Ug0& dZddlZddlmZddlmZmZddlmZm Z m Z ddl m Z ddl Z ddlZddlmZdd lmZmZd d lmZd d lmZmZmZed ddZedddZdZejeZ dej!fdZ"dZ#dZ$ee%edgdgeed ddgeedddgdd ddd!d"dd#Z&dS)$a ============================= Species distribution dataset ============================= This dataset represents the geographic distribution of species. The dataset is provided by Phillips et. al. (2006). The two species are: - `"Bradypus variegatus" `_ , the Brown-throated Sloth. - `"Microryzomys minutus" `_ , also known as the Forest Small Rice Rat, a rodent that lives in Peru, Colombia, Ecuador, Peru, and Venezuela. References ---------- `"Maximum entropy modeling of species geographic distributions" `_ S. J. Phillips, R. P. Anderson, R. E. Schapire - Ecological Modelling, 190:231-259, 2006. Notes ----- For an example of using this dataset, see :ref:`examples/applications/plot_species_distribution_modeling.py `. N)BytesIO)IntegralReal)PathLikemakedirsremove)exists)Bunch)Intervalvalidate_params) get_data_home)RemoteFileMetadata _fetch_remote _pkl_filepathz samples.zipz.https://ndownloader.figshare.com/files/5976075@abb07ad284ac50d9e6d20f1c4211e0fd3c098f7f85955e89d321ee8efe37ac28)filenameurlchecksumz coverages.zipz.https://ndownloader.figshare.com/files/5976078@4d862674d72e79d6cee77e63b98651ec7926043ba7d39dcb31329cf3f6073807zspecies_coverage.pkzcfdt|D}dtfd|D}tj|}t |d}|dkrd||<|S)zjLoad a coverage file from an open file object. This will return a numpy array of the given dtype c8g|]}S)readline).0_Fs f/var/www/surfInsights/venv3-11/lib/python3.11/site-packages/sklearn/datasets/_species_distributions.py z"_load_coverage..Qs! 9 9 9qajjll 9 9 9c|dt|dfS)Nrr)splitfloat)ts r z _load_coverage..Rs+AGGIIaL% ! *=*=>r"c&g|] }|Srr)rline make_tuples r r!z"_load_coverage..Ss#777::d##777r"dtypes NODATA_valuei)rangedictnploadtxtint)r header_lengthr,headerMnodatar*s` @r _load_coverager6Ls : 9 9 9E-$8$8 9 9 9F>>J 7777777 8 8F 1E"""A ( ) )F & Hr"c|dd}t j|ddd}||j_|S)zLoad csv file. Parameters ---------- F : file object CSV file open in byte mode. Returns ------- rec : np.ndarray record array representing the data ascii,rz S22,f4,f4)skiprows delimiterr,)rdecodestripr$r/r0r,names)rr>recs r _load_csvr@\s_ JJLL   ( ( . . 0 0 6 6s ; ;E *Qc E E ECCIO Jr"c|j|jz}||j|jzz}|j|jz}||j|jzz}t j|||j}t j|||j}||fS)a%Construct the map grid from the batch object Parameters ---------- batch : Batch object The object returned by :func:`fetch_species_distributions` Returns ------- (xgrid, ygrid) : 1-D arrays The grid corresponding to the values in batch.coverages )x_left_lower_corner grid_sizeNxy_left_lower_cornerNyr/arange)batchxminxmaxyminymaxxgridygrids r construct_gridsrOps~  $u 6D 58eo- .D  $u 6D 58eo- .D IdD%/ 2 2E IdD%/ 2 2E 5>r"booleanleft)closedgneither) data_homedownload_if_missing n_retriesdelayT)prefer_skip_nested_validationg?ct|}t|st|tddddd}tj}t |t}t|s|stdt dtj d |tt||| }t j|5}|jD]=} t!|| } d | vrt#| } d | vrt#| } > d d d n #1swxYwYt%|t dt&j d |tt&||| } t j| 5}g}|jD]f} t!|| } td| |t/| gt j||}d d d n #1swxYwYt%| t3d|| | d|}t5j||dnt5j|}|S)au Loader for species distribution dataset from Phillips et. al. (2006). Read more in the :ref:`User Guide `. Parameters ---------- data_home : str or path-like, default=None Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in '~/scikit_learn_data' subfolders. download_if_missing : bool, default=True If False, raise an OSError if the data is not locally available instead of trying to download the data from the source site. n_retries : int, default=3 Number of retries when HTTP errors are encountered. .. versionadded:: 1.5 delay : float, default=1.0 Number of seconds between retries. .. versionadded:: 1.5 Returns ------- data : :class:`~sklearn.utils.Bunch` Dictionary-like object, with the following attributes. coverages : array, shape = [14, 1592, 1212] These represent the 14 features measured at each point of the map grid. The latitude/longitude values for the grid are discussed below. Missing data is represented by the value -9999. train : record array, shape = (1624,) The training points for the data. Each point has three fields: - train['species'] is the species name - train['dd long'] is the longitude, in degrees - train['dd lat'] is the latitude, in degrees test : record array, shape = (620,) The test points for the data. Same format as the training data. Nx, Ny : integers The number of longitudes (x) and latitudes (y) in the grid x_left_lower_corner, y_left_lower_corner : floats The (x,y) position of the lower-left corner, in degrees grid_size : float The spacing between points of the grid, in degrees Notes ----- This dataset represents the geographic distribution of species. The dataset is provided by Phillips et. al. (2006). The two species are: - `"Bradypus variegatus" `_ , the Brown-throated Sloth. - `"Microryzomys minutus" `_ , also known as the Forest Small Rice Rat, a rodent that lives in Peru, Colombia, Ecuador, Peru, and Venezuela. - For an example of using this dataset with scikit-learn, see :ref:`examples/applications/plot_species_distribution_modeling.py `. References ---------- * `"Maximum entropy modeling of species geographic distributions" `_ S. J. Phillips, R. P. Anderson, R. E. Schapire - Ecological Modelling, 190:231-259, 2006. Examples -------- >>> from sklearn.datasets import fetch_species_distributions >>> species = fetch_species_distributions() >>> species.train[:5] array([(b'microryzomys_minutus', -64.7 , -17.85 ), (b'microryzomys_minutus', -67.8333, -16.3333), (b'microryzomys_minutus', -67.8833, -16.3 ), (b'microryzomys_minutus', -67.8 , -16.2667), (b'microryzomys_minutus', -67.9833, -15.9 )], dtype=[('species', 'S22'), ('dd long', '>L ,  "*" OMNN N  YYWXXX$ Y)5   W\ " " .aW . .!!A$--a<<%g..EQ;;$W--D  . . . . . . . . . . . . . . . . | 9B R   ' yIU   W^ $ $ ;IW : :!!A$-- /66q99:::  !8!89999 9E:::I  ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ~R ERR\RR Ers'  N"""""""")))))))))) ????????CCCCCCCCCC   8 O      8 O    +  8 $ $%&RX     (68T* ){hxD@@@A(4d9===>  #' WWWWWWWr"