def show_info(self):
"""Show usage text to the user."""
header = html_header()
footer = html_footer()
string = header
heading = m.Heading(self.tr('Shakemap Grid Importer'), **INFO_STYLE)
body = self.tr(
'This tool will convert an earthquake \'shakemap\' that is in '
'grid xml format to a GeoTIFF file. The imported file can be used '
'in InaSAFE as an input for impact functions that require and '
'earthquake layer. To use this tool effectively:')
tips = m.BulletedList()
tips.add(self.tr('Select a grid.xml for the input layer.'))
tips.add(self.tr('Choose where to write the output layer to.'))
tips.add(
self.
tr('Choose the interpolation algorithm that should be used when '
'converting the xml grid to a raster. If unsure keep the default.'
))
tips.add(
self.
tr('If you want to obtain shake data you can get it for free from '
'the USGS shakemap site: '
'http://earthquake.usgs.gov/earthquakes/shakemap/list.php?y=2013'
))
message = m.Message()
message.add(heading)
message.add(body)
message.add(tips)
string += message.to_html()
string += footer
self.webView.setHtml(string)
def show_info(self):
"""Show usage info to the user."""
# Read the header and footer html snippets
header = html_header()
footer = html_footer()
string = header
heading = m.Heading(self.tr('Impact Layer Merge Tool'), **INFO_STYLE)
body = self.tr(
'This tool will merge the outputs from two impact maps for the '
'same area. The maps must be created using the same aggregation '
'areas and same hazard. To use:')
tips = m.BulletedList()
tips.add(
self.tr(
'Run an impact assessment for an area using aggregation. e.g.'
'Flood Impact on Buildings aggregated by municipal boundaries.'
))
tips.add(
self.
tr('Run a second impact assessment for the same area using the same '
'aggregation. e.g. Flood Impact on People aggregated by '
'municipal boundaries.'))
tips.add(
self.
tr('Open this tool and select each impact layer from the pick lists '
'provided below.'))
tips.add(
self.tr(
'Select the aggregation layer that was used to generate the '
'first and second impact layer.'))
tips.add(self.tr('Select an output directory.'))
tips.add(
self.
tr('Check "Use customized report template" checkbox and select the '
'report template file if you want to use your own template. Note '
'that all the map composer components that are needed must be '
'fulfilled.'))
tips.add(
self.tr('Click OK to generate the per aggregation area combined '
'summaries.'))
message = m.Message()
message.add(heading)
message.add(body)
message.add(tips)
string += message.to_html()
string += footer
self.web_view.setHtml(string)
def show_info(self):
"""Show usage info to the user."""
# Read the header and footer html snippets
header = html_header()
footer = html_footer()
string = header
heading = m.Heading(self.tr('OSM Downloader'), **INFO_STYLE)
body = self.tr(
'This tool will fetch building (\'structure\') data from the '
'OpenStreetMap project for you. The downloaded data will have '
'InaSAFE keywords defined and a default QGIS style applied. To '
'use this tool effectively:')
tips = m.BulletedList()
tips.add(
self.
tr('Use QGIS to zoom in to the area for which you want building data '
'to be retrieved.'))
tips.add(
self.
tr('Check the output directory is correct. Note that the saved '
'dataset will be called buildings.shp (and its associated files).'
))
tips.add(
self.
tr('If a dataset already exists in the output directory it will be '
'overwritten.'))
tips.add(
self.
tr('This tool requires a working internet connection and fetching '
'buildings will consume your bandwidth.'))
tips.add(
m.Link(
'http://www.openstreetmap.org/copyright',
text=self.tr(
'Downloaded data is copyright OpenStreetMap contributors'
' (click for more info).')))
message = m.Message()
message.add(heading)
message.add(body)
message.add(tips)
string += message.to_html()
string += footer
self.webView.setHtml(string)
def update_warning(self):
"""Update warning message and enable/disable Ok button."""
if len(self.warning_text) == 0:
self.button_box.button(QDialogButtonBox.Ok).setEnabled(True)
return
header = html_header()
footer = html_footer()
string = header
heading = m.Heading(self.tr('Shakemap Grid Importer'), **INFO_STYLE)
tips = m.BulletedList()
self.button_box.button(QDialogButtonBox.Ok).setEnabled(False)
message = m.Message()
message.add(heading)
for warning in self.warning_text:
tips.add(warning)
message.add(tips)
string += message.to_html()
string += footer
self.webView.setHtml(string)
def show_info(self):
"""Show basic usage instructions."""
header = html_header()
footer = html_footer()
string = header
heading = m.Heading(self.tr('Minimum Needs Calculator'), **INFO_STYLE)
body = self.tr(
'This tool will calculated minimum needs for evacuated people. To '
'use this tool effectively:')
tips = m.BulletedList()
tips.add(
self.
