Merge pull request #36 from ebouchut/fix/image_relative_links

Fix/image relative links

docs/data/glucodyn.md

@@ -16,37 +16,37 @@ Assuming you have a basic Heroku account to host your *Nightscout* website, you
 
 Login to your *Heroku* account to start the process, and then that will take you to your *mLab* information.
 
-![Dash 8](../img/dash8.png){width="750"}
+![Dash 8](img/dash8.png){width="750"}
 {align="center"}
 
 <br/>
-![Dash 6](../img/dash6.png){width="750"}
+![Dash 6](img/dash6.png){width="750"}
 {align="center"}
 
 Your *mLab* database name and API Key can be found on the same page, as shown below.  Copy and paste these bits of information into your User Settings in *Dash*.
 
 The format for the *MongoLab* API URL string is: `https://api.mlab.com/api/1/databases/your-database-name/collections/entries` where you are replacing the `your-database-name` part with your info from the first circled area shown below.
 
-![Dash 7](../img/dash7.png){width="750"}
+![Dash 7](img/dash7.png){width="750"}
 {align="center"}
 
 ### <span translate="no">Dash</span> data presentation
 
 *Dash* provides multiple views of your *mlab* information, and the data is updated live as your *Nightscout* data updates too.  While there are some constraints (cannot set your own low/high range limits), the data views are very useful for identifying difficult times of the day or difficult days of the week.
 
-![Dash 1](../img/dash1.png){width="750"}
+![Dash 1](img/dash1.png){width="750"}
 {align="center"}
 
-![Dash 2](../img/dash2.png){width="750"}
+![Dash 2](img/dash2.png){width="750"}
 {align="center"}
 
-![Dash 3](../img/dash3.png){width="750"}
+![Dash 3](img/dash3.png){width="750"}
 {align="center"}
 
-![Dash 4](../img/dash4.png){width="750"}
+![Dash 4](img/dash4.png){width="750"}
 {align="center"}
 
-![Dash 5](../img/dash5.png){width="750"}
+![Dash 5](img/dash5.png){width="750"}
 {align="center"}
 
 
@@ -59,7 +59,7 @@ Seeing the curves and understanding the effects of bolus timing, carbohydrate ab
 
 Originally, *Loop* used the same carbohydrate absorption and insulin models as *Glucodyn* uses. Those have since been updated in *Loop* with dynamic carbohydrate absorption and exponential curves for insulin. Even with those changes, the *GlucoDyn* tool can still provide users an excellent tool to visualize how small changes in bolusing can affect trends in blood glucose. For example, it’s quite interesting to see the effect of pre-bolusing. By delaying the carb intake by say 20 minutes, you can visualize the reduction of the maximum blood glucose. But, you have to be careful – before the carbohydrates have time to absorb insulin is working, and the minimum blood glucose will also drop. These are the kinds of tradeoffs that are critical to the management of T1D, and thankfully are automated by Loop&#39;s smart bolusing based on carbohydrate absorption estimates.
 
-![Dash 9](../img/dash9.png){width="750"}
+![Dash 9](img/dash9.png){width="750"}
 {align="center"}
 
 

docs/data/health.md

@@ -6,7 +6,7 @@ There's often confusion over the terminology surrounding Apple's health data sto
 
 * **HealthKit** -- Apple's iOS database for storing health-related data. App developers can choose to use HealthKit to store information from their apps such as heart rate, blood glucose, insulin use, and a long list of other parameters
 
-![Health Data](../img/health-data.png){width="350"}
+![Health Data](img/health-data.png){width="350"}
 {align="center"}
 
 * **Health App** -- Apple allows iOS users to manage HealthKit permissions and view stored HealthKit data through the use of Apple's Health app (standard on iPhones and iPods, but not available on iPads).  
@@ -28,7 +28,7 @@ At a minimum, you will need these HealthKit settings:
 
 You can always check your HealthKit settings by opening the Health App, clicking on *Sources* at the bottom bar, and then clicking on the app's name you are interested in, for example, Loop.
 
