7t9KAAQPQpUsXzc9Tp05FbGwsBg8ejJCQEJw/fx62trbVji0qKoK9vb2+i76vTZs2ISgoSKstICAAoaGhiI6Oxttvv22U5RJRA5KZcPfUUT327ecWV+Ll/5yDEID6AYcW1OLuX9gv/+cc0uc+q/supptngK3vAv1mAc0f1blWYzLoAek+ffpg+vTpSEtLw7p16wAAY8aMgYODA5KTkzFw4EA4Ojri9ddfBwC0adMGY8aMkeYJCgqSvuDT0tIQEhICe3t7uLu7Y+LEiYiJiYGiKNi/f7/W2D968cUXAQDnz583yHoSUQOkVgOpPwO7JgI7J+h90PebozdRXKZ+YDBoFiuA4jI11h7T8xYZBdeB7X8FTkbd3Q3WQBj8gPSoUaMwbdo07N27F+PGjQMAVFZWIjg4GD169MC8efNgZ2en05xFRUXo06cPrl+/jgkTJsDDwwPr169HXFxcrcbfuHEDAPDII4/otjJEZB7O7wTO/x9QePcLOq+kEqczdL/gTAiBz3+8Ju1GeuA4AJ/tvYbOPvZQFEXn5QKAX+EKOJ3dCjwaDHh1AR5pD9g46TWXIRg8HLy9veHk5ITk5GRNW1lZGYYNG4a5c/U7Y+Crr75CSkoKtm3bhqFDhwIAwsLC0Llz51qN/+yzz2BpaYlXXnmlxj5lZWUoK9N+uLi1tTWsra31qpmIjKCs4O7FZHdSgdsXgUMxd9vPbQdaOWq6nc4oQs95p+q1tMzccvSar//x1kP/6IQetv+7UK/qYj1bF8C1LeDa7u7LuTXg5A3YOhum6PswyqmsDg4O0llL7733nt7z7dmzB15eXggJCdG02djYYNy4cQgPD7/v2PXr12P16tWYPHkyOnToUGO/uXPnYubMmVptERERmDFjht51E1EdlBfdvRdSeRFQmnf34Tmqe/6Ae6QD8CgAbAe6jgOevOfft9MZABPrueA6ChgDdHnq/n0Kb9x9WdkCjzwKODQ3WjlGCYfCwkK4u7v/vhArK3h7e+s9X1paGnx9faXNtfbt29933KFDh/DWW28hODgYc+bMuW/fqVOnYtKkSVpt3GogMqGm9ndfdq4AfKrvk+969399ngHaP/17+w0bo5dncN5dgPY9TF2FhsHDIT09HXl5eVpf3NbW1rCwkI9917RvTqVSwdLSsk51nDp1CiEhIXjqqaewadMmWFndf1W5C4mo8fDz88OhQ4d0HieEwIgRI5CZmanzWE9PT2zYsEH/Yw5+fnqNMxaDh0NUVBQAIDg4+IF9XVxcqr04LS0tDe3atdP83Lp1a5w7dw5CCK0P/vLly9XOm5ycjP79+8Pd3R0//PADHBwa7lWIRGR4Tk5O6NFDv7/CJ0+ejIkTJ+p0iwxFUTBlyhT07NlTr2U2RAY9lTU2NhazZ89G27ZtNaer3o+vry+OHTuG8vLfT9/atWsXrl3TPgUtODgYGRkZ2LFjh6attLQUK1eulOa8ceMGXnjhBVhYWCAmJgbNmxtvnxwRNT6hoaGws7Ordm9HdSwsLGBnZ4fRo0cbubL6pfeWw+7du5GUlITKykrcvHkTsbGx+PHHH9G6dWvs2LEDNjYP3uf39ttvY9OmTejfvz+GDx+O5ORkrFu3Dr6+vlr9wsLCsGzZMowcORITJkxAy5YtER0drVnGvVsT/fv3R0pKCiZPnozDhw/j8OHDmvdatGiBfv366bvKRPQQcHZ2xubNmzFo0CBYWFhAra75OdMWFhZQFAVbtmyBs7Nz/RVZH4SO1qxZU3XluAAgmjZtKjw8PES/fv3E4sWLRX5+vlb/0NBQYW9vX+N88+fPF15eXsLa2lp0795d/PrrryIwMFAEBgZq9UtJSRGDBg0Stra2onnz5iI8PFxs3rxZABDHjh3T9Lu3tj++/jgnEZm3+Ph4AUDEx8cbfO49e/YIe3t7oSiKUBRF67ukqs3e3l7ExMQYfNkNgSJEXe49a1qLFi3CxIkTkZ6eDi8vL1OXQ0T17OTJkwgICEB8fDyefvrpBw/QUW5uLtauXYslS5ZoXbvl6+uL8ePHIzQ0FE5OprtQzZjMJhxKSkq07tVUWlqKzp07Q6VS4eLFiyasjIhMxdjhUEUIgZycHBQUFMDR0RGurq56n5VkLszmeQ4vvfQSWrVqBX9/f+Tl5WHdunVISkpCdHS0qUsjokZOURS4ubnBzc3N1KXUG7MJh+DgYKxatQrR0dFQqVTo2LEjNmzYgFdffdXUpRERNTpms1uJiOiP6mu30sOIz5AmIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiKJlakLIKL6pVYL7L+YhX3ns1CpEhjq74lu7R8xdVnUwDAciB4iSTfy8e+4ZFy5XaRpO3c9H2GB7TD4T54mrIwaGoYD0UOgUqVG1LE0bPstA2ohv7/yYAp8XOzQyce53mujhonHHIgauaKySkzffgZbTlYfDACgFsCCHy+ioLSifoujBovhQNSIlVeqEbHjLM5k5D+wb05ROZbFXq6HqsgcMByIGrGVh1Jw4UZBrfsfSc7GrsRMI1ZE5oLhQNRIncnIw54zN3Qet+rQFSSm5xq+IDIrDAeiRkgIgVWHUvQaq1ILzP0hCel3ig1cFZkThgNRI3Q0ORvJt4oe3LEGhWWV+GTXeZSUqwxYFZkThgNRIyOEwPpfrtZ5nozcEqw4kGyAisgcMRyIGpnDl28jLdswu4Rik7Jw8uodg8xF5oXhQNSIqNQC646lGXTOlQdToKrpAglqtBgORI3IjlMZyMwtNeic6XdK9Drricwbw4GokcjILUH0sbofa6jOhhNXUVrBg9MPE4YDUSNQXqnGvJgLKKtUG2X+3OIK7DzFi+MeJgwHokZg5aEUXM4qNOoytpzMQGFZpVGXQQ0Hw4HIzP18+Xa9HBMoLKvE5vh0oy+HGgaGA5EZyyuuwPK4+rtZ3vaEDGQVGPaANzVMDAciM7bmyBUUlNbfrp4KlcDqQ1fqbXlkOgwHIjN16WYBYpOy6n25R5KzcTwlu96XS/WL4UBkplYfvgJhomvTlu9P5oOBGjmGA5EZOnzpNs5mPvgBPsZyp6gcy+rxWAfVP4YDkZkprVBh9WH9bsdtSEcuZyPmLK+cbqwYDkRm5psjqbhdWK73eCEEygtzUZx9HeWFuRB12Df1n4MpSLll3OsryDSsTF0AEdXeL1dy8P3p63qNrSguwLVf9iD14GYU387QtNs94oU2vV6GT9f+aGLnqNOc5ZVqzPn+POYP7wRnu6Z61UUNk85bDpGRkVAURfOysbGBp6cngoODsWTJEhQU1P55tcZw4cIFTJw4Ed26dYONjQ0URUFqaqpJayIyhMtZhZi394JeB6Gzzh/HT/96Gee2LEXxbe3bYBTfzsS5LUvx079eRtb547rPXVCGj7edQV4xD1A3JnrvVpo1axaioqLw5Zdf4v333wcAfPDBB/Dz80NiYqLBCtTV0aNHNSH1xBNPmKwOIkM6dS0XH287rdeT2bLOH8cvKyZDVVEKQPzvda+7baqKUpxYMVmvgEjLLsY/N51CRm6JzmOpYdI7HAYMGIA33ngDY8eOxdSpUxETE4OffvoJWVlZCAkJQUlJzf+RFBXp//jCBwkJCUFubi5Onz6N119/3WjLIaoPucXlWHEgGf/afgZFZboHQ0VxAeJXTwcg8MBNDiEgIBC/ejoqinXfA3A9rxSTvk3Akcu3dR5LDY9BD0j36dMH06dPR1paGtatWwcAGDNmDBwcHJCcnIyBAwfC0dFR86Xdpk0bjBkzRponKCgIQUFBWm1paWkICQmBvb093N3dMXHiRMTExEBRFOzfv1/Tz9XVFY6Ouu03JWpoLmcVYsm+S3gz8gS+T7wOfZ+1c+2XPVCVlz44GKoIAVV5KdJPxOi1vOJyFebuTsIXMUm4mc/bbJgzgx+QHjVqFKZNm4a9e/di3LhxAIDKykoEBwejR48emDdvHuzs7HSas6ioCH369MH169cxYcIEeHh4YP369YiLizN0+UQmk11YhqMp2Yg9n4VL99xhtaKkEAWZup+6KoRA8r71kHcjPXAkLv8UjWZeHaAois7LBYB9Je1w+NJtPOXlBD8vJ7R9xB6t3ezh7mgNCwv95qT6ZfBw8Pb2hpOTE5KTf38weVlZGYYNG4a5c+fqNedXX32FlJQUbNu2DUOHDgUAhIWFoXPnzgapuarGsrIyrTZra2tYW1sbbBn0cBNCoKRChbySCuQWV+BOUTlu5JfiWk4JLt4swNWc6p/7XJCZgiOL/1avtZbl3cbRJX/Xe3y3CcvRxPdPSEzPQ2J6nqbd2soCrdzs0NrVHt4utvBysYW7ozU8nW1h08TSEKWTgRjlVFYHBwfprKX33ntP7/n27NkDLy8vhISEaNpsbGwwbtw4hIeH6z3vvebOnYuZM2dqtUVERGDGjBkGmZ8eXkIIFJWrUKlSQy0AaytLtGhmiRbNbPB4y2YPHH/sSAUGLa6HQg3oo0FP4NluXWvdX88NFDIio4RDYWEh3N3df1+IlRW8vb31ni8tLQ2+vr7SJm779u31nvOPpk6dikmTJmm1cauBDEFRFDhY6/9PrZltEwNWUz+a2TaBqz2vezBnBg+H9PR05OXlaX1xW1tbw8JCPvZd0/5MlUoFS8v63cTkLiRqqPz8/HDo0CGdxwkhMGLECGRm6v54T09PT2zYsEHvYw5+fn56jaOGw+DhEBUVBQAIDg5+YF8XFxfk5uZK7WlpaWjXrp3m59atW+PcuXMQQmj9x3r5Mm/8RY2fk5MTevToodfYyZMnY+LEiTrdIkNRFEyZMgU9e/bUa5nUOBj0VNbY2FjMnj0bbdu2rdU1Br6+vjh27BjKy3+/T8yuXbtw7do1rX7BwcHIyMjAjh07NG2lpaVYuXKl4YonaoRCQ0NhZ2dX7ZZ7dSwsLGBnZ4fRo0cbuTJq6PTecti9ezeSkpJQWVmJmzdvIjY2Fj/++CNat26NHTt2wMbG5oFzvP3229i0aRP69++P4cOHIzk5GevWrYOvr69Wv7CwMCxbtgwjR47EhAkT0LJlS0RHR2uWce/WRF5eHpYuXQoA+PnnnwEAy5Ytg7OzM5ydnfH3v+t/BgaRuXF2dsbmzZsxaNAgWFhYQK1W19jXwsICiqJgy5YtcHZ2rr8iqWESOlqzZk3V9fcCgGjatKnw8PAQ/fr1E4sXLxb5+fla/UNDQ4W9vX2N882fP194eXkJa2tr0b17d/Hrr7+KwMBAERgYqNUvJSVFDBo0SNja2ormzZuL8PBwsXnzZgFAHDt2TNPvypUrWvXd+2rdurWuq0vUKOzZs0fY29sLRVGEoiha/y6q2uzt7UVMTIypS9VJfHy8ACDi4+NNXUqjowhhqmdJ1d2iRYswceJEpKenw8vLy9TlEDVoubm5WLt2LZYsWaJ1HZKvry/Gjx+P0NBQODk5mbBC3Z08eRIBAQGIj4/H008/bepyGhWzCYeSkhLY2tpqfi4tLUXnzp2hUqlw8eJFE1ZGZF6EEMjJyUFBQQEcHR3h6uqq91lJpsZwMB6zeZ7DSy+9hFatWsHf3x95eXlYt24dkpKSEB0dberSiMyKoihwc3ODm5ubqUuhBsxswiE4OBirVq1CdHQ0VCoVOnbsiA0bNuDVV181dWlERI2O2exWIiL6I+5WMh4+Q5qIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiIJw4GIiCQMByIikjAciIhIwnAgIiKJlakLaKiEECgoKDB1GUR0H4WFhZr/zc/PN3E15sPR0RGKoty3jyKEEPVUj1nJz8+Hk5OTqcsgIjK4vLw8NGvW7L59GA410GfLIT8/Hz4+Prh27doDP3hz05jXDWjc68d1M0/GXLfabDlwt1INFEXR+xfSrFmzRvcfapXGvG5A414/rpt5MtW68YA0ERFJGA5ERCRhOBiQtbU1IiIiYG1tbepSDK4xrxvQuNeP62aeTL1uPCBNREQSbjkQEZGE4UBERBKGAxERSRgOREQkYTjUg7KyMvj7+0NRFCQkJJi6HIMICQlBq1atYGNjg5YtW2LUqFHIzMw0dVl1lpqairfeegtt27aFra0tfH19ERERgfLyclOXZhBz5sxBt27dYGdnB2dnZ1OXUyfLly9HmzZtYGNjg2eeeQa//PKLqUsyiIMHD2LIkCHw9PSEoijYtm2bSepgONSDyZMnw9PT09RlGFTv3r3x3Xff4cKFC9i8eTOSk5PxyiuvmLqsOktKSoJarcZXX32Fs2fPYuHChVixYgWmTZtm6tIMory8HMOGDcN7771n6lLq5Ntvv8WkSZMQERGBkydPolOnTggODkZWVpapS6uzoqIidOrUCcuXLzdtIYKM6ocffhCPP/64OHv2rAAgfvvtN1OXZBTbt28XiqKI8vJyU5dicJ9//rlo27atqcswqDVr1ggnJydTl6G3rl27ir/97W+an1UqlfD09BRz5841YVWGB0Bs3brVJMvmloMR3bx5E+PGjUNUVBTs7OxMXY7R5OTkIDo6Gt26dUOTJk1MXY7B5eXlwdXV1dRl0P+Ul5cjPj4ezz//vKbNwsICzz//PI4ePWrCyhoXhoORCCEwZswYvPvuu+jSpYupyzGKKVOmwN7eHm5ubrh69Sq2b99u6pIM7vLly1i6dCnCwsJMXQr9z+3bt6FSqdCiRQut9hYtWuDGjRsmqqrxYTjo6MMPP4SiKPd9JSUlYenSpSgoKMDUqVNNXXKt1Xbdqvzzn//Eb7/9hr1798LS0hKjR4+GaKAX3Ou6bgCQkZGB/v37Y9iwYRg3bpyJKn8wfdaN6EF4+wwd3bp1C9nZ2fft065dOwwfPhw7d+7Uume6SqWCpaUlXn/9dXzzzTfGLlVntV23pk2bSu3p6enw8fHBkSNH8NxzzxmrRL3pum6ZmZkICgrCs88+i8jISFhYNNy/o/T5vUVGRuKDDz5Abm6ukaszvPLyctjZ2WHTpk34y1/+omkPDQ1Fbm5uo9qCVRQFW7du1VrP+sLnOeioefPmaN68+QP7LVmyBJ988onm58zMTAQHB+Pbb7/FM888Y8wS9VbbdauOWq0GcPe03YZIl3XLyMhA7969ERAQgDVr1jToYADq9nszR02bNkVAQAD27dun+dJUq9XYt28f/v73v5u2uEaE4WAkrVq10vrZwcEBAODr6wtvb29TlGQwx48fx4kTJ9CjRw+4uLggOTkZ06dPh6+vb4PcatBFRkYGgoKC0Lp1a8ybNw+3bt3SvOfh4WHCygzj6tWryMnJwdWrV6FSqTTX3bRv317z36g5mDRpEkJDQ9GlSxd07doVixYtQlFREcaOHWvq0uqssLAQly9f1vx85coVJCQkwNXVVfpeMSqTnCP1ELpy5UqjOZU1MTFR9O7dW7i6ugpra2vRpk0b8e6774r09HRTl1Zna9asEQCqfTUGoaGh1a5bXFycqUvT2dKlS0WrVq1E06ZNRdeuXcWxY8dMXZJBxMXFVfs7Cg0Nrdc6eMyBiIgkDXtnKhERmQTDgYiIJAwHIiKSMByIiEjCcCAiIgnDgYiIJAwHIiKSMByITERRFMyYMUOr7cSJE+jWrRvs7e21nhy4Z88e+Pv7w8bGBoqimOU9kci8MBzIZCIjIzV3DT18+LD0vhACPj4+UBQFgwcPNkGFtdemTRvNulhYWMDZ2Rl+fn545513cPz48VrNUVFRgWHDhiEnJwcLFy5EVFQUWrdujezsbAwfPhy2trZYvnw5oqKiYG9vb+Q1oocd761EJmdjY4P169ejR48eWu0HDhxAeno6rK2tTVSZbvz9/REeHg4AKCgowPnz57Fx40asXLkSEydOxIIFC7T6l5SUwMrq93+CycnJSEtLw8qVK/H2229r2vfs2YOCggLMnj1b6wE3RMbEcCCTGzhwIDZu3IglS5ZofVmuX78eAQEBuH37tgmrqz0vLy+88cYbWm2fffYZXnvtNSxcuBAdOnTQenazjY2NVt+q5x87OzvXqr0uioqKuPVB98XdSmRyI0eORHZ2Nn788UdNW3l5OTZt2oTXXnut2jFqtRqLFi3Ck08+CRsbG7Ro0QJhYWG4c+eOVr/t27dj0KBB8PT0hLW1NXx9fTF79myoVCqtfkFBQXjqqadw7tw59O7dG3Z2dvDy8sLnn39ep3WztbVFVFQUXF1dMWfOHK2HId17zGHMmDEIDAwEAAwbNgyKoiAoKAhBQUEIDQ0FAPz5z3+GoigYM2aMZo7jx4+jf//+cHJygp2dHQIDA/Hzzz9r1TBjxgwoioJz587htddeg4uLi9ZW2rp16xAQEABbW1u4urpixIgRuHbtmt6fT2lpKWbMmIFHH30UNjY2aNmyJV566SUkJydr+tT290emw3Agk2vTpg2ee+45/Pe//9W07d69G3l5eRgxYkS1Y8LCwvDPf/4T3bt3x+LFizF27FhER0cjODgYFRUVmn6RkZFwcHDApEmTsHjxYgQEBOBf//oXPvzwQ2nOO3fuoH///ujUqRPmz5+Pxx9/HFOmTMHu3bvrtH4ODg548cUXkZGRgXPnztW4PtOmTQMAjB8/HlFRUfjoo4/w0Ucf4Z133gEAzJo1C1FRUZpHlsbGxqJXr17Iz89HREQEPv30U+Tm5qJPnz745ZdfpGUMGzYMxcXF+PTTTzVPtpszZw5Gjx6NDh06YMGCBfjggw+wb98+9OrVSzroXZvPR6VSYfDgwZg5cyYCAgIwf/58TJgwAXl5eThz5ozW+tbm90cmVK/3gCW6R9XtsU+cOCGWLVsmHB0dRXFxsRBCiGHDhonevXsLIYRo3bq1GDRokGbcoUOHBAARHR2tNd+ePXuk9qr57hUWFibs7OxEaWmppi0wMFAAEGvXrtW0lZWVCQ8PD/Hyyy8/cF3+WOMfLVy4UAAQ27dv17QBEBEREZqfq27VvHHjRq2x935OVdRqtejQoYMIDg4WarVaa33btm0r+vXrp2mLiIgQAMTIkSO15k1NTRWWlpZizpw5Wu2nT58WVlZWWu21/Xy+/vprAUAsWLBA+gyq6tTl90emwy0HahCGDx+OkpIS7Nq1CwUFBdi1a1eNu5Q2btwIJycn9OvXD7dv39a8AgIC4ODggLi4OE1fW1tbzf8vKCjA7du30bNnTxQXF0vPVXZwcNA6ZtC0aVN07doVKSkpdV6/qgfpFBQU1HkuAEhISMClS5fw2muvITs7W/MZFBUVoW/fvjh48KDm6XxV3n33Xa2ft2zZArVajeHDh2t9jh4eHujQoYPW51i1Dg/6fDZv3oxHHnkE77//vlRz1SNzdfn9kenwgDQ1CM2bN8fzzz+P9evXo7i4GCqVCq+88kq1fS9duoS8vDy4u7tX+37VAVwAOHv2LD7++GPExsYiPz9fq19eXp7Wz97e3lrP/AYAFxcXJCYm6rNKWgoLCwEAjo6OdZ4LuPsZANAcj6hOXl4eXFxcND+3bdtWmkMIgQ4dOlQ7vkmTJlo/1+bzSU5OxmOPPaZ1YkF1tdf290emw3CgBuO1117DuHHjcOPGDQwYMKDGs3PUajXc3d0RHR1d7ftVz1POzc1FYGAgmjVrhlmzZsHX1xc2NjY4efIkpkyZIv1lbWlpWe18wgDPw6ra396+ffs6zwX8/szuL774Av7+/tX2+eNjP+/diqqaQ1EU7N69u9p1/+N4Q30+tf39kWkxHKjBePHFFxEWFoZjx47h22+/rbGfr68vfvrpJ3Tv3l36wrvX/v37kZ2djS1btqBXr16a9itXrhi07gcpLCzE1q1b4ePjgyeeeMIgc/r6+gIAmjVrpve1D76+vhBCoG3btnj00UcNVtfx48dRUVEhbXnc26c2vz8yLR5zoAbDwcEBX375JWbMmIEhQ4bU2G/48OFQqVSYPXu29F5lZaXmLJuqv3Tv/cu2vLwc//73vw1b+H2UlJRg1KhRyMnJwUcffSTtltFXQEAAfH19MW/ePM0uq3vdunXrgXO89NJLsLS0xMyZM6W//oUQyM7O1rmul19+Gbdv38ayZcuk96qWUdvfH5kWtxyoQbnfPvQqgYGBCAsLw9y5c5GQkIAXXngBTZo0waVLl7Bx40YsXrwYr7zyCrp16wYXFxeEhoZi/PjxUBQFUVFRBtlNVJ2MjAysW7cOwN2thXPnzmHjxo24ceMGwsPDNaegGoKFhQVWrVqFAQMG4Mknn8TYsWPh5eWFjIwMxMXFoVmzZti5c+d95/D19cUnn3yCqVOnIjU1FX/5y1/g6OiIK1euYOvWrXjnnXfwj3/8Q6e6Ro8ejbVr12LSpEn45Zdf0LNnTxQVFeGnn37CX//6VwwdOrTWvz8yLYYDmaUVK1YgICAAX331FaZNmwYrKyu0adMGb7zxBrp37w4AcHNzw65duxAeHo6PP/4YLi4ueOONN9C3b18EBwcbvKaEhASMGjUKiqLA0dERPj4+GDJkCN5++2107drV4MsLCgrC0aNHMXv2bCxbtgyFhYXw8PDAM888U+sg+vDDD/Hoo49i4cKFmDlzJgDAx8cHL7zwAkJCQnSuydLSEj/88APmzJmD9evXY/PmzXBzc0OPHj3g5+en6Veb3x+ZliKM9WcUERGZLR5zICIiCcOBiIgkDAciIpIwHIiISMJwICIiCcOBiIgkDAciIpIwHIiISMJwICIiCcOBiIgkDAciIpIwHIiISMJwICIiyf8Dd8pw5gjF6P4AAAAASUVORK5CYII=", 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -521,9 +619,10 @@ } ], "source": [ - "f_forest_delta2_horizontal = forest_plot(contrasts, \n", - " contrast_labels =['Drug1', 'Drug2', 'Drug3'],\n", - " horizontal=True);\n" + "f_forest_minimeta = forest_plot(\n", + " data = contrasts_mini_meta, \n", + " labels=['mini_meta1', 'mini_meta2', 'mini_meta3'],\n", + " horizontal=True,)\n" ] }, { @@ -543,9 +642,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" + "
" ] }, "metadata": {}, @@ -553,11 +652,10 @@ } ], "source": [ - "f_forest_delta2_custom_palette= forest_plot(contrasts, \n", - " contrast_labels = ['Drug1', 'Drug2', 'Drug3'], \n", - " custom_palette = ['gray', 'blue', 'green'], # or \n", - " # custom_palette = {'Drug1':'gray', 'Drug2':'blue', 'Drug3':'green'}\n", - " );" + "f_forest_minimeta = forest_plot(\n", + " data = contrasts_mini_meta, \n", + " labels=['mini_meta1', 'mini_meta2', 'mini_meta3'],\n", + " custom_palette=['#FF0000', '#00FF00', '#0000FF'],)\n" ] }, { @@ -566,7 +664,7 @@ "metadata": {}, "source": [ "### Plotting other effect sizes \n", - "Forest plots can be drawn for effect sizes other than mean_difference, such as ```deltas' g```, by setting ```effect_size```:" + "Forest plots can be drawn for effect sizes other than mean_difference, such as ```hedges_g```, by setting ```effect_size```:" ] }, { @@ -577,9 +675,9 @@ "outputs": [ { "data": { - "image/png": 