Complete CSV (Excel File)

[AbdJamali202]

Thank you in advance for your assistance. Is there a Python code using BRAILS that can directly generate a CSV file containing the following columns: Latitude, Longitude, NumberOfStories, Geometry, basement, Occupancy, and Fragility Number?

[rjedwardsss]

Yes! Here's a Python script using BRAILS that generates a CSV with those columns. Note that Fragility Number is not a native BRAILS output, so it needs to be derived in post-processing based on occupancy and number of stories.

from brails.InventoryGenerator import InventoryGenerator

# Initialize and generate inventory
invGenerator = InventoryGenerator(
    location='San Rafael, CA',
    fpSource='usastr',   # Provides Geometry + coordinates
    baselineInv='nsi',   # Provides Basement + Occupancy baseline
    lengthUnit='m'
)

invGenerator.generate(
    attributes=['numstories', 'occupancy'],
    GoogleAPIKey='YOUR_GOOGLE_API_KEY'
)

df = invGenerator.inventory

# Rename columns to match desired schema
df = df.rename(columns={
    'lat': 'Latitude',
    'lon': 'Longitude',
    'numstories': 'NumberOfStories',
    'geometry': 'Geometry',
    'basement': 'Basement',
    'occupancy': 'Occupancy'
})

# Derive Fragility Number (customize to your fragility taxonomy)
def assign_fragility(row):
    occ = str(row.get('Occupancy', '')).upper()
    stories = row.get('NumberOfStories', 1)
    if 'RES' in occ and stories <= 2:
        return 'W1'
    elif 'RES' in occ and stories > 2:
        return 'C1M'
    elif 'COM' in occ:
        return 'S1L'
    else:
        return 'UNK'

df['FragilityNumber'] = df.apply(assign_fragility, axis=1)

# Export to CSV
cols = ['Latitude', 'Longitude', 'NumberOfStories', 'Geometry', 'Basement', 'Occupancy', 'FragilityNumber']
df[cols].to_csv('building_inventory.csv', index=False)

A few things to keep in mind:

• fpSource='usastr' (FEMA USA Structures) gives you the building footprint geometry and coordinates.
• baselineInv='nsi' pulls basement and occupancy data from the National Structure Inventory.
• The assign_fragility function above is a simplified example, so swap in whatever fragility classification scheme (HAZUS, FEMA P-58, etc.) your project requires.
• A Google API Key is needed for imagery-based predictions like numstories and occupancy.

[AbdJamali202]

Thank you for your detailed explanation. My project is based in Canada rather than the United States, so I understand that fpSource='usastr' and baselineInv='nsi' may not be suitable, given that usastr corresponds to FEMA USA Structures and NSI is maintained by the U.S. Army Corps of Engineers for U.S.-specific building inventories.

In this context, would you recommend using fpSource='osm', fpSource='ms', or a user-provided GeoJSON as the most appropriate option for a Canadian study area?

Additionally, is a Google API key strictly required when using InventoryGenerator.generate() to predict attributes such as numstories and occupancy? If so, could you please clarify where it should be created and which services need to be enabled?

Finally, I would appreciate any guidance or example of a workflow adapted to a Canadian context.

Best regards,

[AbdJamali202]

Thank you for your detailed explanation. My project is based in Canada rather than the United States, so I understand that fpSource='usastr' and baselineInv='nsi' may not be suitable, given that usastr corresponds to FEMA USA Structures and NSI is maintained by the U.S. Army Corps of Engineers for U.S.-specific building inventories. In this context, would you recommend using fpSource='osm', fpSource='ms', or a user-provided GeoJSON as the most appropriate option for a Canadian study area? Additionally, is a Google API key strictly required when using InventoryGenerator.generate() to predict attributes such as numstories and occupancy? If so, could you please clarify where it should be created and which services need to be enabled? Finally, I would appreciate any guidance or example of a workflow adapted to a Canadian context. Best regards,

