R CMD check passed

Zuguang Gu authored on 20/09/2018 12:48:08
Showing1 changed files
 1 1 deleted file mode 100755 ... ... @@ -1,57 +0,0 @@ 1 -\name{plotDataFrame} 2 -\alias{plotDataFrame} 3 -\title{ 4 -Quickly visualize a data frame 5 -} 6 -\description{ 7 -Quickly visualize a data frame 8 -} 9 -\usage{ 10 -plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 11 - show_column_names = TRUE, group = NULL, group_names = names(group), 12 - main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE, 13 - cluster_columns = TRUE, row_order = NULL, ...) 14 -} 15 -\arguments{ 16 - 17 - \item{df}{a data frame.} 18 - \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are treated as under same measurement and should be grouped.} 19 - \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded, because it doesn't make any sense to visualize a character vector or matrix that contains huge number of unique elements through a heatmap.} 20 - \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 21 - \item{show_column_names}{whether show column names for all heatmaps.} 22 - \item{group}{a list of index that defines the groupping.} 23 - \item{group_names}{names for each group.} 24 - \item{main_heatmap}{which group is the main heatmap?} 25 - \item{km}{a value larger than 1 means applying k-means clustering on rows for the main heatmap.} 26 - \item{split}{one or multiple variables that split the rows.} 27 - \item{cluster_rows}{whether perform clustering on rows of the main heatmap.} 28 - \item{cluster_columns}{whether perform clustering on columns for all heatmaps.} 29 - \item{row_order}{order of rows, remember to turn off \code{cluster_rows}} 30 - \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 31 - 32 -} 33 -\details{ 34 -The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to 35 -visualize information that are stored in a data frame. 36 - 37 -There are only a few settings in this function, so the heamtap generated by this functioin 38 -may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually 39 -constructing a \code{\link{HeatmapList}} object. 40 -} 41 -\value{ 42 -A \code{\link{HeatmapList}} object. 43 -} 44 -\author{ 45 -Zuguang Gu  46 -} 47 -\examples{ 48 -df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 49 - large = runif(10)*100, 50 - t1 = sample(letters[1:3], 10, replace = TRUE), 51 - matrix(runif(60), nrow = 10, dimnames = list(LETTERS[1:10], LETTERS[1:6])), 52 - t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 53 -plotDataFrame(df) 54 -plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 55 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 56 - 57 -}

Merge branch 'master' into devel

z.gu authored on 12/11/2015 10:07:49
Showing1 changed files
 ... ... @@ -10,13 +10,13 @@ Quickly visualize a data frame 10 10  plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 11 11  show_column_names = TRUE, group = NULL, group_names = names(group), 12 12  main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE, 13 - cluster_columns = TRUE, ...) 13 + cluster_columns = TRUE, row_order = NULL, ...) 14 14  } 15 15  \arguments{ 16 16   17 17  \item{df}{a data frame.} 18 - \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare treated as under same measurement and should be grouped.} 19 - \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded, because it doesn't make any sense to visualize a character vector or matrixthat contains huge number of unique elements through a heatmap.} 18 + \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are treated as under same measurement and should be grouped.} 19 + \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded, because it doesn't make any sense to visualize a character vector or matrix that contains huge number of unique elements through a heatmap.} 20 20  \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 21 21  \item{show_column_names}{whether show column names for all heatmaps.} 22 22  \item{group}{a list of index that defines the groupping.} ... ... @@ -26,6 +26,7 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 26 26  \item{split}{one or multiple variables that split the rows.} 27 27  \item{cluster_rows}{whether perform clustering on rows of the main heatmap.} 28 28  \item{cluster_columns}{whether perform clustering on columns for all heatmaps.} 29 + \item{row_order}{order of rows, remember to turn off \code{cluster_rows}} 29 30  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 30 31   31 32  }

Merge branch 'master' into devel

z.gu authored on 07/09/2015 20:39:32
Showing1 changed files
 1 1 old mode 100644 2 2 new mode 100755

resolve conflict from master branch

z.gu authored on 03/09/2015 20:32:44
Showing1 changed files
 ... ... @@ -33,12 +33,12 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 33 33  The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 34  visualize information that are stored in a data frame. 35 35   36 -There are only a few advanced settings in this function, so the heamtap generated by this functioin 36 +There are only a few settings in this function, so the heamtap generated by this functioin 37 37  may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually 38 38  constructing a \code{\link{HeatmapList}} object. 39 39  } 40 40  \value{ 41 -a \code{\link{HeatmapList}} object. 41 +A \code{\link{HeatmapList}} object. 42 42  } 43 43  \author{ 44 44  Zuguang Gu

