In [34]:
MAX_ROWS = 100000
HISTOGRAM_COLOR = (0.5,0.5,0.5)
ALL_GRAPH_COLOR = (0.2,0.2,0.2)
OUTPUT_FORMAT = 'eps'
REPORT_SIZE = True
FULL_FIG_W , FULL_FIG_H = (19 if REPORT_SIZE else 16) , 8
CHROM_FIG_W, CHROM_FIG_H = FULL_FIG_W, 20
config = {
'data_folder': 'probes',
'RUN' : 'run_BWA_JKL_23_JU_1_orig',
'chromosome' : 'SL2.40ch12',
'scaffold' : 'SL2.40sc04878',
'out_folder' : 'reports'
}
if False:
config['BAC' ] = 'JBPP0904'
config['BAC_coord_start'] = 967164
config['BAC_coord_end' ] = 970727
config['BAC_coord' ] = '%012d-%012d' % ( config['BAC_coord_start'], config['BAC_coord_end' ] )
config['RUN' ] = 'run_BWA_JKL_23_JU_1_orig_PROBES'
BAC_MODE = False
cols_to_plot = [
# Col name limit # ticks
[ "K-mer Coverage" , [0,1] , 5 ],
[ "Sequencing Coverage" , None , 5 ],
[ "Ns" , [0.1,1] , 0 ],
[ "AGP Contig" , [0.1,1] , 0 ],
[ "AGP Gap" , [0.1,1] , 0 ],
[ "AGP Unknown" , [0.1,1] , 0 ],
[ "AGP Other" , [0.1,1] , 0 ],
[ "K-mer Coverage averaged: 500 bp" , [0,None], 2 ],
[ "K-mer Coverage averaged: 2.5 Kbp" , [0,None], 2 ],
[ "K-mer Coverage averaged: 5 Kbp" , [0,None], 2 ],
[ "K-mer Coverage averaged: 50 Kbp" , [0,None], 2 ],
[ "K-mer Coverage averaged: 1 Mbp" , [0,None], 2 ],
[ "K-mer Coverage averaged: 5 Kbp before", [0,None], 2 ],
[ "K-mer Coverage averaged: 5 Kbp after" , [0,None], 2 ]
]
if 'BAC' in config:
BAC_MODE = True
cols_to_plot.insert(2, ['BLAST Coverage', [0, None], 5 ])
print "Column Names"
for col_to_plot in cols_to_plot:
print "\t", col_to_plot[0]
print "Config"
for cfg in sorted(config.keys()):
print "\t%-15s: %s" % (cfg, config[cfg])
## For debugging only
NROWS = 1000
NROWS = 10000
NROWS = None
PARSE_VERBOSE = False
#PARSE_VERBOSE = True
In [2]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import gridspec
import os
from IPython.display import HTML
import operator
#import pylab
#pylab.show()
%pylab inline
pd.set_option('display.notebook_repr_html', True)
#pd.set_option('display.max_columns', 20)
#pd.set_option('display.max_rows', 25)
def addHeader(level, text):
display( HTML('''<h%(level)d>%(text)s</h%(level)d>''' % {'level':level, 'text':text}) )
In [3]:
"""
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.sam.SL2.40sc06147.sam.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.sam.SL2.40sc06147.sam.cov.prop.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.sam.SL2.40sc06147.sam.pos
"""
KmerCoverageFile = "%(data_folder)s/%(RUN)s/S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.%(chromosome)s.sam.%(scaffold)s.sam.cov.prop.cov" % config
SequencingCoverageFile = "%(data_folder)s/mapping/out/S_lycopersicum_chromosomes.fa_S_lycopersicum_chromosomes.pos.%(chromosome)s.pos.cov.%(scaffold)s.cov" % config
AgpContigFile = "%(data_folder)s/agp/S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.contig.agp.cov" % config
AgpGapFile = "%(data_folder)s/agp/S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.gap.agp.cov" % config
AgpOtherFile = "%(data_folder)s/agp/S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.other.agp.cov" % config
AgpUnknownFile = "%(data_folder)s/agp/S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.unknown.agp.cov" % config
NsFile = "%(data_folder)s/Ns/S_lycopersicum_scaffolds.fa_NONE.tab.%(chromosome)s.tab.%(scaffold)s.tab.cov" % config
infiles = [KmerCoverageFile, SequencingCoverageFile,
AgpContigFile, AgpGapFile,
AgpUnknownFile, AgpOtherFile, NsFile]
if BAC_MODE:
"""