…

________________________________ De : RJ Edwards ***@***.***> Envoyé : dimanche 29 mars 2026 00:10 À : NHERI-SimCenter/SimCenterCommon ***@***.***> Cc : AbdJamali202 ***@***.***>; Author ***@***.***> Objet : Re: [NHERI-SimCenter/SimCenterCommon] Complete CSV (Excel File) (Discussion #369) Yes! Here's a Python script using BRAILS that generates a CSV with those columns. Note that Fragility Number is not a native BRAILS output, so it needs to be derived in post-processing based on occupancy and number of stories. from brails.InventoryGenerator import InventoryGenerator # Initialize and generate inventory invGenerator = InventoryGenerator( location='San Rafael, CA', fpSource='usastr', # Provides Geometry + coordinates baselineInv='nsi', # Provides Basement + Occupancy baseline lengthUnit='m' ) invGenerator.generate( attributes=['numstories', 'occupancy'], GoogleAPIKey='YOUR_GOOGLE_API_KEY' ) df = invGenerator.inventory # Rename columns to match desired schema df = df.rename(columns={ 'lat': 'Latitude', 'lon': 'Longitude', 'numstories': 'NumberOfStories', 'geometry': 'Geometry', 'basement': 'Basement', 'occupancy': 'Occupancy' }) # Derive Fragility Number (customize to your fragility taxonomy) def assign_fragility(row): occ = str(row.get('Occupancy', '')).upper() stories = row.get('NumberOfStories', 1) if 'RES' in occ and stories <= 2: return 'W1' elif 'RES' in occ and stories > 2: return 'C1M' elif 'COM' in occ: return 'S1L' else: return 'UNK' df['FragilityNumber'] = df.apply(assign_fragility, axis=1) # Export to CSV cols = ['Latitude', 'Longitude', 'NumberOfStories', 'Geometry', 'Basement', 'Occupancy', 'FragilityNumber'] df[cols].to_csv('building_inventory.csv', index=False) A few things to keep in mind: * fpSource='usastr' (FEMA USA Structures) gives you the building footprint geometry and coordinates. * baselineInv='nsi' pulls basement and occupancy data from the National Structure Inventory. * The assign_fragility function above is a simplified example, so swap in whatever fragility classification scheme (HAZUS, FEMA P-58, etc.) your project requires. * A Google API Key is needed for imagery-based predictions like numstories and occupancy. — Reply to this email directly, view it on GitHub<#369?email_source=notifications&email_token=BVBRFROI36Y4MQ7B4KSFVMD4TBLXZA5CNFSNUABIM5UWIORPF5TWS5BNNB2WEL2ENFZWG5LTONUW63SDN5WW2ZLOOQXTCNRTGYYTAMJQUZZGKYLTN5XKMYLVORUG64VFMV3GK3TUVRTG633UMVZF6Y3MNFRWW#discussioncomment-16361010>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/BVBRFRNBCHBG642W6OD322D4TBLXZAVCNFSM6AAAAACXDRQT4CVHI2DSMVQWIX3LMV43URDJONRXK43TNFXW4Q3PNVWWK3TUHMYTMMZWGEYDCMA>. You are receiving this because you authored the thread.Message ID: ***@***.***>

[fmckenna]

1. I suggest you try both (OSM, MS) and see which is better for your area of interest.
2. for the google api key if you look at around 24:30 into the following video you will see how to create the google key and what services you have to turn on for the key you create.

video: https://www.youtube.com/watch?v=SS_-OTvZC4Q

[AbdJamali202]

Hello,
I am using BRAILS for a research project.
It works well for a U.S. case study, but not for my project in Canada.

I cannot use usastr or nsi.
I tried using fpSource='osm', but it did not work properly.
I also tried using a GeoJSON file for building footprints, but the results are not correct.

Is there a recommended way to use BRAILS for Canada?
Are there any specific steps or configurations needed?
Thank you very much for your help.

Best regards,
Abdeslam