B &[_QP @sddlmZddlmZddlmZmZddlmZ ddl m Z ddl m Z edZedZed Zd d Zd+ddZd,ddZddZddZddZddZddZd-ddZdd Zd!d"Zd#d$Zd.d)d*ZdS)/)absolute_import)Number) exceptionsoptional_importsN) graph_objs) make_subplotsZpandasZnumpyz scipy.statsc Cst|tj}t|}t|}tj|ddd}tj|ddd}tj|ddd}||}d|}t||||k} t||||k} |||||| | d S) z6 Calculate statistics for use in violin plot. 2Zlinear) interpolationlowerKZhigherg?)minmaxq1q2q3d1d2)npasarrayfloatr rZ percentile) dataxvals_minvals_maxrrrZiqrZ whisker_distrrrA/tmp/pip-install-l29rncou/plotly/plotly/figure_factory/_violin.py calc_statss"  r#1f77b4 rgb(0, 0, 0)c sHfddttD}tjdd|d|tjjd|ddd dd S) zG Produces a sideways probability distribution fig violin plot. cs4g|],}dd|dd|dqS)z (pdf(y), y)=(z{:0.2f}z, ))format).0i)ryrr 0sz$make_half_violin..linesZtonextxg?Zspline)widthcolorshapetext) rr$modenamer+fill fillcolorline hoverinfoZopacity)rangelenrScatterscatterLine)rr$r/Z linecolorr+r)rr$rmake_half_violin+s r7c Cs4tj|| |gt|tjj|dddddddS)z2 Returns a rugplot fig for a violin plot. z line-ew-open)r)symbolmarkersr'Fr$)r$rmarkerr,r- showlegendr1)rr4r3r5Marker)valsZpdf_maxdistancer)rrrmake_violin_rugplotBsr?c Cs(tjddg||gddtjjddddS)z? Returns the scatterplot fig of most of a violin plot. rr'r&g?z rgb(0,0,0))r(r))rr$r-r,r0)rr4r5r6)rrrrrmake_non_outlier_intervalQs r@c CsBtjddg||gdd|dd|gdtjjdddd d S) z@ Makes the upper and lower quartiles for a violin plot. rzlower-quartile: z{:0.2f}zupper-quartile: r&z rgb(0,0,0))r(r)r+)rr$r+r,r0r1)rr4r!r5r6)rrrrrmake_quartiles^s rBc Cs.tjdg|gdd|gdtddddd S) z; Formats the 'median' hovertext for a violin plot. rzmedian: z{:0.2f}r9Zsquarezrgb(255,255,255))r8r)r+)rr$r+r,r:r1)rr4r!dict)rrrr make_medianos rDc Cs tjj||ddddddd}|S)z- Makes the x-axis for a violin plot. Fr')titler2showgridzerolineshowlinemirrorticksshowticklabels)rlayoutZXAxis)Z xaxis_titleZ xaxis_rangexaxisrrr make_XAxis}srNc Cs tjj|dddddddd}|S)z- Makes the y-axis for a violin plot. TrAF)rErKZ autorangeZticklenrHrGrFrI)rrLZYAxis)Z yaxis_titleyaxisrrr make_YAxissrPTcCst|tj}t|d}t|d}t|d}t|d}t|d}t|d}t|d} t|} t||d} | | } t| } |rd | 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. r rrrrrrdg@ rg?)r/)r>r))rrrr scipy_statsZ gaussian_kdeZlinspacerr7r@rBrDappendr?)r=r/rugplotrrrrrrrZpdfZxxyyZmax_pdfr> plot_xrange plot_datarrr violinplots.           