-

Python library for the detection of peaks and valleys.

+

Python library for the detection of peaks and valleys.

-class findpeaks.findpeaks.findpeaks(method=None, whitelist=['peak', 'valley'], lookahead=200, interpolate=None, limit=None, imsize=None, scale=True, togray=True, denoise='fastnl', window=None, cu=None, params_caerus={}, params={'cu': 0.25, 'window': 3}, figsize=(15, 8), verbose=3)
+class findpeaks.findpeaks.findpeaks(method=None, whitelist=['peak', 'valley'], lookahead=200, interpolate=None, limit=None, imsize=None, scale=True, togray=True, denoise='fastnl', window=None, cu=None, params_caerus={}, params={'window': 3}, figsize=(15, 8), verbose=3)

Python library for the detection of peaks and valleys.

findpeaks is for the detection and vizualization of peaks and valleys in a 1D-vector and 2D-array. In case of 2D-array, the image can be pre-processed by resizing, scaling, and denoising. For a 1D-vector, @@ -203,10 +203,10 @@

-fit(X, x=None)
+fit(X, x=None)

Detect peaks and valleys in a 1D vector or 2D-array (image).

-

Description

+

Description

  • Fit the method on your data for the detection of peaks.

  • See 1dpeaks and 2dpeaks for more details about the input/output parameters.

    • @@ -238,10 +238,10 @@

    Description
    -import_example(data='2dpeaks', url=None, sep=';', datadir=None)
    +import_example(data='2dpeaks', url=None, sep=';', datadir=None)

    Import example dataset from github source.

    -

    Description

    +

    Description

    Import one of the few datasets from github source or specify your own download url link.

    param data:
    @@ -281,7 +281,7 @@

    Description
    -imread(path, verbose=3)
    +imread(path, verbose=3)

    Read file from disk or url.

    Parameters:
    @@ -298,10 +298,10 @@

    Description
    -peaks1d(X, x=None, method='peakdetect')
    +peaks1d(X, x=None, method='peakdetect')

    Detect of peaks in 1D array.

    -

    Description

    +

    Description

    This function only eats the input data. Use the .fit() function for more information regarding the input parameters:

    • method : method to be used for peak detection: ‘topology’ or ‘peakdetect’.

      • @@ -374,10 +374,10 @@

      Description
      -peaks2d(X, method='topology')
      +peaks2d(X, method='topology')

      Detect peaks and valleys in a 2D-array or image.

      -

      Description

      +

      Description

      To handle 2d-arrays or images. Use the .fit() function for more information regarding the input parameters:

      • method : method to be used for peak detection: ‘topology’, or ‘mask’

        • @@ -461,7 +461,7 @@

        Description
        -plot(legend=True, figsize=None, cmap=None, text=True, xlabel='x-axis', ylabel='y-axis')
        +plot(limit=None, legend=True, figsize=None, cmap=None, text=True, xlabel='x-axis', ylabel='y-axis')

        Plot results.

        Parameters:
        @@ -483,7 +483,7 @@

        Description
        -plot1d(legend=True, figsize=None, xlabel='x-axis', ylabel='y-axis')
        +plot1d(legend=True, figsize=None, xlabel='x-axis', ylabel='y-axis')

        Plot the 1D results.

        Parameters:
        @@ -503,7 +503,7 @@

        Description
        -plot2d(figsize=None)
        +plot2d(figsize=None, limit=None)

        Plot the 2d results.

        Parameters:
        @@ -520,7 +520,7 @@

        Description
        -plot_mask(limit=None, figsize=None, cmap=None, text=True)
        +plot_mask(limit=None, figsize=None, cmap=None, text=True)

        Plot the masking.

        Parameters:
        @@ -541,7 +541,7 @@

        Description
        -plot_mesh(wireframe=True, surface=True, rstride=2, cstride=2, cmap=<matplotlib.colors.LinearSegmentedColormap object>, view=None, xlim=None, ylim=None, zlim=None, title='', figsize=None, savepath=None)
        +plot_mesh(wireframe=True, surface=True, rstride=2, cstride=2, cmap=<matplotlib.colors.LinearSegmentedColormap object>, view=None, xlim=None, ylim=None, zlim=None, title='', figsize=None, savepath=None)

        Plot the 3d-mesh.