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_chromosomes.fa_S_lycopersicum_chromosomes.pos.SL2.40ch12.pos.cov.SL2.40sc05611.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.sam.SL2.40sc05611.sam.cov.prop.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727_Product.fasta.blast.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_scaffolds_from_contigs.2.40.agp.SL2.40sc05611.agp.contig.agp.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_scaffolds_from_contigs.2.40.agp.SL2.40sc05611.agp.gap.agp.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_scaffolds_from_contigs.2.40.agp.SL2.40sc05611.agp.other.agp.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_scaffolds_from_contigs.2.40.agp.SL2.40sc05611.agp.unknown.agp.cov
S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.SL2.40ch12.SL2.40sc05611.JBPP0904_primer.000000967164-000000970727.S_lycopersicum_scaffolds.fa_NONE.tab.SL2.40ch12.tab.SL2.40sc05611.tab.cov
"""
config['in_base_name'] = "%(data_folder)s/%(RUN)s/S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.%(chromosome)s.%(scaffold)s.%(BAC)s_primer.%(BAC_coord)s" % config
KmerCoverageFile = "%(in_base_name)s.S_lycopersicum_chromosomes.fa_S_lycopersicum_scaffolds.sam.%(chromosome)s.sam.%(scaffold)s.sam.cov.prop.cov" % config
SequencingCoverageFile = "%(in_base_name)s.S_lycopersicum_chromosomes.fa_S_lycopersicum_chromosomes.pos.%(chromosome)s.pos.cov.%(scaffold)s.cov" % config
BlastCoverageFile = "%(in_base_name)s_Product.fasta.blast.cov" % config
AgpContigFile = "%(in_base_name)s.S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.contig.agp.cov" % config
AgpGapFile = "%(in_base_name)s.S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.gap.agp.cov" % config
AgpOtherFile = "%(in_base_name)s.S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.other.agp.cov" % config
AgpUnknownFile = "%(in_base_name)s.S_lycopersicum_scaffolds_from_contigs.2.40.agp.%(scaffold)s.agp.unknown.agp.cov" % config
NsFile = "%(in_base_name)s.S_lycopersicum_scaffolds.fa_NONE.tab.%(chromosome)s.tab.%(scaffold)s.tab.cov" % config
infiles = [KmerCoverageFile, SequencingCoverageFile,
BlastCoverageFile, AgpContigFile,
AgpGapFile, AgpUnknownFile,
AgpOtherFile, NsFile]
print "%-22s: %-5s %s" % ( "KmerCoverageFile" , os.path.exists(KmerCoverageFile) , KmerCoverageFile )
print "%-22s: %-5s %s" % ( "SequencingCoverageFile", os.path.exists(SequencingCoverageFile), SequencingCoverageFile )
print "%-22s: %-5s %s" % ( "AgpContigFile" , os.path.exists(AgpContigFile) , AgpContigFile )
print "%-22s: %-5s %s" % ( "AgpGapFile" , os.path.exists(AgpGapFile) , AgpGapFile )
print "%-22s: %-5s %s" % ( "AgpOtherFile" , os.path.exists(AgpOtherFile) , AgpOtherFile )
print "%-22s: %-5s %s" % ( "AgpUnknownFile" , os.path.exists(AgpUnknownFile) , AgpUnknownFile )
print "%-22s: %-5s %s" % ( "NsFile" , os.path.exists(NsFile) , NsFile )
if BAC_MODE:
print "%-22s: %-5s %s" % ( "BlastCoverageFile" , os.path.exists(BlastCoverageFile) , BlastCoverageFile )
print
if not all([os.path.exists(x) for x in infiles]):
print "missing file"
#quit()
else:
print "all files present"
In [4]:
config['out_extension'] = OUTPUT_FORMAT
config['out_bn' ] = "%(out_folder)s/%(out_extension)s/%(RUN)s_%(chromosome)s_%(scaffold)s_prop" % config
config['out_bn_img' ] = "%(out_bn)s.%%s.%(out_extension)s" % config
if BAC_MODE:
config['out_bn' ] = "%(out_folder)s/%(out_extension)s/%(RUN)s_%(chromosome)s_%(scaffold)s_%(BAC)s_%(BAC_coord)s" % config
config['out_bn_img' ] = "%(out_bn)s.%%s.%(out_extension)s" % config
output_files = {
'all_data' : '%(out_bn)s.csv' % config,
'all_data_full' : '%(out_bn)s_full.csv' % config,
'K-mer Coverage Stats' : config['out_bn_img'] % 'K-mer_Coverage_Stats',
'Sequencing Coverage Stats' : config['out_bn_img'] % 'Sequencing_Coverage_Stats',
'K-mer Coverage Distribution' : config['out_bn_img'] % 'K-mer_Coverage_Distribution',