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ss28iEzGYiKzAz88PYWFhkCSpWttJAMICXOFby0LTWnZ+BqhmTUSWxmAisgJJkvDss8+atO1zsfWqHWhV0nwAENTK/PslqiEGE5GVjB07Fu7u7nCq4h1nnaSSGSDGdKxt/mK0wUDHp82/XyIzYDARWYm3tzfWr18PSZLuG05OUskRtm+fCjf/xbUuHkCv+YCLu3n3S2QmDCYiK4qLi8PmzZvh5uZW4eE5CSUzPvzvmZboFW7GufKAkpke+v2b8+WRojGYiKwsLi4Of/zxB5YtW4a6deuWWVbX2wXLHg3DtTc6mj+UgtsDQ/8LBDYz736JzIxz5XGuPJJRUlISoqOjjc/3THsQXZt4m/dNvEOAh54CGnbhCDyyCby1OpGM/n44z6yj77zrA23HAmHdgSoOuCBSAgYTkb3xrAO0mwA07slAIpvEYCKyF04qoM1oIOJxQO0idzVEJmMwEdkDr3pAz3ggoKnclRDVGIOJyNaFxgDRLwKams3HR6QUDCYiW6XxBDo9AzwQx9F2ZFcYTES2RpKApn2B9v8A3M18rRORAjCYiGxJvciSOe78G8tdCZHFMJiIbIFXPaDzs0D9jjxsR3aPwUSkdK2GAw9NAtQauSshsgoGE5FSqV2BHrNLphIiciAMJiIlUmuAvouBOq3lroTI6jhfCZESdZnKUCKHxR4TkYxatWqFpKQkYNciQHcVrerVAuq1Lbk2ichB2XyP6Z133kHDhg3h6uqKDh064NChQ3KXRFRlWq0WXbp0QZfmQejSWAutmxqIHMeRd+TQbDqY1q5di6lTpyI+Ph7Hjh1D69atERcXh7S0NLlLIzKN/wNA0INyV0EkK5sOpjfffBOTJk3C+PHjER4ejvfffx/u7u74+OOP5S6NyDQthrC3RA7PZs8xFRQU4OjRo5gxY4bxNScnJ/Ts2RMHDhwod5v8/Hzk5+cbn+v1egDAzz//DA8PToBJMvr9JpBTBOi9gWPH5K6GyGLatm1733VsNphu3ryJ4uJi1K5du8zrtWvXxtmzZ8vdZuHChZg3b949r3fr1s0iNRJV27wouSsgsighxH3XsdlgMsWMGTMwdepU43O9Xo+QkBDs3r2bPSaS1/bXgOb9gbpt5K6ESHY2G0z+/v5QqVRITU0t83pqaiqCgoLK3Uaj0UCjuXdal4iICHh5eVmkTqIqSQ4AHn605FYWRA7OZgc/uLi4IDIyEtu3bze+ZjAYsH37dnTq1EnGyohM4FWPoUT0J5vtMQHA1KlTMXbsWLRr1w4PPfQQli1bhpycHIwfP17u0oiqRxssdwVEimHTwfTYY48hPT0dc+bMwY0bNxAREYGtW7feMyCCSPE8+JklKiWJqgyRsFN6vR5arRY6nY7nmEhelw8ADXgImgiw4XNMRHbFzUfuCogUg8FEpASu7LETlWIwESmBs5vcFRApBoOJSAnUrnJXQKQYDCYiJWCPiciIwURERIrCYCIiIkVhMBERkaIwmBToWlae3CUQEcmGwaRAlzNyqnTPEiIie8RgUqD8IgMycwvlLoOISBYMJoW6lsnDeUTkmBhMCnXlVq7cJRARyYLBpFDJGTlyl0BEJAsGk0Il32QwEZFjYjAp1JVbuRyZR0QOicGkULkFxcjIKZC7DCIiq2MwKdj51Gy5SyAisjoGk4IdSb4ldwlERFbHYFKwPefTkZXLw3lE5FgYTAqi0+mwd+9enDz6E25dPIHbej0+3pcsd1lERFallrsA+svJkyfRtWtX4/PO/3wHO9080La+N2KaBspYGRGR9bDHZANW7LiA86m35S6DiMgqGEw2oKDIgFcTTuOPTE5TRET2j8FkI7JyCzHj25O4kMaeExHZNwaTDcnKLcTL609i+5lUuUshIrIYBpONKSgyYNmP5/HmtnPILSiSuxwiIrNjMNmonefS8dyXx3Hqmk7uUoiIzIrBZMNS9fmY8e1JvLPzArLz2XsiIvvAYLIDW0/dwFOfHsHWU9dRbOCM5ERk2xhMdkKfV4R3dl7EM18cw97zN2FgQBGRjeLMD3bmj8w8LNp6Fo38a+GJjg3QvqEPJEmSuywioipjj8lOXbqZg9cSTuOldSdw5rpe7nKIiKqMwWTnzt64jZfWncCb285Bl1sodzlERPfFYHIQO8+l45kvj+H4lUy5SyEiqhSDSUGEEJU+r6ms3ELM/e5XbPr5mtn3TURkLjYZTMnJyZg4cSIaNWoENzc3hIWFIT4+HgUFtnlTvaysLCxfvhwjRowo8/qx1XPx+65vUJhrvvnxDAL4KOkS3t5xAQVFBrPtl4jIXGxyVN7Zs2dhMBjwwQcfoHHjxjh16hQmTZqEnJwcLF26VO7yqiUxMRHDhg1Dbm7uPb2YfN1NnP52Bc4lfIjIia8hsHkHs73vttOpuHQzBy/2boo6Wjez7ZeIqKYkYSfHdJYsWYL33nsPv//+e5W30ev10Gq10Ol08PLysmB15UtMTES/fv0ghIDBUEnvRZIgQUL7yYvNGk4A4OaswqToUPRsHshh5USkCDZ5KK88Op0Ovr6+la6Tn58PvV5f5iGXrKwsDBs27P6hBABCQEDg6MrZZj2sBwB5hcX4z/bzWLT1HPIKis26byIiU9hFMF24cAErVqzAU089Vel6CxcuhFarNT5CQkKsVOG9Vq9ejdzc3PuHUikhUFxwB38cTrRIPfsu3MTMDScZTkQkO0UF0/Tp0yFJUqWPs2fPltnm2rVr6N27N4YPH45JkyZVuv8ZM2ZAp9MZH1evXrXkj1MhIQRWrFhh0raXdq+z2Ii682nZ+PLQFYvsm4ioqhQ1+GHatGkYN25cpeuEhoYa/56SkoLY2Fh07twZ//3vf++7f41GA41GU9MyaywjIwMXL140YUuB3JvXUJirh0strdnrAoAL6dkW2S8RUVWZFEwTJkyodLkkSXB1dUVwcDBiYmLQqVOnKu03ICAAAQEBVVr32rVriI2NRWRkJFatWgUnJ0V1/iqVnV2zL/+iO7kWC6YHAj0ssl8ioqoyKZh27NiBvLw8pKenAwB8fHwAAJmZJbMKBAQEwGAwICMjA5IkIS4uDuvWrYO7u7tZir527RpiYmLQoEEDLF261FgHAAQFBZnlPSzJw6NmX/5qV/P8O/6dq7MTBkbUs8i+iYiqyqRuxpYtW6DRaDB37lxkZGQYHzdv3kR8fDzc3Nywb98+ZGZmYvbs2di6dStmz55ttqJ/+OEHXLhwAdu3b0dwcDDq1KljfNgCPz8/hIWFmTA8W4K7fz04u1tmaPuoDvXhW8vFIvsmIqoqk65j6tGjB5o0aYL333+/3OWTJ0/G77//jm3btgEARo0ahX379uHy5cs1q9bM5LyOafny5fjXv/5VzYEMEloMew6Nuj1i9nqaBHpgyfDWUDnxWiYikpdJPaaDBw+idevWFS5v3bo19u/fb3zetWtXpKammvJWdmvs2LFwd3ev+rkxSYLKxRXB7ePMXou7iwovxDVlKBGRIpgUTN7e3sbeUHm2bt0Krfavk/PZ2dmyzKygZN7e3li/fj0kSbp/OP0580O7ifPh7O5p1jqcVRJe6dscdb05LRERKYNJwTRp0iRs2rQJjzzyCLZv347Lly/j8uXL2L59Ox555BEkJCSUuabof//7HyIiIsxVs92Ii4vD5s2b4ebmVsn5JgkqZ1c8NHkJApo/ZNb317o549VBLdE6xNus+yUiqgmTzjEJITB9+nS89dZbKC4uO1OASqXCP//5TyxevBiSJOHOnTtYu3YtHnzwQbRp08ZshZuD3HPllcrKysKaNWuwaNEipKSkGF/XaP3RuOfjCH6oN5zdzDuMu9sDAfhH10bwdudgByJSlhpN4pqWlmbsMQFAgwYN0KNHDwQGBpqtQEtSSjCVSkpKQnR0tPF5p+fehl/jis/lmSKygQ8e71AfTWqb95AgEZG51Gjmh8DAQIwcOdJctTi8vx/OM+ds35ENfDDyofpoGsRAIiJlU9SURGR+jQM9MLFLI7SsZ5mZIoiIzI3BZKecVRLGdm6IAQ/WhROHgRORDWEw2aF63m6Y3qcZGvrXkrsUIqJqYzDZmdimAfi/mMZwc1HJXQoRkUkYTHbCz8MFk7uFoWOon9ylEBHVCIPJxmnUThjSth6GtQ2GqzN7SURk+0wOphMnTmDFihU4duwYdDrdPbcIlyTJxJvhUVVIEtCjWW083rE+/D3kv/khEZG5mBRMu3btQu/eveHj44N27drh+PHj6N69O+7cuYMDBw6gRYsWiIyMNHet9KfQgFp4JrYxL5IlIrtkUjDNmTMHoaGhOHjwIAoKChAYGIhXXnkF3bt3x08//YQ+ffpg0aJF5q6VADzaLhgjH6oPtcp27thLRFQdJn27HTt2DBMnToSXlxdUqpLzGqVz5nXo0AFPPfWUWW8MSIBaJWF6n2YY3akhQ4mI7JpJ33BqtRqeniWHkby9veHs7Iy0tDTj8tDQUJw+fdo8FRIA4IVeTRHV2F/uMoiILM6kYGrcuDHOnz8PoGSQQ7NmzbBhwwbj8s2bNyMoKMg8FRL6P1iHoUREDsOkc0x9+/bFxx9/jIULF0KtVmPq1KkYP348mjRpAgC4ePEiFi5caNZCHUGrVq2QlJSEY1cysfbQVXjWDUUtjQqPd2wgd2lERFZj0m0vCgsLodfr4evra5wB+7PPPsP69euhUqnQv39/jBs3zty1mp3SbntRaue5NLy57TcAwCORwRjbuaG8BRERWZFJPSZnZ2f4+ZWdYeCJJ57AE088YZaiqISTBPRtVUfuMoiIrMqkc0yhoaH47rvvKlyekJCA0NBQk4uiEg818kWAJy+eJSLHYlIwJScnIzs7u8Ll2dnZxrvakukeDucAEiJyPCZfEFPZ3VUPHz4Mb29vU3dNADw0arSt7y13GUREVlflc0zLly/H8uXLAZSE0vPPP4+ZM2fes55Op0NWVhZGjRplviodUER9b15IS0QOqcrBFBgYiBYtWgAoOZRXr1491KtXr8w6kiShVq1aiIyMxNNPP23eSh1MeB3ljBIkIrImk4aLx8bGYtasWejRo4clarIaJQ8XD/DQoGU9rdylEBFZnUnDxXfu3GnuOuhvgrSucpdARCSLKgXTnj17TNp5dHS0Sds5OpUkwdfdRe4yiIhkUaVgiomJKTMKTwhR6ai80uWlM45T9Xi5OcPJqeJ/XyIie1alYOKhO+vydnOWuwQiItlUKZi6detm6TroLrU0Jt/xnojI5tX4Qpnr16/jl19+QU5OjjnqIQCuzrx+iYgcl8nfgJs2bUKzZs0QHByMtm3b4qeffgIA3Lx5E23atMHGjRvNVaPDcXNWyV0CEZFsTAqm77//HkOHDoW/vz/i4+Nx96VQ/v7+qFevHlatWmW2Ih0NZ3wgIkdm0jfgq6++iujoaOzduxdTpky5Z3mnTp1w/PjxGhdHRESOx6RgOnXqFB599NEKl9euXRtpaWkmF1Ud+fn5iIiIgCRJ+Pnnn63ynkREZDkmBZO7u3ulgx1+//33e24kaCkvvfQS6tata5X3IiIiyzMpmGJjY7F69WoUFRXds+zGjRv48MMP0atXrxoXdz9btmzBtm3bsHTpUou/FxERWYdJF8y8/vrr6NixI9q3b4/hw4dDkiQkJiZix44d+OCDDyCEQHx8vLlrLSM1NRWTJk3Cxo0b4e7uXqVt8vPzkZ+fb3yu1+stVR4REZnIpB5T06ZNsXfvXvj5+WH27NkQQmDJkiVYsGABWrVqhaSkJDRs2NDMpf5FCIFx48Zh8uTJaNeuXZW3W7hwIbRarfEREhJisRqJiMg0Jt324m6ZmZm4cOECDAYDQkNDERAQYPK+pk+fjkWLFlW6zpkzZ7Bt2zZ8/fXX2L17N1QqFZKTk9GoUSMcP34cERERFW5bXo8pJCREcbe9ICJyZDUOJnNKT09HRkZGpeuEhobi0Ucfxffff19mItni4mKoVCo8/vjjWL16dZXeT6n3YyIicmTVDqb8/Hx89tln2LZtGy5evIjbt2/D09MTjRs3Ru/evTFq1Ci4uFj2lg1Xrlwpc34oJSUFcXFxWLduHTp06IDg4OAq7YfBRESkPNUKppMnT2LQoEG4fPkyhBDQarXw8PBAdnY2dDodJElCaGgovvvuOzRv3tySdZdR1UN5f8dgIiJSnioPfsjOzsbAgQORmpqK119/HVevXkVmZmaZP+fPn4+UlBQMGDCAk7oSEZFJqtxjWrFiBZ5//nls374dMTExFa63Y8cOPPzww/jPf/5T7nRFSsIeExGR8lQ5mHr37g1JkrBly5YqrQsAW7durVl1FsZgIiJSniofyjt58mSlPaW7de/eHSdPnjS1JiIicmBVDqZbt24hKCioSuvWrl0bt27dMrkoIiJyXFUOpvz8fDg7O1dpXbVajYKCApOLIiIix1WtufKSk5Nx7Nix+6536dIlkwsiIiLHVuXBD05OTmVmWqiMEAKSJKG4uLhGxVkaBz8QESlPlXtMvFU6ERFZg6LmyrM29piIiJTHpNteEBERWQqDiYiIFIXBREREisJgIiIiRWEwERGRojCYiIhIURhMRESkKAwmIiJSFAYTEREpCoOJiIgUhcFERESKwmAiIiJFYTAREZGiMJiIiEhRGExERKQoDCYiIlIUBhMRESkKg4mIiBSFwURERIrCYCIiIkVhMBERkaIwmIiISFEYTEREpCgMJiIiUhQGExERKQqDiYiIFIXBREREisJgIiIiRbHpYNq8eTM6dOgANzc3+Pj4YPDgwXKXRERENaSWuwBTrV+/HpMmTcKCBQvQvXt3FBUV4dSpU3KXRURENSQJIYTcRVRXUVERGjZsiHnz5mHixIkm70ev10Or1UKn08HLy8uMFRIRkals8lDesWPHcO3aNTg5OaFNmzaoU6cO+vTpc98eU35+PvR6fZkHEREpi00G0++//w4AmDt3LmbNmoWEhAT4+PggJiYGt27dqnC7hQsXQqvVGh8hISHWKpmIiKpIUcE0ffp0SJJU6ePs2bMwGAwAgJkzZ2LYsGGIjIzEqlWrIEkSvvnmmwr3P2PGDOh0OuPj6tWr1vrRiIioihQ1+GHatGkYN25cpeuEhobi+vXrAIDw8HDj6xqNBqGhobhy5UqF22o0Gmg0GrPUSkRElqGoYAoICEBAQMB914uMjIRGo8G5c+fQpUsXAEBhYSGSk5PRoEEDS5dJREQWpKhgqiovLy9MnjwZ8fHxCAkJQYMGDbBkyRIAwPDhw2WujoiIasImgwkAlixZArVajdGjRyMvLw8dOnTAjh074OPjI3dpRESVyi3Mhbuzu9xlKJZNXsdkLryOiYjkcDrjNJp4N4GzylnuUhRJUaPyiIgcRXpeutwlKBaDiYhIBjdybshdgmIxmIiIZPBH9h9yl6BYDCYiIhlcvc0L/CvCYCIiksFl/WW5S1AsBhMRkQxSslNQbCiWuwxFYjAREcmg0FCItNw0uctQJAYTEZFMkvXJcpegSAwmIiKZ/Jrxq9wlKBKDiYhIJgdTDiK/OF/uMhSHwUREZCU6nQ579+7F0YNHkf5rOjKyMvD9xe/lLktxbHYSVyIiW3Py5El07drV+Dz2jVhs8NyAtrXbIlQbKmNlysIeExGRjIoMRXjryFvQF+jlLkUxGExERDJLy0vDksNLeL7pTwwmIiIF+C3zNyw6tAh5RXlylyI7BhMRkUL8mvEr5uybg9ScVLlLkRWDiYhIQa7cvoLpSdNx8PpBuUuRDYOJiEhhcoty8dbRt/DeL+8htzBX7nKsjsFERKRQu67uwkt7XsIv6b/IXYpVMZiIiBQsPS8dC35agOXHluNm3k25y7EKXmBLRGQD9qfsx+Ebh9G3UV8MDBsIDxcPuUuyGPaYiIhsRKGhEJsubsKzO57Ft+e/tduh5QwmIiIbk1uUi7Xn1uLZ7c/i+4vfo7C4UO6SzIrBRERko24X3sZnZz7D1F1TcfjGYbnLMRsGExGRjUvLS8PSI0vx5pE3cbvgttzl1BiDiYjISoQQFt3/Tzd+wvSk6biku2TR97E0BhMRkYVlZWVh+fLlGDFiRJnXDyw+gN+++w0F2QVme6+beTcRvz/epg/tScLSEa5ger0eWq0WOp0OXl5ecpdDRHYoMTERw4YNQ25ubvk9JglQaVSImhGFoLZBZn3voY2H4pEHHoHKSWXW/Voag4nBREQWkpiYiH79+kEIAYPBUPGKEiBJErrGdzV7ODXzbYYpEVMQ6B5o1v1aEoOJwUREFpCVlYXg4GDk5eVVHkql/uw5DVg1AC4eLmatxVXlin+0+ge6Bne9/8oKwHNMREQWsHr1auTm5lYtlABAAMX5xUjekWz2Wu4U38HbP7+NNb+usfgADHNgMBERmZkQAitWrDBp2/Pfn7dYeGy+tBlbk7daZN/mxGAiIjKzjIwMXLx4sfoBI4CcGzkouG2+UXp/98PlHyy2b3NhMBERmVl2dnaNti/KKzJTJffydPG02L7NhcFERGRmHh41m/lb7Wa5Gz/0rN/TYvs2F5sNpt9++w2DBg2Cv78/vLy80KVLF+zcuVPusoiI4Ofnh7CwMEiSVL0NJaBWUC24eJp3VF6pMG0YoupFWWTf5mSzwdS/f38UFRVhx44dOHr0KFq3bo3+/fvjxo0bcpdGRA5OkiQ8++yzJm3bZECT6gdaFagkFZ588Ek4Scr/2rfJ65hu3ryJgIAA7NmzB127lozLv337Nry8vPDDDz+gZ8+qdVV5HRMRWYqSrmMCgBFNR2BIkyFm368lKD86y+Hn54emTZtizZo1yMnJQVFRET744AMEBgYiMjJS7vKIiODt7Y3169dDkiQ4Od3nq/bPmR+iZkRZJJQ6BHXAoMaDzL5fS7HJW6tLkoQff/wRgwcPhqenJ5ycnBAYGIitW7fCx8enwu3y8/ORn59vfK7X661RLhE5qLi4OGzevFm2ufIA4KGgh/Bsm2dt4hBeKUVVOn36dEiSVOnj7NmzEEJgypQpCAwMRFJSEg4dOoTBgwdjwIABuH79eoX7X7hwIbRarfEREhJixZ+OiBxRXFwc/vjjDyxbtgx169Yts8zV1xUR/4jAgE8GmD2UnJ2c8UTzJ/CvyH/BWeVs1n1bmqLOMaWnpyMjI6PSdUJDQ5GUlIRevXohMzOzzLmhJk2aYOLEiZg+fXq525bXYwoJCeE5JiKyiqSkJERHRxufx74Ri4AWAWZ9DwkSOtftjJHNRiLA3bz7thZFHcoLCAhAQMD9/yFzc3MB4J7jtk5OTpWeZNRoNNBoNDUrkojIRJYYbWfcNyR0qtsJQ5sMRYinbR8NUlQwVVWnTp3g4+ODsWPHYs6cOXBzc8OHH36IS5cuoV+/fnKXR0RkVQ8FPYRHmz5q84FUyiaDyd/fH1u3bsXMmTPRvXt3FBYWokWLFti0aRNat24td3lERFYR5B6ESQ9OQkv/lnKXYlY2GUwA0K5dOyQmJspdBhGRLLqHdMfYFmPhqnaVuxSzs9lgIiJyRK4qV0xsNRHRwdH3X9lGMZiIiGxEc9/mmNx6MoJqmf96JyVhMBERKZzWRYtRzUchOjjapi6UNRWDiYhIoVycXDAgbAAGhA2Am9pN7nKshsFERKRAUXWj8Hjzx+Hn5id3KVbHYCIiUhAfjQ8mt56MiMAIuUuRDYOJiEghmvo0xbR206DVaOUuRVYMJiIiBWjh1wLTH5oOF5Vl7l5rS+x/eAcRkcIFuAVgauRUhtKf2GMiIrKSVq1aISkpCZd0l7Dq1CpoG5YcshvXYhw8XDxkrk45GExERFai1WrRpUsX+Gb4IkEkAAAaejVEZG3eeftuPJRHRCSjfqH9LHo7DFvEYCIikomniyc61ekkdxmKw2AiIpJJt+BuNnfbc2tgMBERycSeZwivCQYTEZEMAt0CUd+zvtxlKBKDiYhIBuH+4Rz0UAEGExGRDEK1oXKXoFgMJiIiGdStVVfuEhSLwUREJAN/N3+5S1AsBhMRkQy8Xb3lLkGxGExERFamUWkc6o601cVgIiKyMg9nTthaGQYTEZGVuapd5S5B0RhMRERWxmCqHIOJiMjKNCqN3CUoGoOJiIgUhcFERESKwmAiIiJFYTAREZGiMJiIiEhRGExERKQoDCYiIlIUBhMRESkKg4mIiBSFwURERIrCYCIiIkVhMBERkaIwmBQmPz8fc+fORX5+vtylkJWwzR0L2/v+JCGEkLsIuQghcPv2bXh6ekKSJLnLAQDo9XpotVrodDp4eXnJXQ5ZAdvcsbC9708tdwFykiSJHwwiIoXhoTwiIlIUBhMRESkKg0lhNBoN4uPjodHwDpeOgm3uWNje9+fQgx+IiEh52GMiIiJFYTAREZGiMJiIiEhRGExERKQoDCYiIlIUBhMRESkKg4nIxgghwKs8yJ4xmIhsRGkYFRcXK2bSYbKcoqIi5OXl4fr168jLy5O7HKtiMNmgmzdv4scff5S7DLKiW7duYebMmejevTvatGmDxYsX47fffpO7LLKQmzdvYsKECWjXrh0aN26MsWPHYv/+/XKXZTWc+cHGZGRkIDw8HOnp6Vi3bh2GDh0qd0lkYampqejWrRtUKhW0Wi3UajX27t2LkSNH4o033kBISIjcJZIZpaamIioqClqtFu3bt4e7uzuWLVuGwYMH44MPPkBAQIDcJVqcQ9/2wtbk5eVh6tSpyM3NRVhYGEaOHIlPP/0Ujz76qNylkYXo9Xo89thj8PPzw4IFCxAVFQW1Wo158+Zh3rx5eOyxxxASEgIhBA/v2YGsrCwMHDgQAQEBWLp0KaKiogAAOTk52LBhg8Mc0uOhPBuyb98+fP755+jfvz8++eQTxMbGYvTo0fj666/lLo0sZN26dbh8+TImT56MLl26QK1WQwiBF198EY0bN8bKlSthMBjkLpPMwGAwYNWqVcjOzsaLL76Izp07G5f5+fkhKCgIR44cwYULF3DhwgXjMns86MUekw3x8vLCqFGj8Pbbb8PLywuzZ89GcXExRo8eDQDsOdkZIQQOHDgAFxcXYxsDJTe4dHd3R3h4OJKTk+HkxN8v7YVWq8UjjzyCQYMGGXvAFy9exJo1a5Ceno4PPvgAP//8Mzw9PfHyyy9j0qRJ9tlTFmQziouLRWZmZpnXDhw4IHr27ClcXFzE2rVrhRBCGAwGGaojS8jKyhLbt28XQghRVFRU5s/Zs2eLwMBAodfrRUFBgWw1kvkUFBSI4uJi4/OUlBRRt25dERUVJRISEkRRUZH49ttvxcMPPywkSRLr16+XsVrL4a9aNsTJyQne3t4A/uq+d+zYEa+99hqio6MxevRorF271vgbVHJyMo4ePSpXuVRDxcXF0Gq16N69OwBApVKV+dPPzw85OTkwGAxQq0sOfuh0Oly6dEmegqnGnJ2d4eTkZPz/fefOHfTr1w+rVq1C3759oVKpMGTIELz00ktwc3NDQkKCzBVbBoNJ4So6fyBJUrnhNGbMGGzatAnXrl3D66+/jujoaJw9e9Yuj0Pbq9I2Lw2giqjVahQUFECtVkOSJNy6dQvvvvsuBg8ezHCyIeX9H5ckCQaDAY0aNcK7776LJk2aQJIkFBUVAQB69uyJBx54AOfOnUNhYaG1S7Y4BpOCCSGM5w8mTJiALVu2oLi42Lj87+E0f/58xMbGYtSoURgzZgxWrlyJWbNmoVmzZvZ5HNoO3a/N7+br64uioiLk5OQYzz/MnDkTjz32GBo1amTNsslElbV36eulvWEhhPHvJ06cQFpaGqKiouDs7CxD5RYm20FEqlRhYaHx7ykpKaJevXoiPDxc7Nixw3iOodTdx6TXr18vateuLSRJEkuWLCl3HVKm6rS5EEIkJCQISZLEnj17xIIFC4QkSeL11183Lue5RmWrbnvfve4rr7wi/Pz8REJCgjVKtToGkwLd/aF88cUXxeDBg0Xr1q2FJEmiadOmYvv27eUGzcWLF8WTTz4pJEkSb731lvF1hpLymdLmmzZtEiqVSkycOFFIkiTmz59vXMY2VzZT/48fPXpUPPvss0KtVovFixdbs2SrYjAp2ODBg0XdunXFSy+9JH788Ufx4osviqZNm4rg4OByP7iff/65kCRJLFiwwPgav6BsS3XafMeOHUKSJLa5DatOe7/77rvC19dXNGjQQCxfvtz4uj22N4NJoXbt2iVcXV3F4sWLRW5urhBCiDt37oiDBw+Kdu3aGT+4d//mlZeXJxITE43P7fEDa8+q2+aZmZmibt264o033jDug21uO6rb3hkZGWLevHnixx9/NO7DXtubwaRQ69evF5IkGYOm9DoVg8Eg9u3bJxo0aCDCw8PvCadS9vqBtWfVafM7d+4IIYTxTyHY5ramOu2dl5dnXFbKns8hclSeApQ36qphw4YAgDNnzgAoub7BYDBAkiS0a9cOMTExOHPmDP7v//4PBw4cAFB2ahLOBqBsNW3zw4cPA/hrSLm4a3QXKU9N2/vIkSMAyv4ft+eRtvwkK0Dpl8vGjRuNr9WuXRvR0dF44403sGvXLgAlH8Ti4mK4uLigTZs26NGjB7y9vTF69GjcvHnTeO0DKZ+52rx07jx7/pKyB+Zq77svvrVnDCaFeO211zBixAgsXrwYAFCvXj384x//QEFBAV5++WXs3LkTkiRBpVLhxo0b2LdvH1q1aoVly5YhMzMT//rXvwCwp2RLzNXmDCXbwPauBlkPJJLRqVOnRO/evUWjRo3KjLBatmyZ8Pf3Fz4+PmLOnDli2bJlYty4cUKj0YivvvpKCCFEXFycaNmypcjIyJCrfDIB29yxsL2rjsEkg7tPUhsMBuPghXPnzolevXqJBg0alLlQ8uuvvxYDBw4UarVaSJIkAgMDy1w8O2zYMNGkSROH+dDaIra5Y2F71wyDycruHkmTlpYmhCj5EJd+kM+ePWv84N79W5VOpxMXL14UJ06cEGfOnDG+vm/fPhEaGiqGDh1qHHJKysI2dyxs75pjMMlk1KhRYsiQIeLSpUtCiJIP890f3OjoaOHj4yOWLl1a4T42btwo4uLihK+vrzh9+rQ1yqYaYJs7Fra36RhMVlI6L1bpn9OmTRM+Pj5i4sSJ5X5wjx8/Ltzc3ERwcLB49dVX79lffHy8aNasmWjWrJk4ceKEdX4Iqha2uWNhe5sPg8nKhg4dKmbNmiWEEOLll18WPj4+YsKECcYPblFRkfF4dExMjGjSpInw9fUVR44cKbOfq1eviq+++kr88ccfVq2fqo9t7ljY3jXHYLKwu2cQnjNnjggKChKrV682Hod+8cUXjR/cCxcuGNc9d+6c6Ny5s1izZo347rvvyuyTV/grG9vcsbC9zU8t93B1e3f3/VM8PT0xYsQIjBgxwngtwuLFiyGEwOrVq5GZmYn58+fDzc0Nn3/+OVJSUhAbG4vg4GAAJTcUc3Jy4rVKCsc2dyxsbwuQORgdwgsvvCAkSRJeXl5i2bJlQoiS34junuNu/vz5Ijg4WEiSJHx8fIQkSWLRokVylUw1xDZ3LGxv82KPyYzEn1PDJCcnA/hrLqxevXrh0KFDOHDgAM6fPw+g5Ort0ulHVCoVZs6cia5du+Lo0aNISUlBp06dMHTo0DL7JeVhmzsWtreVyJmK9iQrK0ssWbJEdOrUSTg5OQlJkkSXLl3E22+/LfLy8sShQ4dEZGSkkCRJfPnll8bt7h6lc/drpRz9WLOSsc0dC9vbeiQhHGBGQAtLTU3FkCFDkJGRgTp16qBnz544c+YMDh48iEuXLmHw4MFYuXIlLl++jPHjx+PkyZNYu3Ythg0bBoC/LdkitrljYXtbmayxaAeuX78u6tevLzp27Ci++uor428/RUVFIi0tTQwaNEhIkiSio6NFVlaWOHz4sIiMjBQuLi5i3bp1xv3Y871V7A3b3LGwva2PwVQD169fFyEhIaJjx47ip59+Mp7oLCwsLPMhHDNmjJAkSYwePVoUFhaKXbt2ifbt2wt3d3exdu1auconE7DNHQvbWx4MJhPl5OSIli1bCrVaLfbu3Wt8/e7jxXePyHn44YeFWq0WmzdvFkIIsXXrVhERESEkSRIXLlzgb1M2gG3uWNje8nHwwfKmKyoqQmxsLFQqFTZu3IiCggIAZe+HpFKpUFRUBAD497//jVq1auGLL74AAMTFxWH+/Pn48ssvERYWxuPPNoBt7ljY3jKSOxltmU6nM16/MG3aNJGTk1Phuunp6aJp06aiQ4cO5Y7C4cgc28A2dyxsb3nwOqYa8PLywuzZswGU/LYkSRLmzZsHd3d34zriz9E4/v7+0Gq1UKlUEEIYr/Au5fBXetsItrljYXvLg8FUQ3//4AIo88Et7b7v3LkT58+fx9y5c40fXLJNbHPHwva2PgaTGZT3wZ07dy5q1aoFAEhJScHXX3+NkJAQREVFAQCPN9s4trljYXtbmWwHEe3Q3cejX3jhBVFQUCAyMjLE/Pnzhbu7u3jvvffkLpHMjG3uWNje1sEekxn9/beq/Px8+Pv7Y+7cuXj99dcxefJkALwK3J6wzR0L29tKZA5Gu6TT6cTLL78sJEkSkiSJBQsWGJdxZI59Yps7Fra3ZbHHZAFeXl6YMWMGCgsLERYWhqeffhoA7hmlQ/aDbe5Y2N6WxUlcLSg/Px8ajQYAP7COgm3uWNjelsFgIiIiRWG8ExGRojCYiIhIURhMRESkKAwmIiJSFAYTEREpCoOJiIgUhcFERESKwmAiIiJFYTAREZGiMJiIiEhRGExERKQo/w97eLFzqmv31AAAAABJRU5ErkJggg==", + "image/png": 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EhNi1j1B/DXq3cMDVqD5BwL097N8PuTUGPNHfNBoNRo8eDbXatjswqSRgdMe60Kjt/LVSeQBd3gS8OX0G2YcBT3SL5557Dj4+PlCpKveroZIAX081no2zs1tFpQa6vAXc08a+/RCBAU9USlhYGNauXQuVSmV1yKukm6Nn1o5pZvusksDNmSV7zAQadrJ9H0S3YMAT3SY+Ph5btmyBr6/vXbtrSo7cf365BTrdG2j7m/qFAv0/Buq3s30fRLdhwBOVIT4+HmlpaZg8eXK5J15D/TV4s3d9pE1ra1+4120JDJoP1Iq2fR9EZeB88JwPnu6iuLgYc+bMwaRJkyzLZgyMxPhu9ew7oSqpgFZPAW2G3+x7J3IwB12RQaRcGo0GcXFxpZbFRWvtC/fgaKDjq0BoEzurIyofA56oOnn5A22fAZoO4FE7VTkGPFF1UKmBZo8ArZ/m+HaqNgx4oqp2Txugw0tAUITclZCbYcATVRUvf6D9i0CjboCds1QS2YIBT1QV6jQHukwF/Oyb24bIHgx4IkdrNgh4+AVAzV8vkhc/gUSOovIAYl8G7usndyVEABjwRI7h5Q90nw6ExchdCZEFA57IXr4hQN+5QGB9uSshKoUBT2QP7wCg7/8BgeFyV0J0B042RmSPzpMZ7uS0GPBEtoruwul9yam5fMB/+umniIyMhLe3N9q1a4fff/9d7pJIgVq0aIEdO3Zgx1fvYcf4lmhRzx944D9yl0VUIZcO+GXLlmHs2LGYMmUK9u7di5YtW6JHjx7IycmRuzRSGK1Wi9jYWMS2aYbYaC20zboAAWFyl0VUIZcO+Llz52LkyJFITExE06ZN8dlnn6FGjRpYvHix3KWR0jXuLXcFRHflsgF/48YN/Pnnn+jatatlmUqlQteuXbFr1y4ZKyPF09QAwlrLXQXRXbnsMMlLly7BZDKhdu3apZbXrl0baWlpZW5jMBhgMBgsz/V6PQBg//798PPzq7piSTlOZQAFdYADB+WuhNxY69bWHWC4bMDbYubMmZg2bdodyzt14l3sqbKWyl0AuTFr77TqsgFfq1YtqNVqXLx4sdTyixcvok6dOmVu8/rrr2Ps2LGW53q9HuHh4UhJSeERPFnn1HagRi2gdlO5KyG6K5cNeE9PT7Rp0wZbt27FwIEDAQBmsxlbt27FCy+8UOY2Xl5e8PLyumN5TEwMb7pN1vHJAsLbcRpgcgkuG/AAMHbsWAwbNgxt27bFgw8+iA8++ADXr19HYmKi3KWRUkkqoEaw3FUQWcWlA/6JJ55Abm4u3nrrLWRnZyMmJgYbN26848QrkcN4awGVyw4+IzcjCWt76xVIr9dDq9VCp9Oxi4ask7WfUwKTy+ChCFFlePrKXQGR1RjwRJWh9pS7AiKrMeCJKkOtkbsCIqsx4IkqQ33nMFsiZ8WAJ6oMXw6RJNfBgCciUigGPBGRQjHgiYgUigFPRKRQDHgiIoViwMvsWsENuUsgIoViwMvsUKYOhTdMcpdBRArEgHcCF/VFcpdARArEgHcCl/INd38REVElMeCdAAOeiKoCA94JnL1SIHcJRKRADHgncCRLL3cJRKRADHgncDL3OnJ4opWIHIwB7ySSj+fKXQIRKQwD3klsOpINk9ltb49LRFWAAS8TnU6H1NRUHPzjN1w5cRCZOZex/S8exROR43jIXYC7OnToEOLi4izP27/0Kb7+LRgPRwXDW6OWsTIiUgoewTuRnDwDvv7tjNxlEJFCMOCdzOr9Wdh98rLcZRCRAjDgndD7m/9CRk6+3GUQkYtjwDuhwmITpq09gsxrhXKXQkQujAHvpK4VFOONVYc40yQR2YwB78Qu59/A6z8cQraOIU9ElceAd3K5eQZMXHkQpy9dl7sUInIxDHgXcOX6DUxYcRA7My7JXQoRuRAGvIsoLDZh5k9p+HRbBgpuGOUuh4hcAAPexWw8nI3RX+9F8vEcCMG5a4iofAx4F3Tl+g28v/kvTFhxEMez8+Quh4icFAPehaVl52H88gOYvSkNOXkcaUNEpTHgZVBcXIzt27eXWnb5xAGYTbb1rW//6xJGf70X/9tzDjeMZkeUSEQKIAk37sjV6/XQarXQ6XQICAio8vfLysrC/PnzkZSUhNzcO6cG9vQLRETsQER0GABvbS2b3iO8pg9e7NIITepU/c9DRM6NAV9NAZ+cnIx+/fqhsLAQJpOp/BdKKqg9vfDAs7NQq1Erm95LJQGPtqmHwQ/Wh4eaX9KI3JVNv/0qlQpqtbrCh6+vLxo3boxRo0bhxIkTDi369OnTGDFiBBo0aAAfHx9ERUVhypQpuHHjhkPfx1GSk5PRrVs3FBQUVBzuACDMMN0wYPenr+BS+j6b3s8sgP/9cR4TVh7kVAdEbsymI/ipU6di9erVOHLkCHr16oXo6GgAQHp6OjZu3IgWLVogISEBGRkZ2LBhA7y9vbF9+3a0bNnSIUVv3LgRy5Ytw+DBgxEdHY3Dhw9j5MiRGDp0KObMmWP1fqrjCD4rKwuNGzdGQUEBzOZK9I9LKqg9vdF58jc2d9cAQICPB97q2wyN6/jbvA8ick023dEpLCwMly5dQlpaGho2bFhqXUZGBuLj49G0aVPMnj0b6enpePjhhzFp0iSsX7/eIUX37NkTPXv2tDxv2LAhjh8/jqSkpEoFfHWYP38+CgsLKxfuwN9H8kU48+saNO79jM3vry804s3Vh/HBEzEIC/SxeT9E5Hps6qKZPXs2xowZc0e4A0B0dDTGjBmDmTNnAgAaNWqEUaNGYefOnfZVehc6nQ41a9as8DUGgwF6vb7UoyoVFxcjKSnp7t0y5RFmnEn90ebRNSUKb5jw7e6zdu2DiFyPTQF//vx5eHiUf/Dv4eGBc+fOWZ5HRkbCYDDY8lZWycjIwMcff4znnnuuwtfNnDkTWq3W8ggPD6+ymgBg/fr1ZY6WqYwb+VeRc2SX3bX8ceYKzGa3PZ9O5JZsCvhmzZohKSkJFy9evGNddnY2kpKS0KxZM8uykydPok6dOnfd72uvvQZJkip8pKWlldomMzMTPXv2xGOPPYaRI0dWuP/XX38dOp3O8rj1j1BVSEtLq/APoTUklRr5F+0/+r5uMPEGIkRuxqb0mTNnjuXk6sCBAy0nWTMyMvDjjz+iuLgYixcvBgAUFRVh6dKl6NWr1133O27cOAwfPrzC19zaLZSVlYXOnTujffv2WLBgwV337+XlBS8vr7u+zlHy8/MhSZJ9O5EkGA0FDqnn4HkdwmvWcMi+iMj52RTw8fHx2LlzJ6ZMmYIffvgBhYU3jwy9vb3RtWtXTJ06Fa1bt7Ysy8rKsmq/ISEhCAkJseq1mZmZ6Ny5M9q0aYMlS5ZApXK+8d5+fn72TwgmBDy8HBPKJ3J5n1cid2Jz/0GrVq2wZs0amM1m5OTkAABCQ0OrJWgzMzMRHx+PiIgIzJkzp1Q/tzVdQdWlSZMmMBrtO0EqzCb41a7vkHpqeKodsh8icg32dRDj5kVP1R2qW7ZsQUZGBjIyMlCvXr1S65zpwtw+ffogJCTErhOtnn5BCG32sN21qCSgy3217d4PEbkO5+vXsMLw4cMhhCjz4Uw0Gg1Gjx4NtdrGI2dJhYjYgVCp7f47jCfbRaBBLV+790NErsMlA96VPPfcc/Dx8al819XfV7JGdOhvdw29W9TFY23r3f2FRKQoDPgqFhYWhrVr10KlUlkf8pIKkiThwWffs2uaAgAY1OoejOrU0P7RPETkchjw1SA+Ph5btmyBr6/v3btr/j5yf2jM/yHYxtkkgZt97qM6ReGZ2AYMdyI3xemCq3k++AULFmDevHnlzAcf9Pd88P3tOnL39/bAhJ5NEBMeaEe1ROTqbDqC379/P7777rtSyzZt2oSOHTuiXbt2+PDDDx1SnNKEhYVh6tSpyMzMxIwZM0qta9L3WXR95wc07v2MXeHepI4/Pvh3DMOdiGwbJjlhwgTUqFEDgwcPBgCcOnUKgwYNQnBwMMLCwjB27Fj4+Pjg2WefdWixSqHRaBAXF1dqWc2olnaNltGoJTzZLgKDWt0DlYpdMkRk4xH8gQMHEBsba3n+5ZdfQq1WY9++fdi9ezceffRRfPbZZw4rkirWrkFNzHuyDf7Vph7DnYgsbDpk1Ol0CA4OtjzfsGEDunXrhlq1bnYtdOvWDT/99JNjKqRyRQTXwH/iGrI7hojKZFPA161bF8eOHQMAXLhwAX/++ScSExMt6/Pz851ybhil8PPywNMPR6BHszo8YieictkU8AMGDMDHH3+MoqIi7N69G15eXhg0aJBl/YEDB8q8GQjZr3OTUIyIbQCtj0buUojIydkU8NOnT0dubi6++uorBAYGYunSpahd++Y8J3q9HitWrMCYMWMcWqi78/PywItdGuHhqOC7v5iICDYGvJ+fH7755pty150/fx41anDecUeJrOWLyX3uQ+0Ab7lLISIXYv8sVrh50tXPzw9qtRoqlQpardYRuyUA7aOD8UrXe+Gt4VS/RFQ5Np8J/eOPP9CzZ0/UqFEDwcHBSElJAQBcunQJAwYMQHJysqNqdFuDH6yP13o2YbgTkU1sCvidO3ciNjYW6enpeOqpp2A2my3ratWqBZ1Oh/nz5zusSHejkoCx3e7FkHb1OY8MEdnMpoCfNGkS7rvvPhw9evSOS+4BoHPnzti9e7fdxbkjSQLGdW+Mzk1C5S6FiFycTQG/Z88eJCYmwsvLq8wjzHvuuQfZ2dl2F+eOHm8bjo73WndfWiKiitgU8BqNplS3zO0yMzPh5+dnc1HuKiK4Bv79QLjcZRCRQtgU8A899BBWrFhR5rrr169jyZIl6NSpk12FKV2LFi2wY8cOfPLtGrR/6VP4hzXE8PaR8FDzCmAicgybhklOmzYNnTp1Qp8+fSwzSh44cAAnT57EnDlzkJubizfffNOhhSqNVqtFbGwsRHouNl4KQmQtX7SJCJK7LCJSEJsCvl27dtiwYQNGjx6Np59+GgAwbtw4AEBUVBQ2bNiA+++/33FVuoEezWpzxAwROZTNFzolJCTg+PHj2L9/P9LT02E2mxEVFYU2bdowqGwQG23fvVeJiG5n95WsMTExiImJcUAp7qtBLV8E1vCUuwwiUhibAn779u0VrpckCd7e3qhXrx7q1q1rU2HupGlY1d8Plojcj00BHx8fb3U3TKNGjTBt2jQ88cQTtryVW7i3NoeUEpHj2RTwGzduxMSJE2EwGDBy5EhER0cDANLT07Fo0SL4+Phg8uTJOHPmDObPn48hQ4ZArVbj0UcfdWjxSlG/pq/cJRCRAklCCFHZjcaOHYtdu3YhJSUFnp6l+46LiooQHx+PTp06YdasWSgqKkLbtm3h4+ODPXv2OKxwR9Dr9dBqtdDpdAgIkKebZEd6LmLCA+HvzRt4EJFj2XRVzTfffIMhQ4bcEe4A4O3tjSeffBJffPGF5flTTz2Fo0eP2lepQqlVEvy8HDJrMxFRKTYF/PXr13Hx4sVy11+4cAH5+fmW54GBgVCrOeVtWfy8PDislIiqhE0Bn5CQgA8++ADr1q27Y93atWvx4YcfIiEhwbJs//79iIyMtLlIJfPhXO9EVEVs6hv45JNP0LlzZwwYMAD33HMPoqKiAAAnTpxAZmYmIiIi8PHHHwO42Sd/9uxZ/Oc//3Fc1QrCm3kQUVWx6SQrABQUFOCzzz7Dpk2bcObMGQBAREQEevTogeeeew6+vs4/MsQZTrJm64pQR8t7rRKR49kc8ErgDAGfk1eEUH8GPBE5HuemlVktXy+5SyAihbKqD/7WE6bWkiQJW7durfR27kal4ggaIqoaVgW82Wy+YyjfuXPncPLkSWi1WjRs2BAAcOrUKVy7dg1RUVEID+ediYiI5GRVwCcnJ5d6npqaiv79+2PhwoUYNmwYPDxu7sZoNGLJkiWYOHEili5d6uhay2QwGNCuXTscOHAA+/bt48yWRER/s6kPfvz48UhMTMSIESMs4Q4AHh4eGDlyJBITEzF27FiHFVmRCRMmICwsrFrei4jIldgU8AcPHrR0y5SlQYMGOHTokM1FWeunn37C5s2bMWfOnCp/LyIiV2NTwIeFhWHZsmUwGo13rDMajVi2bFmVH1VfvHgRI0eOxFdffYUaNWpYtY3BYIBery/1ICJSKpsCfsKECUhNTcVDDz2ERYsWITk5GcnJyVi4cCHatWuHnTt34tVXX3V0rRZCCAwfPhyjRo1C27Ztrd5u5syZ0Gq1lgdPBBORogkbLVq0SNSuXVtIkiRUKpVQqVRCkiQRGhoqFixYYNM+J06cKABU+Dh27Jj48MMPRYcOHYTRaBRCCHHq1CkBQOzbt6/C/RcVFQmdTmd5nDt3TgAQOp3OpnqJiJyZXVeyGo1G7NmzB2fPngVwc6qCtm3bljrxWhm5ubm4fPlyha9p2LAhHn/8caxdu7bU0E2TyQS1Wl1qquK7cYYrWYmIqopLTlVw9uzZUv3nWVlZ6NGjB1asWIF27dqhXr16Vu2HAU9ESmbznSb0ej3mzZuHbdu2IScnB/Pnz8eDDz6IK1euYOnSpejfv7/lVn6OVr9+/VLP/fxu3tM0KirK6nAnIlI6mwL+/Pnz6NSpE86dO4dGjRohLS3NcoOPmjVrYv78+Thz5gw+/PBDhxZLRETWsyngX331VeTl5WH//v0IDQ1FaGhoqfUDBw4s82YgVSUyMhIu2NNERFSlbBomuXnzZrz44oto2rRpmbeba9iwIc6dO2d3cUREZDubAr6wsBAhISHlrs/Ly7O5ICIicgybAr5p06bYvn17uet//PFHtGrVyuaiiIjIfjYF/Msvv4zvv/8es2bNgk6nA3BzSuGMjAwMHToUu3btwiuvvOLQQomIqHJsHgf/7rvvYurUqRBCwGw2Q6VSQQgBlUqF6dOnY+LEiY6u1eE4Dp6IlMyuC53Onj2LlStXIiMjA2azGVFRUXjkkUcqnGnSmTDgiUjJXPJKVkdhwBORkvGm20RECmX1hU73339/pXYsSRIOHDhQ6YKIiMgxrA74mjVrlrqoqbi4GDt37sT999+PoKCgKimOiIhsZ3Mf/KVLlxAaGoqff/4ZCQkJjq6rWrAPnoiUzOY++LKmKCAiIufBk6xERArFgCciUigGPBGRQlk9imbv3r2lnpfMQZOeno7AwMAyt2ndurXtlRERkV2sHkWjUqnuOLEqhCjzZGvJcpPJ5JgqqwhH0RCRkll9BL9kyZKqrIOIiByMc9HwCJ6IFIonWYmIFIoBT0SkUAx4IiKFYsATESkUA56ISKEY8ERECsWAJyJSKAY8EZFCMeCJiBSKAU9EpFAMeCIihWLAExEpFAOeiEihGPBERArFgCciUigGPBGRQjHgiYgUyqUDfv369WjXrh18fHwQFBSEgQMHyl0SEZHTsPqerM5m5cqVGDlyJGbMmIGEhAQYjUYcPnxY7rKIiJyGS96T1Wg0IjIyEtOmTcOIESNs3g/vyUpESuaSXTR79+5FZmYmVCoVWrVqhbp166JXr148giciuoVLBvzJkycBAFOnTsXkyZOxbt06BAUFIT4+HleuXCl3O4PBAL1eX+pBRKRUThXwr732GiRJqvCRlpYGs9kMAHjjjTfwr3/9C23atMGSJUsgSRKWL19e7v5nzpwJrVZreYSHh1fXj0ZEVO2cqg8+NzcXly9frvA1DRs2xK+//oqEhATs2LEDsbGxlnXt2rVD165d8e6775a5rcFggMFgsDzX6/UIDw9nHzwRKZJTjaIJCQlBSEjIXV/Xpk0beHl54fjx45aALy4uxunTpxEREVHudl5eXvDy8nJYvUREzsypAt5aAQEBGDVqFKZMmYLw8HBERERg9uzZAIDHHntM5uqIiJyDSwY8AMyePRseHh4YOnQoCgsL0a5dO/zyyy8ICgqSuzQiIqfgVH3w1Y3j4IlIyZxqFA0RETkOA56IFGvvxb1ylyArBjwRKVb29WwUm4rlLkM2DHgiUiwBgctFFV9bo2QMeCJStCtF5U9fonQMeCJStIvXL8pdgmwY8ESkaCd0J+QuQTYMeCJStAM5B+Cul/sw4IlI0XIKc5B+LV3uMmTBgCcixfvl7C9ylyALBjwRKV5qZip0Bp3cZVQ7BjwRKY5Op0NqaiqO/HEEuUdycT3vOn5I/0Husqqdy84mSURUnkOHDiEuLs7yvPN7nbHZdzM6h3dGpDZSvsKqGY/gicgtmGHGx/s+RpGxSO5Sqg0Dnojcxvn885i3fx7Mwix3KdWCAU9EbmV39m4sPbLULcbGM+CJyO1sOr0Jy44vk7uMKseAJyK3tCpjFZb/tVzuMqoUA56I3NaKv1bgu7TvFNtdw4AnIrf2Y8aPSDqQpMgbgzDgicjtpZxPwZs730RmfqbcpTgUA56ICMAp3SlM3D4Rq9JXKeZongFPRPS3YnMxvj/+PcanjMee7D0u3zfPgCciuk12QTbm/DEHb//2Nk7pTsldjs0Y8ERE5Th6+She3/E65h+Y75KzUTLgiUhRiouLsX379lLLco/kwmy0bXoCAYFfzv2Cscljse3sNpfqtpGEK1XrYHq9HlqtFjqdDgEBAXKXQ0R2yMrKwvz585GUlITc3Nw71ntpvRDVKwpRPaPgE+xj8/vcX+t+jGo5CsE+wfaUWy0Y8Ax4IpeXnJyMfv36obCwECaTqdzXSSoJak81Yt+KRWiLUJvfz0/jh2fvfxbt6razeR/VgV00ROTSkpOT0a1bNxQUFFQY7gAgzAJGgxEpb6Yg51COze+ZX5yPuX/OxZdHvnTqmSkZ8ETksrKystCvXz+YzWaYzVYGrbgZ9KnvpKLwcqFd77/+1HrM2z/PafvlGfBE5LLmz5+PwsJC68O9hACMBiNObDphdw07MncgNTPV7v1UBQY8Ebmk4uJiJCUl3bVbplxm4MSGEzaPrrlVyvkUu/dRFRjwROSS1q9fX+Zomcow6Ay48McFu2tJv5rulH3xDHgicklpaWnw8PCwax+SSoL+vN7uWopMRU55xSsDnohcUn5+PiRJsm8nEmAsNDqknrQraQ7ZjyMx4InIJfn5+dk/ekUAHj72fQsocb34ukP240gMeCJySU2aNIHRaN/RtzALBNRzzEWOzYKbOWQ/juSyAf/XX39hwIABqFWrFgICAhAbG4tt27bJXRYRVZM+ffogJCTErn14ab1Qt21du2t5sM6DaBrc1O79OJrLBnzfvn1hNBrxyy+/4M8//0TLli3Rt29fZGdny10aEVUDjUaD0aNHQ61W27YDFRDVOwoqD/tiMCIgAqNbjrb/fEAVcMm5aC5duoSQkBBs374dcXFxAIC8vDwEBARgy5Yt6Nq1q1X74Vw0RK4tKysLjRs3RkFBQeUudpIAD28P9ErqZdfEYw21DTGp3ST4e/rbvI+q5JJH8MHBwWjcuDG+/PJLXL9+HUajEfPnz0doaCjatGlT7nYGgwF6vb7Ug4hcV1hYGNauXQuVSgWVyso4k24Oj4x9M9aucI8JicFbD7/ltOEOuGjAS5KEn3/+Gfv27YO/vz+8vb0xd+5cbNy4EUFBQeVuN3PmTGi1WssjPDy8GqsmoqoQHx+PLVu2wNfX9+7dNaqbR+6d3ulk12ySvRv0xoQHJsDHw/Y/ENXBqbpoXnvtNcyaNavC1xw7dgyNGzfGwIEDUVxcjDfeeAM+Pj5YtGgR1qxZgz179qBu3bJPmhgMBhgMBstzvV6P8PBwdtEQKUBWVhYWLFiAefPmlT8ffO8oRPWwfT54L7UX/tPiP+hYr6O95VYLpwr43NxcXL58ucLXNGzYEDt27ED37t1x9erVUsHcqFEjjBgxAq+99ppV78c+eCLlKS4uxpw5czBp0iTLsuZDm6PJI03sOqEaHRiNMTFjEOYX5ogyq4VjRvg7SEhIiFXDngoKCgDgjj43lUpV+VnliEhRNBqNZfBFiZBmITaHu4+HD55o/AR6RPaASnKtXm2nCnhrPfzwwwgKCsKwYcPw1ltvwcfHBwsXLsSpU6fQp08fucsjIgWQIKFzeGf8u8m/ofXSyl2OTVwy4GvVqoWNGzfijTfeQEJCAoqLi9GsWTOsXr0aLVu2lLs8InJxTYObYljTYYjURspdil1cMuABoG3btti0aZPcZRCRggR6BWJY02F4OOxhp7xwqbJcNuCJiBwp9p5YJDZLhJ+nn9ylOAwDnojcmkalwYjmI9C5fme5S3E4BjwRua0g7yC82vZVRAVGyV1KlWDAE5Fbig6Mxvi24xHkXf7V766OAU9Ebufhug9jTMwYaNQauUupUgx4InIrXep3wX9a/MflLlqyhfJ/QiKiv7UObe024Q4w4InITWg9tXg+5nm3CXeAXTREpEAtWrTAjh07sDNrJzae2ghtpBZPNH7CqedurwoMeCJSHK1Wi9jYWOhO6vBnjT8R4hOC+PB4ucuqdu7zXYWI3Fb3yO5Qq2y8d6sLY8ATkeJ1COsgdwmyYMATkaJFBEQg2CdY7jJkwYAnIkVrFtxM7hJkw4AnIkVrFNhI7hJkw4AnIkVz9Zt22IMBT0SKJUFCaI1QucuQDQOeiBQrwCsAHir3vdyHAU9EiuWnUc7dmWzBgCcixaqhqSF3CbJiwBORYnmrveUuQVYMeCJSLI1K2Tf0uBsGPBEpljufYAUY8ESkYH6ePMlKRKRIPh4+cpcgKwY8EZFCMeCJiBSKAU9EpFAMeCIihWLAExEpFAOeiEihGPBERArFgCciUigGPBGRQjHgiYgUigFPRKRQDHgiIoViwMvIYDBg6tSpMBgMcpdCVmB7uRa2FyAJIYTcRchFCIG8vDz4+/tDkqRqf3+9Xg+tVgudToeAgIBqf3+qHLaXa2F7AW49G74kSW7b8ESkfOyiISJSKAY8EZFCMeBl5OXlhSlTpsDLy0vuUsgKbC/XwvZy85OsRERKxiN4IiKFYsATESkUA56ISKEY8ERECsWAJyJSKAY8EZFCMeCJyGWYzeZSzznKu2JuPReNo/31118ICgpCSEiI3KWQFVJSUnD06FGcPXsWTz75JO699154enrKXRaVY926ddi6dSvOnDmDQYMGYcCAAZxL6i54BO8gX3/9Ndq3b4/Fixfj0qVLcpdDd7F48WI8/vjjWL16Nb744gsMHDgQu3btAnDnUSLJb/HixXjqqadgMplw6dIlvPfeezh48KDcZTk/QXbbtm2biI6OFm3atBGNGjUS77//vsjNzZW7LCrH2rVrRa1atcQPP/wgTCaTEEKI+Ph40bNnT5kro7L88MMPombNmuKHH36wLGvWrJn4/vvvhRBCmM1mIYSwtCX9g0fwdiouLkZaWhoeeughbNmyBY888gg++ugjfPnllzySd0I6nQ6rV6/GqFGj0K9fPxiNRgDACy+8gAsXLsBkMslcId3q2rVr2LFjByZMmID+/ftblmu1WqxcuRLx8fEYP348Tp8+DZVKxT7527AP3k4ajQY9e/ZE27ZtERQUhPfeew9msxkfffQRAGDo0KGWPnmz2Wz5EMpxgxG6GQwhISFo3bo1PDz++fgHBgbi/PnzuHbtGoKCgqBS8djHGQQGBmLw4MEICQmBWq0GAHTv3h3nzp3DkCFDcOrUKezZswevv/46Pv/8c9SoUUPmip0LA95GJWENAJGRkYiMjLQE93//+19IkmQJ+eHDh0Oj0eC9997DSy+9hNDQUDlLd0u3tte7775r+QNb0mZ+fn7w9/eHt7e35XWrV69G165d4evrK1vd7urW9nrggQcsy8+cOQOTyYRffvkF0dHRAIAZM2ZgwYIF0Ov1DPjbMOBtVPLhO378OBo3bmxZbjKZoFarMWvWLADAxx9/jOvXr2PNmjW4ceMG3n77bVnqdXcl7XXs2DHcd999AP5pKwDw9PSEp6enJcwTEhKg0WhKdQtQ9Snr98toNCIiIgKbNm2Ch4cHjEYjPDw80KBBA9SvXx8+Pj5yluyU+D20km4dYZGcnIz4+Hhs3LgRwM1bAKpUKks/7qxZs9CvXz9MmTIFJpMJf/zxB9RqNUdpVKPb2yshIcHSXmq12tJnW1BQgLy8POTk5KBPnz7IzMzEunXrIEkS+3WrUUW/Xx4eHhBCWP4oe3h4oKioCF9//TWioqKg1WplqdmZMeAr4davjcuWLcPy5ctx9epVvPTSS9iwYQOAf0LebDbj6tWrOHDgAB544AH8/vvv0Gg0MBqN7N+tJta2F3DzCF6j0aBfv37466+/cPjwYUt78XxJ9bC2vSRJQlFRETIyMvDII48gMzMTCxcuBMALn27HpKmEkg/fhAkTMH78eDRq1AivvPIK/P39MX78eKxZswbAPx/CFStW4MSJE0hNTS31lZKqh7XtBdz8+n/u3Dl4eXnh6NGjlnBne1WfyrTXmjVr8PLLL8NgMGDPnj3w8PCAyWTiH+PbyTdC0zUdPXpUREdHi/Xr11uW/frrr2Lw4MGicePGYuPGjZblRqPRMja3uLi42msl69vLaDSK8ePHW9qJ7SUPa9vLZDKJjRs3CqPRKIRge5WHR/B3IW77yqdWq3Hx4kXL+GkAaN++PUaNGgW9Xo8xY8ZYvk6q1WrLsEgeCVYPW9przZo1UKvVmD17Nr9pVTNb2mvt2rVQqVTo0aOH5ZwW26tsDPi7uP0rn6+vL2JiYrB//37o9XrL8o4dOyImJgahoaF455138Pvvv5e7D6o6trTXzJkzS7UXw6L62NJeM2bMKNVePKdVPv7PWOH9999Hv379AAD33HMP4uLi8Mknn2DVqlWWD6FOp4Ovry+efPJJmEwmpKSkyFmyW2N7uRa2V9WRxO3fkagUs9mM5cuXY8SIEejfvz++/fZbAMDzzz+PH3/8EXFxcYiIiMDOnTthNBrx22+/oW/fvlCr1Vi9erXM1bsftpdrYXtVLR7B3+b2MeoqlQqDBg3CN998gw0bNuDxxx8HAMybNw+TJ0+Gv78/du3ahXvvvRfJyckAbvYjNm/enEO2qgHby7WwvaqZbKd3ndyWLVtKPTcYDGLVqlVCq9WKJ554wrLcaDRazuRfu3ZNTJ48WQQHB4tjx45Va73uju3lWthe1YMB/7dbpxrdt2+f8PDwEK+88kqp1xQVFYmlS5cKSZLE888/X2pddna2GDJkiIiMjBT79u2rjpLdGtvLtbC95MGAv83ChQvFd999Jz755BMRGhoqxo8fX2p9RkaGCA8PF5IkicmTJ5dad+TIEXH69OnqLNftsb1cC9urerl9wN96ZPHRRx+JkJAQcezYMXH58mXx6aefipo1a5b6EGZnZ4sRI0aI5ORky1dHqj5sL9fC9pKX2w/4LRlDu2/fPly4cAEffPABmjRpAgAYMmQIAGDSpEk4f/48BgwYgMWLF0Oj0aBjx46QJIkXxVQztpdrYXvJTO6/MM5g9+7dQpIkoVarxZIlS0qty8vLE2vWrBFRUVGiVatWIiEhQdy4cUMI8c+twqh6sb1cC9tLPm4Z8BcuXBAHDx4UX331lTh06JAQ4uZ9HyVJEomJiSInJ+eObYqKisSFCxcsHzrOfVF92F6uhe3lPNwu4FeuXCl69+4t6tSpIwICAoSnp6fo37+/OHfunFi5cqWQJElMnz5dXLt2zbLN7X2BvLlv9WF7uRa2l3Nxq4BfsGCBCAoKEnPmzBE///yzuHr1qnj77bdFo0aNxL333ivOnTsnvvnmGyFJkpgxY4bQ6XRyl+zW2F6uhe3lfNwm4BcsWCA8PT3FypUr71j3v//9TzRv3lzExcUJs9ks5s2bJ9RqtZg0aZLIz8+XoVpie7kWtpdzcouA37Ztm5AkSUybNk0IcfPkjdlsLtXP98knnwgvLy+xYsUKIYQQ77zzjmjfvj1P9MiA7eVa2F7Oyy0mG0tPT8eIESNQs2ZNjBs3DnFxcZZ1t94m7P7770eHDh2QlJQE4OZc1SX35OSUv9WH7eVa2F7Oyy0mG2vUqBE+//xzGAwGvPvuu0hNTbWsK/lg6fV6FBYWIiwsrNQ6fviqH9vLtbC9nJdbBDxw80P40UcfQZIkTJ8+Hb/++mup9SdPnkS9evXw0EMPAfjnTjP88MmD7eVa2F7OyS26aG6Vnp6OF198EUIIvPHGG4iLi4PRaMSAAQOgUqmwevVq3iHGibC9XAvby7m4XcAD/3wIVSoVJk2ahLlz5yItLQ379++HRqMp1W9I8mN7uRa2l/Nwy4AHbn4IX3nlFWzevBkNGzbEoUOHoNFoOPeFk2J7uRa2l3Nw24AHgLS0NMybNw9z586Fh4cHP3xOju3lWthe8nPrgL8VP3yuhe3lWthe8mDAExEpFM90EBEpFAOeiEihGPBERArFgCciUigGPBGRQjHgiYgUigFPRKRQDHgiIoViwBMRKRQDnohIof4flQu3FoIo3jEAAAAASUVORK5CYII=", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -587,8 +685,11 @@ } ], "source": [ - "f_forest_deltasg = forest_plot(contrasts, \n", - " contrast_labels =['Drug1', 'Drug2', 'Drug3'], effect_size='delta_g');" + "f_forest_hedgesg = forest_plot(\n", + " data = contrasts, \n", + " labels =['Drug1', 'Drug2', 'Drug3'], \n", + " effect_size='hedges_g',\n", + ");" ] }, { @@ -598,83 +699,7 @@ "source": [ "### Embedding forest plots into an existing Axes \n", "\n", - "You can plot a forest plot into an existing Axes as a subplot by using the with the ``ax`` parameter. \n", - "\n", - "``Example 1``:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "927f9dae-dc1b-419e-81c6-8b4bf85462dc", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f_two_forest_plots, axes = plt.subplots(1, 2, figsize = [8, 4])\n", - "['Drug1', 'Drug2', 'Drug3']\n", - "forest_plot(contrasts, contrast_labels = ['Drug1', 'Drug2', 'Drug3'], ax = axes[0])\n", - "\n", - "forest_plot(contrasts_mini_meta, contrast_type = \"mini_meta\", contrast_labels = ['mini_meta1', 'mini_meta2', 'mini_meta3'], ax = axes[1])\n", - "\n", - "axes[0].set_title('Delta-Delta Analysis', fontsize = 12);\n", - "axes[1].set_ylabel('');\n", - "axes[1].set_title('Mini-Meta Analysis', fontsize = 12);\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6e0fbdb1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Mini-Meta Analysis')" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f_forest_drug_profiles, axes = plt.subplots(1, 2, figsize = [8, 4])\n", - "['Drug1', 'Drug2', 'Drug3']\n", - "forest_plot(contrasts, contrast_labels = ['Drug1', 'Drug2', 'Drug3'], ax = axes[0])\n", - "forest_plot(contrasts_mini_meta, contrast_type = \"mini_meta\", contrast_labels = ['mini_meta1', 'mini_meta2', 'mini_meta3'], ax = axes[1])\n", - "axes[0].set_title('Delta-Delta Analysis', fontsize = 20)\n", - "axes[1].set_ylabel('')\n", - "axes[1].set_title('Mini-Meta Analysis', fontsize = 20)\n" - ] - }, - { - "cell_type": "markdown", - "id": "829f0d03", - "metadata": {}, - "source": [ - "``Example 2``:" + "You can plot a forest plot into an existing Axes as a subplot by using the with the ``ax`` parameter. " ] }, { @@ -683,21 +708,9 @@ "id": "0e0d544f", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathananns/GitHub/DABEST-python/dabest/plot_tools.py:2882: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n", - " ax.scatter(\n", - "/Users/jonathananns/GitHub/DABEST-python/dabest/plot_tools.py:2882: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n", - " ax.scatter(\n", - "/Users/jonathananns/GitHub/DABEST-python/dabest/plot_tools.py:2882: UserWarning: *c* argument looks like a single numeric RGB or RGBA sequence, which should be avoided as value-mapping will have precedence in case its length matches with *x* & *y*. Please use the *color* keyword-argument or provide a 2D array with a single row if you intend to specify the same RGB or RGBA value for all points.