Matrix marking in two passes
Clear Faulty Sensor Lines
01. The question
A zero sensor reading means its entire row and column are faulty. Return a new matrix with those lines zeroed based only on the original zeros. Do not let newly written zeros trigger more clearing.
| r / c | 0 | 1 | 2 |
|---|---|---|---|
| 0 | 4 | 0 | 6 |
| 1 | 7 | 8 | 9 |
| 2 | 1 | 2 | 3 |
Original zero at [0,1] marks row 0 and column 1. Other lines remain intact.
Before revealing the idea, predict the result and describe what information you would need to track.
02. Worked example
Inputreadings = [[4,0,6],[7,8,9],[1,2,3]]
Output[[0,0,0],[7,0,9],[1,0,3]]
- First mark row 0 and column 1 from the original zero.
- Build an output copy.
- Clear only those marked lines; new zeros do not spread.
Try your code
Define solve(data, parameter="") and return your result. Your code runs locally, not on a server.
Edit your test cases
Use 1-10 objects with data and an optional string parameter. Expected outputs are computed from the lesson. An optional expected field must be correct.
Input contract & reference code
Example data: [[4,0,6],[7,8,9],[1,2,3]]. Parameter: "". Numeric parameters arrive as strings; convert them with int(parameter) when needed.
The example and generated cases use the question’s exact variant. This checks behavior on a small test batch—not performance on every possible input.
Python downloads only when you run code, using compressed runtime assets. Code is not saved or uploaded. Enable JavaScript to run it.
Printed output
Five-second execution limit per batch. Standard-library Python only; additional packages and network access are unavailable. Stop ends execution without blocking the lesson.
03. The idea
Try sketching your own approach first. What would you track, and why would it work?
Reveal the idea
- Collect rows and columns containing original zeros.
- Copy the matrix.
- Clear cells whose row or column was marked.
04. Watch it happen
Use Step to move slowly, or Play to follow the whole trace. Change a preset or load your own input.
Input & settings
Red = current item / blue = active window or cells / green = completed work. A value docks at its actual destination; the original input stays unchanged. Positions start at 0.
Working state / what changes
Ready to begin
Enable JavaScript to step through the animation. The worked example and solution below remain readable without it.
Python / why it changes
The line behind the step
def clear_lines(readings):
rows, cols = set(), set()
for r, row in enumerate(readings):
for c, value in enumerate(row):
if value == 0:
rows.add(r)
cols.add(c)
output = [row[:] for row in readings]
for r, row in enumerate(output):
for c in range(len(row)):
if r in rows or c in cols:
output[r][c] = 0
return outputHow to use this walkthrough
Hover or focus a control for its label. Play forms the input and follows values into the working state. Step shows one change; Back and the slider restore exact snapshots. Reduced motion uses instant updates. Saved snapshots and sorted heap displays are teaching overhead, not algorithm complexity.
05. Python solution
def clear_lines(readings):
rows, cols = set(), set()
for r, row in enumerate(readings):
for c, value in enumerate(row):
if value == 0:
rows.add(r)
cols.add(c)
output = [row[:] for row in readings]
for r, row in enumerate(output):
for c in range(len(row)):
if r in rows or c in cols:
output[r][c] = 0
return output06. Cost & edge cases
- Time
- O(RC)
- Space
- O(R + C) markers plus O(RC) output
- No original zeros means no changes.
- Zeroing a line is not a flood fill.
- This copy-output variant does not claim O(1) extra space or in-place behavior.