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refresh docs

z.gu authored on 12/08/2015 22:49:59
Showing1 changed files
 ... ... @@ -32,6 +32,7 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 32 32  \details{ 33 33  The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 34  visualize information that are stored in a data frame. 35 + 35 36  There are only a few advanced settings in this function, so the heamtap generated by this functioin 36 37  may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually 37 38  constructing a \code{\link{HeatmapList}} object.

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Merge branch 'master' of https://github.com/jokergoo/mheatmap

Commit id: 478962957a34b7a5e87c8336989bae3df54f9559

change default colors

z.gu authored on 12/08/2015 22:03:22
Showing1 changed files
 ... ... @@ -10,7 +10,8 @@ Quickly visualize a data frame 10 10  plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 11 11  show_column_names = TRUE, group = NULL, group_names = names(group), 12 12  main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE, 13 - cluster_columns = TRUE, ...)} 13 + cluster_columns = TRUE, ...) 14 +} 14 15  \arguments{ 15 16   16 17  \item{df}{a data frame.} ... ... @@ -26,6 +27,7 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 26 27  \item{cluster_rows}{whether perform clustering on rows of the main heatmap.} 27 28  \item{cluster_columns}{whether perform clustering on columns for all heatmaps.} 28 29  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 30 + 29 31  } 30 32  \details{ 31 33  The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to ... ... @@ -49,4 +51,5 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 49 51  plotDataFrame(df) 50 52  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 51 53  main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 54 + 52 55  }

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refreshed documentations

z.gu authored on 11/08/2015 10:42:08
Showing1 changed files
 ... ... @@ -2,11 +2,9 @@ 2 2  \alias{plotDataFrame} 3 3  \title{ 4 4  Quickly visualize a data frame 5 - 6 5  } 7 6  \description{ 8 7  Quickly visualize a data frame 9 - 10 8  } 11 9  \usage{ 12 10  plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, ... ... @@ -32,33 +30,17 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 32 30  \details{ 33 31  The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 32  visualize information that are stored in a data frame. 35 - 36 33  There are only a few advanced settings in this function, so the heamtap generated by this functioin 37 34  may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually 38 35  constructing a \code{\link{HeatmapList}} object. 39 - 40 36  } 41 37  \value{ 42 38  a \code{\link{HeatmapList}} object. 43 - 44 39  } 45 40  \author{ 46 41  Zuguang Gu  47 - 48 42  } 49 43  \examples{ 50 - 51 - 52 - 53 - 54 - 55 - 56 - 57 - 58 - 59 - 60 - 61 - 62 44  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 63 45  large = runif(10)*100, 64 46  t1 = sample(letters[1:3], 10, replace = TRUE), ... ... @@ -66,4 +48,5 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 66 48  t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 67 49  plotDataFrame(df) 68 50  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 69 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")} 51 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 52 +}

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comprehensive modifications

z.gu authored on 10/08/2015 22:17:54
Showing1 changed files
 ... ... @@ -54,6 +54,11 @@ Zuguang Gu  54 54   55 55   56 56   57 + 58 + 59 + 60 + 61 + 57 62  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 58 63  large = runif(10)*100, 59 64  t1 = sample(letters[1:3], 10, replace = TRUE),

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Commit id: 73171be89c157222e8e71e85daa8a37ce509a4e2

add border argument in anno_* family functions

z.gu authored on 06/08/2015 17:46:06
Showing1 changed files
 ... ... @@ -53,6 +53,7 @@ Zuguang Gu  53 53   54 54   55 55   56 + 56 57  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 57 58  large = runif(10)*100, 58 59  t1 = sample(letters[1:3], 10, replace = TRUE),

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Commit id: 3429d28233ef2cbeafcd05307042d7c7aa54a2a2

z.gu authored on 06/08/2015 16:40:59
Showing1 changed files
 ... ... @@ -49,6 +49,10 @@ Zuguang Gu  49 49  \examples{ 50 50   51 51   52 + 53 + 54 + 55 + 52 56  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 53 57  large = runif(10)*100, 54 58  t1 = sample(letters[1:3], 10, replace = TRUE),

