Merge pull request #1049 from deeptools/develop

Develop- for the 3.5.1 release

Author: LeilyR

.planemo.sh

@@ -28,5 +28,5 @@ else
 fi
 
 planemo lint ${wrappers}
-planemo test --no_dependency_resolution --galaxy_branch release_18.05 --install_galaxy ${wrappers} 2>&1 | grep -v -e "^galaxy" | grep -v -e "^requests"
+planemo test --no_dependency_resolution --galaxy_branch release_20.09 --install_galaxy ${wrappers} 2>&1 | grep -v -e "^galaxy" | grep -v -e "^requests"
 test ${PIPESTATUS[0]} -eq 0

CHANGES.txt

@@ -1,3 +1,14 @@
+3.5.1
+* cmp usage is updated to fit the recent mpl updates.
+* The requirements.txt is updated.
+* "NA" occurences in plotFingerprint.py have been replaced by numpy.NAN (PR #1002)
+* computeMatrixOperations.xml is fixed (brought up in #1003)
+* plotly error is fixed. (issue #1013)
+* relase version is updated in planemo.sh
+* fixed galaxy tests
+* A bug is taken care of in computeMatrixOperations.py / dataRange
+* in plotProfile.py legen location is changed from auto to best (issue #1042)
+
 3.5.0
 
  * Fixed a small issue in computeGCBias (issue #969)

README.md

@@ -2,7 +2,6 @@
 [![Build Status](https://dev.azure.com/dpryan79/dpryan79/_apis/build/status/deeptools.deepTools?branchName=master)](https://dev.azure.com/dpryan79/dpryan79/_build/latest?definitionId=1&branchName=master)
 [![Documentation Status](https://readthedocs.org/projects/deeptools/badge/)](http://deeptools.readthedocs.org/) [![PyPI Version](https://img.shields.io/pypi/v/deeptools.svg?style=plastic)](https://pypi.org/project/deepTools/) 
 [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/deeptools/README.html)
-[![European Galaxy server](https://img.shields.io/badge/usegalaxy-.eu-brightgreen?logo=data:image/png;base64,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)](https://usegalaxy.eu/root?tool_id=deeptools_multi_bam_summary)
 
 ## User-friendly tools for exploring deep-sequencing data
 

deeptools/_version.py

@@ -2,4 +2,4 @@
 # This file is originally generated from Git information by running 'setup.py
 # version'. Distribution tarballs contain a pre-generated copy of this file.
 
-__version__ = '3.5.0'
+__version__ = '3.5.1'

deeptools/bamPEFragmentSize.py

@@ -341,7 +341,7 @@ def main(args=None):
 
         if args.plotFileFormat == 'plotly':
             fig = go.Figure()
-            fig['data'] = data
+            fig.add_traces(data)
             fig['layout']['yaxis1'].update(title='Frequency')
             fig['layout']['xaxis1'].update(title='Fragment Length')
             fig['layout'].update(title=args.plotTitle)

deeptools/computeGCBias.py

@@ -571,7 +571,7 @@ def plotlyGCbias(file_name, frequencies, reads_per_gc, region_size):
     x = np.linspace(0, 1, frequencies.shape[0])
     trace = go.Scatter(x=x, y=np.log2(frequencies[:, 2]), xaxis='x2', yaxis='y2', showlegend=False, line=dict(color='rgb(107,174,214)'))
     data.append(trace)
-    fig['data'] = data
+    fig.add_traces(data)
     fig['layout']['annotations'] = annos
     py.plot(fig, filename=file_name, auto_open=False)
 

deeptools/computeMatrixOperations.py

@@ -73,7 +73,7 @@ def parse_arguments():
         formatter_class=argparse.ArgumentDefaultsHelpFormatter,
         parents=[infoArgs(), relabelArgs()],
         help="Change sample and/or group label information",
-        usage='An example usage is:\n  computeMatrixOperations relabel -m input.mat.gz -o output.mat.gz --samples "sample 1" "sample 2"\n\n')
+        usage='An example usage is:\n  computeMatrixOperations relabel -m input.mat.gz -o output.mat.gz --sampleLabels "sample 1" "sample 2"\n\n')
 
