def test_generate_report_csv_style(self):
"""Reporting: testing full report w/ csv table data and css file."""
from natcap.invest import reporting
workspace_dir = self.workspace_dir
args = ReportingRegressionTests.generate_base_args()
csv_path = os.path.join(REGRESSION_DATA, 'sample_input',
'sample_csv.csv')
style_path = os.path.join(REGRESSION_DATA, 'sample_input',
'sample_style.css')
args['out_uri'] = os.path.join(workspace_dir, 'report_csv_style.html')
args['elements'][0]['attributes'] = {'class': 'my_class'}
args['elements'][0]['data_type'] = 'csv'
args['elements'][0]['data'] = csv_path
args['elements'][0]['key'] = 'ws_id'
args['elements'][1]['format'] = 'style'
args['elements'][1]['data_src'] = style_path
args['elements'][1]['input_type'] = 'File'
reporting.generate_report(args)
pygeoprocessing.testing.assert_text_equal(
args['out_uri'],
os.path.join(REGRESSION_DATA, 'html_reports',
'report_csv_style.html'))
def test_generate_report_shape_json(self):
"""Reporting: testing full report w/ shape table data and json file."""
from natcap.invest import reporting
workspace_dir = self.workspace_dir
workspace_dir = 'C:/Users/dmf/projects/invest_dev/py36_compatibility/reporting'
args = ReportingRegressionTests.generate_base_args()
shape_path = os.path.join(REGRESSION_DATA, 'sample_input',
'sample_shape.shp')
json_data = "{'key': 0, 'data': {'door' : 1, 'room': 'kitchen'}}"
args['out_uri'] = os.path.join(workspace_dir, 'report_shape_json.html')
args['elements'][0]['data_type'] = 'shapefile'
args['elements'][0]['data'] = shape_path
args['elements'][0]['key'] = 'ws_id'
args['elements'][1]['format'] = 'json'
args['elements'][1]['data_src'] = json_data
args['elements'][1]['input_type'] = 'Text'
reporting.generate_report(args)
print(args['out_uri'])
pygeoprocessing.testing.assert_text_equal(
args['out_uri'],
os.path.join(REGRESSION_DATA, 'html_reports',
'report_shape_json.html'))
def test_generate_report_dict_script(self):
"""Reporting: test full report w/ dict table data and script file."""
from natcap.invest import reporting
workspace_dir = self.workspace_dir
args = ReportingRegressionTests.generate_base_args()
script_path = os.path.join(
REGRESSION_DATA, 'sample_input', 'sample_script.js')
dict_list = [
{'ws_id': 0, 'num_pixels': 47017.0, 'wyield_vol': 50390640.85},
{'ws_id': 1, 'num_pixels': 93339.0, 'wyield_vol': 103843576.83},
{'ws_id': 2, 'num_pixels': 20977.0, 'wyield_vol': 21336791.14}]
args['out_uri'] = os.path.join(
workspace_dir, 'report_dict_script.html')
args['elements'][0]['attributes'] = {'id': 'my_id'}
args['elements'][0]['data_type'] = 'dictionary'
args['elements'][0]['data'] = dict_list
args['elements'][1]['format'] = 'script'
args['elements'][1]['data_src'] = script_path
args['elements'][1]['input_type'] = 'File'
reporting.generate_report(args)
pygeoprocessing.testing.assert_text_equal(
args['out_uri'],
os.path.join(
REGRESSION_DATA, 'html_reports', 'report_dict_script.html'))
def test_generate_report_remove_output(self):
"""Reporting: test full report removes html output if exists."""
from natcap.invest import reporting
workspace_dir = self.workspace_dir
args = ReportingRegressionTests.generate_base_args()
script_path = os.path.join(REGRESSION_DATA, 'sample_input',
'sample_script.js')
dict_list = [{
'ws_id': 0,
'num_pixels': 47017.0,
'wyield_vol': 50390640.85
}, {
'ws_id': 1,
'num_pixels': 93339.0,
'wyield_vol': 103843576.83
}, {
'ws_id': 2,
'num_pixels': 20977.0,
'wyield_vol': 21336791.14
}]
args['out_uri'] = os.path.join(workspace_dir,
'report_test_remove.html')
args['elements'][0]['attributes'] = {'id': 'my_id'}
args['elements'][0]['data_type'] = 'dictionary'
args['elements'][0]['data'] = dict_list
args['elements'][1]['format'] = 'script'
args['elements'][1]['data_src'] = script_path
args['elements'][1]['input_type'] = 'File'
reporting.generate_report(args)
# Run again to make sure output file that was created is removed
reporting.generate_report(args)
regression_path = os.path.join(REGRESSION_DATA, 'html_reports',
'report_dict_script.html')
for source_line, regression_line in itertools.zip_longest(
open(args['out_uri']).readlines(),
open(regression_path).readlines(),
fillvalue=None):
if source_line is None or regression_line is None:
raise AssertionError('Number of lines are unequal.')
# Strip trailing newlines.
self.assertEqual(source_line.rstrip(), regression_line.rstrip())
def _create_results_html(vars_dict):
'''
Creates an HTML file that contains a summary of all harvest totals
for each subregion.
