Contents
Pynomic library.
- class Pynomic.Pynomicplotter(summary)[source]
class for ploting the data in Pynomicproject.
- RGB_image_timeline(band_name, n_id, Red: str, Green: str, Blue: str, Size=(), ax=None, days=False, vmin=0, vmax=255, **kwargs)[source]
Generate a time line of images with line plot showing a RGB function by default.
- Parameters:
band_name (str) – the name of the band in ldata to plot.
n_id (str) – id of the plot.
Red (str) – red band name
Green (str) – green band name
Blue (str) – blue band name
days (bool) – default False converts the x axis.
function (a function that takes as input the array of the plots) – and returns an array to be ploted.
vmin (int) – minimum value to be plotted.
vmax (int) – maximium value to be plotted.
- Return type:
plot and axis
- image_timeline(band_name, n_id, function, ax=None, days=False, vmin=0, vmax=255, **kwargs)[source]
Generate a time line of images with line plot.
- Parameters:
band_name (str) – the name of the band in ldata to plot.
n_id (str) – id of the plot.
days (bool) – default False converts the x axis.
function (function) – a function that takes as input the array of the plots and returns an array to be ploted.
vmin (int) – minimum value to be plotted.
vmax (int) – maximium value to be plotted.
- Return type:
plot and axis
- class Pynomic.Pynomicproject(raw_data: Group, ldata: DataFrame, n_dates: int, dates: list, n_bands: int, bands_name: list)[source]
Contains all the extracted bands from each plot and dates.
- Parameters:
raw_data (zarr.hierarchy.Group) – contains all the data.
ldata (Pandas Dataframe) – contains all the procesed data.
- Calcualte_TI_GLCM(distances: list, angles: list)[source]
Calculates texturial indices from bands.
be aweare the O = (n_dist * n_bands)^n_angles. time and number of variables can scale very quckly.
- Parameters:
distances (list) – list of distances to work usaly 2 or 3 .
algles (lsit) – list of angles to work.
- Return type:
geodataframe.
- Calcualte_green_pixels(Red: str, Blue: str, Green: str, image_shape: tuple, min_val=30, max_val=75, to_data=False)[source]
Extracts the green and non-green pixels from each image HSL.
- Parameters:
Red (str) – name of the column that contains the red band.
Blue (str) – name of the column that contains the blue band.
Green (str) – name of the column that contains the green band.
image_shape (tuple) – (top, bottom, left, right) indicates the area
min_val (int) – in HUE range.
max_val (int) – in HUE range
- Return type:
geodataframe.
- Multispectral_VI(Red, Blue, Green, Red_edge, Nir)[source]
Calculates Multispectral Vegetation index.
- Parameters:
Red (str) – name of the column that contains the red band.
Blue (str) – name of the column that contains the blue band.
Green (str) – name of the column that contains the green band.
Red_edge (str) – name of the column that contains the Red edge band.
NIR (str) – name of the column that contains thee NIR band.
- Return type:
geodataframe
- RGB_VI(Red, Blue, Green)[source]
Calculates RGB Vegetation index.
- Parameters:
Red (str) – name of the column that contains the red band.
Blue (str) – name of the column that contains the blue band.
Green (str) – name of the column that contains the green band.
- Return type:
geodataframe
- generate_unique_feature(function, features_names: list, to_data=False)[source]
Higher order function that iterate through the flight dates.
- Parameters:
function (function) – function that contains a formula and returns a list.
new_name (list) – name of the new features.
to_data (bool) – merges it with the project data.
- Return type:
geodataframe.
- get_senescens_Loess_predictions(band: str, threshold: float, frac_val=0.5, to_data: bool = False, from_day=0)[source]
Generates predictions of senecense by providing threshold.
- Parameters:
band (str) – Band name to be used in the prediciton.
threshold (float) – value to determen if a plot is dry or not.
to_data (bool) – boolean value to save or not the predictions.
- Return type:
Geodataframe
- get_senescens_Splines_predictions(band: str, threshold: float, to_data: bool = False, from_day=0)[source]
Generates predictions of senecense by providing threshold using the spline method.
- Parameters:
band (str) – Band name to be used in the prediciton.
threshold (float) – value to determen if a plot is dry or not.
to_data (bool) – boolean value to save or not the predictions.
- Return type:
Geodataframe
- get_threshold_estimation(band: str, threshold: float, to_data: bool = False, from_day=0)[source]
Generates predictions of senecense by providing threshold and index.
- Parameters:
band (str) – Band name to be used in the prediciton.
threshold (float) – value to determen if a plot is dry or not.
to_data (bool) – boolean value to save or not the predictions.
- Return type:
Geodataframe
- property plot
Generate plots from spectra.
- save(path)[source]
Function to save project in a directory.
- Parameters:
path (str) – Name of the directory.
- Return type:
A directory with the Pynomicproject folders.
- save_indiv_plots_images(folder_path, fun, identification_col, file_type: str)[source]
Creates as many folders as dates in path provided and saves the plot images.
- Parameters:
folder_path (str) – Path where to save the images.
fun (function) – function to use to stack the bands.
identification_col (str) – Column of ldata where the ids are.
file_type (str) – tiff or jpg
- Return type:
folder with images.
- Pynomic.process_stack_tiff(folder_path, grid_path, col_id: str, bands_n=None)[source]
Process all the .tiff files in a folder.
- Parameters:
folder_path (str) – folder that contains the .tiff files.
grid_path (str) – path of the geojson grid.
col_id (str) – unique column name identifier from the grid.
bands_n (str) – list like with the bands names ordered.
- Return type:
PynomicsProject object.