o dBP@sddlmZddlmZddlmZmZddlmZ ddl m Z ddl m Z edZedZed Zd d Zd+ddZd,ddZddZddZddZddZddZd-ddZdd Zd!d"Zd#d$Z    %   % & ' (d.d)d*ZdS)/)absolute_import)Number) exceptionsoptional_importsN) graph_objs) make_subplotspandasnumpyz scipy.statsc Cst|t}t|}t|}tj|ddd}tj|ddd}tj|ddd}||}d|}t||||k} t||||k} |||||| | d S) z6 Calculate statistics for use in violin plot. 2linear) interpolationlowerKhigher?)minmaxq1q2q3d1d2)npasarrayfloatrr percentile) dataxvals_minvals_maxrrriqr whisker_distrrr#b/var/www/html/visualizacion-main/env/lib/python3.10/site-packages/plotly/figure_factory/_violin.py calc_statss$   r%#1f77b4 rgb(0, 0, 0)c sHfddttD}tjdd|d|tjjd|ddd dd S) zG Produces a sideways probability distribution fig violin plot. cs4g|]}dd|dd|dqS)z (pdf(y), y)=({:0.2f}z, ))format).0iryr#r$ /s&z$make_half_violin..linestonextxg?spline)widthcolorshapetext) rr.modenamer7fill fillcolorline hoverinfoopacity)rangelenrScatterscatterLine)rr.r; linecolorr7r#r-r$make_half_violin+s  rEc Cs4tj|| |gt|tjj|dddddddS)z2 Returns a rugplot fig for a violin plot. z line-ew-open)r5symbolmarkersr1Fr.)r.rmarkerr8r9 showlegendr=)rrAr@rBMarker)valspdf_maxdistancer5r#r#r$make_violin_rugplotBsrNc Cs(tjddg||gddtjjddddS)z? Returns the scatterplot fig of most of a violin plot. rr1r0r rgb(0,0,0)r4r5)rr.r9r8r<)rrArBrC)rrr#r#r$make_non_outlier_intervalQsrQc CsBtjddg||gdd|dd|gdtjjdddd d S) z@ Makes the upper and lower quartiles for a violin plot. rzlower-quartile: r(zupper-quartile: r0rOrPr7)rr.r7r8r<r=)rrAr*rBrC)rrr#r#r$make_quartiles^s  rSc Cs.tjdg|gdd|gdtddddd S) z; Formats the 'median' hovertext for a violin plot. rzmedian: r(rGsquarezrgb(255,255,255))rFr5r7)rr.r7r8rHr=)rrAr*dict)rr#r#r$ make_medianos rVc Cs tjj||ddddddd}|S)z- Makes the x-axis for a violin plot. Fr1)titler?showgridzerolineshowlinemirrorticksshowticklabels)rlayoutXAxis) xaxis_title xaxis_rangexaxisr#r#r$ make_XAxis} rcc Cs tjj|dddddddd}|S)z- Makes the y-axis for a violin plot. TrRF)rWr] autorangeticklenrZrYrXr[)rr^YAxis) yaxis_titleyaxisr#r#r$ make_YAxisrdrjTcCs t|t}t|d}t|d}t|d}t|d}t|d}t|d}t|d} t|} t||d} | | } t| } |rMd | d nd }| |d | d g}t| | |d t| | |d t || t ||t |g}|r| t || ||d||fS)z? Refer to FigureFactory.create_violin() for docstring. rrrrrrrdg@ rg?)r;)rMr5)rrrr% scipy_stats gaussian_kdelinspacerrErQrSrVappendrN)rKr;rugplotrr rrrrrpdfxxyymax_pdfrM plot_xrange plot_datar#r#r$ violinplots2           rxc Cs4g} ||D] } | | vr| | q|r| ||g} t| }td|dddd}d}t| D]K\}}t| ||t }|t|krHd}t ||||d\}}t }|D] }| |d|dqY|d7}|dd |dt| ||iq1|dd dtd i|dj| dd d|| d |S)u Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot without colorscale. T皙?Frowscols shared_yaxeshorizontal_spacing print_gridrr;rqr^xaxis{}yaxis{}r1closestrWrI hovermodeautosizeheightr4)rpsortgroupbyr@r enumeraterr get_grouprrxrLayout append_traceupdater*rcrj)r data_header group_headercolorsuse_colorscale group_statsrqrrr4rW group_namer9gbLfig color_indexkgrrKrwrvr^itemr#r#r$violin_no_colorscalesJ        rc ! Csg} ||D] } | | vr| | q|r| | D] } | |vr%tdq||g}t| }td|dddd}t|dtj }t|dtj }g}|D] }|||qOt |}t |}t | D]Q\}}t |||t}|||||}t|||}t|d||d \}}t}|D] }||d|dq|d d |dt| ||iqetjdgdgd td ||d|dgd|dggdddd} || d||d