Updating script following instructions for improved display and ITF cleanup

I need to implement several updates based on the user's instructions. First, the totals display needs adjustments, including keeping the Totals Fair Line for pricing and adding the Most Likely Exact and Most Likely Zone calculations. The cluster projection will shift to the debug context. The ITF branches also need explicit updates.

Fixing display semantics and ITF branches

The user requested both display updates and ITF fixes, so I need to address both. Some files already show missing pieces, like tables and thresholds used in _calGetTables and _detectBimodalSkill. The ITF branches could be added where the default thresholds block, using reasonable parameters. I also need to add the ORP confidence scalar to fix the _adjustStatsByOppQuality. I’ll be careful not to break anything while implementing these updates.

Setting ITF thresholds and calibration table handling

For the ITF threshold in _detectBimodalSkill, I’ll lower it to 0.072 or 0.070 as they requested a more sensitive approach. I think 0.072 works best. As for the _calGetTables, since there aren’t empirical ITF tables, I’ll use CH tables but label them clearly, noting that ITF uses CH tables intentionally.

Defining ITF tables and adding branches

I’ll define ITF tables as clones of CH tables, labeled distinctly to make it clear they aren't identical to ITF tables. We can adjust them later if needed. For now, we’ll set variables like _calRankITF to reference _calRankCH to keep things consistent, but explicit. I’ll also add ITF branches where necessary, like in _mismatchIdxFromSeeds and _pickTaperSeedA. For _markovEffectiveHolds, I’ll tweak the floor/range settings for ITF based on volatility.

Setting ITF values and display fixes

For ITF, I’m considering values like 0.032 for coinflip, 0.11 for weakDir, and 0.63 for blendS. I’ll adjust _adjustStatsByOppQuality with a base of 0.79 and range 0.33 since ITF is noisier. I’ll also update thresholds for getTotalsPick and _winnerDecision, making them more conservative. The display updates will focus on analyzing and fixing the output block, starting with analyzeHook. I’ll search for key strings to implement everything carefully.

{"queries":["Update my script following the instructions and send the updated script as a downloadable txt link.","analyzeHook()","totPmfTopStr","_totMode","Totals Fair Line","getTotalsPick() ITF","function getTotalsPick","Most Likely Ending"],"source_filter":["files_uploaded_in_conversation"]}

Searching for functions and thresholds

I already have snippets for analyzeHook and PMF, but I need more for other functions like getTotalsPick, _winnerDecision, and _mismatchIdxFromSeeds. I’ll search for those specifically, along with thresholds like strongEdge, leanEdge, and ITF branches. I’m planning to modify the code using regex to ensure accurate edits.

{"queries":["function getTotalsPick(","getTotalsPick(","strongEdge","diffGap","function winnerDecision(","dogMinProb","minPrimary","sdThreshold"],"source_filter":["files_uploaded_in_conversation"]}

Refining search for function details

The previous search didn’t find the getTotalsPick function chunk, so it might be located farther in the code. I'll refine the query by searching using just "getTotalsPick" and other related terms like "Totals pick thresholds," "leanEdge," and "dogMinEdge" to find the needed sections.

{"queries":["getTotalsPick","getTotalsPick thresholds","leanEdge getTotalsPick","dogMinEdge","highConfidenceCeiling","minPrimary =","minLean ="],"source_filter":["files_uploaded_in_conversation"]}

Refining search for specific function names

The search still didn’t return relevant results for getTotalsPick, so it might be named differently in earlier versions, like getTotalsPick_Exact. I'll narrow down the search using terms like “TotalsPick,” “totalsDecision,” and “thin-edge” to get more accurate results.

{"queries":["getTotalsPick(","getTotalsPick totalsDecision","thin-edge PASS gate in getTotalsPick","function getTotalsPick","totalsDecision =","getTotalsPick() returns"],"source_filter":["files_uploaded_in_conversation"]}

Refining search for function definitions

I found a reference to getTotalsPick being used, but not its definition. It's probably defined earlier in the file, so I’ll search for "function getTotalsPick," though the results are still unhelpful. It might be defined differently, like var getTotalsPick = function. I’ll adjust the search and try that.

{"queries":["getTotalsPick =","getTotalsPick=function","getTotalsPick (pOver","getTotalsPick(pOver","function getTotalsPick","getTotalsPick(pOverEval"],"source_filter":["files_uploaded_in_conversation"]}

Identifying winner decision functions

I’ve found part of the getTotalsPick function, but we’ll likely need to adjust it for ITF thresholds. The user mentioned only WTA and CH branches, but maybe it already includes ITF in the current code. I’ll inspect that later. For now, I need to search for _winnerDecision to explore possible fallback branches for ITF.

{"queries":["function _winnerDecision","_winnerDecision(","dogMinProb","dogMinEdge","highConfidenceCeiling","leanDogMin","minPrimary tourKey"],"source_filter":["files_uploaded_in_conversation"]}

Looking for _winnerDecision function definition

The search didn’t return the definition for _winnerDecision, so it might be too far in the file or the queries didn’t capture it well. I’ll try again with a more targeted query, focusing on _winnerDecision_ in quotes to narrow it down. Let's see what we get this time.

{"queries":["function winnerDecision","winnerDecision({","winnerDecision policy thresholds","trueWinner","bestBettingSide","classification === "LIVE_DOG""],"source_filter":["files_uploaded_in_conversation"]}

Exploring winnerDecision function for ITF branches

I found a pointer to the _winnerDecision_ definition at chunk 7:10, but I’ll need the full function to check ITF branches and thresholds. I’ll use a file search to explore that part in more detail—maybe search using “7:10” so I can precisely locate it. Let’s proceed with that.

{"pointers":["7:10","7:14","5:15","4:11"]}

Implementing user requested script updates

Based on the user's uploaded file, I need to update the script with fixes for display semantics and ITF threshold branches. This includes clarifying totals and near-line mass for half-lines, while also addressing the instructions for ITF branches like winnerDecision and getTotalsPick. I’ll make these changes and provide the updated script as a downloadable link.

Updating the script using uploaded file

The plan is to load the file into Python to locate the necessary functions and blocks for modifications. I'll first search for the analyzeHook() function definition, then look for the section where the totals output block is built, specifically looking for strings related to "Totals Fair Line" or other references to "fair line."

Implementing the new fields for output

We’ll add the following fields to the output:

• Keep "Totals Fair Line" and the existing "Expected Total."
• Add "Most Likely Ending" with "Most Likely Exact" and "Most Likely Zone". To compute the Most Likely Zone, we’ll calculate the best contiguous window around the mode, selecting a 3 or 5-game window based on the PMF. I'll create a helper function to do this efficiently.

Implementing near-line mass and ITF fixes

We’ll compute a wider local band around the market line, possibly with a width of 3 or 5. For near-line mass on half-lines, we’ll look at the probability of floor plus ceiling. In the analyzeHook, we’ll ensure it computes near-line mass both for exact hits and adjusted ranges for half lines. Additionally, we'll add ITF fixes, incorporating explicit branches in the relevant functions.

Adjusting ITF branches and thresholds

We’ll incorporate explicit ITF branches where needed, like in threshold blocks and ORP confidence in adjustStatsByOppQuality. For calGetTables, we’ll either use existing CH tables or create ITF-specific ones as placeholders until we have data. For detectBimodalSkill, we'll implement a lower flag threshold for ITF, likely 0.072.

Adjusting ITF-specific thresholds

We’ll set ITF-specific thresholds, like 0.50 for the floor and 0.28 for range, to handle volatility more accurately. For the mismatch index, ITF will be recognized earlier, using a floor of 0.50 and range of 0.28. In taper seed selection, ITF’s coinflip and blend values will be closer to CH.

Adjusting thresholds for ITF in decision functions

The function winnerDecision has variables like _cgIsItf but not yet used. We’ll look for key thresholds like "minPrimary" to incorporate ITF-specific adjustments, possibly closely mirroring CH but allowing for more volatility. We’ll identify and modify relevant sections in large functions, starting with winnerDecision and getTotalsPick().

from pathlib import Path, PurePosixPath path = Path("/mnt/data/Tennislocks_V17.4_Cluster_Governor_v17.4.7_UPDATED.txt") text = path.read_text(encoding="utf-8", errors="replace") len(text), text[:2000]

Locating analyzeHook function definition

The text is about 900k characters long, so I'll use search to help locate specific function definitions more efficiently. First step: find the definition of the analyzeHook function. This will allow me to focus on relevant parts of the code for the task at hand.

import re, textwrap def find_snippet(pattern, start=0, context=400): m = re.search(pattern, text[start:], re.MULTILINE) if not m: return None idx = start + m.start() return idx, text[idx-context:idx+context] res = find_snippet(r"function\s+analyzeHook\s*(", context=600) res[0] if res else None

idx, snippet = res print(snippet)

Reviewing analyzeHook function

I found the analyzeHook function in the file, but now I need to update it. Specifically, I need to include near-line mass on half-lines and other adjustments. To do that, I should now examine the rest of the analyzeHook function to understand how to integrate these changes seamlessly.

extract full analyzeHook function content by locating braces

def extract_function(name): # find "function name(" m = re.search(r"function\s+"+re.escape(name)+r"\s*(", text) if not m: return None start = m.start() # find opening brace after this brace_start = text.find("{", m.end()) if brace_start==-1: return None depth=0 for i in range(brace_start, len(text)): if text[i]=="{": depth+=1 elif text[i]=="}": depth-=1 if depth==0: end=i+1 return start, end, text[start:end] return None

start,end,func = extract_function("analyzeHook") print(func[:1500]) print("...tail...\n", func[-500:])

Updating analyzeHook to include near-line mass

The current analyzeHook function is simple, returning over/under/push/hookValue. I'll keep these fields to avoid breaking the script and add new ones like exactLowProb, exactHighProb, nearMass, and bandMass. Since the output expects specific fields, I'll consider adding a new function for the near-line mass, keeping analyzeHook internal, while updating the output to reflect changes like exact hits. So, exact hits will be based on adjacent probabilities for half-lines.

Clarifying analyzeHook behavior and discrepancies

It seems like the previous version of analyzeHook was designed to measure exact probabilities for whole lines, not half-lines like with P(23) and P(24). Currently, the function can't handle push for half-lines, and it doesn't calculate values like P(23). This suggests analyzeHook might only handle whole lines, and another function might handle calculations for half-lines. It’s not matching their description yet.

search for analyzeHook usage

uses = [m.start() for m in re.finditer(r"\banalyzeHook(", text)] len(uses), uses[:10], uses[-1]

Inspecting analyzeHook usage

I see that analyzeHook is used three times: once at the definition, and twice in calls at 815363 and 818160. I need to inspect the code around these lines to understand its behavior and how it's being applied. This will help identify any potential issues or areas to update.

for pos in uses[1:]: print("\n--- usage at", pos, "---") print(text[pos-300:pos+600])

Adjusting analyzeHook to include new fields

analyzeHook originally computed over/under/push values, but their note on P(23) etc. suggests a different "hook readout." We can update analyzeHook to compute extra fields like exactProbBelow, exactProbAbove, nearMass, etc., and adjust output to reflect these changes. For half-lines, this would involve calculating adjacent probabilities, while whole lines could use the exact value.

Defining bands and near-mass on half-lines

For near mass around whole lines, we could calculate it as P(line-1) + P(line) + P(line+1). But since the instructions focus on half-lines, we’ll implement bands for those, such as 22-24 or 23-25 for 23.5. We’ll compute both, then display the one with the higher mass or show them together for clarity.

Computing local band mass and adjusting output

We'll compute two possible 3-game windows around half-line: 22-24 and 23-25, then pick the one with the larger mass for the localBandMass. For the 5-game band, we’ll try two options [floor-2 .. ceil+2] and choose the best. I'll also adjust the output to remove cluster projections and focus on totals. We'll locate and modify the output lines related to totals.

find occurrences of totPmfTopStr

occ = [m.start() for m in re.finditer(r"totPmfTopStr", text)] len(occ), occ[:5]

for pos in occ: print("\n-- around", pos, "--") print(text[pos-500:pos+800])

Adding "Most Likely Ending" and modifying output

I see that the "totPmfTopStr" is built but not currently used. I’ll insert it into the output at the right spot and add the "Most Likely Ending" with the mode and zone. I'll adjust the output to show “Totals Expected” first, followed by mean/median, and then display the most likely ending after that. I'll isolate the totals output section around 811500-813000 for precise updates.

section_start = 810800 section_end = 814000 print(text[section_start:section_end][:5000])

Tweaking output order with most likely ending and mode/zone

The totals context lines are already printed, so I’ll insert the "Most Likely Ending" after the expected total. The "totPmfTopStr" is computed later, but I can print it after calculating the mode and zone. The mode also needs to be computed right after the totPmfTopStr while fixing any weird indentation. I’ll adjust the code around that section to insert new lines after these parts are computed.

Computing zone mass for best PMF zone

I need to stay within the same function where the lines array is, and I think I’ll create a helper function computeTotalsMostLikelyZone(pmf). Since we’re working with a distribution adjusted after correction, we can compute zone mass from that. I'll implement a function to scan the full PMF for the best contiguous zone.

Defining helper function for PMF map and updating output

I'll create a helper function that takes a PMF map and returns the lower and upper bounds along with the mass. We’ll use it for both the totals mode and the near-line mass. We'll also resolve the "Most Likely Exact" and "Most Likely Zone" outputs. Finally, I need to update the cluster projection debug labels and ensure it prints correctly later.

search for "cluster projection" or "Cluster Projection" strings

for s in ["cluster projection", "Cluster Projection", "Projection (cluster", "Cluster proj", "2-set cluster", "3-set cluster"]: pos = text.lower().find(s.lower()) print(s, pos)

Investigating cluster projection references

I’ve found a reference to "cluster projection" near the beginning, probably in the patch notes (around line 9443). That’s not an output line. I see mentions of "2-set cluster" and "3-set cluster" around lines 835917 and 762180, which may be related to output. I’ll investigate those to clarify.

for pos in [762180, 835917]: print("\n---", pos, "---") print(text[pos-400:pos+500])

Searching for cluster median references in output

I’ve found references to "2-set cluster median" in the totals evaluation section, and there might be similar mentions of "3-set cluster" elsewhere as debug lines. I suspect that in the output, it could show something like "Totals Clusters: 2-set median/3-set median." I'll search for these terms near the output assembly.

find lines.push containing "cluster" near totals output

import itertools pattern = r'lines.push$".*cluster.*"$' matches = list(re.finditer(pattern, text)) len(matches)

for m in matches: print("\n--", m.start(), "--", m.group()[:150])

Inspecting outputs and cluster projection field

The line at 777359 says "Cluster projection: ... (mode-pick) | E[T|2 sets] ..." which refers to a debug field. It’s likely placed in the totals section, possibly near "Totals Summary." I’ll check the output around lines 777000 to 779000 to find where it appears earlier for proper labeling.

print(text[776800:778800])

Repositioning cluster projection in output

The "Cluster projection" is in the MATCH_PREVIEW output, possibly in the "set correlation/tanking" section, printing cluster totals, projections, and checks. They want to avoid treating it as a final value. I’m considering renaming it as “[Debug] Cluster projection” or moving it below final results, keeping it clearly labeled as a debug context.

Renaming and ensuring proper positioning of debug output

I’m thinking of renaming the "Cluster projection" to "Debug cluster projection..." and making sure it gets printed after the "Most Likely" lines. The output might have similar lines printed in different spots, like around 776800 and 810800, likely overlapping in "Totals Structure" and "evaluation". I’ll ensure consistency by placing these lines properly based on what outputs we gather.

Finalizing output presentation and ensuring consistency

I’m planning to include the "Most Likely Ending" after the "TotPmfTopStr" line and keep earlier cluster lines but rename them for clarity. We’ll also make sure that the user-facing "Totals Most Likely" displays properly, along with the mode, zone, and top PMF summary. I need to check where the "Hook/Push" info is printed too.

find occurrences of "Hook" in output lines.push

hook_lines = [m for m in re.finditer(r'lines.push(".Hook."', text)] len(hook_lines), [m.start() for m in hook_lines[:10]]

for m in hook_lines: print("\n--", m.start(), "--") print(text[m.start()-200:m.start()+400])

Updating hook line and output blocks

The hook line prints probabilities for values like floor and ceil, such as P(23) and P(24) for 23.5. The analyzeHook itself isn’t the problem; the output line is. I'll update it to include the near-line mass and make sure to rename it appropriately. I'll check both blocks, likely for different output variants, and adjust them accordingly.

print(text[834000:835200])

Modifying output for near-line mass and bands

When making a decision, the block first prints the Market Anchor, followed by the Hook line. I’ll update it to include the near-line mass and possibly local bands. We’ve already computed the probabilities, so I’ll calculate nearMass as _pLf + _pLc and display the best option. We'll show a concise version with different band sizes, ideally focusing on the 3-game and 5-game bands. I’ll make sure the line is clear and concise.

Adjusting hook and near-line mass outputs

For half-lines, we need to prioritize showing near-line mass instead of the hook readout, as requested. I’ll display a main line showing the near-line mass and bands, with an optional second line for the exact probabilities. For whole lines, we’ll keep the push risk and exact push probabilities, and determine whether the line is whole or half with a simple boolean check.

Implementing string output with near-line mass and push risk

For half-lines, I’ll display the near-line mass along with the 3g and 5g bands, following the instructions. For whole-lines, I'll include the push percentage and nearby bands, but might include additional context like the push risk. I'll rename "Exact mass" to "Exact mass (push risk)" for clarity.

Modifying ITF updates and constants

I’ll adjust the calGetTables section to return the ITF tables instead of CH. For the ITF constants, I’ll define them near the CH constants. I’m thinking it’s better to copy the arrays directly to avoid any unintended side effects. Afterward, I'll update the necessary variables and thresholds.

start,end,func = extract_function("getTotalsPick") print(func[:2000])

print(func[2000:4000])

Clarifying totals pick settings

It seems that getTotalsPick already includes ITF in some thresholds, but the user mentioned it doesn't. I need to check the function to confirm if the updates were made. The instruction suggests only WTA and CH should be explicit, with a fallback to ATP and ITF, so I'll search for "strongEdge" and similar terms in the function.

import re for kw in ["strongEdge","leanEdge","diffGap","thin", "p3", "edge"]: if kw in func: print("found", kw, "at", func.find(kw))

print(func[9800:11250])

Adjusting edge policy for ITF

I see that the "Edge policy" section uses _epIsWta and _epIsCh but doesn't include ITF, which seems to be the issue. I need to make sure it also includes ITF. To do this, I'll look at where _epIsWta is defined, probably around line 9000, and adjust accordingly.

find area with _epIsWta in getTotalsPick

pos = func.find("_epIsWta") print(pos) print(func[pos-400:pos+300])

Adjusting thresholds and adding ITF

The issue here is that ITF is missing from the threshold logic where _epIsWta and _epIsCh are used. I'll introduce a new variable, _epIsItf, and adjust values like _epPushLo for ITF with a larger minEdge of around 0.017, considering higher variance and push risks due to low holds. I’ll update the "Probability policy thresholds" accordingly, ensuring ITF is correctly integrated.

Considering ITF specifics and push thresholds

It seems like ITF has lower holds, possibly meaning more breaks and less push. However, for market totals, lines might be set at something like 21.5, which isn't directly affected by push. I’ll probably set the threshold around 0.12 or 0.125 for now and check the rest for consistency.

print(func[pos:pos+1800])

print(func[pos+1800:pos+2500])

Adding ITF to thresholds and winner decision logic

We'll add ITF to the threshold blocks. Further down, there might be a third set of conditions using WTA/CH/default, so I'll search for patterns like "? 0." to find all occurrences of "_epIsWta ?". For the winnerDecision part, we need to ensure ITF is explicitly included where necessary, focusing on policy threshold blocks, not the cluster governor. I'll locate the relevant sections by searching for terms like "minPrimary".

start,end,wd = extract_function("winnerDecision")

find minPrimary occurrences

for kw in ["minPrimary","minLean","dogMinProb","dogMinEdge","leanDogMin","highConfidenceCeiling"]: print(kw, wd.find(kw))

pos = wd.find("minLean") print(wd[pos-500:pos+800])

Adjusting ITF thresholds for dog and favorite values

It looks like the current thresholds include explicit ATP, WTA, and CH, while ITF falls into the "else" category. This is too conservative. I'll set ITF's values between WTA and CH, slightly higher for dogs, more conservative for favorites. For now, I'll set minLean dog at 0.015, fav at 0.022, and minPrimary dog at 0.030, fav at 0.043. Then, I’ll search for "dogMin" to find other relevant thresholds further down.

for kw in ["dogMin", "highConfidence", "ceiling", "leanDog", "dogMinProb", "dogMinP"]: idx = wd.find(kw) print(kw, idx)

Searching for "dogMinEdge" in code

It looks like there could be a separate variable for "dogMinP" in the cluster dog gating process. There's also the potential for a winner decision threshold related to actions. To figure this out, I'll search for "dogMinEdge" throughout the entire text to make sure I don't miss anything.

for kw in ["dogMinProb", "dogMinEdge", "leanDogMin", "highConfidenceCeiling"]: print(kw, text.find(kw))

Inspecting winner decision thresholds

It looks like the code now uses minLean and minPrimary for edge thresholds, possibly replacing previous ones. I need to search for other thresholds inside _winnerDecision_, like "highConfCeiling" or any references to "0.9." Instructions mention dogMinEdge, but I’ll still add an ITF branch where necessary. Let's look around "ceiling" at line 30563.

pos = wd.find("ceiling") print(wd[pos-500:pos+800])

Implementing ITF changes and output updates

No need for new thresholds, just add ITF to the minLean/minPrimary block. User mentioned mismatchIdx, so I'll adjust that, along with markovEffectiveHolds and others for ITF. We also need to modify the ORP confidence, _scBase, _scRange, and detectBimodalSkill. For display updates, I'll add "Totals Most Likely," adjust hook lines, and ensure MC totals are handled properly. Let's patch this carefully with regex and update the analyzeHook function.

Designing a new analyzeHook function

I'll design a new analyzeHook function that takes in marketLine and distributionMap. It checks if line is valid and ensures the distribution is finite. I'll calculate probabilities over/under/exact, then handle normalization around floor and ceiling values. I'll calculate a "nearMass" and create band3/band5 variables to track probability ranges for whole or fractional lines.

Updating range calculations and output structure

For half-line, I'll create two candidate ranges around the boundary between lf and lc, like [lf-2..lc+1] and [lf-1..lc+2], and choose the one with higher probability. For whole-line, I'll use a 5-integer range centered around line. I’ll implement a helper function to sum probabilities across a range and update the return structure to include specific values in a clearer format. Then, I’ll adjust the output at specific file positions.

Modifying hook output for efficiency

I'll search for the string in the code related to the hook output and plan to modify it. The current plan involves using the analyzeHook function with the precomputed _L and mcDistAdj values. I'll calculate the necessary band masses from the analyzeHook results without repeating the same computations, minimizing runtime increase. Even though the values like _pLf and _pLc are already computed earlier, it's okay to use analyzeHook for the final adjustments.

Reusing data and adjusting output format

I realized that the mcLineData computed earlier can be reused, which already includes the necessary data like floor and ceil values. This avoids redundant calculations. I'll adjust the output for both whole-line and half-line cases, ensuring consistent presentation of near masses and band data. I'll also keep the high push risk alert when necessary and adjust the formatting accordingly.

Adjusting output formatting for whole-line case

For the whole-line output, I’ll update the lines.push to include both near-line mass and local band information in a single line. This avoids complication with extra lines and keeps the formatting tidy. I'll replace the lines.push string to focus on near mass, local bands and push risk, ensuring clarity and simplicity.

Handling near-line mass and adding clarity

For half lines, I’ll combine the near-line mass and adjacent probabilities into one line but split them across two to keep it clean. It’ll include both the near mass and adjacent details. For whole lines, I'll replace the old line with a conditional to output accordingly, ensuring clarity and keeping the display concise.

search for existing helper mass in range

for pat in ["massInRange", "pmfMass", "sumRange", "rangeMass", "centralMass"]: print(pat, text.find(pat))

Inspecting centralMass variable

I see there's a centralMass variable being used somewhere, and it might be computed by computeTotalsBlend. I need to check around line 439700—let’s see if I can find where it shows up to verify how it’s being calculated and what it influences in the code.

print(text[439650:440250])

Investigating pmfSumBetween and pmfSumExact functions

I see there are helper functions like pmfSumBetween and pmfSumExact that might be useful. I’ll search for the definition of pmfSumBetween to understand its details, and then possibly check pmfSumExact if they’re related. This should help clarify how they fit into the overall logic.

pos = text.find("function pmfSumBetween") pos

start,end,pmf_func = extract_function("pmfSumBetween") print(pmf_func)

Using pmfSumBetween and pmfFromTotalsArray to optimize computations

I can utilize pmfSumBetween in both analyzeHook and the zone calculations for totals. This will help simplify and reduce code. However, since pmfSumBetween loops over keys, it may be inefficient, though the range of dist keys is small. Now, I’ll check the definition of pmfFromTotalsArray to proceed.

pos = text.find("function pmfFromTotalsArray") pos

start,end,pmf_from = extract_function("pmfFromTotalsArray") print(pmf_from[:800])

Computing best 3-game window for totals zone

For the totals mode and zone, I plan to compute the pmf using pmfFromTotalsArray(gamesListAdj) and get the mode as _totMode. For the zone, I’ll explore possible 3-game windows near the mode and compute the best one based on maximum mass. I'll search for a function like "best3g" for this.

for pat in ["bestZone", "zone", "window", "modeFromSortedTotals"]: if pat!="zone": print(pat, text.find(pat))

Deciding where to implement pmfBestWindow function

It seems like implementing a separate pmfBestWindow function might be best at the top level near the other PMF functions, like pmfSumBetween. Though, I wonder if I could just implement it directly in analyzeHook or the output section, since it's already used multiple times. Though, analyzeHook expects a market line, so maybe I should not use it there.

Creating pmfBestWindow helper function

I’ll create a helper function pmfBestWindow that returns the best contiguous integer window from a PMF map. Given a distribution and a window width, the function will calculate the sum of values over all keys within the window and return the start and end keys of the best window, along with its mass. Even if pmfSumBetween loops over all keys, it should still be efficient with fewer than 900 iterations.

Implementing pmfBestWindow with local vs global logic

I’ll insert the pmfBestWindow function near pmfSumBetween and pmfFromTotalsArray. Since the script is not modular, we’ll put it after pmfSumBetween. For analyzeHook, I’ll compute local candidate windows around bands like band3 and band5. For totals, we’ll stick with the best global window, but around boundaries for half-lines, we’ll compute local windows.

Computing zone and displaying most likely totals

We’ll use pmfBestWindow with a width of 3 to get the local high-density zone. In the totals output block, I’ll compute the totPmf and use pmfBestWindow for both zone3 and possibly zone5, though I'll keep it at 3. We’ll show the most likely zone with the mode, and format the output accordingly for user-facing display.

Adjusting settings for ITF and confidence levels

We’re updating ITF-related variables, like adding ITF to existing functions. For the ORP confidence in ITF, I'm thinking of adjusting _scBase and _scRange values—possibly setting 0.79 for ITF and adjusting the confidence measure lower. This would ensure ITF remains cautious, with a lower schedule confidence. I'll also update UI elements, renaming items to clearly indicate debug.

Implementing ITF-specific changes and code updates

We're adjusting confidence settings for various metrics, including ITF, by modifying base ranges. For ITF, we're making values more conservative with a higher base and wider range. Other changes include adding ITF to several functions and ensuring no name duplication in the insertion of new helper functions. I’ll monitor replacements carefully with regex to avoid errors.

Adding functions for window calculation and updating context

I’m adding a new pmfBestWindow function to identify the best window for a probability mass function (PMF) based on a given width. This will help refine the totals zone. Additionally, I’ll update the analyzeHook function and modify the context output to display the most likely ending and PMF top string in the totals block. Certain adjustments for variable computation order are also needed.

Adjusting printing of most likely totals and PMF

I’ll shift the totPmfTopStr computation inside the if-block and print it after it’s computed, avoiding duplication. I'll push the "Most Likely Totals" after the expected total and then later display "Totals PMF (top ...)" when the totPmfTopStr is ready. This helps solve the structure without repeating the output.

Updating labels and patching output blocks

I'll update the cluster projection label for clarity, changing the line to [Debug] Cluster projection:. For the hook output, I'll replace the try block with the updated lines.push method. This will include using variables like _hk.pFloor, and ensuring the necessary fields exist before computing the near and bands with _b3 and _b5.

Pushing line updates and ITF definitions

I'll push lines based on the value of _isWhole. The first block includes details about the near-line mass information and local sums, while the second block displays push risk and nearby exacts. I'll ensure the required variables like _L and _isWhole are present and properly computed. I'll also define ITF tables like _calRankITF_ just after the CH tables.

Modifying ITF thresholds throughout functions

I'm updating several code blocks for ITF-specific handling. For example, in _calGetTables_, adding ITF-based returns, adjusting sdThreshold to accommodate ITF values, and modifying conditions in _markovEffectiveHolds, _mismatchIdxFromSeeds, and other functions like _pickTaperSeedA and getTotalsPick. I'll set appropriate ITF thresholds, like in the push, central mass, and lean values.

Adding ITF handling in various functions

I’m adjusting several functions to include specific handling for ITF, like _adjustEdgeForFavoriteFragility_ and _winnerDecision_. I'll update thresholds—such as avgHold and range—and add explicit ITF branches where necessary. While not editing all cluster variables, I'll focus on critical value thresholds as advised. Time to move on with the code modifications!

import re updated = text

1) Insert pmfBestWindow after pmfSumBetween function if not already present

if "function pmfBestWindow" not in updated: s,e,pmf_sum = extract_function("pmfSumBetween") insert_at = e pmf_best = """

/**

• Find the best contiguous integer window of a given width in a PMF map.
• Returns { lo, hi, mass } where mass is the probability inside [lo, hi] (inclusive). */ function pmfBestWindow(dist, width) { width = Math.max(1, Math.floor(Number(width) || 1)); if (!dist) return { lo: NaN, hi: NaN, mass: NaN };

var minK = Infinity, maxK = -Infinity; for (var k in dist) { var v = Number(k); if (!Number.isFinite(v)) continue; if (v < minK) minK = v; if (v > maxK) maxK = v; } if (!Number.isFinite(minK) || !Number.isFinite(maxK)) return { lo: NaN, hi: NaN, mass: NaN };

minK = Math.floor(minK); maxK = Math.ceil(maxK);

var bestMass = -1; var bestLo = minK; var bestHi = minK + width - 1;

for (var lo = minK; lo <= (maxK - width + 1); lo++) { var hi = lo + width - 1; var m = pmfSumBetween(dist, lo, hi); if (m > bestMass) { bestMass = m; bestLo = lo; bestHi = hi; } }

return { lo: bestLo, hi: bestHi, mass: bestMass }; } """ updated = updated[:insert_at] + pmf_best + updated[insert_at:]

2) Replace analyzeHook function

start,end,old_analyze = extract_function("analyzeHook") new_analyze = """function analyzeHook(marketLine, distributionMap) { var pOver = 0; var pUnder = 0; var pExact = 0;

var line = Number(marketLine); if (!Number.isFinite(line) || !distributionMap) { return { over: NaN, under: NaN, push: NaN, hookValue: NaN, isWhole: false, floor: NaN, ceil: NaN, pFloor: NaN, pCeil: NaN, nearMass: NaN, band3Mass: NaN, band3Lo: NaN, band3Hi: NaN, band5Mass: NaN, band5Lo: NaN, band5Hi: NaN }; }

// Whole-number market lines can push; half-lines cannot. var isWholeNumber = (line % 1 === 0); var lf = Math.floor(line); var lc = Math.ceil(line);

var pLf = 0; var pLc = 0;

for (var games in distributionMap) { if (!distributionMap.hasOwnProperty(games)) continue; var g = parseFloat(games); var prob = Number(distributionMap[games] || 0); if (!Number.isFinite(g) || !Number.isFinite(prob)) continue;

text
if (g > line) pOver += prob;
else if (g < line) pUnder += prob;
else {
  if (isWholeNumber) pExact += prob;
}

if (g === lf) pLf += prob;
if (g === lc) pLc += prob;

}

// Defensive renormalization var sum = pOver + pUnder + pExact; if (sum > 0 && Math.abs(sum - 1) > 1e-6) { pOver /= sum; pUnder /= sum; pExact /= sum; pLf /= sum; pLc /= sum; }

// Near-line mass: // - Whole line: push mass (exactly on the line) // - Half line: mass on the two adjacent integers (floor + ceil) var nearMass = isWholeNumber ? pExact : (pLf + pLc);

// Local bands (useful display for half-lines): // - 3g candidates: [lf-1..lc] and [lf..lc+1] // - 5g candidates: [lf-2..lc+1] and [lf-1..lc+2] var band3a = pmfSumBetween(distributionMap, lf - 1, lc); var band3b = pmfSumBetween(distributionMap, lf, lc + 1); var band3Mass = (band3a >= band3b) ? band3a : band3b; var band3Lo = (band3a >= band3b) ? (lf - 1) : lf; var band3Hi = (band3a >= band3b) ? lc : (lc + 1);

var band5a = pmfSumBetween(distributionMap, lf - 2, lc + 1); var band5b = pmfSumBetween(distributionMap, lf - 1, lc + 2); var band5Mass = (band5a >= band5b) ? band5a : band5b; var band5Lo = (band5a >= band5b) ? (lf - 2) : (lf - 1); var band5Hi = (band5a >= band5b) ? (lc + 1) : (lc + 2);

// Whole-line bands should be centered on the line. if (isWholeNumber) { band3Lo = lf - 1; band3Hi = lf + 1; band3Mass = pmfSumBetween(distributionMap, band3Lo, band3Hi);

text
band5Lo = lf - 2;
band5Hi = lf + 2;
band5Mass = pmfSumBetween(distributionMap, band5Lo, band5Hi);

}

return { over: pOver, under: pUnder, push: pExact, hookValue: pExact,

text
isWhole: isWholeNumber,
floor: lf,
ceil: lc,
pFloor: pLf,
pCeil: pLc,

nearMass: nearMass,
band3Mass: band3Mass, band3Lo: band3Lo, band3Hi: band3Hi,
band5Mass: band5Mass, band5Lo: band5Lo, band5Hi: band5Hi

}; }""" updated = updated[:start] + new_analyze + updated[end:]

3) Update cal tables for ITF: define ITF tables if not present

if "calRankITF" not in updated: # insert after calHoldCH definition line; locate string "var calHoldCH" m = re.search(r"var calHoldCH\s*=\s*{[^\n]*};", updated) if m: insert_at = m.end() itf_tables = """ var calRankITF = { xs: [3,8,15,28,45,68,100,150,240,450,1050], ys: [0.5,0.5207,0.5239,0.5239,0.5345,0.5671,0.6096,0.6287,0.6548,0.7044,0.8082] }; var calSPWITF = { xs: [-18.5,-9,-4.5,-2,0,2,4.5,9,18.5], ys: [0.0021,0.0249,0.1313,0.3034,0.499,0.7358,0.8971,0.983,0.9987] }; var calHoldITF = { xs: [-37.5,-18.5,-9,-4,0,4,9,18.5,42.5], ys: [0.0004,0.0154,0.0858,0.3365,0.5275,0.6878,0.946,0.9895,0.999] }; """ updated = updated[:insert_at] + "\n" + itf_tables + updated[insert_at:]

modify calGetTables ITF branch to use ITF tables

updated = re.sub( r"if\s*tk\.indexOf\('ITF'\s*>=\s0)\sreturn\s*{\srank:\scalRankCH,\sspw:\scalSPWCH,\shold:\scalHoldCH\s*};", "if (tk.indexOf('ITF') >= 0) return { rank: calRankITF, spw: calSPWITF, hold: calHoldITF };", updated )

4) detectBimodalSkill threshold ITF

updated = updated.replace( "var sdThreshold = (tk.indexOf('WTA') >= 0) ? 0.065 : (tk.indexOf('CH') >= 0) ? 0.070 : 0.075;", "var sdThreshold = (tk.indexOf('WTA') >= 0) ? 0.065 : (tk.indexOf('CH') >= 0) ? 0.070 : (tk.indexOf('ITF') >= 0) ? 0.068 : 0.075;" )

5) markovEffectiveHolds ITF diag thresholds

updated = updated.replace( "var _mkIsWta = (_mkTourK === 'WTA');\n var _mkIsCh = (_mkTourK === 'CH');\n var _mkFloor = _mkIsWta ? 0.50 : _mkIsCh ? 0.51 : 0.52;\n var _mkRange = _mkIsWta ? 0.28 : _mkIsCh ? 0.29 : 0.30;", "var _mkIsWta = (_mkTourK === 'WTA');\n var _mkIsCh = (_mkTourK === 'CH');\n var _mkIsItf = (_mkTourK === 'ITF');\n var _mkFloor = _mkIsWta ? 0.50 : _mkIsCh ? 0.51 : _mkIsItf ? 0.51 : 0.52;\n var _mkRange = _mkIsWta ? 0.28 : _mkIsCh ? 0.29 : _mkIsItf ? 0.30 : 0.30;" )

6) mismatchIdxFromSeeds ITF thresholds

updated = updated.replace( "var _miIsWta = (_miTourK === 'WTA');\n var _miIsCh = (_miTourK === 'CH');\n var _miFloor = _miIsWta ? 0.50 : _miIsCh ? 0.51 : 0.52;\n var _miRange = _miIsWta ? 0.28 : _miIsCh ? 0.29 : 0.30;\n var _miHdFloor = _miIsWta ? 0.04 : _miIsCh ? 0.045 : 0.05;\n var _miHdRange = _miIsWta ? 0.18 : _miIsCh ? 0.19 : 0.20;", "var _miIsWta = (_miTourK === 'WTA');\n var _miIsCh = (_miTourK === 'CH');\n var _miIsItf = (_miTourK === 'ITF');\n var _miFloor = _miIsWta ? 0.50 : _miIsCh ? 0.51 : _miIsItf ? 0.51 : 0.52;\n var _miRange = _miIsWta ? 0.28 : _miIsCh ? 0.29 : _miIsItf ? 0.31 : 0.30;\n var _miHdFloor = _miIsWta ? 0.04 : _miIsCh ? 0.045 : _miIsItf ? 0.045 : 0.05;\n var _miHdRange = _miIsWta ? 0.18 : _miIsCh ? 0.19 : _miIsItf ? 0.22 : 0.20;" )

7) pickTaperSeedA ITF thresholds

updated = updated.replace( "var _ptIsWta = (_ptTourK === 'WTA');\n var _ptIsCh = (_ptTourK === 'CH');\n var _ptCoinflip = _ptIsWta ? 0.025 : _ptIsCh ? 0.028 : 0.03;\n var _ptWeakDir = _ptIsWta ? 0.08 : _ptIsCh ? 0.09 : 0.10;\n var _ptBlendS = _ptIsWta ? 0.60 : _ptIsCh ? 0.62 : 0.65;\n var _ptBlendM = _ptIsWta ? 0.40 : _ptIsCh ? 0.38 : 0.35;", "var _ptIsWta = (_ptTourK === 'WTA');\n var _ptIsCh = (_ptTourK === 'CH');\n var _ptIsItf = (_ptTourK === 'ITF');\n var _ptCoinflip = _ptIsWta ? 0.025 : _ptIsCh ? 0.028 : _ptIsItf ? 0.028 : 0.03;\n var _ptWeakDir = _ptIsWta ? 0.08 : _ptIsCh ? 0.09 : _ptIsItf ? 0.095 : 0.10;\n var _ptBlendS = _ptIsWta ? 0.60 : _ptIsCh ? 0.62 : _ptIsItf ? 0.63 : 0.65;\n var _ptBlendM = _ptIsWta ? 0.40 : _ptIsCh ? 0.38 : _ptIsItf ? 0.37 : 0.35;" )

8) ORP confidence scalar ITF (within adjustStatsByOppQuality function)

updated = updated.replace( "var _scBase = (_scTourK === 'WTA') ? 0.82 : (_scTourK === 'CH') ? 0.81 : 0.80;\n var _scRange = (_scTourK === 'WTA') ? 0.25 : (_scTourK === 'CH') ? 0.28 : 0.30;", "var _scBase = (_scTourK === 'WTA') ? 0.82 : (_scTourK === 'CH') ? 0.81 : (_scTourK === 'ITF') ? 0.83 : 0.80;\n var _scRange = (_scTourK === 'WTA') ? 0.25 : (_scTourK === 'CH') ? 0.28 : (_scTourK === 'ITF') ? 0.35 : 0.30;" )

9) getTotalsPick edge policy ITF (modify _epIs... block)

updated = updated.replace( "var _epTourK = (ctx && ctx.tourLabel) ? taperTourKey(ctx.tourLabel) : 'ATP';\n var _epIsWta = (_epTourK === 'WTA');\n var _epIsCh = (_epTourK === 'CH');", "var _epTourK = (ctx && ctx.tourLabel) ? taperTourKey(ctx.tourLabel) : 'ATP';\n var _epIsWta = (_epTourK === 'WTA');\n var _epIsCh = (_epTourK === 'CH');\n var _epIsItf = (_epTourK === 'ITF');" )

Replace the threshold ternaries in that block

updated = updated.replace("var _epPushLo = _epIsWta ? 0.11 : _epIsCh ? 0.115 : 0.12;", "var _epPushLo = _epIsWta ? 0.11 : _epIsCh ? 0.115 : _epIsItf ? 0.125 : 0.12;") updated = updated.replace("var _epPushHi = _epIsWta ? 0.16 : _epIsCh ? 0.17 : 0.18;", "var _epPushHi = _epIsWta ? 0.16 : _epIsCh ? 0.17 : _epIsItf ? 0.185 : 0.18;") updated = updated.replace("var _epPushBumpLo = _epIsWta ? 0.007 : _epIsCh ? 0.0065 : 0.006;", "var _epPushBumpLo = _epIsWta ? 0.007 : _epIsCh ? 0.0065 : _epIsItf ? 0.006 : 0.006;") updated = updated.replace("var _epPushBumpHi = _epIsWta ? 0.012 : _epIsCh ? 0.011 : 0.010;", "var _epPushBumpHi = _epIsWta ? 0.012 : _epIsCh ? 0.011 : _epIsItf ? 0.010 : 0.010;") updated = updated.replace("var _epCentralHi = _epIsWta ? 0.32 : _epIsCh ? 0.33 : 0.34;", "var _epCentralHi = _epIsWta ? 0.32 : _epIsCh ? 0.33 : _epIsItf ? 0.335 : 0.34;") updated = updated.replace("var _epCentralLo = _epIsWta ? 0.26 : _epIsCh ? 0.27 : 0.28;", "var _epCentralLo = _epIsWta ? 0.26 : _epIsCh ? 0.27 : _epIsItf ? 0.275 : 0.28;") updated = updated.replace("var _epTwoTailG = _epIsWta ? 0.11 : _epIsCh ? 0.115 : 0.12;", "var _epTwoTailG = _epIsWta ? 0.11 : _epIsCh ? 0.115 : _epIsItf ? 0.125 : 0.12;") updated = updated.replace("var _epDisagreeG = _epIsWta ? 0.09 : _epIsCh ? 0.095 : 0.10;", "var _epDisagreeG = _epIsWta ? 0.09 : _epIsCh ? 0.095 : _epIsItf ? 0.105 : 0.10;") updated = updated.replace("var _epMinClamp = _epIsWta ? 0.017 : _epIsCh ? 0.016 : 0.015;", "var _epMinClamp = _epIsWta ? 0.017 : _epIsCh ? 0.016 : _epIsItf ? 0.016 : 0.015;") updated = updated.replace("var _epMaxClamp = _epIsWta ? 0.055 : _epIsCh ? 0.058 : 0.060;", "var _epMaxClamp = _epIsWta ? 0.055 : _epIsCh ? 0.058 : _epIsItf ? 0.060 : 0.060;") updated = updated.replace("var _epLeanMult = _epIsWta ? 0.50 : _epIsCh ? 0.52 : 0.55;", "var _epLeanMult = _epIsWta ? 0.50 : _epIsCh ? 0.52 : _epIsItf ? 0.53 : 0.55;") updated = updated.replace("var _epLeanMin = _epIsWta ? 0.009 : _epIsCh ? 0.0085 : 0.008;", "var _epLeanMin = _epIsWta ? 0.009 : _epIsCh ? 0.0085 : _epIsItf ? 0.0085 : 0.008;")

10) WinnerDecision value thresholds ITF

Replace the block that sets minLean/minPrimary if/else

wd_block_old = r"""if $_wdTourK === 'ATP'$ { minLean = _wdDog ? 0.011 : 0.016; minPrimary = _wdDog ? 0.022 : 0.035; } else if $_wdTourK === 'WTA'$ { minLean = _wdDog ? 0.013 : 0.019; minPrimary = _wdDog ? 0.026 : 0.040; } else if $_wdTourK === 'CH'$ { minLean = _wdDog ? 0.014 : 0.021; minPrimary = _wdDog ? 0.028 : 0.042; } else { minLean = _wdDog ? 0.016 : 0.024; minPrimary = _wdDog ? 0.030 : 0.045; }""" wd_block_new = """if (_wdTourK === 'ATP') { minLean = _wdDog ? 0.011 : 0.016; minPrimary = _wdDog ? 0.022 : 0.035; } else if (_wdTourK === 'WTA') { minLean = _wdDog ? 0.013 : 0.019; minPrimary = _wdDog ? 0.026 : 0.040; } else if (_wdTourK === 'CH') { minLean = _wdDog ? 0.014 : 0.021; minPrimary = _wdDog ? 0.028 : 0.042; } else if (_wdTourK === 'ITF') { minLean = _wdDog ? 0.015 : 0.023; minPrimary = _wdDog ? 0.029 : 0.044; } else { minLean = _wdDog ? 0.016 : 0.024; minPrimary = _wdDog ? 0.030 : 0.045; }""" updated, n = re.subn(wd_block_old, wd_block_new, updated) n

Updating totals output logic

I’m aiming to patch the totals output by inserting new lines after the line containing "Totals Expected: " in the _totSim.. block. I’ll use regular expressions to handle this efficiently. It’s a subtle change, but I’ll get it right and make the necessary update! Time for the patch.

Insert totals most likely after Totals Expected line in that specific output section

marker = 'lines.push("Totals Expected: " + expGamesAdjusted.toFixed(1) + " (mean) | Median: " + totAdjMedian.toFixed(1));' if marker in updated: insert_pos = updated.find(marker) + len(marker) # ensure not already inserted if "Totals Most Likely:" not in updated[insert_pos:insert_pos+500]: insert_text = """ // Display semantics (pricing vs expectation vs most-likely landing): // - Fair Line: pricing (50/50 CDF) // - Expected: mean of the distribution // - Most Likely: mode + local high-density zone (best contiguous window) try { var _pmfAdjDisp = pmfFromTotalsArray(gamesListAdj); var _modeDisp = modeFromSortedTotals(gamesListAdj); var _zone3 = pmfBestWindow(_pmfAdjDisp, 3); if (Number.isFinite(_modeDisp)) { var _zStr = (Number.isFinite(_zone3.mass) ? (_zone3.lo + "–" + _zone3.hi + "g " + (_zone3.mass * 100).toFixed(1) + "%") : "n/a"); lines.push("Totals Most Likely: Exact " + _modeDisp + "g | Zone " + _zStr); } } catch(eML) {} """ updated = updated[:insert_pos] + insert_text + updated[insert_pos:] else: print("marker not found")

Now surface totPmfTopStr after it is built (only once)

pmf_marker = "totPmfTopStr = _arr.slice(0, 8).map(function(e){ return e.g + "g " + (e.p*100).toFixed(1) + "%"; }).join(" | ");" idx = updated.find(pmf_marker) idx, updated[idx-50:idx+len(pmf_marker)+50]

Inserting new output line after block

I'll insert a line in the lines array after the block that sets totPmfTopStr. It seems the marker may appear twice, so I'll ensure I’m targeting the correct location. I’ll add if (totPmfTopStr) { lines.push("Totals PMF (top exacts): " + totPmfTopStr); } right after the block and before the variable _totMode without cluttering the output. Let’s do this!

Inserting at the correct location using regex

I’ll insert the line by targeting the substring }\n\n var _totMode and placing the code in between. But I should be cautious about other similar occurrences. I'll use regex around the totPmfTopStr block and apply re.sub for the insertion to ensure it’s done correctly. Let's proceed!

Insert display line after totPmfTopStr block near the first occurrence

pattern = r'(totPmfTopStr = _arr.slice$0, 8$.mapfunction\(e{ return e.g + "g " + $e\.p\*100$.toFixed$1$ + "%"; }).join$" \| "$;\n}\n)' repl = r'\1\nif (totPmfTopStr) {\n lines.push("Totals PMF (top exacts): " + totPmfTopStr);\n}\n' updated, n_pmf = re.subn(pattern, repl, updated, count=1) n_pmf

Updating cluster projection label

I’m going to replace the "Cluster projection:" line and possibly the "Cluster totals:" line with new string literals. This will update the cluster projection label to match the new structure. Let's make sure the changes are applied only once for clarity and accuracy!

updated = updated.replace('lines.push(" Cluster totals: 2-set ', 'lines.push(" [Debug] 2-set/3-set clusters: 2-set ') updated = updated.replace('lines.push(" Cluster projection: ', 'lines.push(" [Debug] Cluster projection: ')

Ensuring accuracy in string replacement

I’ll ensure the strings match exactly before making any changes. After replacing "Cluster projection:", I’ll count its occurrences to make sure everything was updated correctly. This will help avoid any unexpected errors or mismatches. It’s all about getting those details right!

updated.count("Cluster projection:"), updated.count("[Debug] Cluster projection:")

Checking replacement success

Okay, I've replaced one instance, and now I need to check for the "Cluster totals" line change as well. I’ll count the occurrences to debug and make sure things are working as expected. Just double-checking to be sure I didn’t miss anything important!

updated.count("Cluster totals:"), updated.count("[Debug] 2-set/3-set clusters:")

Updating hook output blocks

Alright, I need to locate the old hook line and replace it with the new code. I’ll use regex to substitute the old try block with the updated one nearby. I’ll also count occurrences and match the pattern from var _lf = Math.floor(_L); to the lines.push line. I’ll identify the updated block and search for that specific string to replace.

hook_str = 'Hook — P(' updated.count(hook_str)

Updating hook output block

I’ll replace the lines.push line with the multi-line code needed, but it’s easier to replace the entire try block. I'll target everything from var _lf = Math.floor(_L); to right before if (Number.isFinite(pMarkov3Set)), then add the conditional lines. I'll inspect the first occurrence of the updated block to ensure accuracy.

pos = updated.find('lines.push(" Hook —') print(updated[pos-300:pos+250])

Updating _hookAlert and lines.push

I need to replace the line starting with _hookAlert and that lines.push line with new code, while also computing the local band masses. However, I’ll keep the _hookAlert line intact. I’ll patch everything by swapping the old lines.push and adding the new lines around it.

Creating replacement for _hookAlert and lines.push

I’m replacing the original two lines for _hookAlert and lines.push with new code that calculates nearMass, b3, and b5 values, and adjusts them based on the value of _isWhole. There will also be conditional logic to display specific details in lines.push depending on whether _isWhole is true or false. This should keep everything consistent.

Creating regex pattern for substitution

I’m setting up a regex to match the lines for _hookAlert and lines.push exactly. The pattern will use re.DOTALL to handle multi-line matching. I’ll use re.subn to replace these lines safely with a new pattern that includes formatting for the proper conditional logic. Looks like the pattern is quite specific!

Refining substitution for simplicity

I’m opting for a simpler approach: I’ll replace just the lines.push(" Hook — P(...g) line and keep the _hookAlert as is. I’ll compute the near mass and other values and then insert it before the var _hookAlert line. After that, I’ll update the _hookAlert to a multi-line version, including the new computations and line pushes. Finally, I’ll clean up by removing the old lines.push line. That seems like a cleaner solution!

Substitution plan for hook line and near-line mass

I’ll replace the line defining _hookAlert with the full block, including new computations and line pushes, while referencing already calculated values like _pLf, _pLc, _lf, and _lc. Then, I’ll remove the old lines.push line and replace it with a comment. I’ll be using a regex pattern to handle the substitution. It seems straightforward enough!

Replace the hook output line blocks (2 occurrences)

pattern = r"""var _hookAlert = \(_isWhole && Number.isFinite$totPushPct$ && totPushPct > 0.12) ? " $HIGH PUSH RISK$" : "";\n\s*lines.push" Hook — P\(" \+ _lf \+ "g: " + $_pLf \* 100$.toFixed$1$ + "% | P$" \+ _lc \+ "g$: " + $_pLc \* 100$.toFixed$1$ + "%" + _isWhole \? " \| Push@" \+ _lf \+ ": " \+ \(totPushPct \* 100.toFixed$1$ + "%" + _hookAlert : ""));\n""" replacement = """var _hookAlert = ((_isWhole) && Number.isFinite(totPushPct) && totPushPct > 0.12) ? " [HIGH PUSH RISK]" : "";

// Near-line mass + local bands (display semantics) // - Half line: near mass = P(floor)+P(ceil) // - Whole line: near mass = push@line var _nearMass = (_isWhole && Number.isFinite(totPushPct)) ? totPushPct : (_pLf + _pLc);

// Local 3g / 5g bands around the market (two candidates for half-lines; centered for whole lines) var _b3a = pmfSumBetween(mcDistAdj, _lf - 1, _lc); var _b3b = pmfSumBetween(mcDistAdj, _lf, _lc + 1); var _b3 = (_b3a >= _b3b) ? _b3a : _b3b; var _b3lo = (_b3a >= _b3b) ? (_lf - 1) : _lf; var _b3hi = (_b3a >= _b3b) ? _lc : (_lc + 1);

var _b5a = pmfSumBetween(mcDistAdj, _lf - 2, _lc + 1); var _b5b = pmfSumBetween(mcDistAdj, _lf - 1, _lc + 2); var _b5 = (_b5a >= _b5b) ? _b5a : _b5b; var _b5lo = (_b5a >= _b5b) ? (_lf - 2) : (_lf - 1); var _b5hi = (_b5a >= _b5b) ? (_lc + 1) : (_lc + 2);

if (_isWhole) { _b3lo = _lf - 1; _b3hi = _lf + 1; _b3 = pmfSumBetween(mcDistAdj, _b3lo, _b3hi);

_b5lo = _lf - 2; _b5hi = _lf + 2; _b5 = pmfSumBetween(mcDistAdj, _b5lo, _b5hi); }

if (!_isWhole) { lines.push(" Near-line mass @" + Number(_L).toFixed(1) + ": " + (_nearMass * 100).toFixed(1) + "% (P(" + _lf + ")+P(" + _lc + ")) | Local " + _b3lo + "–" + _b3hi + ": " + (_b3 * 100).toFixed(1) + "% | " + _b5lo + "–" + _b5hi + ": " + (_b5 * 100).toFixed(1) + "%"); lines.push(" Adjacent exacts: P(" + _lf + "g) " + (_pLf * 100).toFixed(1) + "% | P(" + _lc + "g) " + (_pLc * 100).toFixed(1) + "%"); } else { lines.push(" Push@" + _lf + ": " + (totPushPct * 100).toFixed(1) + "%" + _hookAlert + " | Local " + _b3lo + "–" + _b3hi + ": " + (_b3 * 100).toFixed(1) + "% | " + _b5lo + "–" + _b5hi + ": " + (_b5 * 100).toFixed(1) + "%"); lines.push(" Exact hit: P(" + _lf + "g) " + (_pLf * 100).toFixed(1) + "%"); } """ updated, n_hook = re.subn(pattern, replacement, updated) n_hook

Preparing second patch for variables

It looks like the second occurrence uses slightly different variable names, like _lf0 and _lc0. I’ll need to create a second patch for these. To make sure everything’s covered, I’ll inspect the second block around line 838492 and search for "Hook — P(" to check the count of occurrences.

updated.count('Hook — P(')

Handling the final occurrence

There’s still the _lf0 version to patch. I’ll create a pattern using _lf0, _lc0, and totPushPct to handle this one separately. Once I’ve crafted that, I can apply the patch for this last occurrence. Just making sure all variations are covered before proceeding!

pattern0 = r"""var _hookAlert0 = \(_isWhole && Number.isFinite$totPushPct$ && totPushPct > 0.12) ? " $HIGH PUSH RISK$" : "";\n\s*lines.push" Hook — P\(" \+ _lf0 \+ "g: " + $_pLf0 \* 100$.toFixed$1$ + "% | P$" \+ _lc0 \+ "g$: " + $_pLc0 \* 100$.toFixed$1$ + "%" + _isWhole \? " \| Push@" \+ _lf0 \+ ": " \+ \(totPushPct \* 100.toFixed$1$ + "%" + _hookAlert0 : ""));\n""" replacement0 = """var _hookAlert0 = ((_isWhole) && Number.isFinite(totPushPct) && totPushPct > 0.12) ? " [HIGH PUSH RISK]" : "";

// Near-line mass + local bands (display semantics) // - Half line: near mass = P(floor)+P(ceil) // - Whole line: near mass = push@line var _nearMass0 = (_isWhole && Number.isFinite(totPushPct)) ? totPushPct : (_pLf0 + _pLc0);

// Local 3g / 5g bands around the market (two candidates for half-lines; centered for whole lines) var _b3a0 = pmfSumBetween(mcDistAdj, _lf0 - 1, _lc0); var _b3b0 = pmfSumBetween(mcDistAdj, _lf0, _lc0 + 1); var _b30 = (_b3a0 >= _b3b0) ? _b3a0 : _b3b0; var _b3lo0 = (_b3a0 >= _b3b0) ? (_lf0 - 1) : _lf0; var _b3hi0 = (_b3a0 >= _b3b0) ? _lc0 : (_lc0 + 1);

var _b5a0 = pmfSumBetween(mcDistAdj, _lf0 - 2, _lc0 + 1); var _b5b0 = pmfSumBetween(mcDistAdj, _lf0 - 1, _lc0 + 2); var _b50 = (_b5a0 >= _b5b0) ? _b5a0 : _b5b0; var _b5lo0 = (_b5a0 >= _b5b0) ? (_lf0 - 2) : (_lf0 - 1); var _b5hi0 = (_b5a0 >= _b5b0) ? (_lc0 + 1) : (_lc0 + 2);

if (_isWhole) { _b3lo0 = _lf0 - 1; _b3hi0 = _lf0 + 1; _b30 = pmfSumBetween(mcDistAdj, _b3lo0, _b3hi0);

_b5lo0 = _lf0 - 2; _b5hi0 = _lf0 + 2; _b50 = pmfSumBetween(mcDistAdj, _b5lo0, _b5hi0); }

if (!_isWhole) { lines.push(" Near-line mass @" + Number(_L).toFixed(1) + ": " + (_nearMass0 * 100).toFixed(1) + "% (P(" + _lf0 + ")+P(" + _lc0 + ")) | Local " + _b3lo0 + "–" + _b3hi0 + ": " + (_b30 * 100).toFixed(1) + "% | " + _b5lo0 + "–" + _b5hi0 + ": " + (_b50 * 100).toFixed(1) + "%"); lines.push(" Adjacent exacts: P(" + _lf0 + "g) " + (_pLf0 * 100).toFixed(1) + "% | P(" + _lc0 + "g) " + (_pLc0 * 100).toFixed(1) + "%"); } else { lines.push(" Push@" + _lf0 + ": " + (totPushPct * 100).toFixed(1) + "%" + _hookAlert0 + " | Local " + _b3lo0 + "–" + _b3hi0 + ": " + (_b30 * 100).toFixed(1) + "% | " + _b5lo0 + "–" + _b5hi0 + ": " + (_b50 * 100).toFixed(1) + "%"); lines.push(" Exact hit: P(" + _lf0 + "g) " + (_pLf0 * 100).toFixed(1) + "%"); } """ updated, n_hook0 = re.subn(pattern0, replacement0, updated) n_hook0, updated.count('Hook — P(')

Verifying function usage and patching

I need to confirm that we didn’t accidentally reference pmfSumBetween before its definition, which is at 438516. Since analyzeHook is defined at 436770 and pmfSumBetween is defined afterward, it’s fine since function declarations are hoisted. Next, I'll need to check for duplicates and ensure everything’s in scope. Thank goodness!

Updating edge policy and ensuring correct replacements

I’m focusing on patching the edge policy for ITF and winnerDecision, followed by updates to _markovEffectiveHolds_. The replacement for _mkRange sets both else and itf to 0.30, which is somewhat redundant but still works. I’ll also update _mismatchIdxFromSeeds_. Finally, I’ll confirm that the regex for _calGetTables_ has been replaced correctly.

Extract calGetTables and ensure ITF uses ITF

s,e,calget = extract_function("calGetTables") print(calget)

Adjusting extraction logic

It looks like the regex didn’t apply because the function is using the original text variable. The global text was not updated. I’ll need to adjust the function to extract from the updated text instead. I'll implement a helper to ensure the correct extraction from the updated string.

def extract_function_from(src, name): m = re.search(r"function\s+"+re.escape(name)+r"\s*(", src) if not m: return None start = m.start() brace_start = src.find("{", m.end()) depth=0 for i in range(brace_start, len(src)): if src[i]=="{": depth+=1 elif src[i]=="}": depth-=1 if depth==0: end=i+1 return start,end,src[start:end] return None

s,e,calget_u = extract_function_from(updated, "calGetTables") print(calget_u)

Verifying ITF tables

Okay, everything is corrected now. Next, I’ll make sure that the ITF tables are properly inserted. I’ll search for _calRankITF_ to confirm that everything looks good in the updated code and the tables have been included as expected.

updated.find("calRankITF"), updated[updated.find("calRankITF")-100:updated.find("calRankITF")+200]

Verifying updates to analyzeHook and detectBimodalSkill

Okay, I’ve confirmed that analyzeHook is updated in the string, and we’ve inserted pmfBestWindow after pmfSumBetween. Next, I’ll patch the _detectBimodalSkill_ function and verify that the line looks correct in the updated code.

s,e,detb = extract_function_from(updated, "detectBimodalSkill")

show threshold line snippet

for line in detb.splitlines(): if "sdThreshold" in line: print(line)

Updating markovEffectiveHolds block

I now need to update the _markovEffectiveHolds_ block. Once done, I’ll verify to make sure everything is aligned properly and looking good. Hopefully, no unexpected issues pop up, but I'll double-check just to be sure everything is up to date.

s,e,mk = extract_function_from(updated, "markovEffectiveHolds")

find mkFloor line

for l in mk.splitlines(): if "_mkFloor" in l or "_mkIsItf" in l: print(l)

Checking for mkIsItf occurrences

It seems the replacement didn’t apply as expected. The old _mkFloor line printed, which might be due to indentation differences in the updated function — maybe the replacement string didn’t match because of different spaces. I’ll search for occurrences of _mkIsItf to track down where it’s failing.

updated.count("_mkIsItf"), updated.find("_mkIsItf")

Patching with regex for updates

The replacement didn’t work because I couldn’t find _mkIsItf. I need to patch _markovEffectiveHolds_ and _mismatchIdx with a more robust regex. Specifically, for _markovEffectiveHolds_, I'll modify lines like the ones for _mkTourK, _mkIsWta, _mkIsCh, _mkFloor, and _mkRange. I’ll locate the exact snippet around those updates for the patch to apply.

find snippet around _mkIsWta in updated

pos = updated.find("var _mkIsWta") print(updated[pos-80:pos+220])

Updating with regex patch

I’ll patch the code block using regex. Specifically, I’ll use re.sub to replace the relevant part of the code. This will let me apply the patch dynamically to ensure that everything updates as expected in a robust way without manually adjusting each line.

mk_pattern = r"var _mkTourK = taperTourKey$tourLabel$;\s*\n\svar _mkIsWta = $_mkTourK === 'WTA'$;\s\n\svar _mkIsCh = $_mkTourK === 'CH'$;\s\n\svar _mkFloor = _mkIsWta ? 0.50 : _mkIsCh ? 0.51 : 0.52;\s\n\s*var _mkRange = _mkIsWta ? 0.28 : _mkIsCh ? 0.29 : 0.30;" mk_repl = """var _mkTourK = taperTourKey(tourLabel); var _mkIsWta = (_mkTourK === 'WTA'); var _mkIsCh = (_mkTourK === 'CH'); var _mkIsItf = (_mkTourK === 'ITF'); var _mkFloor = _mkIsWta ? 0.50 : _mkIsCh ? 0.51 : _mkIsItf ? 0.51 : 0.52; var _mkRange = _mkIsWta ? 0.28 : _mkIsCh ? 0.29 : _mkIsItf ? 0.30 : 0.30;""" updated, n_mk = re.subn(mk_pattern, mk_repl, updated) n_mk, updated.count("_mkIsItf")

Confirming occurrences and checking patch

I noticed that while we inserted _mkIsItf once, there are three occurrences. This likely means it appears in other places like the floor and range assignments. I'll also check if the _mismatchIdxFromSeeds_ patch failed by confirming the count for _miIsItf.

updated.count("_miIsItf")

Fixing the mismatchIdx replacement

It looks like the mismatchIdx replacement failed due to spaces earlier, so I'll patch it similarly now. I'll search for the snippet around _miIsWta to ensure the replacement works properly this time and matches the expected pattern.

pos = updated.find("var _miIsWta") print(updated[pos-80:pos+260])

Plan for regex replacement

I’ll go ahead and apply a regex replacement to that block in a similar way as before. Hopefully, this time it'll work correctly and match the patterns more precisely without the issues from earlier. Let me patch it up to avoid those previous problems.

mi_pattern = r"var _miIsWta = $_miTourK === 'WTA'$;\s*\n\svar _miIsCh = $_miTourK === 'CH'$;\s\n\svar _miFloor = _miIsWta ? 0.50 : _miIsCh ? 0.51 : 0.52;\s\n\svar _miRange = _miIsWta ? 0.28 : _miIsCh ? 0.29 : 0.30;\s\n\svar _miHdFloor = _miIsWta ? 0.04 : _miIsCh ? 0.045 : 0.05;\s\n\s*var _miHdRange = _miIsWta ? 0.18 : _miIsCh ? 0.19 : 0.20;" mi_repl = """var _miIsWta = (_miTourK === 'WTA'); var _miIsCh = (_miTourK === 'CH'); var _miIsItf = (_miTourK === 'ITF'); var _miFloor = _miIsWta ? 0.50 : _miIsCh ? 0.51 : _miIsItf ? 0.51 : 0.52; var _miRange = _miIsWta ? 0.28 : _miIsCh ? 0.29 : _miIsItf ? 0.31 : 0.30; var _miHdFloor = _miIsWta ? 0.04 : _miIsCh ? 0.045 : _miIsItf ? 0.045 : 0.05; var _miHdRange = _miIsWta ? 0.18 : _miIsCh ? 0.19 : _miIsItf ? 0.22 : 0.20;""" updated, n_mi = re.subn(mi_pattern, mi_repl, updated) n_mi, updated.count("_miIsItf")

Checking pickTaperSeedA replacement

It seems like I might have missed something when replacing the pickTaperSeedA part earlier, so I should double-check. I'll look at the count for _ptIsItf to confirm if the replacement worked as expected. Hopefully, the issue is clear once I check—time to investigate further.

updated.count("_ptIsItf"), updated.find("_ptIsItf")

Fixing replacement failure

The replacement didn’t work as expected. I’ll patch things up by applying regex in a similar way. To do that, I need to locate the snippet around _ptIsCh, so I can test and ensure the fix is successful. Time to track down and adjust that section.

pos = updated.find("var _ptIsWta") print(updated[pos-80:pos+250])

Applying regex replacement

Looks like the next step is to use regex to replace the problematic part. I'll go ahead and apply that so things function as intended. Once that’s done, I'll check if the fix worked and move forward from there.

pt_pattern = r"var _ptIsWta = $_ptTourK === 'WTA'$;\s*\n\svar _ptIsCh\s=\s*$_ptTourK === 'CH'$;\s*\n\svar _ptCoinflip = _ptIsWta ? 0.025 : _ptIsCh ? 0.028 : 0.03;\s\n\svar _ptWeakDir\s=\s_ptIsWta ? 0.08\s: _ptIsCh ? 0.09\s*: 0.10;\s*\n\svar _ptBlendS\s=\s_ptIsWta ? 0.60\s: _ptIsCh ? 0.62\s*: 0.65;\s*\n\svar _ptBlendM\s=\s_ptIsWta ? 0.40\s: _ptIsCh ? 0.38\s*: 0.35;" pt_repl = """var _ptIsWta = (_ptTourK === 'WTA'); var _ptIsCh = (_ptTourK === 'CH'); var _ptIsItf = (_ptTourK === 'ITF'); var _ptCoinflip = _ptIsWta ? 0.025 : _ptIsCh ? 0.028 : _ptIsItf ? 0.028 : 0.03; var _ptWeakDir = _ptIsWta ? 0.08 : _ptIsCh ? 0.09 : _ptIsItf ? 0.095 : 0.10; var _ptBlendS = _ptIsWta ? 0.60 : _ptIsCh ? 0.62 : _ptIsItf ? 0.63 : 0.65; var _ptBlendM = _ptIsWta ? 0.40 : _ptIsCh ? 0.38 : _ptIsItf ? 0.37 : 0.35;""" updated, n_pt = re.subn(pt_pattern, pt_repl, updated) n_pt, updated.count("_ptIsItf")

Checking ORP confidence scalar patch

Alright, the ORP confidence scalar might have worked, but I need to verify. I'll check for occurrences of _scTourK === 'ITF' to make sure it's matching correctly. Once that’s confirmed, I’ll know if the patch was successful.

updated.count("_scTourK === 'ITF'")

Patching replacement with regex

It seems like our earlier replacement might have failed because of spacing issues. I'll need to patch it using regex in a similar way. To do that, I’ll locate the snippet around _scBase = and focus on applying the necessary fix there. Let's see how that works out.

pos = updated.find("var _scBase") print(updated[pos-80:pos+200])

Replacing with ITF

I’ll replace these two lines with "ITF." This seems like a straightforward fix, and I’m hoping this will align everything correctly. Afterward, I’ll double-check to ensure it doesn’t break anything else and that it behaves as expected. Let's implement this now.

sc_pattern = r"var _scBase = $_scTourK === 'WTA'$ ? 0.82 : $_scTourK === 'CH'$ ? 0.81 : 0.80;\s*\n\s*var _scRange = $_scTourK === 'WTA'$ ? 0.25 : $_scTourK === 'CH'$ ? 0.28 : 0.30;" sc_repl = "var _scBase = (_scTourK === 'WTA') ? 0.82 : (_scTourK === 'CH') ? 0.81 : (_scTourK === 'ITF') ? 0.83 : 0.80;\n var _scRange = (_scTourK === 'WTA') ? 0.25 : (_scTourK === 'CH') ? 0.28 : (_scTourK === 'ITF') ? 0.35 : 0.30;" updated, n_sc = re.subn(sc_pattern, sc_repl, updated) n_sc, updated.count("_scTourK === 'ITF'")

Verifying edge policy modifications

I see that I earlier inserted _epIsItf and replaced other lines as part of the edge policy changes. There might have been issues with spacing that could've prevented the update from being applied. I’ll check by searching for _epIsItf to ensure everything is correctly configured.

updated.count("_epIsItf"), updated.find("_epIsItf")

Finalizing updates and changes

The winner decision min thresholds are done, and the pmfTop line is updated. Now, I'm working on ensuring the analyzeHook uses the newly returned fields. It looks like the current code still expects the old fields, so I need to make sure everything works together, especially with the new Totals Most Likely format. Adjustments for “near-line mass” readout and wider band display are needed too. Almost there!

Finalizing adjustments and ITF integration

We’ve done the ITF calibration and various updates like modifying cluster projections and adjusting the fields to debug labels. Also, we’ve updated the relevant functions to use the new ITF-related variables, such as _miIsItf, _mkIsItf, and _ptIsItf. The getTotalsPick thresholds are now aligned, and everything is integrated as needed.

Updating patch notes and checking compatibility

I'll update the patch notes about Markov synchronization since the user mentioned stale history, although no change was requested. We also added the totPmfTopStr and mode values to the output, confirming those lines are scoped correctly. I'll check for potential issues with non-ASCII characters, like the en dash, which could cause compatibility problems.

Ensuring compatibility with character usage

The current code uses "—", which seems fine for Apps Script, but might break in older environments. Since their output uses it, I'll prefer using the ASCII hyphen "-" for stability. I'll update any inserted ranges or debug lines that use "–" to "-" while keeping the non-ASCII dashes in user text.

Updating code for compatibility and output

To ensure compatibility, I'll replace "–" with "-" in the code to avoid potential parsing issues, especially for older environments. Apps Script should be fine with Unicode, so I’ll leave previously used "–" in user strings. Regarding pmfBestWindow, I'll confirm it’s inserted correctly after its function declaration. Still, I'll perform a syntax check just to be sure. Then, I’ll create a new file and provide a download link.

basic sanity checks

checks = { "analyzeHook has nearMass": "nearMass" in extract_function_from(updated, "analyzeHook")[2], "Totals Most Likely inserted": "Totals Most Likely" in updated, "Totals PMF (top exacts)" in updated, "Hook — P(" not in updated, "calGetTables uses ITF tables": "calRankITF" in extract_function_from(updated, "calGetTables")[2], "_detectBimodalSkill ITF": "ITF" in [l for l in extract_function_from(updated, "detectBimodalSkill")[2].splitlines() if "sdThreshold" in l][0], "_pickTaperSeedA has _ptIsItf": "_ptIsItf" in extract_function_from(updated, "pickTaperSeedA")[2], "_mismatchIdxFromSeeds has _miIsItf": "_miIsItf" in extract_function_from(updated, "mismatchIdxFromSeeds")[2], "_markovEffectiveHolds has _mkIsItf": "_mkIsItf" in extract_function_from(updated, "markovEffectiveHolds")[2], "getTotalsPick has _epIsItf": "_epIsItf" in extract_function_from(updated, "getTotalsPick")[2], "_winnerDecision ITF thresholds": "else if (_wdTourK === 'ITF')" in extract_function_from(updated, "winnerDecision")[2], } checks

checks = { "analyzeHook has nearMass": "nearMass" in extract_function_from(updated, "analyzeHook")[2], "Totals Most Likely inserted": "Totals Most Likely" in updated, "Totals PMF (top exacts) inserted": "Totals PMF (top exacts)" in updated, "Old Hook line removed": 'Hook — P(' not in updated, "calGetTables uses ITF tables": "calRankITF" in extract_function_from(updated, "calGetTables")[2], "_detectBimodalSkill ITF": "ITF" in [l for l in extract_function_from(updated, "detectBimodalSkill")[2].splitlines() if "sdThreshold" in l][0], "_pickTaperSeedA has _ptIsItf": "_ptIsItf" in extract_function_from(updated, "pickTaperSeedA")[2], "_mismatchIdxFromSeeds has _miIsItf": "_miIsItf" in extract_function_from(updated, "mismatchIdxFromSeeds")[2], "_markovEffectiveHolds has _mkIsItf": "_mkIsItf" in extract_function_from(updated, "markovEffectiveHolds")[2], "getTotalsPick has _epIsItf": "_epIsItf" in extract_function_from(updated, "getTotalsPick")[2], "_winnerDecision ITF thresholds": "else if (_wdTourK === 'ITF')" in extract_function_from(updated, "winnerDecision")[2], } checks

Confirming syntax and function placement

I'll check the code for any unmatched braces, though it’s tricky. Since we know the modifications were inserted, I’ll also ensure that pmfBestWindow wasn’t inserted in the wrong spot. To do this, I’ll search for "function pmfBestWindow" and review the surrounding code.

pos = updated.find("function pmfBestWindow") print(updated[pos-200:pos+600])

Checking totals output and indentation

I need to confirm that the inserted totals section is correctly utilizing pmfBestWindow and that it is properly placed within the output block. It's likely fine, but I'll double-check the indentation around that section to ensure everything aligns correctly. Better safe than sorry!

pos = updated.find("Totals Expected:") print(updated[pos-200:pos+800])

Inspecting totals PMF line after insertion

We used an en dash in the string, which seems fine. Now, the Totals PMF line has been inserted after totPmfTopStr. I’ll need to take a look and make sure everything looks accurate and aligned with the rest of the code. Let’s give it a quick inspection to be sure.

pos = updated.find("Totals PMF (top exacts)") print(updated[pos-200:pos+300])

Inspecting indentation and patching hook blocks

Okay, I've noticed an indentation issue: there's a blank line, followed by var _totMode with four spaces in front. That looks good as it matches existing patterns. Now, I need to focus on patching the hook blocks. I'll inspect an area where this patch will be applied to ensure consistency.

pos = updated.find("Near-line mass @") print(updated[pos-200:pos+500])

Preparing file for download link

To create the updated script, we need to ensure it doesn’t exceed the variable length. After adjusting everything, I’ll save the file. I’ll create it in the Python environment and then provide a link to the user. I'll use markdown to share the sandbox path for easy access.

out_path = Path("/mnt/data/Tennislocks_V17.4_Cluster_Governor_v17.4.7_UPDATED_DISPLAYFIX_ITF.txt") out_path.write_text(updated, encoding="utf-8") out_path, out_path.stat().st_size

Thought for 14m 26s