wolfhece.irm_qdf ================ .. py:module:: wolfhece.irm_qdf .. autoapi-nested-parse:: Author: HECE - University of Liege, Pierre Archambeau Date: 2024 Copyright (c) 2024 University of Liege. All rights reserved. This script and its content are protected by copyright law. Unauthorized copying or distribution of this file, via any medium, is strictly prohibited. Module Contents --------------- .. py:data:: Montana_a1 :value: 'a1' .. py:data:: Montana_a2 :value: 'a2' .. py:data:: Montana_a3 :value: 'a3' .. py:data:: Montana_b1 :value: 'b1' .. py:data:: Montana_b2 :value: 'b2' .. py:data:: Montana_b3 :value: 'b3' .. py:data:: RT2 :value: '2' .. py:data:: RT5 :value: '5' .. py:data:: RT10 :value: '10' .. py:data:: RT15 :value: '15' .. py:data:: RT20 :value: '20' .. py:data:: RT25 :value: '25' .. py:data:: RT30 :value: '30' .. py:data:: RT40 :value: '40' .. py:data:: RT50 :value: '50' .. py:data:: RT75 :value: '75' .. py:data:: RT100 :value: '100' .. py:data:: RT200 :value: '200' .. py:data:: RT .. py:data:: freqdep .. py:data:: freqndep .. py:data:: dur10min :value: '10 min' .. py:data:: dur20min :value: '20 min' .. py:data:: dur30min :value: '30 min' .. py:data:: dur1h :value: '1 h' .. py:data:: dur2h :value: '2 h' .. py:data:: dur3h :value: '3 h' .. py:data:: dur6h :value: '6 h' .. py:data:: dur12h :value: '12 h' .. py:data:: dur1d :value: '1 d' .. py:data:: dur2d :value: '2 d' .. py:data:: dur3d :value: '3 d' .. py:data:: dur4d :value: '4 d' .. py:data:: dur5d :value: '5 d' .. py:data:: dur7d :value: '7 d' .. py:data:: dur10d :value: '10 d' .. py:data:: dur15d :value: '15 d' .. py:data:: dur20d :value: '20 d' .. py:data:: dur25d :value: '25 d' .. py:data:: dur30d :value: '30 d' .. py:data:: durationstext .. py:data:: durations .. py:data:: durationsd .. py:data:: durations .. py:data:: durations_seconds .. py:class:: MontanaIRM(coeff: pandas.DataFrame, time_bounds=None) Classe pour la gestion des relations de Montana pour les précipitations .. py:attribute:: coeff .. py:method:: get_ab(dur, T) Get the Montana coefficients for a given duration and return period :param dur: the duration :param T: the return period .. py:method:: get_meanrain(dur, T, ab=None) Get the mean rain for a given duration and return period :param dur: the duration :param T: the return period :param ab: the Montana coefficients .. py:method:: get_instantrain(dur, T, ab=None) Get the instantaneous rain for a given duration and return period :param dur: the duration :param T: the return period :param ab: the Montana coefficients .. py:method:: get_Q(dur, T) Get the quantity of rain for a given duration and return period :param dur: the duration :param T: the return period .. py:method:: get_hyeto(durmax, T, r=0.5) Get the hyetogram for a given return period :param durmax: the maximum duration of the hyetogram :param T: the return period :param r: Decentration coefficient .. py:method:: plot_hyeto(durmax, T, r=0.5) Plot the hyetogram for a given return period :param durmax: the maximum duration of the hyetogram :param T: the return period :param r: Decentration coefficient .. py:method:: plot_hyetos(durmax, r=0.5) Plot the hyetograms for all return periods :param durmax: the maximum duration of the hyetograms :param r: Decentration coefficient .. py:class:: Qdf_IRM(store_path='irm', code: int = 0, name='', force_import=False, ins: Literal['2018', '2019', '2025', 2018, 2019, 2025] = 2018, localities: wolfhece.ins.Localities = None, dataframe: pandas.DataFrame = None) Gestion des relations QDF calculées par l'IRM Exemple d'utilisation : Pour importer les fichiers depuis le site web de l'IRM meteo.be from wolfhece.irm_qdf import Qdf_IRM qdf = Qdf_IRM(force_import=True) qdf = Il est possible de spécifier le répertoire de stockage des fichiers Excel Par défaut, il s'agit d'un sous-répertoire 'irm' du répertoire courant qui sera créé s'il n'exsiste pas Une fois importé/téléchargé, il est possible de charger une commune sur base de l'INS ou de son nom myqdf = Qdf_IRM(name='Jalhay') Les données sont ensuite disponibles dans les propriétés, qui sont des "dataframes" pandas (https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html) : - qdf : les relation Quantité/durée/fréquence - standarddev : l'écart-type de l'erreur - confintlow : la valeur inférieure de l'intervalle de confiance (-2*stddev) - confintup : la valeur supérieure de l'intervalle de confiance (+2*stddev) - montanacoeff : les coeffciients de Montana L'index est le temps (dur10min, dur30min, dur1h, ... -- durationstext) et les colonnes sont les périodes de retour (RT2, RT5, RT10, ... -- RT). Il est par exemple possible d'accéder aux coefficients de Montana via l'une de ces lignes ou une combinaison : display(myqdf.montanacoeff) rt = myqdf.montanacoeff.index display(myqdf.montanacoeff.loc[rt[0]]) display(myqdf.montanacoeff.iloc[0]) display(myqdf.get_Montanacoeff(qdf.RT2)) .. py:attribute:: store .. py:attribute:: qdf :value: None .. py:attribute:: standarddev :value: None .. py:attribute:: confintlow :value: None .. py:attribute:: confintup :value: None .. py:attribute:: montanacoeff :value: None .. py:attribute:: montana :value: None .. py:attribute:: _code :value: None .. py:attribute:: _name :value: None .. py:attribute:: _qdf_image_table :value: None .. py:attribute:: _qdf_image_plot :value: None .. py:method:: has_data_for_locality() -> bool Has this instance been initialized with data from a locality ? .. py:property:: name .. py:property:: code .. py:property:: code_name .. py:property:: name_code .. py:method:: export_allmontana2xls() Export all Montana coefficients to an Excel file .. py:method:: importfromwebsite(store_path: pathlib.Path = 'irm', verbose: bool = False, waitingtime: float = 0.01, ins: Literal['2018', '2019', '2025', 2018, 2019, 2025] = 2018, ins_code: int = None) :classmethod: Import Excel files for one or all municipalities from the IRM website :param store_path: Where to store the downloaded data. Directory will be created if it doesn't exists. :param verbose: If `True`, will print some progress information. If `False`, will do nothing. If a callable, then will call it with a float in [0, 1]. 0 means nothing downloaded, 1 means everything downloaded. :param waitingtime: How long to wait (in seconds) betwenn the download of each station (will make sure we don't overwhelm IRM's website). :param ins: The year of the INS codes to use. :param code: Restricts the data download to a specific NIS code. `None` means full download. .. py:method:: _read_csv_or_excel(code='', name='') Lecture des caractéristiques d'une commune depuis le fichier CSV ou Excel associé au code INS :param code: le code INS de la commune :param name: le nom de la commune .. py:method:: _read_csv_or_excel_Montana_only(code='', name='') Lecture des caractéristiques d'une commune depuis le fichier CSV Excel associé au code INS :param code: le code INS de la commune :param name: le nom de la commune .. py:method:: convert_xls2csv(store_path='irm', ins: Literal['2018', '2019', '2025', 2018, 2019, 2025] = 2018) :classmethod: Convert all Excel files to CSV files :param store_path: Where to store the downloaded data. Directory will be created if it doesn't exists. :param ins: The year of the INS codes to use. .. py:method:: plot_idf(T=None, which: Literal['All', 'Montana', 'QDFTable'] = 'All', color=[27.0 / 255.0, 136.0 / 255.0, 245.0 / 255.0]) Plot IDF relations on a new figure :param T : the return period (based on RT constants) :param which : information to plot - 'Montana' - 'QDFTable' - 'All' .. py:method:: plot_qdf(T=None, which: Literal['All', 'Montana', 'QDFTable'] = 'All', color=[27.0 / 255.0, 136.0 / 255.0, 245.0 / 255.0]) Plot QDF relations on a new figure :param T : the return period (based on RT constants) :param which : information to plot - 'Montana' - 'QDFTable' - 'All' .. py:method:: plot_cdf(dur=None) Plot the cdf of the QDF data for a given duration .. py:method:: fit_all() Fit all durations with a Generalized Extreme Value distribution .. py:method:: save_fits_json() Save the fits in a csv file .. py:method:: load_fits_json() Load the fits from a json file .. py:method:: fit_cdf(dur=None, plot=False) Fit the cdf of the QDF data with a Generalized Extreme Value distribution :param dur: the duration to fit :param plot: if True, will plot the cdf with the fit .. py:method:: get_Tfromrain(Q, dur=dur1h) Get the return period for a given quantity of rain :param Q: the quantity of rain :param dur: the duration .. py:method:: get_rainfromT(T, dur=dur1h) Get the quantity of rain for a given return period and duration :param T: the return period :param dur: the duration .. py:method:: get_MontanacoeffforT(return_period) Get the Montana coefficients for a given return period :param return_period: the return period .. py:method:: plot_hyeto(durmax, T, r=0.5) Plot the hyetogram for a given return period :param durmax: the maximum duration of the hyetogram :param T: the return period :param r: the decentration coefficient .. py:method:: plot_hyetos(durmax, r=0.5) Plot the hyetograms for all return periods :param durmax: the maximum duration of the hyetograms :param r: the decentration coefficient .. py:method:: make_image_qdf_plot(T=None, which: Literal['All', 'Montana', 'QDFTable'] = 'All', color=[27.0 / 255.0, 136.0 / 255.0, 245.0 / 255.0]) Create an image of the QDF plot. We use the `matplotlib` library to create a PNG image of the QDF data. The image will be saved in the store path with the name `_qdf_plot.png`. :param durmax: the maximum duration of the hyetograms :param r: Decentration coefficient :return: a PNG image .. py:method:: make_image_qdf_table() Create an image of the QDF data. We use the `dataframe_image` library to create a PNG image of the QDF data. Added style to the DataFrame to make it more readable. :return: a PNG image .. py:method:: make_images() Create all images for the QDF data. .. py:property:: path_image_plot Get the path for the QDF plot image. .. py:property:: path_image_table Get the path for the QDF table image. .. py:class:: QDF_Belgium(store_path='irm', ins: Literal['2018', '2019', '2025', 2018, 2019, 2025] = 2018, force_import: bool = False) Class to manage all QDF data for Belgium .. py:attribute:: localities .. py:attribute:: store_path .. py:attribute:: all :type: dict[int, Qdf_IRM] .. py:method:: make_images() Create all images for all QDF data. .. py:data:: TRANSLATION_HEADER .. py:data:: RE_REFERENCE .. py:class:: Climate_IRM(store_path='irm', ins: Literal['2018', '2019', '2025', 2018, 2019, 2025] = 2018) .. py:attribute:: store_path .. py:attribute:: localities .. py:attribute:: _climate_data .. py:method:: importfromwebsite(store_path='irm', verbose: bool = False, waitingtime: float = 0.01, ins: Literal['2018', '2019', '2025', 2018, 2019, 2025] = 2018, ins_code: int = None, convert=False) :classmethod: Import Excel files for one or all municipalities from the IRM website :param store_path: Where to store the downloaded data. Directory will be created if it doesn't exists. :param verbose: If `True`, will print some progress information. If `False`, will do nothing. If a callable, then will call it with a float in [0, 1]. 0 means nothing downloaded, 1 means everything downloaded. :param waitingtime: How long to wait (in seconds) betwenn the download of each station (will make sure we don't overwhelm IRM's website). :param ins: The year of the INS codes to use. :param code: Restricts the data download to a specific NIS code. `None` means full download. :param convert: Converts the downloaded PDF to Excel files. .. py:method:: _scrap_table(t) :classmethod: Helper method to transform a table represented as a list of list to a pandas DataFrame. .. py:method:: _convert_irm_file(pdf_file: Union[str, pathlib.Path]) :classmethod: Scrap a PDF from IRM into two tables in a single Excel file with two sheets. .. py:data:: PLUVIO_INI :value: 'pluvio.ini' .. py:data:: MATCH_NUM_ZONE_SHAPEFILE_INS_INDEX :value: 'Match_num_zone_shapefile_INS_index.txt' .. py:data:: EXTREME_PRECIP_COMMUNES :value: 'Extreme_rain_ins.txt' .. py:data:: GEOMETRY_MUNICIPALITIES :value: 'PDS__COMMUNES.shp' .. py:class:: QDF_Hydrology(store_path=DATADIR / 'irm_qdf', ini_file: str = PLUVIO_INI, ins: Literal['2018', 2018] = 2018, geometry: str = GEOMETRY_MUNICIPALITIES) Prepare data from IRM website for WOLF hydrology calculations. We need : - pluvio.ini - Match_num_zone_shapefile_INS_index.txt "pluvio.ini" contains the path to the rainfall data files for each locality: - Extreme_precip_communes.txt .. py:attribute:: store_path .. py:attribute:: _data :type: dict[int, Qdf_IRM] .. py:attribute:: _ins :value: 2018 .. py:attribute:: _extreme_file :value: 'Extreme_rain_ins.txt' .. py:attribute:: _nb_lines_extreme_file :value: 0 .. py:attribute:: _nb_cols_extreme_file :value: 0 .. py:attribute:: localities .. py:attribute:: _ini_file :value: 'pluvio.ini' .. py:attribute:: _geometry :value: 'PDS__COMMUNES.shp' .. py:attribute:: _geometry_df :value: None .. py:method:: read_data() Read the data from the ini file and the extreme precipitation file. .. py:method:: download_municipalities_2018(force: bool = False) Download the municipalities shapefile from HECE. :param force: If `True`, will download the file even if it already exists. .. py:method:: create_match_num_zone_shapefile() Create the Match_num_zone_shapefile_INS_index.txt file. This file contains the mapping between the INS codes and the shapefile indices. .. py:method:: create_default_data() Create data from scratch for WOLF hydrology calculations. .. py:method:: create_extreme_precipitation_file() Create the extreme precipitation file for all localities. Each line of the file contains the following data: - INS code - Duration in seconds - Quantity for each return period (RT2, RT5, RT10, RT20, RT50, RT100) .. py:method:: create_ini_file() Create a parameter file for the class .. py:method:: get_all_ins() -> list[int] Get a list of all INS codes. .. py:class:: QDF_Hydrology_Draw(store_path=DATADIR / 'irm_qdf', ins: Literal['2018', 2018] = 2018, idx: str = '', plotted: bool = True, mapviewer=None) Bases: :py:obj:`wolfhece.drawing_obj.Element_To_Draw` .. autoapi-inheritance-diagram:: wolfhece.irm_qdf.QDF_Hydrology_Draw :parts: 1 :private-bases: Class to draw the QDF hydrology data on a map. This class is used to draw the QDF hydrology data on a map using the WOLF hydrology calculations. .. py:attribute:: _qdf_hydrology .. py:attribute:: _scale_factor :value: 1.0 .. py:attribute:: _geometry_zones .. py:attribute:: _geometry_tables .. py:attribute:: _geometry_plots .. py:attribute:: _centroids .. py:attribute:: _show_table :value: False .. py:attribute:: _show_plot :value: False .. py:attribute:: _reload_images :value: True .. py:attribute:: _current_images :value: None .. py:method:: _get_vector_tables(ins: str | int) -> wolfhece.PyVertexvectors.vector Get the vector for a given INS code. .. py:method:: _get_vector_plots(ins: str | int) -> wolfhece.PyVertexvectors.vector Get the vector for a given INS code. .. py:property:: store_path Get the store path for the QDF hydrology data. .. py:method:: _prepare_image_location() Set the default size for the images. .. py:method:: set_images_as_legend(plot_or_table: Literal['plot', 'table'] = 'plot', which: list = None) Set all images in the collection as legend images. .. py:method:: hide_all_images() Hide all images in the collection. .. py:method:: check_plot() Generic function responding to check operation from mapviewer .. py:method:: find_nearest_centroid(x: float, y: float, bounds: tuple[float, float, float, float]) Pick the municipality at the given coordinates. :param x: The x coordinate. :param y: The y coordinate. :return: The name of the municipality or an empty string if not found. .. py:method:: pick_municipality(x: float, y: float, bounds: tuple[float, float, float, float]) Activate plot for the nearest municipality to the given coordinates. .. py:method:: find_centroids_in_polygon(polygon: wolfhece.PyVertexvectors.Polygon) -> list[tuple[wolfhece.PyVertexvectors.vector, str]] Find all centroids in a given polygon. :param polygon: A shapely Polygon object defining the area to search. .. py:method:: find_centroid_in_bounds(bounds: tuple[float, float, float, float]) -> list[tuple[wolfhece.PyVertexvectors.vector, str]] Find all centroids within the given bounds. :param bounds: A tuple of (minx, miny, maxx, maxy) defining the bounding box. .. py:property:: show_plot :type: bool Check if the plot is shown. .. py:property:: show_table :type: bool Check if the table is shown. .. py:method:: scale_images(factor: float = 1.0) Scale the images in the collection by a given factor. :param factor: The scaling factor to apply to the images. .. py:method:: plot(sx=None, sy=None, xmin=None, ymin=None, xmax=None, ymax=None, size=None) Plot the QDF hydrology data on the map.