Update docs of visualization module
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@ -20,7 +20,7 @@ These plots can be used as a rough indication of the smartphone monitoring cover
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## 2. Heatmaps of overall data yield
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## 2. Heatmaps of overall data yield
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These heatmaps are a break down per time segment and per participant of [Visualization 1](#1-histograms-of-phone-data-yield). Heatmap's rows represent participants, columns represent time segment instances and the cells’ color represent the valid yielded minute or hour ratio for a participant during a time segment instance.
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These heatmaps are a break down per time segment and per participant of [Visualization 1](#1-histograms-of-phone-data-yield). Heatmap's rows represent participants, columns represent time segment instances and the cells’ color represent the valid yielded minute or hour ratio for a participant during a time segment instance.
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As different participants might join a study on different dates and time segments can be of any length and start on any day, the x-axis can be labelled with the absolute time of the start of each time segment instance or the time delta between the start of each time segment instance minus the start of the first instance. These plots provide a quick study overview of the monitoring coverage per person and per time segment.
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As different participants might join a study on different dates and time segments can be of any length and start on any day, the x-axis can be labelled with the absolute time of each time segment instance or the time delta between each time segment instance and the start of the first instance for each participant. These plots provide a quick study overview of the monitoring coverage per person and per time segment.
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The figure below shows the heatmap of the valid yielded minute ratio for participants example01 and example02 on daily segments and, as we inferred from the previous histogram, the lighter (yellow) color on most time segment instances (cells) indicate both phones sensed data without interruptions for most days (except for the first and last ones).
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The figure below shows the heatmap of the valid yielded minute ratio for participants example01 and example02 on daily segments and, as we inferred from the previous histogram, the lighter (yellow) color on most time segment instances (cells) indicate both phones sensed data without interruptions for most days (except for the first and last ones).
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@ -63,7 +63,7 @@ The figure below shows this heatmap for phone sensors collected by participant e
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## 4. Heatmap of sensor row count
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## 4. Heatmap of sensor row count
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These heatmaps are a per-sensor breakdown of [Visualization 1](#1-histograms-of-phone-data-yield) and [Visualization 2](#2-heatmaps-of-overall-data-yield). Note that the second row (ratio of valid yielded minutes) of this heatmap matches the respective participant (bottom) row the screenshot in Visualization 2.
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These heatmaps are a per-sensor breakdown of [Visualization 1](#1-histograms-of-phone-data-yield) and [Visualization 2](#2-heatmaps-of-overall-data-yield). Note that the second row (ratio of valid yielded minutes) of this heatmap matches the respective participant (bottom) row the screenshot in Visualization 2.
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In these heatmaps rows represent phone or Fitbit sensors, columns represent time segment instances and cell’s color shows the normalized (0 to 1) row count of each sensor within a time segment instance. RAPIDS creates one heatmap per participant and they can be used to judge missing data on a per participant and per sensor basis.
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In these heatmaps rows represent phone or Fitbit sensors, columns represent time segment instances and cell’s color shows the normalized (0 to 1) row count of each sensor within a time segment instance. A grey cell represents missing data in that time segment instance. RAPIDS creates one heatmap per participant and they can be used to judge missing data on a per participant and per sensor basis.
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The figure below shows data for 14 phone sensors (including data yield) of example01’s daily segments. From the top two rows, we can see that the phone was sensing data for most of the monitoring period (as suggested by Figure 3 and Figure 4). We can also infer how phone usage influenced the different sensor streams; there are peaks of screen events during the first day (Apr 23rd), peaks of location coordinates on Apr 26th and Apr 30th, and no sent or received SMS except for Apr 23rd, Apr 29th and Apr 30th (unlabeled row between screen and locations).
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The figure below shows data for 14 phone sensors (including data yield) of example01’s daily segments. From the top two rows, we can see that the phone was sensing data for most of the monitoring period (as suggested by Figure 3 and Figure 4). We can also infer how phone usage influenced the different sensor streams; there are peaks of screen events during the first day (Apr 23rd), peaks of location coordinates on Apr 26th and Apr 30th, and no sent or received SMS except for Apr 23rd, Apr 29th and Apr 30th (unlabeled row between screen and locations).
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