     # subset
     subparsers.add_parser(
@@ -795,10 +795,9 @@ def main(args=None):
     hm = heatmapper.heatmapper()
     if not isinstance(args.matrixFile, list):
         hm.read_matrix_file(args.matrixFile)
-
     if args.command == 'info':
         printInfo(hm)
-    if args.command == 'dataRange':
+    elif args.command == 'dataRange':
         printDataRange(hm)
     elif args.command == 'subset':
         sIdx = getSampleBounds(args, hm)

deeptools/correlation.py

@@ -1,5 +1,6 @@
 import sys
 import itertools
+import copy
 import numpy as np
 import scipy.cluster.hierarchy as sch
 import scipy.stats
@@ -291,7 +292,7 @@ def plot_correlation(self, plot_filename, plot_title='', vmax=None,
                                link_color_func=lambda k: 'darkred')
         axdendro.set_xticks([])
         axdendro.set_yticks([])
-        cmap = plt.get_cmap(colormap)
+        cmap = copy.copy(plt.get_cmap(colormap))
 
         # this line simply makes a new cmap, based on the original
         # colormap that goes from 0.0 to 0.9
@@ -421,7 +422,7 @@ def plotly_scatter(self, plot_filename, corr_matrix, plot_title='', minXVal=None
         data[-1]['colorbar'].update(title="log10(instances per bin)", titleside="right")
         data[-1].update(showscale=True)
 
-        fig['data'] = data
+        fig.add_traces(data)
         fig['layout'].update(title=plot_title, showlegend=False, annotations=annos)
 
         offline.plot(fig, filename=plot_filename, auto_open=False)
@@ -588,7 +589,7 @@ def plotly_pca(self, plotFile, Wt, pvar, PCs, eigenvalues, cols, plotTitle):
         annos.append({'yanchor': 'bottom', 'xref': 'paper', 'xanchor': 'center', 'yref': 'paper', 'text': 'PCA', 'y': 1.0, 'x': 0.25, 'font': {'size': 16}, 'showarrow': False})
         annos.append({'yanchor': 'bottom', 'xref': 'paper', 'xanchor': 'center', 'yref': 'paper', 'text': 'Scree plot', 'y': 1.0, 'x': 0.75, 'font': {'size': 16}, 'showarrow': False})
 
-        fig['data'] = data
+        fig.add_traces(data)
         fig['layout']['annotations'] = annos
         offline.plot(fig, filename=plotFile, auto_open=False)
 

deeptools/correlation_heatmap.py

@@ -6,6 +6,7 @@
 import scipy.cluster.hierarchy as sch
 from matplotlib import rcParams
 import matplotlib.colors as pltcolors
+import copy
 
 rcParams['pdf.fonttype'] = 42
 rcParams['svg.fonttype'] = 'none'
@@ -43,7 +44,7 @@ def plot_correlation(corr_matrix, labels, plotFileName, vmax=None,
                            link_color_func=lambda k: 'darkred')
     axdendro.set_xticks([])
     axdendro.set_yticks([])
-    cmap = plt.get_cmap(colormap)
+    cmap = copy.copy(plt.get_cmap(colormap))
 
     # this line simply makes a new cmap, based on the original
     # colormap that goes from 0.0 to 0.9

deeptools/plotCoverage.py

@@ -320,7 +320,7 @@ def main(args=None):
         # Don't clip plots
         y_max = max(y_max)
         if args.plotFileFormat == "plotly":
-            fig['data'] = data
+            fig.add_traces(data)
             fig['layout']['yaxis1'].update(range=[0.0, min(1, y_max + (y_max * 0.10))])
             fig['layout']['yaxis2'].update(range=[0.0, 1.0])
             py.plot(fig, filename=args.plotFile, auto_open=False)

deeptools/plotEnrichment.py

@@ -440,7 +440,7 @@ def plotEnrichment(args, featureCounts, totalCounts, features):
                 ax.set_ylim(0.0, 100.0)
 
     if args.plotFileFormat == 'plotly':
-        fig['data'] = data
+        fig.add_traces(data)
         py.plot(fig, filename=args.plotFile, auto_open=False)
         # colors
     else:

deeptools/plotFingerprint.py

@@ -202,10 +202,10 @@ def getCHANCE(args, idx, mat):
     """
     # Get the index of the reference sample
     if args.JSDsample not in args.bamfiles:
-        return ["NA", "NA", "NA"]
+        return [np.NAN, np.NAN, np.NAN]
     refIdx = args.bamfiles.index(args.JSDsample)
     if refIdx == idx:
-        return ["NA", "NA", "NA"]
+        return [np.NAN, np.NAN, np.NAN]
 
     subMatrix = np.copy(mat[:, [idx, refIdx]])
     subMatrix[np.isnan(subMatrix)] = 0
@@ -271,10 +271,10 @@ def getJSD(args, idx, mat):
 