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allow reordering

z.gu authored on 04/08/2015 20:24:37
Showing1 changed files
 ... ... @@ -47,6 +47,8 @@ Zuguang Gu  47 47   48 48  } 49 49  \examples{ 50 + 51 + 50 52  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 51 53  large = runif(10)*100, 52 54  t1 = sample(letters[1:3], 10, replace = TRUE),

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remove plot.HeatmapList and print.HeatmapList

z.gu authored on 18/07/2015 18:14:29
Showing1 changed files
 ... ... @@ -1,44 +1,45 @@ 1 1  \name{plotDataFrame} 2 2  \alias{plotDataFrame} 3 3  \title{ 4 -Visualize a data frame 4 +Quickly visualize a data frame 5 5   6 6  } 7 7  \description{ 8 -Visualize a data frame 8 +Quickly visualize a data frame 9 9   10 10  } 11 11  \usage{ 12 -plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE, 13 - group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL, 14 - cluster_rows = TRUE, cluster_columns = TRUE, ...)} 12 +plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, 13 + show_column_names = TRUE, group = NULL, group_names = names(group), 14 + main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE, 15 + cluster_columns = TRUE, ...)} 15 16  \arguments{ 16 17   17 - \item{df}{a data frame} 18 - \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.} 19 - \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.} 18 + \item{df}{a data frame.} 19 + \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare treated as under same measurement and should be grouped.} 20 + \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded, because it doesn't make any sense to visualize a character vector or matrixthat contains huge number of unique elements through a heatmap.} 20 21  \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 21 - \item{show_column_names}{whether show column names for all heatmaps} 22 - \item{group}{a list of index that defines the groupping} 23 - \item{group_names}{names for each group} 24 - \item{main_heatmap}{which group is the main heatmap} 25 - \item{km}{apply k-means clustering on rows for the main heatmap} 26 - \item{split}{set a splitting variable on rows for the main heatmap} 27 - \item{cluster_rows}{whether perform clustering on rows of the first heatmap} 28 - \item{cluster_columns}{whether perform clustering on columns for all heatmaps} 22 + \item{show_column_names}{whether show column names for all heatmaps.} 23 + \item{group}{a list of index that defines the groupping.} 24 + \item{group_names}{names for each group.} 25 + \item{main_heatmap}{which group is the main heatmap?} 26 + \item{km}{a value larger than 1 means applying k-means clustering on rows for the main heatmap.} 27 + \item{split}{one or multiple variables that split the rows.} 28 + \item{cluster_rows}{whether perform clustering on rows of the main heatmap.} 29 + \item{cluster_columns}{whether perform clustering on columns for all heatmaps.} 29 30  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 30 31  } 31 32  \details{ 32 -The data frame contains information from different aspects and different measurements are applied 33 -on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to 33 +The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 34  visualize information that are stored in a data frame. 35 35   36 -There are not many advanced settings in this function. Users can customize the style of the heatmaps 37 -by constructing a \code{\link{HeatmapList}} object. 36 +There are only a few advanced settings in this function, so the heamtap generated by this functioin 37 +may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually 38 +constructing a \code{\link{HeatmapList}} object. 38 39   39 40  } 40 41  \value{ 41 -a \code{\link{HeatmapList}} object 42 +a \code{\link{HeatmapList}} object. 42 43   43 44  } 44 45  \author{ ... ... @@ -46,7 +47,6 @@ Zuguang Gu  46 47   47 48  } 48 49  \examples{ 49 - 50 50  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 51 51  large = runif(10)*100, 52 52  t1 = sample(letters[1:3], 10, replace = TRUE),

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Commit id: 4cbce102eabb1633fc8980b1374795bfb44507df

Merge branch 'master' of https://github.com/jokergoo/ComplexHeatmap

Commit id: a15bbec76c85c15bc27273ce15f5118ea087132f

refreshed documentatinos

Commit id: b1fe0a94aa09a4a47e5a02383ce662580f057bdc

ColorMapping object has default value for name slot

z.gu authored on 16/07/2015 15:21:23
Showing1 changed files
 ... ... @@ -46,6 +46,7 @@ Zuguang Gu  46 46   47 47  } 48 48  \examples{ 49 + 49 50  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 50 51  large = runif(10)*100, 51 52  t1 = sample(letters[1:3], 10, replace = TRUE),