ddtdi|d j| ddd|| d|S)zr Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot with colorscale. zRAll values/groups in the index column must be represented as a key in group_stats.rzTr{Fr|rzrgb{}rr^rrG)sizecmincmax colorscale showscale)rr.r8rHrIrr1rr)rprr PlotlyErrorrr@rclrs color_parser unlabel_rgbrrrrrrrfind_intermediate_colorrxr*rrrrrcrArUrj)!rrrrrrrqrrr4rWrr9grouprrrlowcolor highcolorgroup_stats_valueskey max_value min_valuerrrKintermedintermed_colorrwrvr^r trace_dummyr#r#r$violin_colorscale s|        rc Cs4g} ||D] } | | vr| | q|r| | D] } | |vr%tdq||g}t| }td|dddd}t| D]?\}}t | ||t }t ||||d\}}t }|D] }||d|dq]|dd |dt| ||iq=|dd dtd i|dj| dd d|| d |S)ryzMIf colors is a dictionary, all the group names must appear as keys in colors.rzTr{Fr|rr^rrr1rr)rprrrrr@rrrrrrrxrrrrr*rcrj)rrrrrrrqrrr4rWrr9rrrrrrrKrwrvr^rr#r#r$ violin_dictpsJ     rFXViolin and Rug Plotc  Cst|tr t|d} nt|d} |durt|tr4t|dkr&tdt dd|Ds4tdt rNt|t j j j rN|durGtd||j}t|| d|d \} } tj| d tjjd d |d | td | td dd }|dtd d d dtj| |d}|St|t j j j std|durtd|d urt| trt|||| |||||| | }|St|||| |||||| | }|St| trtdt| dkrtdt|tstdt|||| |||||| | }|S)a} **deprecated**, use instead the plotly.graph_objects trace :class:`plotly.graph_objects.Violin`. :param (list|array) data: accepts either a list of numerical values, a list of dictionaries all with identical keys and at least one column of numeric values, or a pandas dataframe with at least one column of numbers. :param (str) data_header: the header of the data column to be used from an inputted pandas dataframe. Not applicable if 'data' is a list of numeric values. :param (str) group_header: applicable if grouping data by a variable. 'group_header' must be set to the name of the grouping variable. :param (str|tuple|list|dict) colors: either a plotly scale name, an rgb or hex color, a color tuple, a list of colors or a dictionary. An rgb color is of the form 'rgb(x, y, z)' where x, y and z belong to the interval [0, 255] and a color tuple is a tuple of the form (a, b, c) where a, b and c belong to [0, 1]. If colors is a list, it must contain valid color types as its members. :param (bool) use_colorscale: only applicable if grouping by another variable. Will implement a colorscale based on the first 2 colors of param colors. This means colors must be a list with at least 2 colors in it (Plotly colorscales are accepted since they map to a list of two rgb colors). Default = False :param (dict) group_stats: a dictionary where each key is a unique value from the group_header column in data. Each value must be a number and will be used to color the violin plots if a colorscale is being used. :param (bool) rugplot: determines if a rugplot is draw on violin plot. Default = True :param (bool) sort: determines if violins are sorted alphabetically (True) or by input order (False). Default = False :param (float) height: the height of the violin plot. :param (float) width: the width of the violin plot. :param (str) title: the title of the violin plot. Example 1: Single Violin Plot >>> from plotly.figure_factory import create_violin >>> import plotly.graph_objs