     # Get the index of the reference sample
     if args.JSDsample not in args.bamfiles:
-        return "NA"
+        return np.NAN
     refIdx = args.bamfiles.index(args.JSDsample)
     if refIdx == idx:
-        return "NA"
+        return np.NAN
 
     # These will hold the coverage histograms
     chip = np.zeros(MAXLEN, dtype=np.int)
@@ -338,7 +338,7 @@ def signalAndBinDist(x):
 
     if abs(sum(PMFinput) - 1) > 0.01 or abs(sum(PMFchip) - 1) > 0.01:
         sys.stderr.write("Warning: At least one PMF integral is significantly different from 1! The JSD will not be returned")
-        return "NA"
+        return np.NAN
 
     # Compute the JSD from the PMFs
     M = (PMFinput + PMFchip) / 2.0
@@ -430,7 +430,7 @@ def main(args=None):
 
         if args.plotFileFormat == 'plotly':
             fig = go.Figure()
-            fig['data'] = data
+            fig.add_traces(data)
             fig['layout'].update(title=args.plotTitle)
             fig['layout']['xaxis1'].update(title="rank")
             fig['layout']['yaxis1'].update(title="fraction w.r.t bin with highest coverage")

deeptools/plotHeatmap.py

@@ -9,17 +9,17 @@
 matplotlib.use('Agg')
 matplotlib.rcParams['pdf.fonttype'] = 42
 matplotlib.rcParams['svg.fonttype'] = 'none'
-from deeptools import cm  # noqa: F401
 import matplotlib.pyplot as plt
 from matplotlib.font_manager import FontProperties
 import matplotlib.gridspec as gridspec
 from matplotlib import ticker
-
+import copy
 import sys
 import plotly.offline as py
 import plotly.graph_objs as go
 
 # own modules
+from deeptools import cm  # noqa: F401
 from deeptools import parserCommon
 from deeptools import heatmapper
 from deeptools.heatmapper_utilities import plot_single, plotly_single
@@ -371,7 +371,7 @@ def plotlyMatrix(hm,
         trace.update(zmin=zMinUse, zmax=zMaxUse, colorscale=convertCmap(cmap[0], vmin=zMinUse, vmax=zMaxUse))
 
     dataSummary.extend(dataHeatmap)
-    fig['data'] = dataSummary
+    fig.add_traces(dataSummary)
     fig['layout']['annotations'] = annos
     py.plot(fig, filename=outFilename, auto_open=False)
 
@@ -477,7 +477,8 @@ def plotMatrix(hm, outFileName,
     if colorMapDict['colorMap']:
         cmap = []
         for color_map in colorMapDict['colorMap']:
-            cmap.append(plt.get_cmap(color_map))
+            copy_cmp = copy.copy(plt.get_cmap(color_map))
+            cmap.append(copy_cmp)
             cmap[-1].set_bad(colorMapDict['missingDataColor'])  # nans are printed using this color
 
     if colorMapDict['colorList'] and len(colorMapDict['colorList']) > 0:
@@ -529,7 +530,6 @@ def plotMatrix(hm, outFileName,
     else:
         color_list = cmap_plot(np.arange(numgroups) / numgroups)
     alpha = colorMapDict['alpha']
-
     if image_format == 'plotly':
         return plotlyMatrix(hm,
                             outFileName,
@@ -735,7 +735,7 @@ def plotMatrix(hm, outFileName,
                         col = sample
                     ax = fig.add_subplot(grids[-1, col])
                     tick_locator = ticker.MaxNLocator(nbins=3)
-                    cbar = fig.colorbar(img, cax=ax, alpha=alpha, orientation='horizontal', ticks=tick_locator)
+                    cbar = fig.colorbar(img, cax=ax, orientation='horizontal', ticks=tick_locator)
                     labels = cbar.ax.get_xticklabels()
                     ticks = cbar.ax.get_xticks()
                     if ticks[0] == 0:
@@ -759,15 +759,15 @@ def plotMatrix(hm, outFileName,
             grid_start = 0
 
         ax = fig.add_subplot(grids[grid_start:, -1])
-        fig.colorbar(img, cax=ax, alpha=alpha)
+        fig.colorbar(img, cax=ax)
 
     if box_around_heatmaps:
         plt.subplots_adjust(wspace=0.10, hspace=0.025, top=0.85, bottom=0, left=0.04, right=0.96)
     else:
         #  When no box is plotted the space between heatmaps is reduced
         plt.subplots_adjust(wspace=0.05, hspace=0.01, top=0.85, bottom=0, left=0.04, right=0.96)
 