'''
do_batch = vars_dict['do_batch']
if do_batch is True:
basename = os.path.splitext(
os.path.basename(vars_dict['population_csv_uri']))[0]
filename = 'results_page_' + basename + '.html'
elif vars_dict['results_suffix'] is not '':
filename = 'results_page_' + vars_dict['results_suffix'] + '.html'
else:
filename = 'results_page.html'
uri = os.path.join(vars_dict['output_dir'], filename)
recruitment_type = vars_dict['recruitment_type']
Spawners_t = vars_dict['Spawners_t']
H_tx = vars_dict['H_tx']
V_tx = vars_dict['V_tx']
equilibrate_timestep = int(vars_dict['equilibrate_timestep'])
Regions = vars_dict['Regions']
# Set Reporting Arguments
rep_args = {}
rep_args['title'] = "Fisheries Results Page"
rep_args['out_uri'] = uri
rep_args['sortable'] = True # JS Functionality
rep_args['totals'] = True # JS Functionality
total_timesteps = len(H_tx)
# Create Model Run Overview Table
overview_columns = [{
'name': 'Attribute',
'total': False
}, {
'name': 'Value',
'total': False
}]
overview_body = [
{
'Attribute': 'Model Type',
'Value': vars_dict['population_type']
},
{
'Attribute': 'Recruitment Type',
'Value': vars_dict['recruitment_type']
},
{
'Attribute': 'Sex-Specific?',
'Value': ('Yes' if vars_dict['sexsp'] == 2 else 'No')
},
{
'Attribute': 'Classes',
'Value': str(len(vars_dict['Classes']))
},
{
'Attribute': 'Regions',
'Value': str(len(Regions))
},
]
# Create Final Cycle Harvest Summary Table
final_cycle_columns = [{
'name': 'Subregion',
'total': False
}, {
'name': 'Harvest',
'total': True
}]
if vars_dict['val_cont']:
final_cycle_columns.append({'name': 'Valuation', 'total': True})
final_timestep_body = []
for i in range(0, len(H_tx[-1])): # i is a cycle
sub_dict = {}
sub_dict['Subregion'] = Regions[i]
sub_dict['Harvest'] = "%.2f" % H_tx[-1, i]
if vars_dict['val_cont']:
sub_dict['Valuation'] = "%.2f" % V_tx[-1, i]
final_timestep_body.append(sub_dict)
# Create Harvest Time Step Table
timestep_breakdown_columns = [{
'name': 'Time Step',
'total': False
}, {
'name': 'Equilibrated?',
'total': False
}, {
'name': 'Spawners',
'total': True
}, {
'name': 'Harvest',
'total': True
}]
timestep_breakdown_body = []
for i in range(0, total_timesteps):
sub_dict = {}
sub_dict['Time Step'] = str(i)
if i == 0:
sub_dict['Spawners'] = "(none)"
elif recruitment_type == 'Fixed':
sub_dict['Spawners'] = "(fixed recruitment)"
else:
sub_dict['Spawners'] = "%.2f" % Spawners_t[i]
sub_dict['Harvest'] = "%.2f" % H_tx[i].sum()
# This can be more rigorously checked
if equilibrate_timestep and i >= equilibrate_timestep:
sub_dict['Equilibrated?'] = 'Y'
else:
sub_dict['Equilibrated?'] = 'N'
timestep_breakdown_body.append(sub_dict)
# Generate Report
css = """body { background-color: #EFECCA; color: #002F2F; }
h1 { text-align: center }
h1, h2, h3, h4, strong, th { color: #046380 }
h2 { border-bottom: 1px solid #A7A37E }
table { border: 5px solid #A7A37E; margin-bottom: 50px; \
background-color: #E6E2AF; }
table.sortable thead:hover { border: 5px solid #A7A37E; \
margin-bottom: 50px; background-color: #E6E2AF; }
td, th { margin-left: 0px; margin-right: 0px; padding-left: \
8px; padding-right: 8px; padding-bottom: 2px; padding-top: \
2px; text-align: left; }
td { border-top: 5px solid #EFECCA }
img { margin: 20px }"""
elements = [{
'type': 'text',
'section': 'body',
'text': '<h2>Model Run Overview</h2>'
}, {
'type': 'table',
'section': 'body',
'sortable': True,
'checkbox': False,
'total': False,
'data_type': 'dictionary',
'columns': overview_columns,
'data': overview_body
}, {
'type':
'text',
'section':
'body',
'text':
'<h2>Final Harvest by Subregion After ' + str(total_timesteps - 1) +
' Time Steps</h2>'
}, {
'type': 'table',
'section': 'body',
'sortable': True,
'checkbox': False,
'total': True,
'data_type': 'dictionary',
'columns': final_cycle_columns,
'data': final_timestep_body
}, {
'type': 'text',
'section': 'body',
'text': '<h2>Time Step Breakdown</h2>'
}, {
'type': 'table',
'section': 'body',
'sortable': True,
'checkbox': False,
'total': False,
'data_type': 'dictionary',
'columns': timestep_breakdown_columns,
'data': timestep_breakdown_body
}, {
'type': 'head',
'section': 'head',
'format': 'style',
'data_src': css,
'input_type': 'Text'
}]
equilibrium_warning = [{
'type':
'text',
'section':
'body',
'text':
'<h2 style="color:red">Warning: Population Did Not Reach Equilibrium State</h2>'
}]
if not bool(vars_dict['equilibrate_timestep']):
elements = equilibrium_warning + elements
rep_args['elements'] = elements
reporting.generate_report(rep_args)