as graph_objects >>> import numpy as np >>> from scipy import stats >>> # create list of random values >>> data_list = np.random.randn(100) >>> # create violin fig >>> fig = create_violin(data_list, colors='#604d9e') >>> # plot >>> fig.show() Example 2: Multiple Violin Plots with Qualitative Coloring >>> from plotly.figure_factory import create_violin >>> import plotly.graph_objs as graph_objects >>> import numpy as np >>> import pandas as pd >>> from scipy import stats >>> # create dataframe >>> np.random.seed(619517) >>> Nr=250 >>> y = np.random.randn(Nr) >>> gr = np.random.choice(list("ABCDE"), Nr) >>> norm_params=[(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)] >>> for i, letter in enumerate("ABCDE"): ... y[gr == letter] *=norm_params[i][1]+ norm_params[i][0] >>> df = pd.DataFrame(dict(Score=y, Group=gr)) >>> # create violin fig >>> fig = create_violin(df, data_header='Score', group_header='Group', ... sort=True, height=600, width=1000) >>> # plot >>> fig.show() Example 3: Violin Plots with Colorscale >>> from plotly.figure_factory import create_violin >>> import plotly.graph_objs as graph_objects >>> import numpy as np >>> import pandas as pd >>> from scipy import stats >>> # create dataframe >>> np.random.seed(619517) >>> Nr=250 >>> y = np.random.randn(Nr) >>> gr = np.random.choice(list("ABCDE"), Nr) >>> norm_params=[(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)] >>> for i, letter in enumerate("ABCDE"): ... y[gr == letter] *=norm_params[i][1]+ norm_params[i][0] >>> df = pd.DataFrame(dict(Score=y, Group=gr)) >>> # define header params >>> data_header = 'Score' >>> group_header = 'Group' >>> # make groupby object with pandas >>> group_stats = {} >>> groupby_data = df.groupby([group_header]) >>> for group in "ABCDE": ... data_from_group = groupby_data.get_group(group)[data_header] ... # take a stat of the grouped data ... stat = np.median(data_from_group) ... # add to dictionary ... group_stats[group] = stat >>> # create violin fig >>> fig = create_violin(df, data_header='Score', group_header='Group', ... height=600, width=1000, use_colorscale=True, ... group_stats=group_stats) >>> # plot >>> fig.show() rgbNrzRIf data is a list, it must be nonempty and contain either numbers or dictionaries.css|]}t|tVqdS)N) isinstancer)r+elementr#r#r$ Rsz create_violin..z0If data is a list, it must contain only numbers.zVdata_header must be the column name with the desired numeric data for the violin plot.rF )rr1r) rWrfontrrIr4rbrirri)rZr]r\)rr^zGError. You must use a pandas DataFrame if you are using a group header.zFThe colors param cannot be a dictionary if you are using a colorscale.rzHcolors must be a list with at least 2 colors. A Plotly scale is allowed.z,Your group_stats param must be a dictionary.)rrUrvalidate_colors_dictvalidate_colorslistr@rrallpdcoreframe DataFramevaluestolistrxrrr^FontrcrjrFigurerrr)rrrrrrrqrrr4rW valid_colorsrwrvr^rr#r#r$ create_violins              r)r&r')r&)r&T) NNNFNTFrrr) __future__rnumbersrplotlyrr plotly.colorsrrplotly.graph_objsrplotly.subplotsr get_modulerrrmr%rErNrQrSrVrcrjrxrrrrr#r#r#r$s@           'CgJ