-![Health App](../img/healthapp.jpg){width="350"}
+![Health App](img/healthapp.jpg){width="350"}
 {align="center"}
 
 Potential conflicts can arise when third-party apps are granted access to HealthKit permissions that may interfere with Loop's specified data permissions. For example, carbohydrate data is stored in *Nightscout* and Spike for some users...you wouldn't want to enable *Spike* app to write duplicate carbohydrate entries that Loop would be reading. Therefore, you should disable other apps from writing carbohydrate data to HealthKit so that Loop does not read those other entries unintentionally.  Also, good practice, because carbohydrate entries in HealthKit that were created by non-Loop apps will not be able to customize carbohydrate absorption times nor be edited later if needed.
@@ -38,22 +38,22 @@ Potential conflicts can arise when third-party apps are granted access to Health
 Summaries of your carbohydrates, insulin, and blood glucose results can be found by clicking on the *Health Data* at the bottom bar, and then selecting either the large *Nutrition* box (for carbohydrates) or smaller *Results* line (for insulin deliveries and blood glucose results).
 
 
-![Health Data](../img/health_data.jpg){width="350"}
+![Health Data](img/health_data.jpg){width="350"}
 {align="center"}
 
 If you toggle on the "add to favorites" slider for the individual data categories (insulin, blood glucose, carbohydrates), the data from those categories will be added to your *Today* view for easy quick reference and access.
 
-![Today Health](../img/todayhealth.jpg){width="500"}
+![Today Health](img/todayhealth.jpg){width="500"}
 {align="center"}
 
 The summary data for the categories can help you follow monthly trends, help identify periods of insulin sensitivity/resistance, evaluate total daily insulin use, breakdown of basal rate vs bolus insulin, and carbohydrate consumption. You can sort your data trends by day, week, month, or year views and scroll back through time in each of those data trends.  You can even quickly use these data for endocrinology appointment discussions...as they provide the endocrinologist with a very quick and useful set of data points directly from your *Loop*.
 
 
-![Health 1](../img/health1.jpg){width="750"}
+![Health 1](img/health1.jpg){width="750"}
 {align="center"}
 
 If you drag two fingers separately like you are spreading them apart, you can get averages for the data set your fingers are covering, as shown below.
 
 
-![Health Average](../img/health-avg.jpg){width="350"}
+![Health Average](img/health-avg.jpg){width="350"}
 {align="center"}

docs/data/nightscout.md

@@ -5,7 +5,7 @@
 ## Nightscout Display
 *Nightscout* is highly recommended for *Loop* users, especially those using *Loop* as caregivers. *Nightscout* displays are often the easiest way to troubleshoot *Loop* settings if you are having problems and seeking input from others.  Below is some discussion about the general *Nightscout* display, as well as some <span translate="no">Loop</span>-specific display information.
 
-![Example](../img/example.jpg){width="700"}
+![Example](img/example.jpg){width="700"}
 {align="center"}
 
 ### Blood Glucose
@@ -42,37 +42,37 @@ The SAGE, BAGE, and CAGE pills are for sensor age, pump battery age, and cannula
 You can access the Reports tab from within your NS settings (the three horizontal lines in the upper right corner of your NS site).  There are several types of reports which may be useful to you and/or your health care provider. The report types are listed in tabs at the top of the Reports section, and you can also select the range of dates you'd like any report to cover.
 
 
-![Reports](../img/reports.png){width="700"}
+![Reports](img/reports.png){width="700"}
 {align="center"}
 
 ### Day to Day report
 
 The day-to-day report will show a detailed overlay of boluses, basal rates, carbohydrates, CGM, and treatment notes. If you select the optional check boxes, you can also see information such as the insulin distribution pie graphs shown on the right of the figure below.
 
