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Merge pull request #204 from kostrykin/dev/curve_fitting
Update `ip_curve_fitting`: Relax rigidity of required input + Migrate to standard output format
2 parents 9ef338b + 9485ed4 commit 1a195a2

10 files changed

Lines changed: 182 additions & 38 deletions

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‎tools/curve_fitting/creators.xml‎

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../../macros/creators.xml

‎tools/curve_fitting/curve_fitting.py‎

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"""
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import argparse
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import os
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import numpy as np
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import pandas as pd
@@ -51,21 +52,23 @@ def curve_fitting(seq, degree=2, penalty='abs'):
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return compute_curve(xx, result.x)
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def curve_fitting_io(fn_in, fn_out, degree=2, penalty='abs', alpha=0.01):
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# read all sheets
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xl = pd.ExcelFile(fn_in)
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nSpots = len(xl.sheet_names)
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data_all = []
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def curve_fitting_io(input_list, output, degree=2, penalty='abs', alpha=0.01):
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# read all inputs
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nSpots = len(input_list)
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df_all, data_all = [], []
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for i in range(nSpots):
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df = pd.read_excel(xl, xl.sheet_names[i])
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df = pd.read_csv(input_list[i], delimiter='\t')
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df.columns = df.columns.str.strip() # remove whitespaces from header names
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df_all.append(df)
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data_all.append(np.array(df))
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col_names = df.columns.tolist()
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ncols_ori = len(col_names)
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# curve_fitting
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diff = np.array([], dtype=('float64'))
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for i in range(nSpots):
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seq = data_all[i][:, -1]
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seq = data_all[i][:, col_names.index('intensity')]
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seq_fit = seq.copy()
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idx_valid = ~np.isnan(seq)
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seq_fit[idx_valid] = curve_fitting(seq[idx_valid], degree=degree, penalty=penalty)
@@ -82,25 +85,21 @@ def curve_fitting_io(fn_in, fn_out, degree=2, penalty='abs', alpha=0.01):
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seq_assist = data_all[i][:, -1] + sig3
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data_all[i] = np.concatenate((data_all[i], seq_assist.reshape(-1, 1)), axis=1)
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# write to file
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with pd.ExcelWriter(fn_out) as writer:
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for i in range(nSpots):
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df = pd.DataFrame()
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for c in range(ncols_ori):
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df[col_names[c]] = data_all[i][:, c]
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df['CURVE'] = data_all[i][:, ncols_ori]
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if alpha > 0:
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df['CURVE_A'] = data_all[i][:, ncols_ori + 1]
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df.to_excel(writer, sheet_name=xl.sheet_names[i], index=False, float_format='%.2f')
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writer.save()
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# write to files
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for i in range(nSpots):
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df = df_all[i]
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df['curve'] = data_all[i][:, ncols_ori]
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if alpha > 0:
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df['curve_a'] = data_all[i][:, ncols_ori + 1]
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df.to_csv(os.path.join(output, f'curve{i + 1}.tsv'), sep='\t', lineterminator='\n', index=False)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Fit (1st- or 2nd-degree) polynomial curves to data points")
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parser.add_argument("fn_in", help="File name of input data points (xlsx)")
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parser.add_argument("fn_out", help="File name of output fitted curves (xlsx)")
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parser.add_argument("--input", help="File name of input data points (tsv)", action='append', type=str, required=True)
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parser.add_argument("output", help="Name of output directory")
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parser.add_argument("degree", type=int, help="Degree of the polynomial function")
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parser.add_argument("penalty", help="Optimization objective for fitting")
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parser.add_argument("alpha", type=float, help="Significance level for generating assistive curves")
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args = parser.parse_args()
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curve_fitting_io(args.fn_in, args.fn_out, args.degree, args.penalty, args.alpha)
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curve_fitting_io(args.input, args.output, args.degree, args.penalty, args.alpha)