tr('Load a polygon layer in QGIS. Typically the layer will '
'represent administrative districts where people have gone to an '
'evacuation center.'))
tips.add(
self.
tr('Ensure that the layer has an INTEGER attribute for the number of '
'displaced people associated with each feature.'))
tips.add(
self.
tr('Use the pick lists below to select the layer and the population '
'field and then press \'OK\'.'))
tips.add(
self.
tr('A new layer will be added to QGIS after the calculation is '
'complete. The layer will contain the minimum needs per district '
'/ administrative boundary.'))
message = m.Message()
message.add(heading)
message.add(body)
message.add(tips)
string += message.to_html()
string += footer
self.webView.setHtml(string)
def check_memory_usage(buffered_geo_extent, cell_size):
"""Helper to check if analysis is feasible when extents change.
For simplicity, we will do all our calculations in geocrs.
:param buffered_geo_extent: An extent in the for [xmin, ymin, xmax, ymax]
:type buffered_geo_extent: list
:param cell_size: The size of a cell (assumes in the X direction).
:type cell_size: float
:returns: True if it appears we have enough memory (or we can't compute
it), False if it appears we do not have enough.
:rtype: bool
:raises: A Message containing notes about how much memory is needed
for a single raster and if this is likely to result in an error.
:returns: True if it is supposed that there is sufficient memory,
False if it is supposed that too little memory exists.
:rtype: bool
"""
message = m.Message()
check_heading = m.Heading(tr('Checking available memory'),
**PROGRESS_UPDATE_STYLE)
message.add(check_heading)
width = buffered_geo_extent[2] - buffered_geo_extent[0]
height = buffered_geo_extent[3] - buffered_geo_extent[1]
try:
# noinspection PyAugmentAssignment
width = width / cell_size
# noinspection PyAugmentAssignment
height = height / cell_size
except TypeError:
# Could have been a vector layer for example
reason = tr(
'Computed cellsize was None. Memory check currently only works '
'for raster input layers.')
message.add(reason)
send_message(message)
return True # assume enough mem since we have no vector check logic
bullet_list = m.BulletedList()
bullet = m.Paragraph(m.ImportantText(tr('Width: ')), str(width))
bullet_list.add(bullet)
bullet = m.Paragraph(m.ImportantText(tr('Height: ')), str(height))
bullet_list.add(bullet)
bullet = m.Paragraph(m.ImportantText(tr('Cell Size: ')), str(cell_size))
bullet_list.add(bullet)
message.add(bullet_list)
# Compute mem requirement in MB (assuming numpy uses 8 bytes by per
# cell) see this link:
# http://stackoverflow.com/questions/11784329/
# python-memory-usage-of-numpy-arrays
# Also note that the on-disk requirement of the clipped tifs is about
# half this since the tifs as in single precision,
# whereas numpy arrays are in double precision.
requirement = ((width * height * 8) / 1024 / 1024)
try:
free_memory = get_free_memory()
except ValueError:
error_heading = m.Heading(tr('Memory check error'), **WARNING_STYLE)
error_message = tr('Could not determine free memory')
message.add(error_heading)
message.add(error_message)
send_message(message)
LOGGER.exception(message)
return True # still let the user try to run their analysis
# We work on the assumption that if more than 10% of the available
# memory is occupied by a single layer we could run out of memory
# (depending on the impact function). This is because multiple
# in memory copies of the layer are often made during processing.
warning_limit = 10
usage_indicator = (float(requirement) / float(free_memory)) * 100
counts_message = tr('Memory requirement: about %d mb per raster layer ('
'%d mb available)') % (requirement, free_memory)
usage_message = tr('Memory used / available: %d/%d') % (usage_indicator,
warning_limit)
message.add(counts_message)
message.add(usage_message)
if warning_limit <= usage_indicator:
warning_heading = m.Heading(tr('Potential memory issue'),
**WARNING_STYLE)
warning_message = tr(
'There may not be enough free memory to run this analysis. You can'
' attempt to run the analysis anyway, but note that your computer '
'may become unresponsive during execution, and / or the analysis '
'may fail due to insufficient memory. Proceed at your own risk.')
suggestion_heading = m.Heading(tr('Suggestion'), **INFO_STYLE)
suggestion = tr(
'Try zooming in to a smaller area or using a raster layer with a '
'coarser resolution to speed up execution and reduce memory '
'requirements. You could also try adding more RAM to your '
'computer.')
message.add(warning_heading)
message.add(warning_message)
message.add(suggestion_heading)
message.add(suggestion)
send_message(message)
LOGGER.info(message.to_text())
return False
send_message(message)
LOGGER.info(message.to_text())
return True