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Commit id: ff9ffa810ca9f16a253861d97301062962dbe38b

titles support expression now

z.gu authored on 13/07/2015 21:26:16
Showing1 changed files
 ... ... @@ -46,8 +46,6 @@ Zuguang Gu  46 46   47 47  } 48 48  \examples{ 49 - 50 - 51 49  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 52 50  large = runif(10)*100, 53 51  t1 = sample(letters[1:3], 10, replace = TRUE),

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Commit id: e811f8100ef035ff75c16312b3e5112cc82d4a49

continuous legend is supported

z.gu authored on 13/07/2015 10:21:55
Showing1 changed files
 ... ... @@ -46,6 +46,8 @@ Zuguang Gu  46 46   47 47  } 48 48  \examples{ 49 + 50 + 49 51  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 50 52  large = runif(10)*100, 51 53  t1 = sample(letters[1:3], 10, replace = TRUE),

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Commit id: 2786dac4ddaa97c69cc24e29e121ed1a1624cdf4

Merge branch 'master' of https://github.com/jokergoo/mheatmap

Commit id: a61c101325601aa0d4d3ba81e10c33d4a8b34c63

rows can be split if providing a clustering object

z.gu authored on 06/07/2015 22:31:19
Showing1 changed files
 ... ... @@ -46,8 +46,6 @@ Zuguang Gu  46 46   47 47  } 48 48  \examples{ 49 - 50 - 51 49  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 52 50  large = runif(10)*100, 53 51  t1 = sample(letters[1:3], 10, replace = TRUE), ... ... @@ -55,6 +53,4 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 55 53  t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 56 54  plotDataFrame(df) 57 55  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 58 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 59 - 60 -} 56 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

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refreshed documentations

z.gu authored on 23/06/2015 10:24:06
Showing1 changed files
 ... ... @@ -47,6 +47,7 @@ Zuguang Gu  47 47  } 48 48  \examples{ 49 49   50 + 50 51  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 51 52  large = runif(10)*100, 52 53  t1 = sample(letters[1:3], 10, replace = TRUE),

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refreshed documentations

z.gu authored on 23/06/2015 08:33:59
Showing1 changed files
 ... ... @@ -46,6 +46,7 @@ Zuguang Gu  46 46   47 47  } 48 48  \examples{ 49 + 49 50  df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 50 51  large = runif(10)*100, 51 52  t1 = sample(letters[1:3], 10, replace = TRUE), ... ... @@ -53,4 +54,6 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 53 54  t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 54 55  plotDataFrame(df) 55 56  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 56 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")} 57 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 58 + 59 +}

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refresh documentations and NAMESPACE

z.gu authored on 22/06/2015 21:57:04
Showing1 changed files
 ... ... @@ -1,25 +1,22 @@ 1 1  \name{plotDataFrame} 2 2  \alias{plotDataFrame} 3 3  \title{ 4 -Visualize a data frame  5 - 4 +Visualize a data frame 6 5   7 6  } 8 7  \description{ 9 -Visualize a data frame  10 - 8 +Visualize a data frame 11 9   12 10  } 13 11  \usage{ 14 12  plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE, 15 13  group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL, 16 - cluster_rows = TRUE, cluster_columns = TRUE, ...) 17 -} 14 + cluster_rows = TRUE, cluster_columns = TRUE, ...)} 18 15  \arguments{ 19 16   20 17  \item{df}{a data frame} 21 - \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.} 22 - \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.} 18 + \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.} 19 + \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.} 23 20  \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 24 21  \item{show_column_names}{whether show column names for all heatmaps} 25 22  \item{group}{a list of index that defines the groupping} ... ... @@ -30,23 +27,22 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_colum 30 27  \item{cluster_rows}{whether perform clustering on rows of the first heatmap} 31 28  \item{cluster_columns}{whether perform clustering on columns for all heatmaps} 32 29  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 33 - 34 30  } 35 31  \details{ 36 -The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  37 - 38 -There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  32 +The data frame contains information from different aspects and different measurements are applied 33 +on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 +visualize information that are stored in a data frame. 39 35   36 +There are not many advanced settings in this function. Users can customize the style of the heatmaps 37 +by constructing a \code{\link{HeatmapList}} object. 40 38   41 39  } 42 40  \value{ 43 -a \code{\link{HeatmapList}} object  44 - 41 +a \code{\link{HeatmapList}} object 45 42   46 43  } 47 44  \author{ 48 -Zuguang Gu  49 - 45 +Zuguang Gu  50 46   51 47  } 52 48  \examples{ ... ... @@ -57,5 +53,4 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 57 53  t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 58 54  plotDataFrame(df) 59 55  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 60 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 61 -} 56 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