‎tools/curve_fitting/curve_fitting.xml‎

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@@ -1,29 +1,43 @@
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<tool id="ip_curve_fitting" name="Perform curve fitting" version="0.0.3-2" profile="20.05">
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<tool id="ip_curve_fitting" name="Perform curve fitting" version="0.0.4" profile="20.05">
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<description></description>
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<macros>
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<import>creators.xml</import>
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</macros>
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<creator>
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<expand macro="creators/bmcv"/>
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</creator>
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<edam_operations>
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<edam_operation>operation_3443</edam_operation>
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</edam_operations>
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<xrefs>
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<xref type="bio.tools">galaxy_image_analysis</xref>
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</xrefs>
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<requirements>
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<requirement type="package" version="1.20.2">numpy</requirement>
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<requirement type="package" version="3.0.7">openpyxl</requirement>
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<requirement type="package" version="1.2.4">pandas</requirement>
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<requirement type="package" version="1.6.2">scipy</requirement>
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<requirement type="package" version="2.3.5">numpy</requirement>
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<requirement type="package" version="2.2.2">pandas</requirement>
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<requirement type="package" version="1.16.3">scipy</requirement>
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</requirements>
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<command>
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<![CDATA[
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python '$__tool_directory__/curve_fitting.py'
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'$fn_in'
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./output.xlsx
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$degree
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$penalty
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$alpha
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mkdir ./output &&
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python '$__tool_directory__/curve_fitting.py'
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#for $input in $input_list
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#if $input
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--input '$input'
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#end if
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#end for
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./output
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$degree
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$penalty
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$alpha
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]]>
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</command>
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<inputs>
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<param name="fn_in" type="data" format="xlsx" label="File name of input data points (xlsx)" />
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<param name="input_list" type="data" format="tsv,tabular" multiple="true" label="Lists of intensity values"/>
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<param name="degree" type="select" label="Degree of the polynomial function">
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<option value="2" selected="True">2nd degree</option>
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<option value="1">1st degree</option>
@@ -36,21 +50,39 @@ python '$__tool_directory__/curve_fitting.py'
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<param name="alpha" type="float" value="0.01" label="Significance level for generating assistive curves" />
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</inputs>
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<outputs>
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<data format="xlsx" name="fn_out" from_work_dir="output.xlsx"/>
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<collection type="list" name="output" label="Curve fitting on ${on_string}">
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<discover_datasets directory="output" pattern="__name__" format="tsv"/>
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</collection>
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</outputs>
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<tests>
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<test>
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<param name="fn_in" value="spots_linked.xlsx"/>
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<param name="input_list" value="input1.tsv"/>
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<param name="degree" value="2"/>
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<param name="penalty" value="abs"/>
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<param name="alpha" value="0.01"/>
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<output_collection name="output" type="list" count="1">
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<element name="curve1.tsv" value="output1/curve1.tsv" ftype="tsv" compare="diff"/>
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</output_collection>
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</test>
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<test>
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<param name="input_list" value="input1.tsv,input2.tsv"/>
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<param name="degree" value="2"/>
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<param name="penalty" value="abs"/>
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<param name="alpha" value="0.01"/>
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<output name="fn_out" value="curves_fitted.xlsx" ftype="xlsx" compare="sim_size"/>
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<output_collection name="output" type="list" count="2">
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<element name="curve1.tsv" value="output2/curve1.tsv" ftype="tsv" compare="diff"/>
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<element name="curve2.tsv" value="output2/curve2.tsv" ftype="tsv" compare="diff"/>
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</output_collection>
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</test>
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</tests>
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<help>
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**What it does**
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This tool fits (1st- or 2nd-degree) polynomial curves to data points. Optional: Given a significance level, assistive curves will also be generated.
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**Perform curve fitting for lists of intensity values.**
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This tool fits 1st- or 2nd-order polynomial curves to 1-D data points (tabular list of values).
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Optionally, given a significance level, assistive curves are generated.
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</help>
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<citations>
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<citation type="doi">10.1097/j.pain.0000000000002642</citation>

‎tools/curve_fitting/test-data/curves_fitted.xlsx‎

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‎tools/curve_fitting/test-data/input1.tsv‎

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‎tools/curve_fitting/test-data/input2.tsv‎

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‎tools/curve_fitting/test-data/output1/curve1.tsv‎

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frame pos_x pos_y intensity curve curve_a
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‎tools/curve_fitting/test-data/output2/curve1.tsv‎

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‎tools/curve_fitting/test-data/output2/curve2.tsv‎

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‎tools/curve_fitting/test-data/spots_linked.xlsx‎

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