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Numpy Inspector, a command line tool, developed for working with *.npy and *.npz files containing numpy arrays. It can be used to visualise data, modify and many other NumPy operations without writing explicit code for routine tasks.

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array_xpl: A command line tool for exploring and manipulating arrays

Reference

General

  • --key: list the keys in the npz file
  • --tag: list the tag in the npz file
  • --verbose: verbose level

Manipulations

  • --cat: Concatenating arrays
  • --stack: Stacking arrays

View

  • --summary: summarize the data
  • --sig_dig: number of significant digits
  • --print: print the data
  • --p_bar: show a progress bar
  • --table_fmt: Table format, as in tabulate python module

Plotting

  • --plot: plot the data
  • --line_plot: plot the data as a line plot
  • --line_plot_opt: Line plot options
  • --hist1D: plot the data as a histogram
  • --hist1D_opt: Histogram plot options
  • --get_frequency: get the frequency of the data
  • --scatter: plot the data as a scatter plot
  • --scatter3D: plot the data as a 3D scatter plot
  • --image_plot: view the data as images
  • --no_pool: pool the plots on a single figure
  • --fig_size: figure size
  • --add_grid: add a grid
  • --x_label: x label
  • --y_label: y label
  • --x_lim: x limit
  • --y_lim: y limit
  • --y_log: y axis in log scale
  • --eq_axs: equalize the axes
  • --title: title
  • --no_axs: no axes
  • --tight_layout: tight layout

Transformations

  • --scale: scale the data
  • --shift: shift the data

File Operations

  • --files: list the files in the directory
  • --merge: merge the files
  • --append:
  • --remove: a list of keys to be removed from the *.npz file
  • --rename: a pair of keys to be renamed, in the order of source and target

Save

  • --saveas: save the data as a file
  • --saveas_json: save the data as a json file
  • --saveas_dat: save the data as a text file
  • --log_dir: log directory

Evaluations

  • --r2_score: R^2 score of two arrays

About

Numpy Inspector, a command line tool, developed for working with *.npy and *.npz files containing numpy arrays. It can be used to visualise data, modify and many other NumPy operations without writing explicit code for routine tasks.

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