'Sequencing Coverage Distribution': config['out_bn_img'] % 'Sequencing_Coverage_Distribution',
'Gaps Distribution' : config['out_bn_img'] % 'Gaps_Distribution',
'Ns Distribution' : config['out_bn_img'] % 'Ns_Distribution',
'Combined graph' : config['out_bn_img'] % 'Combined_graph'
}
if BAC_MODE:
output_files['BLAST Coverage Stats' ] = config['out_bn_img'] % 'BLAST_Coverage_Stats'
output_files['BLAST Coverage Distribution'] = config['out_bn_img'] % 'BLAST_Coverage_Distribution'
for of in sorted(output_files.keys()):
print "%-32s: %s" % ( of, output_files[of] )
In [5]:
class size_controller(object):
def __init__(self, w, h):
self.w = w
self.h = h
def __enter__(self):
self.o = rcParams['figure.figsize']
rcParams['figure.figsize'] = self.w, self.h
return None
def __exit__(self, type, value, traceback):
rcParams['figure.figsize'] = self.o
col_type_int = np.int64
col_type_flo = np.float64
col_type_str = np.object
col_type_bol = np.int8
In [6]:
col_info = [
[ "Position" , col_type_int ],
[ "K-mer Coverage" , col_type_flo ],
[ "K-mer Coverage averaged: 500 bp" , col_type_flo ],
[ "K-mer Coverage averaged: 2.5 Kbp" , col_type_flo ],
[ "K-mer Coverage averaged: 5 Kbp" , col_type_flo ],
[ "K-mer Coverage averaged: 50 Kbp" , col_type_flo ],
[ "K-mer Coverage averaged: 1 Mbp" , col_type_flo ],
[ "K-mer Coverage averaged: 5 Kbp before", col_type_flo ],
[ "K-mer Coverage averaged: 5 Kbp after" , col_type_flo ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print "\n".join( col_names )
In [7]:
SKIP_ROWS = 1
print KmerCoverageFile
KmerData = pd.read_csv(KmerCoverageFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( KmerData.shape[0], KmerData.shape[1] )
if PARSE_VERBOSE:
print KmerData.head()
In [8]:
col_info = [
[ "Position" , col_type_int ],
[ "Sequencing Coverage" , col_type_int ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [9]:
SKIP_ROWS = 0
print SequencingCoverageFile
SequencingCoverageData = pd.read_csv(SequencingCoverageFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( SequencingCoverageData.shape[0], SequencingCoverageData.shape[1] )
if PARSE_VERBOSE:
print SequencingCoverageData.head()
In [10]:
if BAC_MODE:
addHeader(1,'BLAST')
col_info = [
[ "Position" , col_type_int ],
[ "BLAST Coverage" , col_type_flo ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [11]:
if BAC_MODE:
SKIP_ROWS = 0
print BlastCoverageFile
BlastCoverageData = pd.read_csv(BlastCoverageFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( BlastCoverageData.shape[0], BlastCoverageData.shape[1] )
if PARSE_VERBOSE:
print BlastCoverageData.head()
In [12]:
SKIP_ROWS = 0
In [13]:
col_info = [
[ "Position" , col_type_int ],
[ "AGP Contig" , col_type_bol ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [14]:
print AgpContigFile
AgpContigData = pd.read_csv(AgpContigFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( AgpContigData.shape[0], AgpContigData.shape[1] )
if PARSE_VERBOSE:
print AgpContigData.head()
In [15]:
col_info = [
[ "Position" , col_type_int ],
[ "AGP Gap" , col_type_bol ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [16]:
print AgpGapFile
AgpGapData = pd.read_csv(AgpGapFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( AgpGapData.shape[0], AgpGapData.shape[1] )
if PARSE_VERBOSE:
print AgpGapData.head()
In [17]:
col_info = [
[ "Position" , col_type_int ],
[ "AGP Unknown" , col_type_bol ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [18]:
print AgpUnknownFile
AgpUnknownData = pd.read_csv(AgpUnknownFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( AgpUnknownData.shape[0], AgpUnknownData.shape[1] )
if PARSE_VERBOSE:
print AgpUnknownData.head()
In [19]:
col_info = [
[ "Position" , col_type_int ],
[ "AGP Other" , col_type_bol ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [20]:
print AgpOtherFile
AgpOtherData = pd.read_csv(AgpOtherFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( AgpOtherData.shape[0], AgpOtherData.shape[1] )
if PARSE_VERBOSE:
print AgpOtherData.head()
In [21]:
col_info = [
[ "Position" , col_type_int ],
[ "Ns" , col_type_bol ]
]
col_names=[cf[0] for cf in col_info]
col_types=dict(zip([c[0] for c in col_info], [c[1] for c in col_info]))
if PARSE_VERBOSE:
print col_names
col_types
In [22]:
print NsFile
NsData = pd.read_csv(NsFile, header=None, names=col_names, dtype=col_types, nrows=NROWS, \
skiprows=SKIP_ROWS, verbose=PARSE_VERBOSE, delimiter="\t", comment="#")
print "Loaded %d rows and %d columns" % ( NsData.shape[0], NsData.shape[1] )
if PARSE_VERBOSE:
print NsData.head()
In [23]:
Data = pd.DataFrame(KmerData, copy=True)
Data.combine_first( KmerData )
Data["AGP Contig" ] = AgpContigData[ "AGP Contig" ]
Data["AGP Gap" ] = AgpGapData[ "AGP Gap" ]
Data["AGP Unknown" ] = AgpUnknownData[ "AGP Unknown" ]
Data["AGP Other" ] = AgpOtherData[ "AGP Other" ]
Data["Ns" ] = NsData[ "Ns" ]
Data["Sequencing Coverage"] = SequencingCoverageData["Sequencing Coverage"]
if BAC_MODE:
Data["BLAST Coverage" ] = BlastCoverageData[ "BLAST Coverage" ]
print "Saved %d rows and %d columns" % ( Data.shape[0], Data.shape[1] )
if PARSE_VERBOSE:
print Data.head()
In [24]:
with size_controller(FULL_FIG_W, FULL_FIG_H):
bqc = Data.boxplot(column=["K-mer Coverage",
"K-mer Coverage averaged: 500 bp",
"K-mer Coverage averaged: 2.5 Kbp",
"K-mer Coverage averaged: 5 Kbp",
"K-mer Coverage averaged: 50 Kbp",
"K-mer Coverage averaged: 1 Mbp",
"K-mer Coverage averaged: 5 Kbp before",
"K-mer Coverage averaged: 5 Kbp after"], return_type='dict', rot=45)
plt.setp(bqc['boxes' ], color='black')
plt.setp(bqc['medians' ], color='black')
plt.setp(bqc['whiskers'], color='black')
plt.setp(bqc['fliers' ], color='black')
savefig(output_files['K-mer Coverage Stats'])
In [25]:
with size_controller(FULL_FIG_W, FULL_FIG_H):
bqc = Data.boxplot(column=['Sequencing Coverage'], return_type='dict')
plt.setp(bqc['boxes' ], color='black')
plt.setp(bqc['medians' ], color='black')
plt.setp(bqc['whiskers'], color='black')
plt.setp(bqc['fliers' ], color='black')
savefig(output_files['Sequencing Coverage Stats'])
In [26]:
if BAC_MODE:
addHeader(2,'BLAST Coverage Stats')
with size_controller(FULL_FIG_W, FULL_FIG_H):
bqc = Data.boxplot(column=['BLAST Coverage'], return_type='dict')
plt.setp(bqc['boxes' ], color='black')
plt.setp(bqc['medians' ], color='black')
plt.setp(bqc['whiskers'], color='black')
plt.setp(bqc['fliers' ], color='black')
savefig(output_files['BLAST Coverage Stats'])
In [27]:
with size_controller(FULL_FIG_W, FULL_FIG_H):
hf = Data[ Data["K-mer Coverage"] > 0 ]['Position']
print hf.size
if hf.size > 0:
hs = hf.hist(color=HISTOGRAM_COLOR)
savefig(output_files['K-mer Coverage Distribution'])
In [28]:
with size_controller(FULL_FIG_W, FULL_FIG_H):
hf = Data[ Data["Sequencing Coverage"] > 0 ]['Position']
print hf.size
if hf.size > 0:
hs = hf.hist(color=HISTOGRAM_COLOR)
savefig(output_files['Sequencing Coverage Distribution'])
In [29]:
if BAC_MODE:
addHeader(2,'BLAST Coverage Distribution')
with size_controller(FULL_FIG_W, FULL_FIG_H):
hf = Data[ Data["BLAST Coverage"] > 0 ]['Position']
print hf.size
if hf.size > 0:
hs = hf.hist(color=HISTOGRAM_COLOR)
savefig(output_files['BLAST Coverage Distribution'])
In [30]:
with size_controller(FULL_FIG_W, FULL_FIG_H):
hf = Data[ Data["AGP Gap"] > 0 ]['Position']
print hf.size