-    plt.savefig(outFileName, bbox_inches='tight', pdd_inches=0, dpi=dpi, format=image_format)
+    plt.savefig(outFileName, bbox_inches='tight', pad_inches=0.1, dpi=dpi, format=image_format)
     plt.close()
 
 

deeptools/plotProfile.py

@@ -99,7 +99,7 @@ def __init__(self, hm, out_file_name,
                  plot_type='lines',
                  image_format=None,
                  color_list=None,
-                 legend_location='auto',
+                 legend_location='best',
                  plots_per_row=8,
                  label_rotation=0,
                  dpi=200):
@@ -454,7 +454,7 @@ def plotly_hexbin(self):
         for trace in data:
             trace.update(zmin=vmin, zmax=vmax)
 
-        fig['data'] = data
+        fig.add_traces(data)
         fig['layout']['annotations'] = annos
         py.plot(fig, filename=self.out_file_name, auto_open=False)
 
@@ -668,7 +668,7 @@ def plotly_heatmap(self):
                 zmaxUse = self.y_max[i % len(self.y_max)]
             trace.update(zmin=zminUse, zmax=zmaxUse)
 
-        fig['data'] = data
+        fig.add_traces(data)
         fig['layout']['annotations'] = annos
         py.plot(fig, filename=self.out_file_name, auto_open=False)
 
@@ -828,15 +828,16 @@ def plotly_profile(self):
         yMin = None
         yMax = None
         for i in range(self.numplots):
-            row = rows - i / self.plots_per_row - 1
+            row = np.floor(i / self.plots_per_row)
+            # row = rows - i / self.plots_per_row - 1
             col = i % self.plots_per_row
             xanchor = 'x{}'.format(i + 1)
             yanchor = 'y{}'.format(i + 1)
             base = row * (domainHeight + bufferHeight)
             domain = [base, base + domainHeight]
             titleY = base + domainHeight
-            base = col * (domainWidth + bufferWidth)
             fig['layout']['yaxis{}'.format(i + 1)] = {'domain': domain, 'title': self.y_axis_label, 'anchor': xanchor, 'autorange': False}
+            base = col * (domainWidth + bufferWidth)
             domain = [base, base + domainWidth]
             titleX = base + 0.5 * domainWidth
             fig['layout']['xaxis{}'.format(i + 1)] = {'domain': domain, 'anchor': yanchor}
@@ -900,7 +901,7 @@ def plotly_profile(self):
                 yRange[1] = self.y_max[i % len(self.y_max)]
             fig['layout'][yaxis].update(range=yRange)
 
-        fig['data'] = data
+        fig.add_traces(data)
         fig['layout']['annotations'] = annos
         py.plot(fig, filename=self.out_file_name, auto_open=False)
 

deeptools/utilities.py

@@ -41,7 +41,7 @@ def convertCmap(c, vmin=0, vmax=1):
     h = 1.0 / 254
     colorScale = []
     for k in range(255):
-        C = map(np.uint8, np.array(cmap(k * h)[:3]) * 255)
+        C = list(map(np.uint8, np.array(cmap(k * h)[:3]) * 255))
         colorScale.append([k * h, 'rgb' + str((C[0], C[1], C[2]))])
 
     return colorScale

galaxy/wrapper/computeMatrixOperations.xml

@@ -74,6 +74,7 @@
             #else if $submodule.command == "dataRange":
                 dataRange
                 -m $submodule.matrixFile
+                > $outFileTxt
             #end if
 ]]>
     </command>
@@ -159,7 +160,6 @@
             <when value="dataRange">
                 <param argument="matrixFile" format="deeptools_compute_matrix_archive" type="data"
                        label="Matrix file from the computeMatrix tool" help=""/>
-                </param>
             </when>
         </conditional>
     </inputs>

galaxy/wrapper/deepTools_macros.xml

@@ -1,10 +1,10 @@
 <macros>
 
     <token name="@THREADS@">--numberOfProcessors "\${GALAXY_SLOTS:-4}"</token>
-    <token name="@WRAPPER_VERSION@">3.5.0.0</token>
+    <token name="@WRAPPER_VERSION@">3.5.1.0</token>
     <xml name="requirements">
         <requirements>
-            <requirement type="package" version="3.5.0">deeptools</requirement>
+            <requirement type="package" version="3.5.1">deeptools</requirement>
             <requirement type="package" version="1.9">samtools</requirement>
         </requirements>
         <expand macro="stdio" />

