| Next changeset 1:c54cf4ce6baf (2021-07-22) |
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Commit message:
"planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tree/master/tools/curve_fitting/ commit ef82d0882741042922349499cafa35d20d70ce70" |
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added:
curve_fitting.py curve_fitting.xml test-data/curves_fitted.xlsx test-data/spots_linked.xlsx |
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| diff -r 000000000000 -r 8bf2c507af3a curve_fitting.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/curve_fitting.py Thu Jul 22 19:34:36 2021 +0000 |
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| @@ -0,0 +1,106 @@ +""" +Copyright 2021 Biomedical Computer Vision Group, Heidelberg University. +Author: Qi Gao (qi.gao@bioquant.uni-heidelberg.de) + +Distributed under the MIT license. +See file LICENSE for detail or copy at https://opensource.org/licenses/MIT + +""" + +import argparse + +import numpy as np +import pandas as pd +from scipy.optimize import least_squares + + +def compute_curve(x, par): + assert len(par) in [2, 3], 'The degree of curve must be 1 or 2!' + if len(par) == 3: + return par[0] * x + par[1] + par[2] * x ** 2 + elif len(par) == 2: + return par[0] * x + par[1] + + +def fitting_err(par, xx, seq, penalty): + assert penalty in ['abs', 'quadratic', 'student-t'], 'Unknown penalty function!' + curve = compute_curve(xx, par) + if penalty == 'abs': + err = np.sqrt(np.abs(curve - seq)) + elif penalty == 'quadratic': + err = (curve - seq) + elif penalty == 'student-t': + a = 1000 + b = 0.001 + err = np.sqrt(a * np.log(1 + (b * (curve - seq)) ** 2)) + return err + + +def curve_fitting(seq, degree=2, penalty='abs'): + assert len(seq) > 5, 'Data is too short for curve fitting!' + assert degree in [1, 2], 'The degree of curve must be 1 or 2!' + + par0 = [(seq[-1] - seq[0]) / len(seq), np.mean(seq[0:3])] + if degree == 2: + par0.append(-0.001) + + xx = np.array([i for i in range(len(seq))]) + 1 + x = np.array(par0, dtype='float64') + result = least_squares(fitting_err, x, args=(xx, seq, penalty)) + + return compute_curve(xx, result.x) + + +def curve_fitting_io(fn_in, fn_out, degree=2, penalty='abs', alpha=0.01): + # read all sheets + xl = pd.ExcelFile(fn_in) + nSpots = len(xl.sheet_names) + data_all = [] + for i in range(nSpots): + df = pd.read_excel(xl, xl.sheet_names[i]) + data_all.append(np.array(df)) + col_names = df.columns.tolist() + ncols_ori = len(col_names) + + # curve_fitting + diff = np.array([], dtype=('float64')) + for i in range(nSpots): + seq = data_all[i][:, -1] + seq_fit = seq.copy() + idx_valid = ~np.isnan(seq) + seq_fit[idx_valid] = curve_fitting(seq[idx_valid], degree=2, penalty='abs') + data_all[i] = np.concatenate((data_all[i], seq_fit.reshape(-1, 1)), axis=1) + if alpha > 0: + diff = np.concatenate((diff, seq_fit[idx_valid] - seq[idx_valid])) + + # add assistive curve + if alpha > 0: + sorted_diff = np.sort(diff) + fac = 1 - alpha / 2 + sig3 = sorted_diff[int(diff.size * fac)] + for i in range(nSpots): + seq_assist = data_all[i][:, -1] + sig3 + data_all[i] = np.concatenate((data_all[i], seq_assist.reshape(-1, 1)), axis=1) + + # write to file + with pd.ExcelWriter(fn_out) as writer: + for i in range(nSpots): + df = pd.DataFrame() + for c in range(ncols_ori): + df[col_names[c]] = data_all[i][:, c] + df['CURVE'] = data_all[i][:, ncols_ori] + if alpha > 0: + df['CURVE_A'] = data_all[i][:, ncols_ori + 1] + df.to_excel(writer, sheet_name=xl.sheet_names[i], index=False, float_format='%.2f') + writer.save() + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Fit (1st- or 2nd-degree) polynomial curves to data points") + parser.add_argument("fn_in", help="File name of input data points (xlsx)") + parser.add_argument("fn_out", help="File name of output fitted curves (xlsx)") + parser.add_argument("degree", type=int, help="Degree of the polynomial function") + parser.add_argument("penalty", help="Optimization objective for fitting") + parser.add_argument("alpha", type=float, help="Significance level for generating assistive curves") + args = parser.parse_args() + curve_fitting_io(args.fn_in, args.fn_out, args.degree, args.penalty, args.alpha) |
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| diff -r 000000000000 -r 8bf2c507af3a curve_fitting.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/curve_fitting.xml Thu Jul 22 19:34:36 2021 +0000 |
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| @@ -0,0 +1,49 @@ +<tool id="ip_curve_fitting" name="Curve Fitting" version="0.0.1" profile="20.05"> + <description>to data points using (1st- or 2nd-degree) polynomial function</description> + <requirements> + <requirement type="package" version="1.20.2">numpy</requirement> + <requirement type="package" version="3.0.7">openpyxl</requirement> + <requirement type="package" version="1.2.4">pandas</requirement> + <requirement type="package" version="1.6.2">scipy</requirement> + </requirements> + <command> + <![CDATA[ +python '$__tool_directory__/curve_fitting.py' + '$fn_in' + ./output.xlsx + '$degree' + '$penalty' + '$alpha' + ]]> + </command> + <inputs> + <param name="fn_in" type="data" format="xlsx" label="File name of input data points (xlsx)" /> + <param name="degree" type="integer" label="Degree of the polynomial function"> + <option value="2" selected="True">2nd degree</option> + <option value="1">1st degree</option> + </param> + <param name="penalty" type="select" label="Optimization objective for fitting"> + <option value="abs" selected="True">Least absolute deviations (LAD)</option> + <option value="quadratic">Least squares (LS)</option> + <option value="student-t">Robust non-convex penalty</option> + </param> + <param name="alpha" type="float" value="0.01" label="Significance level for generating assistive curves" /> + </inputs> + <outputs> + <data format="xlsx" name="fn_out" from_work_dir="output.xlsx"/> + </outputs> + <tests> + <test> + <param name="fn_in" value="spots_linked.xlsx"/> + <param name="degree" value="2"/> + <param name="penalty" value="abs"/> + <param name="alpha" value="0.01"/> + <output name="fn_out" value="curves_fitted.xlsx" ftype="xlsx" compare="sim_size"/> + </test> + </tests> + <help> + **What it does** + + This tool fits (1st- or 2nd-degree) polynomial curves to data points. Optional: Given a significance level, assistive curves will also be generated. + </help> +</tool> |
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| diff -r 000000000000 -r 8bf2c507af3a test-data/curves_fitted.xlsx |
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| Binary file test-data/curves_fitted.xlsx has changed |
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| diff -r 000000000000 -r 8bf2c507af3a test-data/spots_linked.xlsx |
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| Binary file test-data/spots_linked.xlsx has changed |