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rotation for heatmap title supported

z.gu authored on 22/06/2015 15:09:06
Showing1 changed files
 ... ... @@ -1,22 +1,25 @@ 1 1  \name{plotDataFrame} 2 2  \alias{plotDataFrame} 3 3  \title{ 4 -Visualize a data frame 4 +Visualize a data frame  5 + 5 6   6 7  } 7 8  \description{ 8 -Visualize a data frame 9 +Visualize a data frame  10 + 9 11   10 12  } 11 13  \usage{ 12 14  plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE, 13 15  group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL, 14 - cluster_rows = TRUE, cluster_columns = TRUE, ...)} 16 + cluster_rows = TRUE, cluster_columns = TRUE, ...) 17 +} 15 18  \arguments{ 16 19   17 20  \item{df}{a data frame} 18 - \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.} 19 - \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.} 21 + \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.} 22 + \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.} 20 23  \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 21 24  \item{show_column_names}{whether show column names for all heatmaps} 22 25  \item{group}{a list of index that defines the groupping} ... ... @@ -27,22 +30,23 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_colum 27 30  \item{cluster_rows}{whether perform clustering on rows of the first heatmap} 28 31  \item{cluster_columns}{whether perform clustering on columns for all heatmaps} 29 32  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 33 + 30 34  } 31 35  \details{ 32 -The data frame contains information from different aspects and different measurements are applied 33 -on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 -visualize information that are stored in a data frame. 36 +The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  37 + 38 +There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  35 39   36 -There are not many advanced settings in this function. Users can customize the style of the heatmaps 37 -by constructing a \code{\link{HeatmapList}} object. 38 40   39 41  } 40 42  \value{ 41 -a \code{\link{HeatmapList}} object 43 +a \code{\link{HeatmapList}} object  44 + 42 45   43 46  } 44 47  \author{ 45 -Zuguang Gu  48 +Zuguang Gu  49 + 46 50   47 51  } 48 52  \examples{ ... ... @@ -53,4 +57,5 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 53 57  t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 54 58  plotDataFrame(df) 55 59  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 56 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")} 60 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 61 +}

Commit made by the Bioconductor Git-SVN bridge.

check row orders

z.gu authored on 21/06/2015 17:44:09
Showing1 changed files
 ... ... @@ -1,25 +1,22 @@ 1 1  \name{plotDataFrame} 2 2  \alias{plotDataFrame} 3 3  \title{ 4 -Visualize a data frame  5 - 4 +Visualize a data frame 6 5   7 6  } 8 7  \description{ 9 -Visualize a data frame  10 - 8 +Visualize a data frame 11 9   12 10  } 13 11  \usage{ 14 12  plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE, 15 13  group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL, 16 - cluster_rows = TRUE, cluster_columns = TRUE, ...) 17 -} 14 + cluster_rows = TRUE, cluster_columns = TRUE, ...)} 18 15  \arguments{ 19 16   20 17  \item{df}{a data frame} 21 - \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.} 22 - \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.} 18 + \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.} 19 + \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.} 23 20  \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 24 21  \item{show_column_names}{whether show column names for all heatmaps} 25 22  \item{group}{a list of index that defines the groupping} ... ... @@ -30,23 +27,22 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_colum 30 27  \item{cluster_rows}{whether perform clustering on rows of the first heatmap} 31 28  \item{cluster_columns}{whether perform clustering on columns for all heatmaps} 32 29  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 33 - 34 30  } 35 31  \details{ 36 -The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  37 - 38 -There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  32 +The data frame contains information from different aspects and different measurements are applied 33 +on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to 34 +visualize information that are stored in a data frame. 39 35   36 +There are not many advanced settings in this function. Users can customize the style of the heatmaps 37 +by constructing a \code{\link{HeatmapList}} object. 40 38   41 39  } 42 40  \value{ 43 -a \code{\link{HeatmapList}} object  44 - 41 +a \code{\link{HeatmapList}} object 45 42   46 43  } 47 44  \author{ 48 -Zuguang Gu  49 - 45 +Zuguang Gu  50 46   51 47  } 52 48  \examples{ ... ... @@ -57,5 +53,4 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett 57 53  t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 58 54  plotDataFrame(df) 59 55  plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 60 - main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 61 -} 56 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

Commit made by the Bioconductor Git-SVN bridge.