 
-![Day to Day](../img/day-to-day.png){width="700"}
+![Day to Day](img/day-to-day.png){width="700"}
 {align="center"}
 
 ### Daily Stats report
 
 The daily stats report is a pie chart showing the daily breakdown of your low, in-range, and high time in target, as well as other statistical analysis of your BG trends.
 
-![Daily Stats](../img/daily-stats.png){width="700"}
+![Daily Stats](img/daily-stats.png){width="700"}
 {align="center"}
 
 ### Distribution report
 
 The distribution report is a combination of all the individual daily stats reports all into one pie chart for the date range selected.
 
 
-![Distribution](../img/distribution.png){width="700"}
+![Distribution](img/distribution.png){width="700"}
 {align="center"}
 
 ### Glucose Percentile report
 
 The glucose percentile report will help you see just how consistent your blood glucose is at various times of the day.  The average blood glucose is shown as a dark black line in the center of the colored bars.  The wider the colored areas spread out from the center black line, the more scattered and variable your blood glucose values at that time have tended to be.
 
-![Percentile](../img/percentile.png){width="700"}
+![Percentile](img/percentile.png){width="700"}
 {align="center"}
 
 For the graph above, for example, the blood glucose control around 4-6 am is very consistent.  The most variable time appears to be near lunchtime.  The time of day, when low blood glucose seems to be the most problematic, is between 4-6 pm, which happens to be this person's exercise time.  Based on the data in this graph, the person may benefit from setting a higher target about 2 hours before exercise time in order to help with the pattern of low blood glucose that occurs most often during that time.
@@ -81,5 +81,5 @@ For the graph above, for example, the blood glucose control around 4-6 am is ver
 
 The treatments report will show a listing of all the temporary basal rates set by *Loop*, as well as boluses, carbohydrates, site changes, and any other "treatments" which have been entered into NS.
 
-![Treatments](../img/treatments.png){width="=700"}
+![Treatments](img/treatments.png){width="=700"}
 {align="center"}

docs/data/tidepool.md

@@ -18,7 +18,7 @@ In Tidepool's own words, their commitment to diabetes data and accessibility
 Once you start uploading data into your *Tidepool* account, you'll see some of the benefits pretty quickly. Tidepool's data presentation is easy on the eyes. Lots of calm colors, logical data layout, quick to access important information...basically a breeze to get your needed data and get on with your analysis.
 
 
-![Tidepool Sample](../img/tidepool_sample.png){width="750"}
+![Tidepool Sample](img/tidepool_sample.png){width="750"}
 {align="center"}
 
 To use Tidepool's services, the process is pretty standard:
@@ -49,7 +49,7 @@ However, there has been a very exciting development! Tidepool's Mobile iOS a
 Sharing the data is simple. You can click on your account’s Share option and enter in the email addresses for those that you want to share with. Those people will need a *Tidepool* account. If they don’t have one currently, they will follow easy prompts for an account setup after they’ve received your share invitation. Clinics using *Tidepool* will have a *Tidepool* account email that you can add to your account, enabling the clinic to easily view your data. You can also remove access for anyone with a simple click.
 
 
-![Share Tidepool](../img/share_tidepool.png){width="550"}
+![Share Tidepool](img/share_tidepool.png){width="550"}
 {align="center"}
 
 ## Viewing your Tidepool data
@@ -68,13 +68,13 @@ There are two distinct viewing options for your *Tidepool* data, and they are no
 ### What Loop data will you see in desktop Chrome?
 You will see your Loop's temporary basals, CGM readings, boluses, notes, carbohydrates, and various metrics about your data distribution. If you separately load your blood glucose meter or any other supported device to *Tidepool*, those will also overlay.
 