\n", - " ax.scatter(\n" - ] - }, { "data": { - "image/png": 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", + "image/png": 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" ] @@ -708,51 +721,26 @@ ], "source": [ "f_forest_drug_profiles, axes = plt.subplots(2, 2, figsize=[15, 14])\n", - "contrast_labels1 = ['Drug1', 'Drug2', 'Drug3']\n", - "unpaired_delta_01.mean_diff.plot( \n", + "f_forest_drug_profiles.subplots_adjust(hspace=0.3, wspace=0.3)\n", + "\n", + "for ax, contrast in zip(axes.flatten(), [unpaired_delta_01, unpaired_delta_02, unpaired_delta_03]):\n", + " contrast.mean_diff.plot( \n", " contrast_label='Mean Diff',\n", - " fig_size = (5, 5),\n", " raw_marker_size = 1,\n", " es_marker_size = 5,\n", " color_col='Genotype',\n", - " ax = axes[0,0]\n", - ")\n", + " ax = ax\n", + " )\n", "\n", - "unpaired_delta_02.mean_diff.plot( \n", - " contrast_label='',\n", - " fig_size = (5, 5),\n", - " raw_marker_size = 1,\n", - " es_marker_size = 5,\n", - " color_col='Genotype',\n", - " ax = axes[0,1]\n", - ")\n", + "forest_plot(\n", + " data = contrasts, \n", + " labels = ['Drug1', 'Drug2', 'Drug3'], \n", + " ax = axes[1,1], \n", + " )\n", "\n", - "\n", - "unpaired_delta_03.mean_diff.plot( \n", - " contrast_label='Mean Diff',\n", - " fig_size = (5, 5),\n", - " raw_marker_size = 1,\n", - " es_marker_size = 5,\n", - " color_col='Genotype',\n", - " ax = axes[1,0]\n", - ")\n", - "forest_plot(contrasts, contrast_labels = contrast_labels1 , ax = axes[1,1], )\n", - "axes[0,0].set_title('Drug1', fontsize = 12);\n", - "axes[0,0].set_ylabel('')\n", - "axes[0,1].set_ylabel('')\n", - "axes[0,1].set_title('Drug2', fontsize = 12);\n", - "axes[1,0].set_title('Drug3', fontsize = 12);\n", - "axes[0,1].set_ylabel('')\n", - "axes[1,1].set_title('Forest plot', fontsize = 12) ;\n" + "for ax, title in zip(axes.flatten(), ['Drug 1', 'Drug 2', 'Drug 3', 'Forest plot']):\n", + " ax.set_title(title, fontsize = 12)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a0aa6992-cebb-4bed-998a-1a5c11f67fb8", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From d658e1d0e97067e61cea58de46e59e253f82c1b5 Mon Sep 17 00:00:00 2001 From: Jonathan Anns Date: Tue, 7 Jan 2025 15:38:41 +0800 Subject: [PATCH 2/3] Bug fix with argument type setting --- dabest/forest_plot.py | 12 ++++++------ nbs/API/forest_plot.ipynb | 12 ++++++------ 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/dabest/forest_plot.py b/dabest/forest_plot.py index b2ff793f..6b48d348 100644 --- a/dabest/forest_plot.py +++ b/dabest/forest_plot.py @@ -321,8 +321,8 @@ def color_palette( def forest_plot( - data: List, - idx: Optional[List[int]] = None, + data: list, + idx: Optional[list[int]] = None, ax: Optional[plt.Axes] = None, fig_size: tuple[int, int] = None, effect_size: str = "mean_diff", @@ -333,16 +333,16 @@ def forest_plot( halfviolin_alpha: float = 0.8, halfviolin_desat: float = 1, - labels: List[str] = None, + labels: list[str] = None, labels_rotation: int = None, labels_fontsize: int = 10, title: str = "ΔΔ Forest", title_fontsize: int = 16, ylabel: str = None, ylabel_fontsize: int = 12, - ylim: Optional[tuple[float, float] | list[float, float]] = None, - yticks: Optional[tuple[float] | list[float]] = None, - yticklabels: Optional[tuple[str] | list[str]] = None, + ylim: Optional[list[float, float]] = None, + yticks: Optional[list[float]] = None, + yticklabels: Optional[list[str]] = None, remove_spines: bool = True, violin_kwargs: Optional[dict] = None, diff --git a/nbs/API/forest_plot.ipynb b/nbs/API/forest_plot.ipynb index 606903a9..60bac21f 100644 --- a/nbs/API/forest_plot.ipynb +++ b/nbs/API/forest_plot.ipynb @@ -380,8 +380,8 @@ "\n", "\n", "def forest_plot(\n", - " data: List,\n", - " idx: Optional[List[int]] = None,\n", + " data: list,\n", + " idx: Optional[list[int]] = None,\n", " ax: Optional[plt.Axes] = None,\n", " fig_size: tuple[int, int] = None,\n", " effect_size: str = \"mean_diff\",\n", @@ -392,16 +392,16 @@ " halfviolin_alpha: float = 0.8,\n", " halfviolin_desat: float = 1,\n", "\n", - " labels: List[str] = None,\n", + " labels: list[str] = None,\n", " labels_rotation: int = None,\n", " labels_fontsize: int = 10,\n", " title: str = \"ΔΔ Forest\",\n", " title_fontsize: int = 16,\n", " ylabel: str = None,\n", " ylabel_fontsize: int = 12,\n", - " ylim: Optional[tuple[float, float] | list[float, float]] = None,\n", - " yticks: Optional[tuple[float] | list[float]] = None,\n", - " yticklabels: Optional[tuple[str] | list[str]] = None,\n", + " ylim: Optional[list[float, float]] = None,\n", + " yticks: Optional[list[float]] = None,\n", + " yticklabels: Optional[list[str]] = None,\n", " remove_spines: bool = True,\n", "\n", " violin_kwargs: Optional[dict] = None,\n", From c562db9c088e6f59c5d09b34360769662a756ff3 Mon Sep 17 00:00:00 2001 From: Jonathan Anns Date: Tue, 7 Jan 2025 17:34:36 +0800 Subject: [PATCH 3/3] add an error for if the custom_palette supplied is a dict but no labels were supplied --- dabest/forest_plot.py | 2 ++ nbs/API/forest_plot.ipynb | 2 ++ 2 files changed, 4 insertions(+) diff --git a/dabest/forest_plot.py b/dabest/forest_plot.py index 6b48d348..bd9d1743 100644 --- a/dabest/forest_plot.py +++ b/dabest/forest_plot.py @@ -177,6 +177,8 @@ def check_for_errors( # Custom palette if custom_palette is not None and not isinstance(custom_palette, (dict, list, str, type(None))): raise TypeError("The `custom_palette` must be either a dictionary, list, string, or `None`.") + if isinstance(custom_palette, dict) and labels is None: + raise ValueError("The `labels` argument must be provided if `custom_palette` is a dictionary.") # Halfviolin alpha and desat diff --git a/nbs/API/forest_plot.ipynb b/nbs/API/forest_plot.ipynb index 60bac21f..2d9bbf3d 100644 --- a/nbs/API/forest_plot.ipynb +++ b/nbs/API/forest_plot.ipynb @@ -236,6 +236,8 @@ " # Custom palette\n", " if custom_palette is not None and not isinstance(custom_palette, (dict, list, str, type(None))):\n", " raise TypeError(\"The `custom_palette` must be either a dictionary, list, string, or `None`.\")\n", + " if isinstance(custom_palette, dict) and labels is None:\n", + " raise ValueError(\"The `labels` argument must be provided if `custom_palette` is a dictionary.\")\n", "\n", "\n", " # Halfviolin alpha and desat\n",