def test_cut_xs_new(self):
df = pd.read_excel(self.f, 'irregular_multiple_panels')
level = 15 # at top
for level in [0, 2, 8, 5, 10, 11, 12, 15, 20]:
xs = df['offset'].values
ys = df['Z'].values
ns = df['roughness_N'].values
ps = df['new_panel'].values
lines = river_tools.cut_xs_new(xs, ys, ns, ps, level)
fig, axes = plt.subplots(2,
sharex=True,
gridspec_kw={
'height_ratios': [1, 3],
'hspace': 0.001
})
river_tools.plot_xs(df, level, fig, axes)
axes[1].plot([np.min(df['offset']),
np.max(df['offset'])], [level, level],
linestyle='--')
for line in lines:
axes[1].plot(line['offset'],
line['Z'],
linewidth=3,
linestyle='--',
label='a')
# axes[1].plot([np.min(df['offset']), np.max(df['offset'])], [level, level], linestyle='--')
plt.legend()
plt.show()
def test_panel_conveyance15(self):
# TODO: need to get this one tested using the testing section for single one
df = pd.read_excel(self.f, 'irregular_multiple_panels')
rows = []
for depth in [15]:
v = river_tools.panel_conveyance(df, depth, 'single')
# rows.append(v[:-1])
df_wet = v[-1]
df_wet.to_csv(
r'C:\Users\Mel.Meng\Documents\GitHub\SewerAnalysis\source\test\river\wet.csv'
)
df_wet['new_panel'] = 0
print('width:', v[3])
fig, axes = plt.subplots(2,
sharex=True,
gridspec_kw={
'height_ratios': [1, 3],
'hspace': 0.001
})
river_tools.plot_xs(df_wet, 'line', fig, axes)
axes[1].plot(df['offset'], df['Z'], linestyle='--')
axes[1].plot([np.min(df['offset']),
np.max(df['offset'])], [depth, depth],
linestyle='--')
plt.show()
self.fail()
def test_plot_xs(self):
csv_path = './test/river/icm/xs.csv'
output_folder = './test/river/icm/tmp'
df = pd.read_csv(csv_path)
xs_name = 'BalzerC_Reach1_4_000'
fig = river_tools.plot_xs(df, xs_name)
out_png = os.path.join(output_folder, '%s.png' % 'test')
fig.savefig(out_png)
self.fail()
def test_batch_print(self):
csv_path = './test/river/icm/xs_sample_csv_export/xs_sample_cross_section_survey_section_array.csv'
output_folder = './test/river/icm/tmp'
xs_list = river_tools.read_icm_cross_section_survey_section_array_csv(
csv_path)
xs_list = river_tools.icm_xs_add_offset(xs_list)
for k in xs_list:
out_csv = os.path.join(output_folder,
'%s.csv' % str(k).replace('.', '_'))
xs_list[k].to_csv(out_csv, index_label='no')
fig = river_tools.plot_xs(xs_list[k], k)
out_png = os.path.join(output_folder,
'%s.png' % str(k).replace('.', '_'))
fig.savefig(out_png)
self.fail('check output folder for batch conversions')
def test_cut_cross_section_line(self):
csv_path = './test/river/icm/xs.csv'
output_folder = './test/river/icm/tmp'
df = pd.read_csv(csv_path)
river_tools.plot_xs(df, 'line')
plt.show()
xs = df['offset'].values
ys = df['Z'].values
ns = df['roughness_N'].values
ps = df['new_panel'].values
all_checks = {
311.8: [{
'sta': 4.42043478377046,
'width': 105.24753803024845
}, {
'sta': 142.78310982485263,
'width': 10.481538460915516
}, {
'sta': 192.5851427915494,
'width': 3.1768285709524093
}],
312: [{
'sta': 20.44083333254138,
'width': 105.24753803024845
}, {
'sta': 142.78310982485263,
'width': 10.481538460915516
}, {
'sta': 192.5851427915494,
'width': 3.1768285709524093
}],
311.6: [{
'sta': 20.44083333254138,
'width': 105.24753803024845
}, {
'sta': 142.78310982485263,
'width': 10.481538460915516
}, {
'sta': 192.5851427915494,
'width': 3.1768285709524093
}]
}
for level in [
# 311.8, # higher than righ
# 312, # higher than both left and right
311.6
]: # below than both sides
checks = all_checks[level]
lines = river_tools.cut_cross_section(xs, ys, ns, ps, level)
fig, axes = plt.subplots(2,
sharex=True,
gridspec_kw={
'height_ratios': [1, 3],
'hspace': 0.001
})
axes[1].plot(df['offset'], df['Z'])
axes[1].plot([np.min(df['offset']),
np.max(df['offset'])], [level, level])
for idx, line in enumerate(lines):
df2 = pd.DataFrame(
line, columns=['offset', 'Z', 'roughness_N', 'new_panel'])
river_tools.plot_xs(df2, 'line', fig, axes)
plt.show()