-![Loop in Tidepool](../img/loop_in_tidepool.png){width="750"}
+![Loop in Tidepool](img/loop_in_tidepool.png){width="750"}
 {align="center"}
 
-![Loop in Tidepool 2](../img/loop_in_tidepool2.png){width="750"}
+![Loop in Tidepool 2](img/loop_in_tidepool2.png){width="750"}
 {align="center"}
 
-![Loop in Tidepool 3](../img/loop_in_tidepool3.png){width="750"}
+![Loop in Tidepool 3](img/loop_in_tidepool3.png){width="750"}
 {align="center"}
 
 ### What Loop data will you see in the Tidepool Mobile app?
@@ -86,7 +86,7 @@ You will see your Loop's temporary basals, CGM readings, boluses, notes, car
 
 For example, here’s a sample note+data set below from my *Tidepool* Mobile app.  Over the last couple of hours, my daughter noticed that she was staying above target (unusual for her on *Loop* with the meal she had) for quite a while. She had given a couple of small corrections (see the two 1-unit correction boluses?) without result. She started her secondary troubleshooting…if it’s not the food, maybe it’s the infusion site? She realized it has been 4.5 days since changing her site. She changed the site and logged a note using the *Tidepool* Mobile app. That note appears in the <span>*Tidepool Mobile* application</span>, on my phone. It also shows up on her Tidepool&#39;s data, for her endocrinologist to see too, and we can refresh the view to see how blood glucose trends for the next 7 hours after the site change.
 
-![iOS Tidepool Example](../img/ios_tidepool_example.png){width="250"}
+![iOS Tidepool Example](img/ios_tidepool_example.png){width="250"}
 {align="center"}
 
 ## Tidepool&#39;s Mobile app for iOS/iPhone
@@ -106,7 +106,7 @@ You mean, what OTHER cool thing can the *Tidepool* Mobile application do besides
 
 For an easy example, search for the word burrito (doesn’t have to be a hashtag), and any notes with the word “burrito” will be available for review, as well as any added comments.
 
-![iOS Tidepool Example 2](../img/ios_tidepool_example2.png){width="450"}
+![iOS Tidepool Example 2](img/ios_tidepool_example2.png){width="450"}
 {align="center"}
 
 Hormones can also be easily tracked with notes. *What day-of-the-month and how did I change the basals?* Looking to find patterns in those female hormones? This could be a really slick tracking tool to easily log periods of insulin resistance and what part of the cycle they are occurring at.

docs/how-to/bolus.md

@@ -14,7 +14,7 @@ The transition to Loop use may be confusing at first for these meals since you c
 
 For an example of Loop's bolus adjustments using carbohydrate absorption time, let's take a look at an example meal.  This is an example of a long absorption complex carbohydrate meal. This is a mushroom (arborio) risotto dish with heavy cream and cheese ingredients. While some white rice can be fairly quick acting, after several times eating this dish, the family has noticed that the meal tends to have a longer duration of impact on blood glucose. Using a "taco" icon (3 hours absorption) was causing slight low blood glucose soon after eating the meal. Therefore, they have been using the pizza icon to enter the meal's carbohydrate absorption time.
 
-![Pizza Bolus](../img/pizza_bolus.jpg){width="400"}
+![Pizza Bolus](img/pizza_bolus.jpg){width="400"}
 {align="center"}
 
 The initial meal entry was 70g at a "pizza" icon aborption time (4 hours). Based on carbohydrate ratio of 8 g/U, the initial bowl of risotto at 60g should have been a bolus of 7.5 units. Loop recommended 5.3 units, or about 70% of the total bolus that would be needed to cover the total carbohydrates. Loop recommended the lower upfront bolus because a full bolus would have overwhelmed the slow absorption of carbohydrates, and the likelihood would be a low blood glucose shortly after eating. 

docs/how-to/exercise.md

@@ -28,7 +28,7 @@ There are three types of exercise:
 * Mixed
     * Mixed exercise is combination of the aerobic and anaerobic activity such as basketball or soccer. Managing blood glucose levels with mixed exercise is difficult, but using a tool like a continuous glucose monitor can help greatly.
 