rYc CsBg} x"||D]} | | kr| | qW|r4| ||g} t| }td|dddd}d}xt| D]\}}t| ||tj }|t|krd}t ||||d\}}t }x|D]}| |d|dqW|d7}|dd |dt| ||iqhW|dd dtd i|dj| dd d|| d |S)zu Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot without colorscale. Tg?F)rowscols shared_yaxeshorizontal_spacing print_gridr)r/rUrLzxaxis{}zyaxis{}r'closest)rEr; hovermodeautosizeheightr()rTsortgroupbyr3r enumeraterr get_grouprrYrLayout append_traceupdater!rNrP)r data_header group_headercolorsuse_colorscale group_statsrUrdrcr(rE group_namer-gbLfigZ color_indexkgrr=rXrWrLitemrrrviolin_no_colorscales@   "rwc ! Csg} x"||D]} | | kr| | qW|r4| x| D]} | |kr:tdq:W||g}t| }td|dddd}t|dtj }t|dtj }g}x|D]}|||qWt |}t |}xt | D]\}}t |||t j}|||||}t|||}t|d||d \}}t}x |D]}||d|dq@W|d d |dt| ||iqWtjdgdgd 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.rZTg?F)r[r\r]r^r_rzrgb{})r/rUrLzxaxis{}r9)sizeZcminZcmaxZ colorscaleZ showscale)rr$r,r:r;zyaxis{}r'r`)rEr;rarbrcr()rTrdr PlotlyErrorrer3rclrsZ color_parserZ unlabel_rgbrr rfrrrgrZfind_intermediate_colorrYr!rrhrirjrNr4rCrP)!rrkrlrmrnrorUrdrcr(rErpr-grouprqrrrsZlowcolorZ highcolorZgroup_stats_valueskeyZ max_valueZ min_valuertrur=ZintermedZintermed_colorrXrWrLrvZ trace_dummyrrrviolin_colorscale sj     "r~c CsFg} x"||D]} | | kr| | qW|r4| x| D]} | |kr:tdq:W||g}t| }td|dddd}xt| D]\}}t | ||tj }t ||||d\}}t }x|D]}||d|dqW|dd |dt| ||iqW|dd dtd i|dj| dd d|| d |S)zu Refer to FigureFactory.create_violin() for docstring. Returns fig for violin plot without colorscale. zMIf colors is a dictionary, all the group names must appear as keys in colors.rZTg?F)r[r\r]r^r_)r/rUrLzxaxis{}zyaxis{}r'r`)rEr;rarbrcr()rTrdrrzrer3rrfrrrgrrYrrhrirjr!rNrP)rrkrlrmrnrorUrdrcr(rErpr-r|rqrrrsrtrur=rXrWrLrvrrr violin_dictps>    "rFXViolin and Rug Plotc  Cst|trt|d} n t|d} |dkrt|trjt|dkrNtdt dd|Dsjtdt rt|t j j j r|dkrtd||j}t|| d|d \} } tj| d tjjd d |d | td | td dd }|dtd d d dtj| |d}|St|t j j j s*td|dkr>td|d krt| trtt|||| |||||| | }|St|||| |||||| | }|Sndt| trtdt| dkrtdt|tstdt|||| |||||| | }|SdS)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 dictioanry 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() ZrgbNrzRIf data is a list, it must be nonempty and contain either numbers or dictionaries.css|]}t|tVqdS)N) isinstancer)r"elementrrr 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.)r/rUF )ryr'r`) rErbfontrcr;r(rMrOrarO)rHrKrJ)rrLzGError. 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.rxzHcolors must be a list with at least 2 colors. A Plotly scale is allowed.z,Your group_stats param must be a dictionary.)rrCr{Zvalidate_colors_dictZvalidate_colorslistr3rrzallpdcoreframeZ DataFramevaluestolistrYrrhrLZFontrNrPrjZFigurerrwr~)rrkrlrmrnrorUrdrcr(rEZ valid_colorsrXrWrLrsrrr create_violins           r)rr)r)rT) NNNFNTFrrr) __future__rZnumbersrZplotlyrrZ plotly.colorsrmr{Zplotly.graph_objsrZplotly.subplotsrZ get_modulerrrSrr7r?r@rBrDrNrPrYrwr~rrrrrrs<            'CgJ