if hf.size > 0:
hs = hf.hist(color=HISTOGRAM_COLOR)
savefig(output_files['Gaps Distribution'])
In [31]:
with size_controller(FULL_FIG_W, FULL_FIG_H):
hf = Data[ Data["Ns"] > 0 ]['Position']
print hf.size
if hf.size > 0:
hs = hf.hist(color=HISTOGRAM_COLOR)
savefig(output_files['Ns Distribution'])
In [35]:
SAMPLE_EVERY = 1
while ( Data.shape[0] / SAMPLE_EVERY ) > MAX_ROWS:
SAMPLE_EVERY += 1
print "Original Size %d rows and %d columns" % ( Data.shape[0], Data.shape[1] )
if SAMPLE_EVERY != 1:
print "SAMPLING EVERY %d ROWS" % SAMPLE_EVERY
print "Saving full data to: ", output_files['all_data_full']
Data.to_csv(output_files['all_data_full'], sep='\t', index=False)
DataSampled = Data[::SAMPLE_EVERY]
print "New Size %d rows and %d columns" % ( Data.shape[0], Data.shape[1] )
if PARSE_VERBOSE:
print Data.head()
else:
print "no need to sample"
DataSampled = Data
print "Saving data to :", output_files['all_data']
DataSampled.to_csv(output_files['all_data'], sep='\t', index=False)
In [36]:
num_cols = len(cols_to_plot)
with size_controller(CHROM_FIG_W, CHROM_FIG_H):
if True:
#fig, axes = plt.subplots(nrows=len(cols_to_plot)+2, ncols=1)
plt.subplots_adjust(wspace=0.5, hspace=0.5)
num_extra_rows = 2
num_row_span = 3
if BAC_MODE:
num_extra_rows = 3
num_row_span = 3
num_cols_e = num_cols + (num_extra_rows*num_row_span)
axes = []
axes.append( plt.subplot2grid((num_cols_e,1), (0 , 0), rowspan=num_row_span) )
axes.append( plt.subplot2grid((num_cols_e,1), (num_row_span, 0), rowspan=num_row_span) )
if BAC_MODE:
axes.append( plt.subplot2grid((num_cols_e,1), (num_row_span*2, 0), rowspan=num_row_span) )
for i in xrange ( num_cols - num_extra_rows ):
axes.append( plt.subplot2grid((num_cols_e,1), ((num_extra_rows*num_row_span)+i, 0) ) )
for col_to_plot_i, col_to_plot_info in enumerate(cols_to_plot):
col_to_plot, col_ylim, col_yticks = col_to_plot_info
axis = axes[col_to_plot_i]
DataSampled[col_to_plot].plot(ax=axis, kind='area', stacked=False, color=ALL_GRAPH_COLOR)
axis.set_title(col_to_plot)
if col_ylim is not None:
col_ylim_min, col_ylim_max = col_ylim
if col_ylim_min is not None:
axis.set_ylim( bottom = col_ylim_min )
if col_ylim_max is not None:
axis.set_ylim( top = col_ylim_max )
if col_yticks is not None:
if col_yticks == 0:
axis.set_yticks([])
else:
ylim_min, ylim_max = axis.get_ylim()
ylim_diff = ylim_max - ylim_min
ylim_step = ylim_diff / (col_yticks*1.0)
#print col_to_plot, ylim_min, ylim_max, ylim_diff, ylim_step
axis.set_yticks(np.arange(ylim_min,ylim_max+ylim_step,ylim_step))
savefig(output_files['Combined graph'])
In [ ]:
#%install_ext https://raw.githubusercontent.com/rasbt/python_reference/master/ipython_magic/watermark.py
%reload_ext watermark
%watermark --author "Saulo Aflitos" --date --updated --python --hostname --machine --githash --packages numpy,scipy,matplotlib,pandas,IPython
In [37]:
#http://stackoverflow.com/questions/27934885/how-to-hide-code-from-cells-in-ipython-notebook-visualized-with-nbviewer
#from IPython.display import HTML
HTML('''<script>
code_show=true;
function code_toggle() {
var classes_to_hide = ['div.input', 'div.output_stderr', 'div.output_prompt', 'div.input_prompt', 'div.prompt'];
if (code_show){
for ( var c in classes_to_hide ) {
$(classes_to_hide[c]).hide();
$(classes_to_hide[c]).css('visibility', 'hidden');
}
} else {
for ( var c in classes_to_hide ) {
$(classes_to_hide[c]).show();
$(classes_to_hide[c]).css('visibility', 'visible');
}
}
code_show = !code_show
}
$( document ).ready(code_toggle);
</script>
<form action="javascript:code_toggle()"><input type="submit" value="Click here to toggle on/off the raw code."></form>''')
Out[37]: