def ex1():
plt.figure(1)
ax = plt.axes([0, 0, 1, 1])
ax.set_yticks([0, 5])
ax.set_yticklabels(["label yang sangat panjang"])
make_axes_area_auto_adjustable(ax)
def draw_count(c, title, fig_name, out_path):
categories = c.keys()
freq = [max(np.log10(max(c[cat], 0.1)), 0) for cat in categories]
if all([isinstance(cat, str) for cat in categories]) or all(
[isinstance(cat, tuple) for cat in categories]):
categories_rev = [cat[::-1] for cat in categories]
categories_rev = [x for _, x in sorted(zip(freq, categories_rev))]
freq = sorted(freq)
else: # Integers, sort by value
categories_rev = [cat for cat in categories]
freq = [x for _, x in sorted(zip(categories_rev, freq))]
categories_rev = sorted(categories_rev)
xticks = np.arange(int(max(freq)) + 1)
xtick_labels = [np.power(10, t) for t in xticks]
fig, ax = plt.subplots(figsize=(20, 10))
y_pos = np.arange(len(categories))
rects = ax.barh(y_pos, freq, align='center', color='green', ecolor='black')
ax.set_yticks(y_pos)
ax.set_yticklabels(categories_rev)
ax.set_xticks(xticks)
ax.set_xticklabels(xtick_labels)
ax.set_xlabel('מספר מופעים'[::-1])
ax.set_title(title)
make_axes_area_auto_adjustable(ax)
autolabel(rects, ax)
plt.savefig(out_path + '/' + fig_name + '.pdf')
plt.close()
def draw_double_count(c_c, title, fig_name, out_path):
n_bins = int(np.floor(np.log2(max(c_c.keys()))))
categories = ['1'] + \
[str(int(np.power(2, i + 1))) + '-' + str(int(np.power(2, i + 2)) - 1) for i in range(n_bins - 2)] + \
[str(int(np.power(2, n_bins - 1))) + '+']
# For example categories may be ['1', '2-3', '4-7', '8-15', '16-31', '32-63', '64-127', '128+']
y_pos = np.arange(len(categories))
freq = np.zeros(n_bins)
for n in c_c.keys():
b = min(n_bins - 1, int(np.log2(n)))
freq[b] += c_c[n]
freq = [max(np.log10(max(f, 0.1)), 0) for f in freq]
xticks = np.arange(int(max(freq)) + 1)
xtick_labels = [np.power(10, t) for t in xticks]
fig, ax = plt.subplots(figsize=(20, 10))
rects = ax.barh(y_pos, freq, align='center', color='green', ecolor='black')
ax.set_yticks(y_pos)
ax.set_yticklabels(categories)
ax.set_xticks(xticks)
ax.set_xticklabels(xtick_labels)
ax.set_xlabel('מספר מופעים'[::-1])
ax.set_title(title)
make_axes_area_auto_adjustable(ax)
autolabel(rects, ax)
plt.savefig(out_path + '/' + fig_name + '.pdf')
plt.close()
def graph_term_import(df_row, theme_num, word_qty=50):
#INPUT: df_row, a row from the output of pandas_visualization
#INPUT: theme_num, the theme number
#OUPUT: Horizontal Bar Chart of term import in theme
#x is labels, y is values
x = [df_row[i * 2 + 1] for i in range(1, word_qty)]
y = [
float(df_row[i * 2]) if str(df_row[i * 2]) > '0' else 0
for i in range(1, word_qty)
]
x_pos = np.arange(word_qty - 1)
ticks_font = font_manager.FontProperties(style='normal',
size=7,
weight='normal',
stretch='normal')
fig = plt.figure(figsize=(16, 12))
ax = fig.add_subplot(111)
ax.barh(x_pos, y, align='center', alpha=0.4)
ax.set_yticks(x_pos)
ax.set_yticklabels(x)
for label in ax.get_yticklabels():
label.set_fontproperties(ticks_font)
ax.set_xlabel('Word Probability')
ax.set_ylabel('Terms')
ax.set_title('Theme {}'.format(theme_num))
make_axes_area_auto_adjustable(ax)
plt.savefig('visualizations/visualization{}.png'.format(theme_num))
def graph_term_import(df_row, theme_num):
#INPUT: df_row, a row from the output of pandas_visualization
#INPUT: theme_num, the theme number
#OUPUT: Horizontal Bar Chart of term import in theme
#output is limited to 3 top terms.
x = [df_row[i*2] for i in range(0, 3)]
y = [float(df_row[i*2+1]) if str(df_row[i*2]) > '0' else 0 for i in range(0, 3)]
print y, '\n\n\n'
x_pos = np.arange(3)
ticks_font = font_manager.FontProperties(family='Helvetica', style='normal',
size=16, weight='normal', stretch='normal')
fig = plt.figure(figsize = (16,12))
ax = fig.add_subplot(111)
ax.barh(x_pos, y, align='center', alpha=0.4)
ax.set_yticks(x_pos)
ax.set_yticklabels(x)
for label in ax.get_yticklabels():
label.set_fontproperties(ticks_font)
ax.set_xlabel('Correlation')
ax.set_ylabel('Terms')
ax.set_title('Theme {}'.format(theme_num))
make_axes_area_auto_adjustable(ax)
plt.savefig('visualization{}.png'.format(theme_num))
def ex1():
plt.figure(1)
ax = plt.axes([0, 0, 1, 1])
#ax = plt.subplot(111)
ax.set_yticks([0.5])
ax.set_yticklabels(["very long label"])
make_axes_area_auto_adjustable(ax)
def ex1():
plt.figure(1)
ax = plt.axes([0, 0, 1, 1])
#ax = plt.subplot(111)
ax.set_yticks([0.5])
ax.set_yticklabels(["very long label"])
make_axes_area_auto_adjustable(ax)
def test_auto_adjustable():
fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1])
pad = 0.1
make_axes_area_auto_adjustable(ax, pad=pad)
fig.canvas.draw()
tbb = ax.get_tightbbox(fig._cachedRenderer)
assert tbb.x0 == pytest.approx(pad * fig.dpi)
assert tbb.x1 == pytest.approx(fig.bbox.width - pad * fig.dpi)
assert tbb.y0 == pytest.approx(pad * fig.dpi)
assert tbb.y1 == pytest.approx(fig.bbox.height - pad * fig.dpi)
def ex2():
plt.figure(2)
ax1 = plt.axes([0, 0, 1, 0.5])
ax2 = plt.axes([0, 0.5, 1, 0.5])
ax1.set_yticks([0.5])
ax1.set_yticklabels(["label yang sangat panjang"])
ax1.set_ylabel("Y label")
ax2.set_title("Judul")
make_axes_area_auto_adjustable(ax1, pad=0.1, use_axes=[ax1, ax2])
make_axes_area_auto_adjustable(ax2, pad=0.1, use_axes=[ax1, ax2])
def plotFy():
for i in range(0,nTimesteps,100):
fig = plt.figure()
ax = plt.axes([0,0,1,1])
ax.set_color_cycle(palettable.colorbrewer.qualitative.Dark2_8.mpl_colors)
plt.plot(spanLoc,b1Fy[:,i])
plt.xlabel('Span location (m)')
plt.ylabel('Blade 1 - Normal force (N)')
make_axes_area_auto_adjustable(ax)
plt.savefig('B1Fy_t{}.png'.format(i))
plt.close(fig)
def plotTwoTurbineOutput(d1x,d1y,case1Label,d2x,d2y,case2Label,chanName,chanUnit=''):
fig = plt.figure()
ax = plt.axes([0,0,1,1])
ax.set_color_cycle(palettable.colorbrewer.qualitative.Dark2_8.mpl_colors)
plt.plot(d1x,d1y,label=case1Label)
plt.plot(d2x,d2y,label=case2Label)
plt.xlabel('Time (s)')
plt.ylabel('{} ({})'.format(chanName,chanUnit))
plt.legend(loc=0)
make_axes_area_auto_adjustable(ax)
plt.savefig('compare{}_{}_{}.png'.format(case1Label,case2Label,chanName))
plt.close(fig)
def ex2():
plt.figure(2)
ax1 = plt.axes([0, 0, 1, 0.5])
ax2 = plt.axes([0, 0.5, 1, 0.5])
ax1.set_yticks([0.5])
ax1.set_yticklabels(["very long label"])
ax1.set_ylabel("Y label")
ax2.set_title("Title")
make_axes_area_auto_adjustable(ax1, pad=0.1, use_axes=[ax1, ax2])
make_axes_area_auto_adjustable(ax2, pad=0.1, use_axes=[ax1, ax2])
def ex2():
plt.figure(2)
ax1 = plt.axes([0, 0, 1, 0.5])
ax2 = plt.axes([0, 0.5, 1, 0.5])
ax1.set_yticks([0.5])
ax1.set_yticklabels(["very long label"])
ax1.set_ylabel("Y label")
ax2.set_title("Title")
make_axes_area_auto_adjustable(ax1, pad=0.1, use_axes=[ax1, ax2])
make_axes_area_auto_adjustable(ax2, pad=0.1, use_axes=[ax1, ax2])
def plot_unit(distribution, plot_dir, plot_extension, unit):
fig, axes = plt.subplots(figsize=(6.4, 0.85 + len(distribution) / 2))
axes.set(title=unit,
xlabel="aantal studenten",
ylabel="vraag")
for name, marks in distribution:
left = 0
for mark, count in marks:
axes.barh(name, count, left=left, color=f"C{round(float(str(mark).replace(',', '.')))}")
if int(count) > 0:
axes.text(left + int(count) / 2, name, str(mark), verticalalignment="center")
left += count
make_axes_area_auto_adjustable(axes)
filename = os.path.join(plot_dir, f"unit_{unit}.{plot_extension}")
fig.savefig(filename)
plt.close()
return unit, filename
def draw_reference_dist(vals, ax, title):
label = 'כל התיקים'
col = 'green'
freq, rects = draw_durations_dist(vals, ax, label, col)
y_pos = np.arange(n_weeks)
categories = [7 * (i + 1) for i in range(n_weeks)]
ax.set_yticks(y_pos)
ax.set_yticklabels([str(int(2 * c / 7)) + 'w' for c in categories])
xticks = np.arange(int(max(freq)) + 1)
xtick_labels = [np.power(10, t) for t in xticks]
ax.set_xticks(xticks)
ax.set_xticklabels(xtick_labels)
ax.set_xlabel('מספר תיקים פשוטים לפי משך'[::-1])
ax.set_ylabel('משך'[::-1])
ax.set_title(title[::-1])
make_axes_area_auto_adjustable(ax)
draw_utils.autolabel(rects, ax)
return freq
def test2_timeseries(self, boreholeno, compound, datefrom, dateto):
""" Based of matplotlib.plot_date
TEST: Use of ax - one borehole multiple compounds
"""
# Figure 1
from mpl_toolkits.axes_grid1 import make_axes_locatable
from mpl_toolkits.axes_grid1.axes_divider import make_axes_area_auto_adjustable
plt.figure(1)
ax = plt.axes([0, 0, 1, 1])
# ax = plt.subplot(111)
ax.set_yticks([0.5])
ax.set_yticklabels(["very long label"])
make_axes_area_auto_adjustable(ax)
plt.show()
# Figure 2
plt.figure(2)
ax1 = plt.axes([0, 0, 1, 0.5])
ax2 = plt.axes([0, 0.5, 1, 0.5])
ax1.set_yticks([0.5])
ax1.set_yticklabels(["very long label"])
ax1.set_ylabel("Y label")
ax2.set_title("Title")
make_axes_area_auto_adjustable(ax1, pad=0.1, use_axes=[ax1, ax2])
make_axes_area_auto_adjustable(ax2, pad=0.1, use_axes=[ax1, ax2])
# Figure 3
fig = plt.figure(3)
ax1 = plt.axes([0, 0, 1, 1])
divider = make_axes_locatable(ax1)
ax2 = divider.new_horizontal("100%", pad=0.3, sharey=ax1)
ax2.tick_params(labelleft="off")
fig.add_axes(ax2)
divider.add_auto_adjustable_area(use_axes=[ax1],
pad=0.1,
adjust_dirs=["left"])
divider.add_auto_adjustable_area(use_axes=[ax2],
pad=0.1,
adjust_dirs=["right"])
divider.add_auto_adjustable_area(use_axes=[ax1, ax2],
pad=0.1,
adjust_dirs=["top", "bottom"])
ax1.set_yticks([0.5])
ax1.set_yticklabels(["very long label"])
ax2.set_title("Title")
ax2.set_xlabel("X - Label")
return True
def plot_kmer_matrix(self, kmer_matrix):
interval_size = 1
if len(kmer_matrix) > self.max_kmers_to_show:
interval_size = int(
math.ceil(len(kmer_matrix) / self.max_kmers_to_show))
base_sample_names = []
common_prefix = os.path.commonprefix(self.assemblies)
for assembly in self.assemblies:
stripped_assembly = assembly.replace(common_prefix, '').replace(
'/filtered_scaffolds.fasta', '')
base_sample_names.append(os.path.basename(stripped_assembly))
fig, ax = plt.subplots()
ax.matshow(kmer_matrix, cmap=plt.cm.Greys, aspect='auto')
plt.ylabel('Samples')
plt.xlabel('k-mers')
ax.set_yticks(range(len(base_sample_names)))
ax.set_yticklabels(base_sample_names)
make_axes_area_auto_adjustable(ax)
plt.savefig(self.output_filename())
def create_gantt(wps, **config):
# plot config
width = config.get('barwidth', 0.9)
markersize = config.get('markersize', 50)
wp_offset = 1 - config.get('id_first_wp', 1)
show_delivmile = config.get('show_delivmile', True)
collapse_wp = config.get('collapse_wp', False)
fontsize = config.get('fontsize', 10.0)
# pyplot params
plt.rcParams['xtick.bottom'] = plt.rcParams['xtick.labelbottom'] = False
plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
plt.rcParams['font.size'] = fontsize
# find number of displayed lines
disp = 0
for wp in wps:
if collapse_wp:
disp += 1
else:
disp += len(wp['tasks'])
disp += 1 if show_delivmile else 0
disp -= 1
# axis range
max_month = 0 # to be computed
# plot
fig, ax = plt.subplots()
ticks = []
labels = []
wpspace = len(wps)
for i, wp in enumerate(wps):
wpspace_size = 0.5 * wpspace
if collapse_wp:
# WP only
wp_start = min([task[1] for task in wp['tasks']])
wp_end = max([task[2] for task in wp['tasks']])
ticks.append(disp + wpspace_size)
labels.append('WP' + str(i + 1 - wp_offset))
ax.broken_barh([(wp_start - 1, wp_end - wp_start + 1)],
(disp - width / 2.0 + wpspace_size, width),
facecolors=wp['color'])
if wp_end > max_month:
max_month = wp_end + 1
disp -= 1
else:
# tasks
for task in wp['tasks']:
ticks.append(disp + wpspace_size)
labels.append(task[0])
ax.broken_barh([(task[1] - 1, task[2] - task[1] + 1)],
(disp - width / 2.0 + wpspace_size, width),
facecolors=wp['color'])
if task[2] > max_month:
max_month = task[2] + 1
disp -= 1
# deliverables and milestones
if show_delivmile:
ticks.append(disp + wpspace_size)
labels.append('WP' + str(i + 1 - wp_offset) +
' Deliverables and Milestones')
ax.scatter(wp['deliverables'],
[disp + width / 4.0 + wpspace_size] *
len(wp['deliverables']),
s=markersize,
color=wp['color'],
marker="^")
if len(wp['milestones']) > 0:
ax.scatter(wp['milestones'],
[disp - width / 4.0 + wpspace_size] *
len(wp['milestones']),
s=markersize,
color=wp['color'],
marker="d")
disp -= 1
wpspace -= 1
ax.set_yticks(ticks)
ax.set_yticklabels(labels)
ax.set_xticks(range(0, max_month + 1, 6))
ax.set_xticklabels(['M' + str(x) for x in range(0, max_month + 1, 6)])
ax.set_axisbelow(True)
ax.grid(True, axis='x')
make_axes_area_auto_adjustable(ax)
no_eggs = [line for line in uniq_copes.index if line not in uniq_eggs.index]
copes_match = copes[~copes['sample_original_projname'].isin(no_eggs)]
# get the average lat and lon of the samples for each project
lat_lon = copes.groupby('sample_original_projname').agg({
'object_lat': ['mean'],
'object_lon': ['mean']
})
lat_lon = eggs.groupby('sample_original_projname').agg({
'object_lat': ['mean'],
'object_lon': ['mean']
})
fig1, ax1 = plt.subplots()
uniq_copes.plot(kind='barh', ax=ax1)
make_axes_area_auto_adjustable(ax1)
ax1.set_title('All Copepods (mean lat, mean long)')
ax1.set_ylabel('Project Name')
ax1.set_xlabel('# Copepods')
for ii, item in enumerate(uniq_copes.iteritems()):
lat = lat_lon.loc[item[0]]['object_lat']['mean']
lon = lat_lon.loc[item[0]]['object_lon']['mean']
ax1.text(item[1] + 3,
ii + 0.25,
f'({np.round(lat,2)}, {np.round(lon,2)})',
color='blue',
fontweight='bold')
fig1, ax1 = plt.subplots()
uniq_eggs.plot(kind='barh', ax=ax1, color='m')
def axis_on(self):
self.axes.set_axis_on()
make_axes_area_auto_adjustable(self.axes)
===================================
"""
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
from mpl_toolkits.axes_grid1.axes_divider import make_axes_area_auto_adjustable
plt.figure()
ax = plt.axes([0, 0, 1, 1])
ax.set_yticks([0.5])
ax.set_yticklabels(["very long label"])
make_axes_area_auto_adjustable(ax)
###############################################################################
plt.figure()
ax1 = plt.axes([0, 0, 1, 0.5])
ax2 = plt.axes([0, 0.5, 1, 0.5])
ax1.set_yticks([0.5])
ax1.set_yticklabels(["very long label"])
ax1.set_ylabel("Y label")
ax2.set_title("Title")
make_axes_area_auto_adjustable(ax1, pad=0.1, use_axes=[ax1, ax2])
make_axes_area_auto_adjustable(ax2, pad=0.1, use_axes=[ax1, ax2])
with open(options.legend) as f:
labels = f.read().splitlines()
plt.figure()
ax = plt.axes()
weights = zip(*weightList)
if options.non_zero:
weights,feature_names = zip(*[d for d in zip(weights,feature_names) if np.any(np.array(d[0])>options.limit) ])
if options.sort:
sortingmeasure = [np.sum(np.array(d)) for d in weights]
weights,feature_names = zip(*[(x,f) for (s,x,f) in sorted(zip(sortingmeasure,weights,feature_names), key=lambda pair: pair[0],reverse=True)])
width = 1./(len(weightList)+1)
offset = -0.5 * width * (NumberOfWeightFiles-1)
x_pos = 1.0 * np.arange(len(feature_names))
l = ''
for i in xrange(NumberOfWeightFiles):
if len(options.legend) > 0:
l = labels[i]
plt.bar(x_pos+offset, [w[i] for w in weights], color=colors[i],align='center', width=width,log=options.logscale,linewidth=0,label=l)
offset += width
plt.xticks(x_pos, feature_names, rotation='vertical', fontsize=options.fontsize)
plt.legend(prop={'size':6})
make_axes_area_auto_adjustable(ax)
plt.savefig(options.out_file)