galaxy/wrapper/test-data/bamPEFragmentSize_result1.txt

@@ -12,7 +12,7 @@ Median: 242.0
 Max.: 251.0
 Std: 4.496912521077347
 MAD: 1.0
-Len. 10%: 241.20000000000002
+Len. 10%: 241.2
 Len. 20%: 241.4
 Len. 30%: 241.6
 Len. 40%: 241.8

galaxy/wrapper/test-data/bamPEFragmentSize_table1.txt

@@ -1,2 +1,2 @@
 	Frag. Sampled	Frag. Len. Min.	Frag. Len. 1st. Qu.	Frag. Len. Mean	Frag. Len. Median	Frag. Len. 3rd Qu.	Frag. Len. Max	Frag. Len. Std.	Frag. Med. Abs. Dev.	Frag. Len. 10%	Frag. Len. 20%	Frag. Len. 30%	Frag. Len. 40%	Frag. Len. 60%	Frag. Len. 70%	Frag. Len. 80%	Frag. Len. 90%	Frag. Len. 99%	Reads Sampled	Read Len. Min.	Read Len. 1st. Qu.	Read Len. Mean	Read Len. Median	Read Len. 3rd Qu.	Read Len. Max	Read Len. Std.	Read Med. Abs. Dev.	Read Len. 10%	Read Len. 20%	Read Len. 30%	Read Len. 40%	Read Len. 60%	Read Len. 70%	Read Len. 80%	Read Len. 90%	Read Len. 99%
-bowtie2 test1.bam	3	241.0	241.5	244.66666666666666	242.0	246.5	251.0	4.496912521077347	1.0	241.20000000000002	241.4	241.6	241.8	243.8	245.6	247.4	249.2	250.82	3	251.0	251.0	251.0	251.0	251.0	251.0	0.0	0.0	251.0	251.0	251.0	251.0	251.0	251.0	251.0	251.0	251.0
+bowtie2 test1.bam	3	241.0	241.5	244.66666666666666	242.0	246.5	251.0	4.496912521077347	1.0	241.2	241.4	241.6	241.8	243.8	245.6	247.4	249.2	250.82	3	251.0	251.0	251.0	251.0	251.0	251.0	0.0	0.0	251.0	251.0	251.0	251.0	251.0	251.0	251.0	251.0	251.0

galaxy/wrapper/test-data/plotFingerprint_quality_metrics.tabular

@@ -1,3 +1,3 @@
 Sample	AUC	Synthetic AUC	X-intercept	Synthetic X-intercept	Elbow Point	Synthetic Elbow Point	JS Distance	Synthetic JS Distance	% genome enriched	diff. enrichment	CHANCE divergence
-bowtie2 test1.bam	0.00493632029863651	0.481650684757865	0.984443061605476	1.1531044350267195e-24	0.9849408836341008	0.5232688298112538	NA	0.26900449806812143	NA	NA	NA
-bowtie2 test1.bam	0.00493632029863651	0.481650684757865	0.984443061605476	1.1531044350267195e-24	0.9849408836341008	0.5232688298112538	0.0	0.26900449806812143	0	0	0
+bowtie2 test1.bam	0.00493632029863651	0.481650684757865	0.984443061605476	1.1531044350267195e-24	0.9849408836341008	0.5232688298112538	nan	0.2690044980681214	nan	nan	nan
+bowtie2 test1.bam	0.00493632029863651	0.481650684757865	0.984443061605476	1.1531044350267195e-24	0.9849408836341008	0.5232688298112538	0.0	0.2690044980681214	0	0	0

galaxy/wrapper/test-data/plotPCA_result2.tabular

@@ -1,4 +1,4 @@
 #plotPCA --outFileNameData
 Component	bowtie2-test1.bam	bowtie2-test1.bam	Eigenvalue
 1	-0.7071067811865476	-0.7071067811865475	4.0
-2	-0.7071067811865475	0.7071067811865476	1.2325951644078315e-32
+2	-0.7071067811865475	0.7071067811865476	2.49319462166397e-32

requirements.txt

@@ -1,9 +1,9 @@
 numpy>=1.9.0
 scipy>=0.17.0
-matplotlib>=3.1.0
+matplotlib>=3.3.0
 pysam>=0.14.0
 py2bit>=0.2.0
 numpydoc>=0.5
 pyBigWig>=0.2.1
-plotly>=2.0.0
+plotly>=4.9
 deeptoolsintervals>=0.1.8