        Parameters:
        @@ -612,7 +612,7 @@

        Description
        -plot_persistence(figsize=(20, 8), fontsize_ax1=14, fontsize_ax2=14, xlabel='x-axis', ylabel='y-axis', verbose=None)
        +plot_persistence(figsize=(20, 8), fontsize_ax1=14, fontsize_ax2=14, xlabel='x-axis', ylabel='y-axis', verbose=None)

        Plot the homology-peristence.

        Parameters:
        @@ -635,7 +635,7 @@

        Description
        -plot_preprocessing()
        +plot_preprocessing()

        Plot the pre-processing steps.

        Return type:
        @@ -646,7 +646,7 @@

        Description
        -preprocessing(X, showfig=False)
        +preprocessing(X, showfig=False)

        Preprocessing steps of the 2D array (image).

        The pre-processing has 4 (optional) steps.
          @@ -677,10 +677,10 @@

          Description
          -findpeaks.findpeaks.import_example(data='2dpeaks', url=None, sep=';', verbose=3, datadir=None)
          +findpeaks.findpeaks.import_example(data='2dpeaks', url=None, sep=';', verbose=3, datadir=None)

          Import example dataset from github source.

          -

          Description

          +

          Description

          Import one of the few datasets from github source or specify your own download url link.

          param data:
          @@ -720,15 +720,15 @@

          Description
          -findpeaks.findpeaks.is_url(url)
          +findpeaks.findpeaks.is_url(url)

          -
          +
          -findpeaks.stats.denoise(X, method='fastnl', window=9, cu=0.25, verbose=3)
          +findpeaks.stats.denoise(X, method='fastnl', window=9, cu=0.25, verbose=3)

          Denoise input data.

          -

          Description

          +

          Description

          Denoising the data is very usefull before detection of peaks. Multiple methods are implemented to denoise the data. The bilateral filter uses a Gaussian filter in the space domain, but it also uses one more (multiplicative) Gaussian filter component which is a function of pixel intensity differences. @@ -817,16 +817,16 @@

          Description
          -findpeaks.stats.disable_tqdm(verbose)
          +findpeaks.stats.disable_tqdm(verbose)

          Set the verbosity messages.

          -findpeaks.stats.mask(X, limit=0, verbose=3)
          +findpeaks.stats.mask(X, limit=0, verbose=3)

          Determine peaks in 2d-array using a mask.

          -

          Description

          +

          Description

          Takes an image and detect the peaks using the local maximum filter. Returns a boolean mask of the peaks (i.e. 1 when the pixel’s value is the neighborhood maximum, 0 otherwise)

          @@ -865,7 +865,7 @@

          Description
          -findpeaks.stats.resize(X, size=None, verbose=3)
          +findpeaks.stats.resize(X, size=None, verbose=3)

          Resize image.

          Parameters:
          @@ -886,10 +886,10 @@

          Description
          -findpeaks.stats.scale(X, verbose=3)
          +findpeaks.stats.scale(X, verbose=3)

          Normalize data (image) by scaling.

          -

          Description

          +

          Description

          Scaling in range [0-255] by img*(255/max(img))

          param X:
          @@ -916,10 +916,10 @@

          Description
          -findpeaks.stats.togray(X, verbose=3)
          +findpeaks.stats.togray(X, verbose=3)

          Convert color to grey-image.

          -

          Description

          +

          Description

          Convert 3d-RGB colors to 2d-grey image.

          param X:
          @@ -946,10 +946,10 @@

          Description
          -findpeaks.stats.topology(X, limit=None, reverse=True, verbose=3)
          +findpeaks.stats.topology(X, limit=None, reverse=True, verbose=3)

          Determine peaks using toplogy method.

          -

          Description

          +

          Description

          The idea behind the topology method: Consider the function graph of the function that assigns each pixel its level. Now consider a water level that continuously descents to lower levels. At local maxima islands pop up (birth). At saddle points two islands merge; we consider the lower island to be merged to the higher island (death). The so-called persistence diagram (of the 0-th dimensional homology classes, our islands) depicts death- over birth-values of all islands. The persistence of an island is then the difference between the birth- and death-level; the vertical distance of a dot to the grey main diagonal. The figure labels the islands by decreasing persistence. @@ -1020,10 +1020,10 @@

          Description
          -findpeaks.stats.topology2d(X, limit=None, whitelist=['peak', 'valley'], verbose=3)
          +findpeaks.stats.topology2d(X, limit=None, whitelist=['peak', 'valley'], verbose=3)

          Determine peaks and valleys in 2d-array using toplogy method.

          -

          Description

          +

          Description

          This function calls the topology function that ONLY computes peaks in case of 2d-arrays. To detect the valleys, the image is inverted and the topology function is called. The final results is the combined peak and valleys.

          @@ -1070,9 +1070,9 @@

          Description
          +
          -findpeaks.interpolate.interpolate_line1d(X, n=3, method=2, showfig=False, verbose=3)
          +findpeaks.interpolate.interpolate_line1d(X, n=3, method=2, showfig=False, verbose=3)

          Interpolate 1d-vector.

          Parameters:
          @@ -1113,10 +1113,10 @@

          Description
          -findpeaks.interpolate.interpolate_line2d(xs, ys=None, interpol=3, window=3, verbose=3)
          +findpeaks.interpolate.interpolate_line2d(xs, ys=None, interpol=3, window=3, verbose=3)

          interpolate 2D vector.

          -

          Description

          +

          Description

          Smoothing a 2d vector can be challanging if the data is low sampled. This function contains two steps. First interpolation of the input line followed by a convolution.

          @@ -1162,7 +1162,7 @@

          Description
          -findpeaks.interpolate.interpolate_nans(X, method='linear', replace_value_to_nan=None, verbose=3)
          +findpeaks.interpolate.interpolate_nans(X, method='linear', replace_value_to_nan=None, verbose=3)

          Interpolate the nan values in an 1D array.

          Parameters:
          @@ -1201,34 +1201,34 @@

          Description
          -findpeaks.interpolate.plot(X, bootstdata, method)
          +findpeaks.interpolate.plot(X, bootstdata, method)

          -
          +
          -findpeaks.filters.frost.calculate_all_Mi(window_flat, factor_A, window)
          +findpeaks.filters.frost.calculate_all_Mi(window_flat, factor_A, window)

          Compute all the weights of pixels in the window.

          -findpeaks.filters.frost.calculate_local_weight_matrix(window, factor_A)
          +findpeaks.filters.frost.calculate_local_weight_matrix(window, factor_A)

          Returns an array with the weights for the pixels in the given window.

          -findpeaks.filters.frost.compute_coef_var(image, x_start, x_end, y_start, y_end)
          +findpeaks.filters.frost.compute_coef_var(image, x_start, x_end, y_start, y_end)

          Compute coefficient of variation in a window of [x_start: x_end] and [y_start:y_end] within the image.

          -findpeaks.filters.frost.frost_filter(img, damping_factor=2.0, win_size=3)
          +findpeaks.filters.frost.frost_filter(img, damping_factor=2.0, win_size=3)

          Frost filter.

          -

          Description

          +

          Description

          Apply frost filter to a numpy matrix containing the image, with a window of win_size x win_size. By default, the window size is 3x3.

          param img:
          @@ -1278,12 +1278,12 @@

          Description
          +
          -findpeaks.filters.lee.lee_filter(img, win_size=3, cu=0.25)
          +findpeaks.filters.lee.lee_filter(img, win_size=3, cu=0.25)

          Lee filter.

          -

          Description

          +

          Description

          The Additive Noise Lee Despeckling Filter. Apply lee to a numpy matrix containing the image, with a window of win_size x win_size. Let’s assume that the despeckling noise is additive with a constant mean of zero, a constant variance, and drawn from a Gaussian distribution. Use a window (I x J pixels) to scan the image with a stride of 1 pixels (and I will use reflective boundary conditions). The despeckled value of the pixel in the center of the window located in the ith row and jth column is, zhat_ij = mu_k + W*(z_ij = mu_z), where mu_k is the mean value of all pixels in the window centered on pixel i,j, z_ij is the unfiltered value of the pixel, and W is a weight calculated as, W = var_k / (var_k + var_noise), where var_k is the variance of all pixels in the window and var_noise is the variance of the speckle noise. A possible alternative to using the actual value of the center pixel for z_ij is to use the median pixel value in the window. @@ -1340,12 +1340,12 @@

          Description
          +
          -findpeaks.filters.kuan.kuan_filter(img, win_size=3, cu=0.25)
          +findpeaks.filters.kuan.kuan_filter(img, win_size=3, cu=0.25)

          Kuan filter.

          -

          Description

          +

          Description

          Apply kuan to a numpy matrix containing the image, with a window of win_size x win_size.

          param img:
          @@ -1397,14 +1397,14 @@

          Description
          -findpeaks.filters.kuan.weighting(window, cu=0.25)
          +findpeaks.filters.kuan.weighting(window, cu=0.25)

          Computes the weighthing function for Kuan filter using cu as the noise coefficient.

          -
          +
          -findpeaks.filters.lee_enhanced.assert_parameters(win_size, k, cu, cmax)
          +findpeaks.filters.lee_enhanced.assert_parameters(win_size, k, cu, cmax)

          Asserts parameters in range. Parameters:

          @@ -1418,10 +1418,10 @@

          Description
          -findpeaks.filters.lee_enhanced.lee_enhanced_filter(img, win_size=3, k=1.0, cu=0.523, cmax=1.73)
          +findpeaks.filters.lee_enhanced.lee_enhanced_filter(img, win_size=3, k=1.0, cu=0.523, cmax=1.73)

          Lee enhanced filter.

          -

          Description

          +

          Description

          Apply Enhanced Lee filter to a numpy matrix containing the image, with a window of win_size x win_size.

          param img:
          @@ -1485,23 +1485,23 @@

          Description
          -findpeaks.filters.lee_enhanced.weighting(pix_value, window, k=1.0, cu=0.523, cmax=1.73)
          +findpeaks.filters.lee_enhanced.weighting(pix_value, window, k=1.0, cu=0.523, cmax=1.73)

          Computes the weighthing function for Lee filter using cu as the noise coefficient.

          -
          +
          -findpeaks.filters.mean.assert_indices_in_range(width, height, xleft, xright, yup, ydown)
          +findpeaks.filters.mean.assert_indices_in_range(width, height, xleft, xright, yup, ydown)

          Asserts index out of image range.

          -findpeaks.filters.mean.mean_filter(img, win_size=3)
          +findpeaks.filters.mean.mean_filter(img, win_size=3)

          Mean filter.

          -

          Description

          +

          Description

          Apply a ‘mean filter’ to ‘img’ with a window size equal to ‘win_size’.

          param img:
          @@ -1545,12 +1545,12 @@

          Description
          +
          -findpeaks.filters.median.median_filter(img, win_size=3)
          +findpeaks.filters.median.median_filter(img, win_size=3)

          Median Filter.

          -

          Description

          +

          Description

          Apply a ‘median filter’ to ‘img’ with a window size equal to ‘win_size’.

          param img:
          diff --git a/docs/pages/html/genindex.html b/docs/pages/html/genindex.html index f57e2ba..0994541 100644 --- a/docs/pages/html/genindex.html +++ b/docs/pages/html/genindex.html @@ -11,11 +11,11 @@ - - - - - + + + + + @@ -33,7 +33,7 @@ findpeaks
          - 2.4.7 + 2.5.3
          diff --git a/docs/pages/html/index.html b/docs/pages/html/index.html index 0a34fb5..e529a25 100644 --- a/docs/pages/html/index.html +++ b/docs/pages/html/index.html @@ -12,11 +12,11 @@ - - - - - + + + + + @@ -35,7 +35,7 @@ findpeaks
          - 2.4.7 + 2.5.3
          @@ -148,7 +148,7 @@
          -

          findpeaks’s documentation!

          +

          findpeaks’s documentation!

          |Python |Python Version Sphinx documentation Stars lines of code Downloads per month Downloads in total License Github Forks Open Issues Project Status Medium Blog Colab example Cite repo-size donate

          findpeaks is Python package for the detection of peaks and valleys in a 1d-vector and 2d-array (images). Peaks and valleys can be detected using topology, mask, and the peakdetect approach. In addition to peak-detection, various functions @@ -165,7 +165,7 @@

          findpeaks’s documentation!
          -

          Content

          +

          Content

          Background

            @@ -277,7 +277,7 @@

            Content -

            Indices and tables

            +

            Indices and tables

            • Index

            • Module Index

              • diff --git a/docs/pages/html/objects.inv b/docs/pages/html/objects.inv index 5a1bf4d76381ac74bb77898d894ccffbf36dd1f0..66c8d32b5e03084cc2be97076d2d012bda7488f0 100644 GIT binary patch delta 14 VcmX@Ye}sR6J+rBv@kXa6b^s-41d9Lw delta 14 VcmX@Ye}sR6J+q0P`9`NEb^s-H1dadz diff --git a/docs/pages/html/py-modindex.html b/docs/pages/html/py-modindex.html index 8202e1b..c3b3fb4 100644 --- a/docs/pages/html/py-modindex.html +++ b/docs/pages/html/py-modindex.html @@ -11,11 +11,11 @@ - - - - - + + + + + @@ -36,7 +36,7 @@ findpeaks
              - 2.4.7 + 2.5.3
              diff --git a/docs/pages/html/search.html b/docs/pages/html/search.html index ec92357..cf23f43 100644 --- a/docs/pages/html/search.html +++ b/docs/pages/html/search.html @@ -12,11 +12,11 @@ - - - - - + + + + + @@ -36,7 +36,7 @@ findpeaks
              - 2.4.7 + 2.5.3
              diff --git a/docs/pages/html/searchindex.js b/docs/pages/html/searchindex.js index 9d23918..cb982db 100644 --- a/docs/pages/html/searchindex.js +++ b/docs/pages/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["Abstract", "Caerus", "Coding quality", "Denoise", "Documentation", "Examples", "Installation", "Mask", "Peakdetect", "Performance", "Plots", "Pre-processing", "Topology", "Use-cases", "findpeaks.findpeaks", "index", "sponsor"], "filenames": ["Abstract.rst", "Caerus.rst", "Coding quality.rst", "Denoise.rst", "Documentation.rst", "Examples.rst", "Installation.rst", "Mask.rst", "Peakdetect.rst", "Performance.rst", "Plots.rst", "Pre-processing.rst", "Topology.rst", "Use-cases.rst", "findpeaks.findpeaks.rst", "index.rst", "sponsor.rst"], "titles": ["Abstract", "Caerus", "Coding quality", "Denoise", "Sponsor", "Quick Examples", "Quickstart", "Mask", "Peakdetect", "Performance", "One-dimensional plots", "Interpolate/impute", "Topology", "Stock Markets", 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100644 --- a/docs/pages/html/sponsor.html +++ b/docs/pages/html/sponsor.html @@ -12,11 +12,11 @@ - - - - - + + + + + @@ -34,7 +34,7 @@ findpeaks
              - 2.4.7 + 2.5.3
              diff --git a/docs/source/helper.py b/docs/source/helper.py index 233b5ac..30bc8f7 100644 --- a/docs/source/helper.py +++ b/docs/source/helper.py @@ -18,7 +18,7 @@ def add_includes_to_rst_files(top=True, bottom=True): skipfiles = ['sponsor.rst'] for file_path in glob("*.rst"): if not np.isin(file_path, skipfiles): - with open(file_path, "r+") as file: + with open(file_path, "r+", encoding='utf8') as file: contents = file.read() if top and ".. include:: add_top.add" not in contents: file.seek(0)