-![3 Types of Exercise Chart](../img/3-types-of-exercise-chart.png){width="750"}
+![3 Types of Exercise Chart](img/3-types-of-exercise-chart.png){width="750"}
 {align="center"}
 
 Glucose levels during sports affect performance in many ways: strength, stamina, speed, agility, flexibility, safety and mental sharpness.

docs/how-to/iob.md

@@ -17,7 +17,7 @@ This Looped group post started the conversation:
 
 To illustrate how to use morning IOB and blood glucose to check your basal rates, we will walk through a series of screenshots from a recent Loop experience. When the Looper woke up, she was below her 95 mg/dL target, but relatively steady. At about 8:48am, Nightscout showed negative IOB of -1.33 units, blood glucose of 90 mg/dL and slightly rising but still below a target of 95 mg/dL. (Note: this situation is similar to what the original Facebook poster above was describLooped2](ing.)
 
-![Looped2](../img/looped2.jpg){width="750"}
+![Looped2](img/looped2.jpg){width="750"}
 {align="center"}
 
 Looking back on the night, blood glucose was pretty much below target the whole night and her scheduled basal delivery was turning off/on in an alternating pattern (the blue pattern area). Blood glucose wasn't concerning nor were alarms going off. *However*, this combination of data is a great indicator that basal rates need to be decreased. The tendency could be to let Loop just keep plodding along like this, but it can lead to certain less than desirable stress points on the algorithm.
@@ -39,31 +39,31 @@ In this example,  the user's basal rates were lowered across the board. All of t
 
 The adjustment to basal rates caused Loop to reevaluate its math. After adjustment, Loop now has a negative IOB of -0.55 units vs the previous value of -1.33 units. This is a more reasonable given the situation. The prediction line with a -0.55 units IOB was not predicting nearly as aggressive of a "rebound" blood glucose rise.
 
-![Looped3](../img/looped3.jpg){width="750"}
+![Looped3](img/looped3.jpg){width="750"}
 {align="center"}
 
 Why did IOB and prediction change?
 
 The visualization below might be easier. The red line is how loop knew things to be before basal rates were adjusted lower. The purple line is how Loop viewed basal schedule after the adjustment lower.
 
-![Looped4](../img/looped4.jpg){width="750"}
+![Looped4](img/looped4.jpg){width="750"}
 {align="center"}
 
 The green arrows highlight parts of the graph that are recalculated by Loop when the basal schedule was adjusted lower. Instead of Loop thinking those were NEEDED basals (aka, conforming to the old basal schedule), now Loop perceives those as "extra basal" insulin deliveries. Now those insulin deliveries are sitting ABOVE my scheduled basal dotted line in Nightscout. They are actually instances of positive IOB and therefore Loop is now correctly getting closer to realizing that perhaps all of that extra wasn't needed.
 
-![Looped5](../img/looped5.jpg){width="750"}
+![Looped5](img/looped5.jpg){width="750"}
 {align="center"}
 
 The negative/positive IOB plus a quick glance at overnight Loop actions/blood glucose relative to targets is a quick easy check on overnight basals.
 
 If one was really exacting, you could adjust basals until a number closer to 0 IOB. In practical use though, getting roughly closer is usually helpful enough and smaller adjustments could be made later if still needed. The graph below shows the results several hours after the basals were decreased.  As you can see, looking pretty decent.
 
-![Looped7](../img/looped7.jpg){width="750"}
+![Looped7](img/looped7.jpg){width="750"}
 {align="center"}
 
 The confirmation that adjustments were on-track would also be provided by looking at morning blood glucose and IOB the following morning. As you can see below, the user was at target blood glucose and carrying a very small amount of IOB. Also, there are far fewer instances of basals alternating off/on. All good signs that the basal adjustments were reasonable.
 
-![Looped6](../img/looped6.jpg){width="350"}
+![Looped6](img/looped6.jpg){width="350"}
 {align="center"}