Commit id: 7ce8bf6b9a307c61c0f6297e94039cb5e8386bd2

support main heatmap in plotDataFrame()

z.gu authored on 15/06/2015 18:58:19
Showing1 changed files
 ... ... @@ -11,9 +11,9 @@ Visualize a data frame 11 11   12 12  } 13 13  \usage{ 14 -plotDataFrame(df, overlap = 0.5, nlevel = 30, show_row_names = TRUE, 15 - group = NULL, group_name = names(group), cluster_rows = TRUE, 16 - cluster_columns = TRUE) 14 +plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE, 15 + group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL, 16 + cluster_rows = TRUE, cluster_columns = TRUE, ...) 17 17  } 18 18  \arguments{ 19 19   ... ... @@ -21,10 +21,15 @@ plotDataFrame(df, overlap = 0.5, nlevel = 30, show_row_names = TRUE, 21 21  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.} 22 22  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.} 23 23  \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 24 + \item{show_column_names}{whether show column names for all heatmaps} 24 25  \item{group}{a list of index that defines the groupping} 25 - \item{group_name}{names for each group} 26 + \item{group_names}{names for each group} 27 + \item{main_heatmap}{which group is the main heatmap} 28 + \item{km}{apply k-means clustering on rows for the main heatmap} 29 + \item{split}{set a splitting variable on rows for the main heatmap} 26 30  \item{cluster_rows}{whether perform clustering on rows of the first heatmap} 27 31  \item{cluster_columns}{whether perform clustering on columns for all heatmaps} 32 + \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}} 28 33   29 34  } 30 35  \details{ ... ... @@ -45,8 +50,12 @@ Zuguang Gu  45 50   46 51  } 47 52  \examples{ 48 -df = data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10, 10),  49 - l1 = letters[1:10], l2 = LETTERS[1:10]) 53 +df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])), 54 + large = runif(10)*100, 55 + t1 = sample(letters[1:3], 10, replace = TRUE), 56 + matrix(runif(60), nrow = 10, dimnames = list(LETTERS[1:10], LETTERS[1:6])), 57 + t2 = sample(LETTERS[1:3], 10, replace = TRUE)) 50 58  plotDataFrame(df) 51 -plotDataFrame(df, group = list(number = 1:3, letters = 4:5)) 59 +plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"), 60 + main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title") 52 61  }

Commit made by the Bioconductor Git-SVN bridge.

Commit id: c2a58ed184d534d16fc4ec5cb5df64fa199fe5b0

change the way to overlap two intervals

Commit id: 7a90e91451128103fee12f7eeb03176aba3d724d

add plotDataFrame() which visualize a data frame

 1 1 new file mode 100644 ... ... @@ -0,0 +1,52 @@ 1 +\name{plotDataFrame} 2 +\alias{plotDataFrame} 3 +\title{ 4 +Visualize a data frame  5 + 6 + 7 +} 8 +\description{ 9 +Visualize a data frame  10 + 11 + 12 +} 13 +\usage{ 14 +plotDataFrame(df, overlap = 0.5, nlevel = 30, show_row_names = TRUE, 15 + group = NULL, group_name = names(group), cluster_rows = TRUE, 16 + cluster_columns = TRUE) 17 +} 18 +\arguments{ 19 + 20 + \item{df}{a data frame} 21 + \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.} 22 + \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.} 23 + \item{show_row_names}{whether show row names after the last heatmap if there are row names.} 24 + \item{group}{a list of index that defines the groupping} 25 + \item{group_name}{names for each group} 26 + \item{cluster_rows}{whether perform clustering on rows of the first heatmap} 27 + \item{cluster_columns}{whether perform clustering on columns for all heatmaps} 28 + 29 +} 30 +\details{ 31 +The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  32 + 33 +There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  34 + 35 + 36 +} 37 +\value{ 38 +a \code{\link{HeatmapList}} object  39 + 40 + 41 +} 42 +\author{ 43 +Zuguang Gu  44 + 45 + 46 +} 47 +\examples{ 48 +df = data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10, 10),  49 + l1 = letters[1:10], l2 = LETTERS[1:10]) 50 +plotDataFrame(df) 51 +plotDataFrame(df, group = list(number = 1:3, letters = 4:5)) 52 +}